From 59b18a6d54745c6cff21af40d6d3fb1cffe40abc Mon Sep 17 00:00:00 2001
From: adamhsparks <adamhsparks@icloud.com>
Date: Sun, 8 Dec 2024 08:44:09 +0000
Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20adamhspa?=
 =?UTF-8?q?rks/read.abares@c1cab730a4c19aa855c317ff84af7c919ca4450c=20?=
 =?UTF-8?q?=F0=9F=9A=80?=
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---
 CODE_OF_CONDUCT.html                          |  10 +-
 CONTRIBUTING.html                             | 106 ++++--------------
 index.html                                    |   1 +
 news/index.html                               |  18 +--
 pkgdown.yml                                   |   2 +-
 reference/print_soil_thickness_metadata.html  |   2 +-
 ...ead_estimates_by_performance_category.html |   6 +-
 .../read_historical_national_estimates.html   |   6 +-
 .../read_historical_regional_estimates.html   |   6 +-
 .../read_historical_state_estimates.html      |   6 +-
 search.json                                   |   2 +-
 sitemap.xml                                   |   1 +
 12 files changed, 55 insertions(+), 111 deletions(-)
diff --git a/CODE_OF_CONDUCT.html b/CODE_OF_CONDUCT.html
index 968de9e..d800d84 100644
--- a/CODE_OF_CONDUCT.html
+++ b/CODE_OF_CONDUCT.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Contributor Covenant Code of Conduct • read.abares</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="Contributor Covenant Code of Conduct"><meta property="og:image" content="https://adamhsparks.github.io/read.abares/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Contributor Covenant Code of Conduct • read.abares</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="Contributor Covenant Code of Conduct"><meta property="og:image" content="https://adamhsparks.github.io/read.abares/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="index.html">read.abares</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -32,7 +32,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="logo.png" class="logo" alt=""><h1>Contributor Covenant Code of Conduct</h1>
-      <small class="dont-index">Source: <a href="https://github.com/adamhsparks/read.abares/blob/main/CODE_OF_CONDUCT.md" class="external-link"><code>CODE_OF_CONDUCT.md</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/adamhsparks/read.abares/blob/main/.github/CODE_OF_CONDUCT.md" class="external-link"><code>.github/CODE_OF_CONDUCT.md</code></a></small>
     </div>
 
 <div id="contributor-covenant-code-of-conduct" class="section level1">
@@ -68,7 +68,7 @@ <h2 id="scope">Scope<a class="anchor" aria-label="anchor" href="#scope"></a></h2
 </div>
 <div class="section level2">
 <h2 id="enforcement">Enforcement<a class="anchor" aria-label="anchor" href="#enforcement"></a></h2>
-<p>Instances of abusive, harassing, or otherwise unacceptable behavior may be reported to the community leaders responsible for enforcement at <a href="mailto:adamhsparks@gmail.com" class="email">adamhsparks@gmail.com</a>. All complaints will be reviewed and investigated promptly and fairly.</p>
+<p>Instances of abusive, harassing, or otherwise unacceptable behavior may be reported to the community leaders responsible for enforcement at <a href="mailto:codeofconduct@posit.co" class="email">codeofconduct@posit.co</a>. All complaints will be reviewed and investigated promptly and fairly.</p>
 <p>All community leaders are obligated to respect the privacy and security of the reporter of any incident.</p>
 </div>
 <div class="section level2">
@@ -108,7 +108,7 @@ <h2 id="attribution">Attribution<a class="anchor" aria-label="anchor" href="#att
 
 
     <footer><div class="pkgdown-footer-left">
-  <p>Developed by Adam H. Sparks.</p>
+  <p>Developed by Adam H. Sparks, Grains Research and Development Corporation.</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/CONTRIBUTING.html b/CONTRIBUTING.html
index 3c7e0df..5c7bbc4 100644
--- a/CONTRIBUTING.html
+++ b/CONTRIBUTING.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>NA • read.abares</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="NA"><meta property="og:image" content="https://adamhsparks.github.io/read.abares/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Contributing to read.abares • read.abares</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="Contributing to read.abares"><meta property="og:image" content="https://adamhsparks.github.io/read.abares/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -31,98 +31,40 @@
 </nav><div class="container template-title-body">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
-      <img src="logo.png" class="logo" alt=""><h1>NA</h1>
-      <small class="dont-index">Source: <a href="https://github.com/adamhsparks/read.abares/blob/main/CONTRIBUTING.md" class="external-link"><code>CONTRIBUTING.md</code></a></small>
+      <img src="logo.png" class="logo" alt=""><h1>Contributing to read.abares</h1>
+      <small class="dont-index">Source: <a href="https://github.com/adamhsparks/read.abares/blob/main/.github/CONTRIBUTING.md" class="external-link"><code>.github/CONTRIBUTING.md</code></a></small>
     </div>
 
+<div id="contributing-to-readabares" class="section level1">
 
-<p>t seems relevant. - Possibly your input and the output - Can you reliably reproduce the issue? And can you also reproduce it with older versions?</p>
-<div class="section level4">
-<h4 id="how-do-i-submit-a-good-bug-report">How Do I Submit a Good Bug Report?<a class="anchor" aria-label="anchor" href="#how-do-i-submit-a-good-bug-report"></a></h4>
-<blockquote>
-<p>You must never report security related issues, vulnerabilities or bugs including sensitive information to the issue tracker, or elsewhere in public. Instead sensitive bugs must be sent by email to <a href="mailto:marcelo.araya@ucr.ac.cr" class="email">marcelo.araya@ucr.ac.cr</a>.</p>
-</blockquote>
-<p>We use GitHub issues to track bugs and errors. If you run into an issue with the project:</p>
-<ul><li>Open an <a href="https://github.com/ropensci/baRulho/issues/new" class="external-link">Issue</a>. (Since we can’t be sure at this point whether it is a bug or not, we ask you not to talk about a bug yet and not to label the issue.)</li>
-<li>Explain the behavior you would expect and the actual behavior.</li>
-<li>Please provide as much context as possible and describe the <em>reproduction steps</em> that someone else can follow to recreate the issue on their own. This usually includes your code. For good bug reports you should isolate the problem and create a reduced test case.</li>
-<li>Provide the information you collected in the previous section. be marked <code>needs-fix</code>, as well as possibly other tags (such as <code>critical</code>), and the issue will be left to be implemented by someone.</li>
-</ul></div>
-<div class="section level3">
-<h3 id="suggesting-enhancements">Suggesting Enhancements<a class="anchor" aria-label="anchor" href="#suggesting-enhancements"></a></h3>
-<p>This section guides you through submitting an enhancement suggestion, <strong>including completely new features and minor improvements to existing functionality</strong>. Following these guidelines will help maintainers and the community to understand your suggestion and find related suggestions.</p>
-<div class="section level4">
-<h4 id="before-submitting-an-enhancement">Before Submitting an Enhancement<a class="anchor" aria-label="anchor" href="#before-submitting-an-enhancement"></a></h4>
-<ul><li>Make sure that you are using the latest version.</li>
-<li>Read the <a href="https://docs.ropensci.org/baRulho//articles/" class="external-link">documentation</a> carefully and find out if the functionality is already covered, maybe by an individual configuration.</li>
-<li>Perform a <a href="https://github.com/ropensci/baRulho/issues/" class="external-link">search</a> to see if the enhancement has already been suggested. If it has, add a comment to the existing issue instead of opening a new one.</li>
-<li>Find out whether your idea fits with the scope alved it better and which could serve as inspiration.</li>
-</ul></div>
-</div>
+<p>This outlines how to propose a change to read.abares. For a detailed discussion on contributing to this and other tidyverse packages, please see the <a href="https://rstd.io/tidy-contrib" class="external-link">development contributing guide</a> and our <a href="https://code-review.tidyverse.org/" class="external-link">code review principles</a>.</p>
 <div class="section level2">
-<h2 id="attribution">Attribution<a class="anchor" aria-label="anchor" href="#attribution"></a></h2>
-<p>This guide is based on the <strong>contributing.md</strong>. <a href="https://contributing.md/" class="external-link">Make your own</a>!nd aims of the project. It’s up to you to make a strong case to convince the project’s developers of the merits of this feature. Keep in mind that we want features that will be useful to the majority of our users and not just a small subset. If you’re just targeting a minority of users, consider writing an add-on/plugin library.</p>
-<div class="section level4">
-<h4 id="how-do-i-submit-a-good-enhancement-suggestion">How Do I Submit a Good Enhancement Suggestion?<a class="anchor" aria-label="anchor" href="#how-do-i-submit-a-good-enhancement-suggestion"></a></h4>
-<p>Enhancement suggestions are tracked as <a href="https://github.com/ropensci/baRulho/issues/" class="external-link">GitHub issues</a>.</p>
-<ul><li><p>Use a <strong>clear and descriptive title</strong> for the issue to identify the suggestion.</p></li>
-<li><p>Provide a <strong>step-by-step description of the suggested enhancement</strong> in as many details as possible.</p></li>
-<li><p><strong>Describe the current behavior</strong> and <strong>explain which behavior you expected to see instead</strong> and why. At this point you can also tell which alternatives do not work for you.</p></li>
-<li><p>You may want to <strong>include screenshots and animated GIFs</strong> which help you demonstrate the steps or point out the part which the suggestion is related to. You can use <a href="https://www.cockos.com/licecap/" class="external-link">this tool</a> to record GIFs on macOS and Windows, and <a href="https://github.com/colinkeenan/silentcast" class="external-link">this tool</a> or <a href="https://github.com/GNOME/byzanz" class="external-link">this tool</a> on Linux.</p></li>
-<li><p><strong>Explain why this enhancement would be useful</strong> to most users. You may also want to point out the other projects that so Once it’s filed:</p></li>
-<li><p>The project team will label the issue accordingly.</p></li>
-<li><p>A team member will try to reproduce the issue with your provided steps. If there are no reproduction steps or no obvious way to reproduce the issue, the team will ask you for those steps and mark the issue as <code>needs-repro</code>. Bugs with the <code>needs-repro</code> tag will not be addressed until they are reproduced.</p></li>
-<li><p>If the team is able to reproduce the issue, it will# Contributing</p></li>
-</ul><p>First off, thanks for taking the time to contribute!</p>
-<p>All types of contributions are encouraged and valued. See the <a href="#table-of-contents">Table of Contents</a> for different ways to help and details about how this project handles them. Please make sure to read the relevant section before making your contribution. It will make it a lot easier for us maintainers and smooth out the experience for all involved. The community looks forward to your contributions.</p>
-<p>And if you like the project, but just don’t have time to contribute, that’s fine. There are other easy ways to support the project and show your appreciation, which we would also be very happy about: - Star the project - Tweet about it - Refer this project in your project’s readme - Mention the project at local meetups and tell your friends/colleagues</p>
-</div>
+<h2 id="fixing-typos">Fixing typos<a class="anchor" aria-label="anchor" href="#fixing-typos"></a></h2>
+<p>You can fix typos, spelling mistakes, or grammatical errors in the documentation directly using the GitHub web interface, as long as the changes are made in the <em>source</em> file. This generally means you’ll need to edit <a href="https://roxygen2.r-lib.org/articles/roxygen2.html" class="external-link">roxygen2 comments</a> in an <code>.R</code>, not a <code>.Rd</code> file. You can find the <code>.R</code> file that generates the <code>.Rd</code> by reading the comment in the first line.</p>
 </div>
 <div class="section level2">
-<h2 id="table-of-contents">Table of Contents<a class="anchor" aria-label="anchor" href="#table-of-contents"></a></h2>
-<ul><li><a href="#code-of-conduct">Code of Conduct</a></li>
-<li><a href="#i-have-a-question">I Have a Question</a></li>
-<li><a href="#i-want-to-contribute">I Want To Contribute</a></li>
-<li><a href="#reporting-bugs">Reporting Bugs</a></li>
-<li><a href="#suggesting-enhancements">Suggesting Enhancements</a></li>
+<h2 id="bigger-changes">Bigger changes<a class="anchor" aria-label="anchor" href="#bigger-changes"></a></h2>
+<p>If you want to make a bigger change, it’s a good idea to first file an issue and make sure someone from the team agrees that it’s needed. If you’ve found a bug, please file an issue that illustrates the bug with a minimal <a href="https://www.tidyverse.org/help/#reprex" class="external-link">reprex</a> (this will also help you write a unit test, if needed). See our guide on <a href="https://code-review.tidyverse.org/issues/" class="external-link">how to create a great issue</a> for more advice.</p>
+<div class="section level3">
+<h3 id="pull-request-process">Pull request process<a class="anchor" aria-label="anchor" href="#pull-request-process"></a></h3>
+<ul><li><p>Fork the package and clone onto your computer. If you haven’t done this before, we recommend using <code>usethis::create_from_github("adamhsparks/read.abares", fork = TRUE)</code>.</p></li>
+<li><p>Install all development dependencies with <code>devtools::install_dev_deps()</code>, and then make sure the package passes R CMD check by running <code>devtools::check()</code>. If R CMD check doesn’t pass cleanly, it’s a good idea to ask for help before continuing.</p></li>
+<li><p>Create a Git branch for your pull request (PR). We recommend using <code>usethis::pr_init("brief-description-of-change")</code>.</p></li>
+<li><p>Make your changes, commit to git, and then create a PR by running <code>usethis::pr_push()</code>, and following the prompts in your browser. The title of your PR should briefly describe the change. The body of your PR should contain <code>Fixes #issue-number</code>.</p></li>
+<li><p>For user-facing changes, add a bullet to the top of <code>NEWS.md</code> (i.e. just below the first header). Follow the style described in <a href="https://style.tidyverse.org/news.html" class="external-link uri">https://style.tidyverse.org/news.html</a>.</p></li>
 </ul></div>
-<div class="section level2">
-<h2 id="code-of-conduct">Code of Conduct<a class="anchor" aria-label="anchor" href="#code-of-conduct"></a></h2>
-<p>Please note that baRulho is released with a <a href="https://ropensci.org/code-of-conduct/" class="external-link">Contributor Code of Conduct</a>. By contributing to this project you agree to abide by its terms. See rOpenSci <a href="https://devguide.ropensci.org/contributingguide.html" class="external-link">contributing guide</a> for further details.</p>
-</div>
-<div class="section level2">
-<h2 id="i-have-a-question">I Have a Question<a class="anchor" aria-label="anchor" href="#i-have-a-question"></a></h2>
-<p>If you want to ask a question, we assume that you have read the available <a href="https://docs.ropensci.org/baRulho//articles/" class="external-link">Documentation</a>.</p>
-<p>Before you ask a question, it is best to search for existing <a href="https://github.com/ropensci/baRulho/issues/" class="external-link">Issues</a> that might help you. In case you have found a suitable issue and still need clarification, you can write your question in this issue. It is also advisable to search the internet for answers first.</p>
-<p>If you then still feel the need to ask a question and need clarification, we recommend the following:</p>
-<ul><li>Open an <a href="https://github.com/ropensci/baRulho/issues/new" class="external-link">https://github.com/ropensci/baRulho/issues/</a>.</li>
-<li>Provide as much context as you can about what you’re running into.</li>
-<li>Provide project and platform versions (nodejs, npm, etc), depending on what seems relevant.</li>
-</ul><p>We will then take care of the issue as soon as possible.</p>
-</div>
-<div class="section level2">
-<h2 id="i-want-to-contribute">I Want To Contribute<a class="anchor" aria-label="anchor" href="#i-want-to-contribute"></a></h2>
-<blockquote>
-<h3 id="legal-notice">Legal Notice</h3>
-<p>When contributing to this project, you must agree that you have authored 100% of the content, that you have the necessary rights to the content and that the content you contribute may be provided under the project license.</p>
-</blockquote>
 <div class="section level3">
-<h3 id="reporting-bugs">Reporting Bugs<a class="anchor" aria-label="anchor" href="#reporting-bugs"></a></h3>
-<div class="section level4">
-<h4 id="before-submitting-a-bug-report">Before Submitting a Bug Report<a class="anchor" aria-label="anchor" href="#before-submitting-a-bug-report"></a></h4>
-<p>A good bug report shouldn’t leave others needing to chase you up for more information. Therefore, we ask you to investigate carefully, collect information and describe the issue in detail in your report. Please complete the following steps in advance to help us fix any potential bug as fast as possible.</p>
-<ul><li>Make sure that you are using the latest version.</li>
-<li>Determine if your bug is really a bug and not an error on your side e.g. using incompatible environment components/versions (Make sure that you have read the <a href="https://docs.ropensci.org/baRulho//articles/" class="external-link">documentation</a>. If you are looking for support, you might want to check <a href="#i-have-a-question">this section</a>).</li>
-<li>To see if other users have experienced (and potentially already solved) the same issue you are having, check if there is not already a bug report existing for your bug or erro.</li>
-<li>Also make sure to search the internet (including Stack Overflow) to see if users outside of the GitHub community have discussed the issue.</li>
-<li>Collect information about the bug:</li>
-<li>Stack trace (Traceback)</li>
-<li>OS, Platform and Version (Windows, Linux, macOS, x86, ARM)</li>
-<li>Version of the interpreter, compiler, SDK, runtime environment, package manager, depending on wha</li>
+<h3 id="code-style">Code style<a class="anchor" aria-label="anchor" href="#code-style"></a></h3>
+<ul><li><p>New code should follow the tidyverse <a href="https://style.tidyverse.org" class="external-link">style guide</a>. You can use the <a href="https://CRAN.R-project.org/package=styler" class="external-link">styler</a> package to apply these styles, but please don’t restyle code that has nothing to do with your PR.</p></li>
+<li><p>We use <a href="https://cran.r-project.org/package=roxygen2" class="external-link">roxygen2</a>, with <a href="https://cran.r-project.org/web/packages/roxygen2/vignettes/rd-formatting.html" class="external-link">Markdown syntax</a>, for documentation.</p></li>
+<li><p>We use <a href="https://cran.r-project.org/package=testthat" class="external-link">testthat</a> for unit tests. Contributions with test cases included are easier to accept.</p></li>
 </ul></div>
 </div>
+<div class="section level2">
+<h2 id="code-of-conduct">Code of Conduct<a class="anchor" aria-label="anchor" href="#code-of-conduct"></a></h2>
+<p>Please note that the read.abares project is released with a <a href="CODE_OF_CONDUCT.html">Contributor Code of Conduct</a>. By contributing to this project you agree to abide by its terms.</p>
+</div>
 </div>
-
 
   </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
diff --git a/index.html b/index.html
index b77ec9c..e19be44 100644
--- a/index.html
+++ b/index.html
@@ -193,6 +193,7 @@ <h2 data-toc-skip>License</h2>
 <h2 data-toc-skip>Community</h2>
 <ul class="list-unstyled">
 <li><a href="CONTRIBUTING.html">Contributing guide</a></li>
+<li><a href="CODE_OF_CONDUCT.html">Code of conduct</a></li>
 </ul>
 </div>
 
diff --git a/news/index.html b/news/index.html
index 6c056b2..bb35f55 100644
--- a/news/index.html
+++ b/news/index.html
@@ -38,21 +38,14 @@
     <div class="section level2">
 <h2 class="pkg-version" data-toc-text="1.0.0" id="readabares-100">read.abares 1.0.0<a class="anchor" aria-label="anchor" href="#readabares-100"></a></h2>
 <div class="section level3">
-<h3 id="major-changes-1-0-0">Major changes<a class="anchor" aria-label="anchor" href="#major-changes-1-0-0"></a></h3>
+<h3 id="breaking-changes-1-0-0">Breaking changes<a class="anchor" aria-label="anchor" href="#breaking-changes-1-0-0"></a></h3>
 <ul><li><p>Rename functions that both download and read files into active R session from <code>get_</code> to <code>read_</code> to avoid confusion with functions that only fetch data and have separate <code>read_</code> functions</p></li>
 <li><p>Adds new function, <code><a href="../reference/print_agfd_nc_file_format.html">print_agfd_nc_file_format()</a></code> to provide details on the AGFD NetCDF files’ contents</p></li>
 <li><p>Uses Geopackages for {sf} objects rather than .Rds, faster and smaller file sizes when caching</p></li>
 <li><p>Checks and corrects the geometries of the AAGIS Regions shapefile upon import and applies to the cached object if applicable</p></li>
 </ul></div>
 <div class="section level3">
-<h3 id="bug-fixes-1-0-0">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-1-0-0"></a></h3>
-<ul><li><p>No longer checks the length of a Boolean vector when checking the number of files in the cache before proceeding with removing them</p></li>
-<li><p>Fixes bugs in <code><a href="../reference/get_agfd.html">get_agfd()</a></code> when creating the directories for saving the downloaded file</p></li>
-<li><p>Fixes bug in <code>get_aagis_regions()</code> when creating the cached object file</p></li>
-<li><p>Fixes “URL” field in DESCRIPTION file, thanks <a href="https://github.com/mpadge" class="external-link">@mpadge</a></p></li>
-</ul></div>
-<div class="section level3">
-<h3 id="minor-changes-1-0-0">Minor changes<a class="anchor" aria-label="anchor" href="#minor-changes-1-0-0"></a></h3>
+<h3 id="new-features-1-0-0">New features<a class="anchor" aria-label="anchor" href="#new-features-1-0-0"></a></h3>
 <ul><li>
 <p>Improved documentation</p>
 <ul><li><p>All data sets now have an <code>@source</code> field that points to the file being provided</p></li>
@@ -70,6 +63,13 @@ <h3 id="minor-changes-1-0-0">Minor changes<a class="anchor" aria-label="anchor"
 <li><p>Tests are run in parallel for quicker testing</p></li>
 <li><p>{sf} operations are now quiet when reading data where possible</p></li>
 </ul></div>
+<div class="section level3">
+<h3 id="minor-improvements-and-fixes-1-0-0">Minor improvements and fixes<a class="anchor" aria-label="anchor" href="#minor-improvements-and-fixes-1-0-0"></a></h3>
+<ul><li><p>No longer checks the length of a Boolean vector when checking the number of files in the cache before proceeding with removing them</p></li>
+<li><p>Fixes bugs in <code><a href="../reference/get_agfd.html">get_agfd()</a></code> when creating the directories for saving the downloaded file</p></li>
+<li><p>Fixes bug in <code>get_aagis_regions()</code> when creating the cached object file</p></li>
+<li><p>Fixes “URL” field in DESCRIPTION file (<a href="https://github.com/mpadge" class="external-link">@mpadge</a> <a href="https://github.com/adamhsparks/read.abares/issues/1" class="external-link uri">https://github.com/adamhsparks/read.abares/issues/1</a>)</p></li>
+</ul></div>
 </div>
     <div class="section level2">
 <h2 class="pkg-version" data-toc-text="0.1.0" id="readabares-010">read.abares 0.1.0<a class="anchor" aria-label="anchor" href="#readabares-010"></a></h2>
diff --git a/pkgdown.yml b/pkgdown.yml
index c1d5077..83d28f0 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -3,7 +3,7 @@ pkgdown: 2.1.1
 pkgdown_sha: ~
 articles:
   read.abares: read.abares.html
-last_built: 2024-12-08T06:27Z
+last_built: 2024-12-08T08:43Z
 urls:
   reference: https://adamhsparks.github.io/read.abares/reference
   article: https://adamhsparks.github.io/read.abares/articles
diff --git a/reference/print_soil_thickness_metadata.html b/reference/print_soil_thickness_metadata.html
index e8314d0..86be138 100644
--- a/reference/print_soil_thickness_metadata.html
+++ b/reference/print_soil_thickness_metadata.html
@@ -79,7 +79,7 @@ <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span> <span class="co"># interactive()</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="get_soil_thickness.html">get_soil_thickness</a></span><span class="op">(</span>cache <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op">|&gt;</span></span></span>
-<span class="r-in"><span><span class="fu">print_soil_thickness_metadata</span><span class="op">(</span><span class="op">)</span></span></span>
+<span class="r-in"><span>  <span class="fu">print_soil_thickness_metadata</span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">}</span></span></span>
 </code></pre></div>
     </div>
diff --git a/reference/read_estimates_by_performance_category.html b/reference/read_estimates_by_performance_category.html
index 7e1689c..eac5beb 100644
--- a/reference/read_estimates_by_performance_category.html
+++ b/reference/read_estimates_by_performance_category.html
@@ -72,10 +72,10 @@ <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span> <span class="co"># interactive()</span></span></span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="fu">read_estimates_by_performance_category</span><span class="op">(</span><span class="op">)</span></span></span>
+<span class="r-in"><span><span class="fu">read_estimates_by_performance_category</span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="co"># or shorter</span></span></span>
-<span class="r-in"><span> <span class="fu">read_est_by_perf_cat</span><span class="op">(</span><span class="op">)</span></span></span>
+<span class="r-in"><span><span class="co"># or shorter</span></span></span>
+<span class="r-in"><span><span class="fu">read_est_by_perf_cat</span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">}</span></span></span>
 </code></pre></div>
     </div>
diff --git a/reference/read_historical_national_estimates.html b/reference/read_historical_national_estimates.html
index 1ad3f8d..55e586c 100644
--- a/reference/read_historical_national_estimates.html
+++ b/reference/read_historical_national_estimates.html
@@ -78,10 +78,10 @@ <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span> <span class="co"># interactive()</span></span></span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="fu">read_historical_national_estimates</span><span class="op">(</span><span class="op">)</span></span></span>
+<span class="r-in"><span><span class="fu">read_historical_national_estimates</span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="co"># or shorter</span></span></span>
-<span class="r-in"><span> <span class="fu">read_hist_nat_est</span><span class="op">(</span><span class="op">)</span></span></span>
+<span class="r-in"><span><span class="co"># or shorter</span></span></span>
+<span class="r-in"><span><span class="fu">read_hist_nat_est</span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">}</span></span></span>
 </code></pre></div>
     </div>
diff --git a/reference/read_historical_regional_estimates.html b/reference/read_historical_regional_estimates.html
index 0e490e9..31ead76 100644
--- a/reference/read_historical_regional_estimates.html
+++ b/reference/read_historical_regional_estimates.html
@@ -77,10 +77,10 @@ <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span> <span class="co"># interactive()</span></span></span>
-<span class="r-in"><span> <span class="fu">read_historical_regional_estimates</span><span class="op">(</span><span class="op">)</span></span></span>
+<span class="r-in"><span><span class="fu">read_historical_regional_estimates</span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="co"># or shorter</span></span></span>
-<span class="r-in"><span> <span class="fu">read_hist_reg_est</span><span class="op">(</span><span class="op">)</span></span></span>
+<span class="r-in"><span><span class="co"># or shorter</span></span></span>
+<span class="r-in"><span><span class="fu">read_hist_reg_est</span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">}</span></span></span>
 </code></pre></div>
     </div>
diff --git a/reference/read_historical_state_estimates.html b/reference/read_historical_state_estimates.html
index 2d45e7a..82c2365 100644
--- a/reference/read_historical_state_estimates.html
+++ b/reference/read_historical_state_estimates.html
@@ -77,10 +77,10 @@ <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span> <span class="co"># interactive()</span></span></span>
-<span class="r-in"><span> <span class="fu">read_historical_state_estimates</span><span class="op">(</span><span class="op">)</span></span></span>
+<span class="r-in"><span><span class="fu">read_historical_state_estimates</span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span> <span class="co"># or shorter</span></span></span>
-<span class="r-in"><span> <span class="fu">read_hist_sta_est</span><span class="op">(</span><span class="op">)</span></span></span>
+<span class="r-in"><span><span class="co"># or shorter</span></span></span>
+<span class="r-in"><span><span class="fu">read_hist_sta_est</span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">}</span></span></span>
 </code></pre></div>
     </div>
diff --git a/search.json b/search.json
index dc7ff12..0be8524 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
-[{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"how-do-i-submit-a-good-bug-report","dir":"","previous_headings":"","what":"How Do I Submit a Good Bug Report?","title":"NA","text":"must never report security related issues, vulnerabilities bugs including sensitive information issue tracker, elsewhere public. Instead sensitive bugs must sent email marcelo.araya@ucr.ac.cr. use GitHub issues track bugs errors. run issue project: Open Issue. (Since can’t sure point whether bug , ask talk bug yet label issue.) Explain behavior expect actual behavior. Please provide much context possible describe reproduction steps someone else can follow recreate issue . usually includes code. good bug reports isolate problem create reduced test case. Provide information collected previous section. marked needs-fix, well possibly tags (critical), issue left implemented someone.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"suggesting-enhancements","dir":"","previous_headings":"","what":"Suggesting Enhancements","title":"NA","text":"section guides submitting enhancement suggestion, including completely new features minor improvements existing functionality. Following guidelines help maintainers community understand suggestion find related suggestions.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"before-submitting-an-enhancement","dir":"","previous_headings":"Suggesting Enhancements","what":"Before Submitting an Enhancement","title":"NA","text":"Make sure using latest version. Read documentation carefully find functionality already covered, maybe individual configuration. Perform search see enhancement already suggested. , add comment existing issue instead opening new one. Find whether idea fits scope alved better serve inspiration.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"NA","text":"guide based contributing.md. Make !nd aims project. ’s make strong case convince project’s developers merits feature. Keep mind want features useful majority users just small subset. ’re just targeting minority users, consider writing add-/plugin library.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"how-do-i-submit-a-good-enhancement-suggestion","dir":"","previous_headings":"Attribution","what":"How Do I Submit a Good Enhancement Suggestion?","title":"NA","text":"Enhancement suggestions tracked GitHub issues. Use clear descriptive title issue identify suggestion. Provide step--step description suggested enhancement many details possible. Describe current behavior explain behavior expected see instead . point can also tell alternatives work . may want include screenshots animated GIFs help demonstrate steps point part suggestion related . can use tool record GIFs macOS Windows, tool tool Linux. Explain enhancement useful users. may also want point projects ’s filed: project team label issue accordingly. team member try reproduce issue provided steps. reproduction steps obvious way reproduce issue, team ask steps mark issue needs-repro. Bugs needs-repro tag addressed reproduced. team able reproduce issue, # Contributing First , thanks taking time contribute! types contributions encouraged valued. See Table Contents different ways help details project handles . Please make sure read relevant section making contribution. make lot easier us maintainers smooth experience involved. community looks forward contributions. like project, just don’t time contribute, ’s fine. easy ways support project show appreciation, also happy : - Star project - Tweet - Refer project project’s readme - Mention project local meetups tell friends/colleagues","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"table-of-contents","dir":"","previous_headings":"","what":"Table of Contents","title":"NA","text":"Code Conduct Question Want Contribute Reporting Bugs Suggesting Enhancements","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"NA","text":"Please note baRulho released Contributor Code Conduct. contributing project agree abide terms. See rOpenSci contributing guide details.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"i-have-a-question","dir":"","previous_headings":"","what":"I Have a Question","title":"NA","text":"want ask question, assume read available Documentation. ask question, best search existing Issues might help . case found suitable issue still need clarification, can write question issue. also advisable search internet answers first. still feel need ask question need clarification, recommend following: Open https://github.com/ropensci/baRulho/issues/. Provide much context can ’re running . Provide project platform versions (nodejs, npm, etc), depending seems relevant. take care issue soon possible.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"i-want-to-contribute","dir":"","previous_headings":"","what":"I Want To Contribute","title":"NA","text":"contributing project, must agree authored 100% content, necessary rights content content contribute may provided project license.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"before-submitting-a-bug-report","dir":"","previous_headings":"I Want To Contribute > Reporting Bugs","what":"Before Submitting a Bug Report","title":"NA","text":"good bug report shouldn’t leave others needing chase information. Therefore, ask investigate carefully, collect information describe issue detail report. Please complete following steps advance help us fix potential bug fast possible. Make sure using latest version. Determine bug really bug error side e.g. using incompatible environment components/versions (Make sure read documentation. looking support, might want check section). see users experienced (potentially already solved) issue , check already bug report existing bug erro. Also make sure search internet (including Stack Overflow) see users outside GitHub community discussed issue. Collect information bug: Stack trace (Traceback) OS, Platform Version (Windows, Linux, macOS, x86, ARM) Version interpreter, compiler, SDK, runtime environment, package manager, depending wha","code":""},{"path":"https://adamhsparks.github.io/read.abares/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 read.abares authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://adamhsparks.github.io/read.abares/articles/read.abares.html","id":"working-with-agfd-data","dir":"Articles","previous_headings":"","what":"Working With AGFD Data","title":"read.abares","text":"can download files pipe directly class object desire Australian Farm Gridded Data (AGFD) data.","code":""},{"path":"https://adamhsparks.github.io/read.abares/articles/read.abares.html","id":"description-of-the-australian-farm-gridded-data","dir":"Articles","previous_headings":"Working With AGFD Data","what":"Description of the Australian Farm Gridded Data","title":"read.abares","text":"Directly DAFF website: Australian Gridded Farm Data set national scale maps containing simulated data historical broadacre farm business outcomes including farm profitability 0.05-degree (approximately 5 km) grid. data produced read.abares part ongoing Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using read.abares farmpredict model, turn based read.abares Agricultural Grazing Industries Survey (AAGIS) data. maps provide estimates farm business profit, revenue, costs production location (grid cell) year period 1990-91 2022-23. data include actual observed outcomes rather model predicted outcomes representative ‘typical’ broadacre farm businesses location considering likely farm characteristics prevailing weather conditions commodity prices. Australian Gridded Farm Data remain active development, considered experimental. – Australian Department Agriculture, Fisheries Forestry. Load {read.abares} library. Check file format information NetCDF files. Download load local cache read AGFD files list {stars} objects. Download load local cache read AGFD files terra::rast object. Download load local cache read AGFD files list {tidync} objects. Download load local cache read AGFD files {data.table} object.","code":"library(read.abares) print_agfd_nc_file_format() #> ──────────────────────────────────────────────────────────────────────────────────────────────────── #> Each of the layers in simulation output data is represented as a 2D raster in NETCDF files, with #> the following grid format: #> CRS: EPSG:4326 - WGS 84 – Geographic #> Extent: 111.975 -44.525 156.275 -9.975 #> Unit: Degrees #> Width: 886 #> Height: 691 #> Cell size: 0.05 degree x 0.05 degree #> ──────────────────────────────────────────────────────────────────────────────────────────────────── #> For further details, see the ABARES website, #> <https://www.agriculture.gov.au/abares/research-topics/surveys/farm-survey-data/australian-gridded-farm-data> ## A list of {stars} objects star <- get_agfd(cache = TRUE) |>   read_agfd_stars() #> Will return stars object with 612226 cells. #> No projection information found in nc file.  #>  Coordinate variable units found to be degrees,  #>  assuming WGS84 Lat/Lon.  head(star[[1]]) #> stars object with 2 dimensions and 6 attributes #> attribute(s): #>                         Min.         1st Qu.         Median           Mean        3rd Qu. #> farmno          15612.000000 233091.50000000 329567.0000000 324737.7187618 418508.5000000 #> R_total_hat_ha      2.954396      7.88312157     21.7520529    169.5139301    174.8553843 #> C_total_hat_ha      1.304440      4.34079101      9.9449849     93.2210542     95.7221857 #> FBP_fci_hat_ha   -143.759785      3.60529967     11.5796641     76.2928759     77.6748501 #> FBP_fbp_hat_ha   -349.521639      3.36599833     11.5074294     60.0750936     62.8596117 #> A_wheat_hat_ha      0.000000      0.04062786      0.1114289      0.1365683      0.2112845 #>                           Max.   NA's #> farmno          669706.0000000 443899 #> R_total_hat_ha    2415.7556059 443899 #> C_total_hat_ha    1853.5385298 443899 #> FBP_fci_hat_ha    1186.5830232 443899 #> FBP_fbp_hat_ha    1240.6003218 443899 #> A_wheat_hat_ha       0.5047761 565224 #> dimension(s): #>     from  to refsys              values x/y #> lon    1 886 WGS 84 [886] 112,...,156.2 [x] #> lat    1 691 WGS 84 [691] -44.5,...,-10 [y] ## A {terra} `rast` object terr <- get_agfd(cache = TRUE) |>   read_agfd_terra()  head(terr[[1]]) #> class       : SpatRaster  #> dimensions  : 6, 886, 41  (nrow, ncol, nlyr) #> resolution  : 0.05, 0.05  (x, y) #> extent      : 111.975, 156.275, -10.275, -9.975  (xmin, xmax, ymin, ymax) #> coord. ref. : lon/lat WGS 84 (CRS84) (OGC:CRS84)  #> source(s)   : memory #> names       : farmno, R_tot~at_ha, C_tot~at_ha, FBP_f~at_ha, FBP_f~at_ha, A_whe~at_ha, ...  #> min values  :    NaN,         NaN,         NaN,         NaN,         NaN,         NaN, ...  #> max values  :    NaN,         NaN,         NaN,         NaN,         NaN,         NaN, ... ## A list of {tidync} objects tdnc <- get_agfd(cache = TRUE) |>   read_agfd_tidync()  head(tdnc[[1]]) #> $source #> # A tibble: 1 × 2 #>   access              source                                                                         #>   <dttm>              <chr>                                                                          #> 1 2024-12-08 10:28:31 /Users/adamsparks/Library/Caches/org.R-project.R/R/read.abares/historical_cli… #>  #> $axis #> # A tibble: 84 × 3 #>     axis variable       dimension #>    <int> <chr>              <int> #>  1     1 lon                    0 #>  2     2 lat                    1 #>  3     3 farmno                 0 #>  4     4 farmno                 1 #>  5     5 R_total_hat_ha         0 #>  6     6 R_total_hat_ha         1 #>  7     7 C_total_hat_ha         0 #>  8     8 C_total_hat_ha         1 #>  9     9 FBP_fci_hat_ha         0 #> 10    10 FBP_fci_hat_ha         1 #> # ℹ 74 more rows #>  #> $grid #> # A tibble: 3 × 4 #>   grid  ndims variables         nvars #>   <chr> <int> <list>            <int> #> 1 D0,D1     2 <tibble [41 × 1]>    41 #> 2 D0        1 <tibble [1 × 1]>      1 #> 3 D1        1 <tibble [1 × 1]>      1 #>  #> $dimension #> # A tibble: 2 × 8 #>      id name  length unlim coord_dim active start count #>   <int> <chr>  <dbl> <lgl> <lgl>     <lgl>  <int> <int> #> 1     0 lon      886 FALSE TRUE      TRUE       1   886 #> 2     1 lat      691 FALSE TRUE      TRUE       1   691 #>  #> $variable #> # A tibble: 43 × 7 #>       id name            type      ndims natts dim_coord active #>    <int> <chr>           <chr>     <int> <int> <lgl>     <lgl>  #>  1     0 lon             NC_DOUBLE     1     2 TRUE      FALSE  #>  2     1 lat             NC_DOUBLE     1     2 TRUE      FALSE  #>  3     2 farmno          NC_DOUBLE     2     1 FALSE     TRUE   #>  4     3 R_total_hat_ha  NC_DOUBLE     2     1 FALSE     TRUE   #>  5     4 C_total_hat_ha  NC_DOUBLE     2     1 FALSE     TRUE   #>  6     5 FBP_fci_hat_ha  NC_DOUBLE     2     1 FALSE     TRUE   #>  7     6 FBP_fbp_hat_ha  NC_DOUBLE     2     1 FALSE     TRUE   #>  8     7 A_wheat_hat_ha  NC_DOUBLE     2     1 FALSE     TRUE   #>  9     8 H_wheat_dot_hat NC_DOUBLE     2     1 FALSE     TRUE   #> 10     9 A_barley_hat_ha NC_DOUBLE     2     1 FALSE     TRUE   #> # ℹ 33 more rows #>  #> $attribute #> # A tibble: 49 × 4 #>       id name       variable       value        #>    <int> <chr>      <chr>          <named list> #>  1     0 _FillValue lon            <dbl [1]>    #>  2     1 units      lon            <chr [1]>    #>  3     0 _FillValue lat            <dbl [1]>    #>  4     1 units      lat            <chr [1]>    #>  5     0 _FillValue farmno         <dbl [1]>    #>  6     0 _FillValue R_total_hat_ha <dbl [1]>    #>  7     0 _FillValue C_total_hat_ha <dbl [1]>    #>  8     0 _FillValue FBP_fci_hat_ha <dbl [1]>    #>  9     0 _FillValue FBP_fbp_hat_ha <dbl [1]>    #> 10     0 _FillValue A_wheat_hat_ha <dbl [1]>    #> # ℹ 39 more rows ## A {data.table} object get_agfd(cache = TRUE) |>   read_agfd_dt() |>   head() #>                            id farmno R_total_hat_ha C_total_hat_ha FBP_fci_hat_ha FBP_fbp_hat_ha #>                        <char>  <num>          <num>          <num>          <num>          <num> #> 1: f2022.c1991.p2022.t2022.nc  15612       7.636519       4.405228       3.231292       1.766127 #> 2: f2022.c1991.p2022.t2022.nc  21495      14.811169       9.165632       5.645538       6.178280 #> 3: f2022.c1991.p2022.t2022.nc  23418      24.874456      14.858595      10.015861      15.504923 #> 4: f2022.c1991.p2022.t2022.nc  24494      15.043653       9.326359       5.717294       7.212161 #> 5: f2022.c1991.p2022.t2022.nc  32429      23.630099      13.681063       9.949036       9.612778 #> 6: f2022.c1991.p2022.t2022.nc  32485      15.009926       9.815501       5.194425       6.582035 #>    A_wheat_hat_ha H_wheat_dot_hat A_barley_hat_ha H_barley_dot_hat A_sorghum_hat_ha #>             <num>           <num>           <num>            <num>            <num> #> 1:            NaN             NaN             NaN              NaN              NaN #> 2:            NaN             NaN             NaN              NaN              NaN #> 3:            NaN             NaN             NaN              NaN              NaN #> 4:            NaN             NaN             NaN              NaN              NaN #> 5:            NaN             NaN             NaN              NaN              NaN #> 6:            NaN             NaN             NaN              NaN              NaN #>    H_sorghum_dot_hat A_oilseeds_hat_ha H_oilseeds_dot_hat R_wheat_hat_ha R_sorghum_hat_ha #>                <num>             <num>              <num>          <num>            <num> #> 1:               NaN               NaN                NaN            NaN              NaN #> 2:               NaN               NaN                NaN            NaN              NaN #> 3:               NaN               NaN                NaN            NaN              NaN #> 4:               NaN               NaN                NaN            NaN              NaN #> 5:               NaN               NaN                NaN            NaN              NaN #> 6:               NaN               NaN                NaN            NaN              NaN #>    R_oilseeds_hat_ha R_barley_hat_ha Q_wheat_hat_ha Q_barley_hat_ha Q_sorghum_hat_ha #>                <num>           <num>          <num>           <num>            <num> #> 1:               NaN             NaN            NaN             NaN              NaN #> 2:               NaN             NaN            NaN             NaN              NaN #> 3:               NaN             NaN            NaN             NaN              NaN #> 4:               NaN             NaN            NaN             NaN              NaN #> 5:               NaN             NaN            NaN             NaN              NaN #> 6:               NaN             NaN            NaN             NaN              NaN #>    Q_oilseeds_hat_ha S_wheat_cl_hat_ha S_sheep_cl_hat_ha S_sheep_births_hat_ha #>                <num>             <num>             <num>                 <num> #> 1:               NaN               NaN    0.000046854152        0.000048411171 #> 2:               NaN               NaN    0.000066325878        0.000057753874 #> 3:               NaN               NaN    0.000007771546        0.000007320093 #> 4:               NaN               NaN    0.000070963917        0.000062521929 #> 5:               NaN               NaN    0.000007780997        0.000006834211 #> 6:               NaN               NaN    0.000059600116        0.000053976389 #>    S_sheep_deaths_hat_ha S_beef_cl_hat_ha S_beef_births_hat_ha S_beef_deaths_hat_ha Q_beef_hat_ha #>                    <num>            <num>                <num>                <num>         <num> #> 1:        0.000007187978       0.02034820          0.005212591          0.000989490   0.004790528 #> 2:        0.000009039695       0.02974461          0.007970856          0.001468278   0.009646485 #> 3:        0.000000000000       0.05393181          0.014745383          0.002867331   0.014401773 #> 4:        0.000009726773       0.03057606          0.008602196          0.001446424   0.009577272 #> 5:        0.000000000000       0.04944272          0.011527594          0.002491037   0.014668761 #> 6:        0.000008478467       0.03322463          0.008456550          0.001627910   0.009281578 #>    Q_sheep_hat_ha Q_lamb_hat_ha R_beef_hat_ha R_sheep_hat_ha R_lamb_hat_ha C_fodder_hat_ha #>             <num>         <num>         <num>          <num>         <num>           <num> #> 1:  0.00007117650             0      7.392679    0.010222802             0       0.3553107 #> 2:  0.00009448864             0     14.281910    0.014485890             0       0.7040333 #> 3:  0.00001299674             0     24.308574    0.001821158             0       0.9473936 #> 4:  0.00010191595             0     14.518771    0.015352095             0       0.7060111 #> 5:  0.00001283228             0     23.060943    0.001892115             0       1.0269189 #> 6:  0.00008869032             0     14.474964    0.013278806             0       0.7019839 #>    C_fert_hat_ha C_fuel_hat_ha C_chem_hat_ha A_total_cropped_ha FBP_pfe_hat_ha farmland_per_cell #>            <num>         <num>         <num>              <num>          <num>             <num> #> 1:  0.0007795925     0.4282799  0.0002169123     0.000001588013       2.142158          62.26270 #> 2:  0.0670951492     0.5663560  0.0212989625     0.000144292922       6.679382          61.71605 #> 3:  0.1475929946     0.9244438  0.0398376851     0.000296036096      16.185389          61.82964 #> 4:  0.0764850563     0.5688555  0.0223214940     0.000151675639       7.711993          72.85995 #> 5:  0.1592835324     0.8337981  0.0416492516     0.000316535762      10.294743          61.82964 #> 6:  0.0997758317     0.5575842  0.0293469147     0.000201161236       7.101658          61.71605 #>       lon    lat #>     <num>  <num> #> 1: 142.60 -10.75 #> 2: 136.75 -11.05 #> 3: 132.90 -11.15 #> 4: 136.70 -11.20 #> 5: 133.45 -11.60 #> 6: 136.25 -11.60"},{"path":"https://adamhsparks.github.io/read.abares/articles/read.abares.html","id":"working-with-the-soil-thickness-map","dir":"Articles","previous_headings":"","what":"Working With the Soil Thickness Map","title":"read.abares","text":"can download soil depth map import {stars} terra::rast() object. convenience, {read.abares} re-exports terra::plot(), can just use plot() {terra} objects {read.abares}.","code":"library(read.abares) get_soil_thickness(cache = TRUE) |>   read_soil_thickness_stars() #> stars object with 2 dimensions and 1 attribute #> attribute(s), summary of first 100000 cells: #>         Min. 1st Qu. Median Mean 3rd Qu. Max.   NA's #> thpk_1    NA      NA     NA  NaN      NA   NA 100000 #> dimension(s): #>   from   to offset delta refsys x/y #> x    1 4150  112.5  0.01 WGS 84 [x] #> y    1 3401 -9.995 -0.01 WGS 84 [y]  x <- get_soil_thickness(cache = TRUE) |>   read_soil_thickness_terra() plot(x)"},{"path":"https://adamhsparks.github.io/read.abares/articles/read.abares.html","id":"soil-thickness-metadata","dir":"Articles","previous_headings":"Working With the Soil Thickness Map","what":"Soil Thickness Metadata","title":"read.abares","text":"default, brief bit metadata printed console call soil thickness object R session. , {read.abares} provides function browse soil thickness metadata console. can also access directly use pander::pander() include document like vignette. Dataset ANZLIC ID ANZCW1202000149 Title Soil Thickness Australian areas intensive agriculture Layer 1 (Horizon - top-soil) (derived soil mapping) Custodian CSIRO, Land & Water Jurisdiction Australia Description Abstract Surface predicted Thickness soil layer 1 (Horizon - top-soil) surface intensive agricultural areas Australia. Data modelled area based observations made soil agencies State CSIRO presented .0.01 degree grid cells. Topsoils (horizons) defined surface soil layers organic matter accumulates, may include dominantly organic surface layers (O P horizons). depth topsoil important , higher organic matter contents, topsoils (horizon) generally suitable properties agriculture, including higher permeability higher levels soil nutrients. Estimates soil depths needed calculate amount soil constituent either volume mass terms (bulk density also needed) - example, volume water stored rooting zone potentially available plant use, assess total stores soil carbon Greenhouse inventory assess total stores nutrients. pattern soil depth strongly related topography - shape slope land. Deeper soils typically found river valleys soils accumulate floodplains footslopes ranges (zones deposition), soils hillslopes (zones erosion) tend shallow. Map thickness topsoil derived soil map data interpreted tables soil properties specific soil groups. quality data soil depth existing soil profile datasets questionable thickness soil horizons varies locally topography, values map units general averages. final ASRIS polygon attributed surfaces mosaic data obtained various state federal agencies. surfaces constructed best available soil survey information available time. surfaces also rely number assumptions. One area weighted mean good estimate soil attributes polygon map-unit. Another assumption made look-tables provided McKenzie et al. (2000), state territories accurately depict soil attribute values soil type. accuracy maps dependent scale original polygon data sets level soil survey taken place state. scale various soil maps used deriving map available accessing data-source grid, scale used assessment likely accuracy modelling. Atlas Australian Soils considered least accurate dataset therefore used state based data. state datasets Western Australian sub-systems, South Australian land systems NSW soil landscapes reconnaissance mapping reliable based scale. NSW soil landscapes reconnaissance mapping use one dominant soil type per polygon estimation attributes. South Australia Western Australia use several soil types per polygon map-unit. digital map data provided geographical coordinates based World Geodetic System 1984 (WGS84) datum. raster data set grid resolution 0.001 degrees (approximately equivalent 1.1 km). data set product National Land Water Resources Audit (NLWRA) base dataset. Search Word(s) AGRICULTURE SOIL Physics Models Geographic Extent Name(s) GEN Category GEN Custodial Jurisdiction GEN Name Geographic Bounding Box North Bounding Latitude -10.707149 South Bounding Latitude -43.516831 East Bounding Longitude 113.19673 West Bounding Longitude 153.990779 Geographic Extent Polygon(s) 115.0 -33.5,115.7 -33.3,115.7 -31.7,113.2 -26.2,113.5 -25.4,114.1 -26.4,114.3 -26.0,113.4 -24.3,114.1 -21.8,122.3 -18.2,122.2 -17.2,126.7 -13.6,129.1 -14.9,130.6 -12.3,132.6 -12.1,132.5 -11.6,131.9 -11.3,132.0 -11.1,137.0 -12.2,135.4 -14.7,140.0 -17.7,140.8 -17.4,141.7 -15.1,141.4 -13.7,142.2 -10.9,142.7 -10.7,143.9 -14.5,144.6 -14.1,145.3 -14.9,146.3 -18.8,148.9 -20.5,150.9 -22.6,153.2 -25.9,153.7 -28.8,153.0 -31.3,150.8 -34.8,150.0 -37.5,147.8 -37.9,146.3 -39.0,144.7 -38.4,143.5 -38.8,141.3 -38.4,139.7 -37.3,139.7 -36.9,139.9 -36.7,138.9 -35.5,138.1 -35.7,138.6 -34.7,138.1 -34.2,137.8 -35.1,136.9 -35.3,137.0 -34.9,137.5 -34.9,137.4 -34.0,137.9 -33.5,137.8 -32.6,137.3 -33.6,135.9 -34.7,136.1 -34.8,136.0 -35.0,135.1 -34.6,135.2 -34.5,135.4 -34.5,134.7 -33.3,134.0 -32.9,133.7 -32.1,133.3 -32.2,132.2 -32.0,131.3 -31.5,127.3 -32.3,126.0 -32.3,123.6 -33.9,123.2 -34.0,122.1 -34.0,121.9 -33.8,119.9 -34.0,119.6 -34.4,118.0 -35.1,116.0 -34.8,115.0 -34.3,115.0 -33.5 147.8 -42.9,147.9 -42.6,148.2 -42.1,148.3 -42.3,148.3 -41.3,148.3 -41.0,148.0 -40.7,147.4 -41.0,146.7 -41.1,146.6 -41.2,146.5 -41.1,146.4 -41.2,145.3 -40.8,145.3 -40.7,145.2 -40.8,145.2 -40.8,145.2 -40.8,145.0 -40.8,144.7 -40.7,144.7 -41.2,145.2 -42.2,145.4 -42.2,145.5 -42.4,145.5 -42.5,145.2 -42.3,145.5 -43.0,146.0 -43.3,146.0 -43.6,146.9 -43.6,146.9 -43.5,147.1 -43.3,147.0 -43.1,147.2 -43.3,147.3 -42.8,147.4 -42.9,147.6 -42.8,147.5 -42.8,147.8 -42.9,147.9 -43.0,147.7 -43.0,147.8 -43.2,147.9 -43.2,147.9 -43.2,148.0 -43.2,148.0 -43.1,148.0 -42.9,147.8 -42.9 136.7 -13.8,136.7 -13.7,136.6 -13.7,136.6 -13.8,136.4 -13.8,136.4 -14.1,136.3 -14.2,136.9 -14.3,137.0 -14.2,136.9 -14.2,136.7 -14.1,136.9 -13.8,136.7 -13.8,136.7 -13.8 139.5 -16.6,139.7 -16.5,139.4 -16.5,139.2 -16.7,139.3 -16.7,139.5 -16.6 153.0 -25.2,153.0 -25.7,153.1 -25.8,153.4 -25.0,153.2 -24.7,153.2 -25.0,153.0 -25.2 137.5 -36.1,137.7 -35.9,138.1 -35.9,137.9 -35.7,137.6 -35.7,137.6 -35.6,136.6 -35.8,136.7 -36.1,137.2 -36.0,137.5 -36.1 143.9 -39.7,144.0 -39.6,144.1 -39.8,143.9 -40.2,143.9 -40.0,143.9 -39.7 148.0 -39.7,147.7 -39.9,147.9 -39.9,148.0 -40.1,148.1 -40.3,148.3 -40.2,148.3 -40.0,148.0 -39.7 148.1 -40.4,148.0 -40.4,148.4 -40.3,148.4 -40.5,148.1 -40.4 130.4 -11.3,130.4 -11.2,130.6 -11.3,130.7 -11.4,130.9 -11.3,131.0 -11.4,131.1 -11.3,131.2 -11.4,131.3 -11.2,131.5 -11.4,131.5 -11.5,131.0 -11.9,130.8 -11.8,130.6 -11.7,130.0 -11.8,130.1 -11.7,130.3 -11.7,130.1 -11.5,130.4 -11.3 Data Currency Beginning date 1999-09-01 Ending date 2001-03-31 Dataset Status Progress COMPLETE Maintenance Update Frequency PLANNED Access Stored Data Format DIGITAL - ESRI Arc/Info integer GRID Available Format Type DIGITAL - ESRI Arc/Info integer GRID Access Constraint Subject terms & condition data access & management agreement National Land & Water Audit ANZLIC parties Data Quality Lineage soil attribute surface created using following datasets 1. digital polygon coverage Soil-Landforms Murray Darling Basis (MDBSIS)(Bui et al. 1998), classified principal profile forms (PPF’s) (Northcote 1979). 2. digital Atlas Australian Soils (Northcote et al.1960-1968)(Leahy, 1993). 3. Western Australia land systems coverage (Agriculture WA). 4. Western Australia sub-systems coverage (Agriculture WA). 5. Ord river catchment soils coverage (Agriculture WA). 6. Victoria soils coverage (Victorian Department Natural Resources Environment - NRE). 7. NSW Soil Landscapes reconnaissance soil landscape mapping (NSW Department Land Water Conservation - DLWC). 8. New South Wales Land systems west (NSW Department Land Water Conservation - DLWC). 9. South Australia soil land-systems (Primary Industries Resources South Australia - PIRSA). 10. Northern Territory soils coverage (Northern Territory Department Lands, Planning Environment). 11. mosaic Queensland soils coverages (Queensland Department Natural Resources - QDNR). 12. look-table linking PPF values Atlas Australian Soils interpreted soil attributes (McKenzie et al. 2000). 13. Look_up tables provided WA Agriculture linking WA soil groups interpreted soil attributes. 14. Look_up tables provided PIRSA linking SA soil groups interpreted soil attributes. continuous raster surface representing Thickness soil layer 1 created combining national state level digitised land systems maps soil surveys linked look-tables listing soil type corresponding attribute values. thickness used sparingly Factual Key, estimations thickness look-tables made using empirical correlations particular soil types. estimate soil attribute one soil type given polygon map-unit, soil attribute values related soil type look-table weighted according area occupied soil type within polygon map-unit. final soil attribute values area weighted average polygon map-unit. polygon data converted continuous raster surface using soil attribute values calculated polygon. ASRIS soil attribute surfaces created using polygon attribution relied number data sets various state agencies. polygon data set turned continuous surface grid based calculated soil attribute value polygon. grids merged basis , available, state data replaced Atlas Australian Soils MDBSIS. MDBSIS derived soil attribute values restricted areas MDBSIS deemed accurate Atlas Australian Soils (see Carlile et al (2001a). cases soil type missing look-table layer 2 exist soil type, percent area soils remaining adjusted prior calculating final soil attribute value. method used attribute polygons dependent data supplied individual State agencies. modelled grid resampled 0.0025 degree cells 0.01 degree cells using bilinear interpolation Positional Accuracy predictive surface 0.01 X 0.01 degree grid locational accurate 1m. positional accuracy defining polygons variable positional accuracy locations expected within 100m recorded location. vertical accuracy relevant. positional assessment made considering tools used generate locational information contacting data providers. parameters used production led surface range positional accuracy ranging + - 50 m + - kilometres. contribute loss attribute accuracy surface. Attribute Accuracy Input attribute accuracy areas highly variable. predictive variable much lower attribute accuracy due irregular distribution limited positional accuracy parameters used modelling. several sources error estimating soil depth thickness horizons look-tables. thickness used sparingly Factual Key, estimations thickness look-tables made using empirical correlations particular soil types. quality data soil depth existing soil profile datasets questionable, soil mapping, thickness soil horizons varies locally topography, values map units general averages. definition depth soil regolith imprecise can difficult determine lower limit soil. assumption made area weighted mean soil attribute values based soil type good estimation soil property debatable, supply soil attribute value given location. Rather designed show national regional patterns soil properties. use surfaces farm catchment scale modelling may prove inaccurate. Also use look-tables attribute soil types accurate number observations used estimate attribute value soil type. soil types look-tables may observations, yet average attribute value still taken attribute value soil type. Different states using different taxonomic schemes making national soil database difficult. Another downfall area weighted approach soil types may listed look-tables. soil type dominant one within polygon map-unit, listed within look-table attributed within look-table final soil attribute value polygon biased towards minor soil types exist. may also happen large area occupied soil type B horizon. case final soil attribute value area weighted soils B horizon, ignoring major soil type within polygon map-unit. layer 2 surfaces large areas -data soils listed particular map-unit polygon B horizon. Logical Consistency Surface fully logically consistent one parameter shown, predicted average Soil Thickness within grid cell Completeness Surface nearly complete. areas (%1 missing) insufficient parameters known provide useful prediction thus attributes absent areas. Contact Information Contact Organisation (s) CSIRO, Land & Water Contact Position Project Leader Mail Address ACLEP, GPO 1666 Locality Canberra State ACT Country AUSTRALIA Postcode 2601 Telephone 02 6246 5922 Facsimile 02 6246 5965 Electronic Mail Address neil.mckenzie@cbr.clw.csiro.au Metadata Date Metadata Date 2001-07-01 Additional Metadata Additional Metadata Entity Attributes Entity Name Soil Thickness Layer 1 (derived mapping) Entity description Estimated Soil Thickness (mm) Layer 1 cell cell basis Feature attribute name VALUE Feature attribute definition Predicted average Thickness (mm) soil layer 1 0.01 X 0.01 degree quadrat Data Type Spatial representation type RASTER Projection Map projection GEOGRAPHIC Datum WGS84 Map units DECIMAL DEGREES Scale Scale/ resolution 1:1 000 000 Usage Purpose Estimates soil depths needed calculate amount soil constituent either volume mass terms (bulk density also needed) - example, volume water stored rooting zone potentially available plant use, assess total stores soil carbon Greenhouse inventory assess total stores nutrients. Provide indications probable Thickness soil layer 1 agricultural areas soil thickness testing carried ","code":"library(read.abares) get_soil_thickness(cache = TRUE) #>  #> ── Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - top-soil) ── #>  #> ── Dataset ANZLIC ID ANZCW1202000149 ── #>  #> Feature attribute definition Predicted average Thickness (mm) of soil layer 1 in the 0.01 X 0.01 #> degree quadrat. #>  #> Custodian: CSIRO Land & Water #>  #> Jurisdiction Australia #>  #> Short Description The digital map data is provided in geographical coordinates based on the World #> Geodetic System 1984 (WGS84) datum. This raster data set has a grid resolution of 0.001 degrees #> (approximately equivalent to 1.1 km). #>  #> The data set is a product of the National Land and Water Resources Audit (NLWRA) as a base dataset. #>  #> Data Type: Spatial representation type RASTER #>  #> Projection Map: projection GEOGRAPHIC #>  #> Datum: WGS84 #>  #> Map Units: DECIMAL DEGREES #>  #> Scale: Scale/ resolution 1:1 000 000 #>  #> Usage Purpose Estimates of soil depths are needed to calculate the amount of any soil constituent #> in either volume or mass terms (bulk density is also needed) - for example, the volume of water #> stored in the rooting zone potentially available for plant use, to assess total stores of soil #> carbon for greenhouse inventory or to assess total stores of nutrients. #>  #> Provide indications of probable thickness soil layer 1 in agricultural areas where soil thickness #> testing has not been carried out. #>  #> Use Limitation: This dataset is bound by the requirements set down by the National Land & Water #> Resources Audit #> To see the full metadata, call `print_soil_thickness_metadata()` on a soil thickness object in your #> R session. library(read.abares) get_soil_thickness(cache = TRUE) |>   print_soil_thickness_metadata() #>  #> ── Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - top-soil) ── #>  #> ── Dataset ANZLIC ID ANZCW1202000149 ── #>  #> Dataset ANZLIC ID ANZCW1202000149 #>  #> Title Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - #> top-soil) (derived from soil mapping) #>  #> Custodian CSIRO, Land & Water #>  #> Jurisdiction Australia #>  #> Description Abstract Surface of predicted Thickness of soil layer 1 (A Horizon - top-soil) surface #> for the intensive agricultural areas of Australia.  Data modelled from area based observations made #> by soil agencies both State and CSIRO and presented as .0.01 degree grid cells. #>  #> Topsoils (A horizons) are defined as the surface soil layers in which organic matter accumulates, #> and may include dominantly organic surface layers (O and P horizons). #>  #> The depth of topsoil is important because, with their higher organic matter contents, topsoils (A #> horizon) generally have more suitable properties for agriculture, including higher permeability and #> higher levels of soil nutrients. #>  #> Estimates of soil depths are needed to calculate the amount of any soil constituent in either #> volume or mass terms (bulk density is also needed) - for example, the volume of water stored in the #> rooting zone potentially available for plant use, to assess total stores of soil carbon for #> Greenhouse inventory or to assess total stores of nutrients. #>  #> The pattern of soil depth is strongly related to topography - the shape and slope of the land. #> Deeper soils are typically found in the river valleys where soils accumulate on floodplains and at #> the footslopes of ranges (zones of deposition), while soils on hillslopes (zones of erosion) tend #> to be shallow.  Map of thickness of topsoil was derived from soil map data and interpreted tables #> of soil properties for specific soil groups. #>  #> The quality of data on soil depth in existing soil profile datasets is questionable and as the #> thickness of soil horizons varies locally with topography, values for map units are general #> averages. #>  #> The final ASRIS polygon attributed surfaces are a mosaic of all of the data obtained from various #> state and federal agencies. The surfaces have been constructed with the best available soil survey #> information available at the time. The surfaces also rely on a number of assumptions. One being #> that an area weighted mean is a good estimate of the soil attributes for that polygon or map-unit. #> Another assumption made is that the look-up tables provided by McKenzie et al. (2000), state and #> territories accurately depict the soil attribute values for each soil type. #>  #> The accuracy of the maps is most dependent on the scale of the original polygon data sets and the #> level of soil survey that has taken place in each state.  The scale of the various soil maps used #> in deriving this map is available by accessing the data-source grid, the scale is used as an #> assessment of the likely accuracy of the modelling.  The Atlas of Australian Soils is considered to #> be the least accurate dataset and has therefore only been used where there is no state based data. #> Of the state datasets Western Australian sub-systems, South Australian land systems and NSW soil #> landscapes and reconnaissance mapping would be the most reliable based on scale. NSW soil #> landscapes and reconnaissance mapping use only one dominant soil type per polygon in the estimation #> of attributes.  South Australia and Western Australia use several soil types per polygon or #> map-unit. #>  #> The digital map data is provided in geographical coordinates based on the World Geodetic System #> 1984 (WGS84) datum. This raster data set has a grid resolution of 0.001 degrees (approximately #> equivalent to 1.1 km). #>  #> The data set is a product of the National Land and Water Resources Audit (NLWRA) as a base dataset. #>  #> Search Word(s) AGRICULTURE SOIL Physics Models #>  #> Geographic Extent Name(s) GEN Category #>  #> GEN Custodial Jurisdiction #>  #> GEN Name #>  #> Geographic Bounding Box North Bounding Latitude -10.707149 South Bounding Latitude -43.516831 East #> Bounding Longitude 113.19673 West Bounding Longitude 153.990779 #>  #> Geographic Extent Polygon(s) 115.0 -33.5,115.7 -33.3,115.7 -31.7,113.2 -26.2,113.5 -25.4,114.1 #> -26.4,114.3 -26.0,113.4 -24.3,114.1 -21.8,122.3 -18.2,122.2 -17.2,126.7 -13.6,129.1 -14.9,130.6 #> -12.3,132.6 -12.1,132.5 -11.6,131.9 -11.3,132.0 -11.1,137.0 -12.2,135.4 -14.7,140.0 -17.7,140.8 #> -17.4,141.7 -15.1,141.4 -13.7,142.2 -10.9,142.7 -10.7,143.9 -14.5,144.6 -14.1,145.3 -14.9,146.3 #> -18.8,148.9 -20.5,150.9 -22.6,153.2 -25.9,153.7 -28.8,153.0 -31.3,150.8 -34.8,150.0 -37.5,147.8 #> -37.9,146.3 -39.0,144.7 -38.4,143.5 -38.8,141.3 -38.4,139.7 -37.3,139.7 -36.9,139.9 -36.7,138.9 #> -35.5,138.1 -35.7,138.6 -34.7,138.1 -34.2,137.8 -35.1,136.9 -35.3,137.0 -34.9,137.5 -34.9,137.4 #> -34.0,137.9 -33.5,137.8 -32.6,137.3 -33.6,135.9 -34.7,136.1 -34.8,136.0 -35.0,135.1 -34.6,135.2 #> -34.5,135.4 -34.5,134.7 -33.3,134.0 -32.9,133.7 -32.1,133.3 -32.2,132.2 -32.0,131.3 -31.5,127.3 #> -32.3,126.0 -32.3,123.6 -33.9,123.2 -34.0,122.1 -34.0,121.9 -33.8,119.9 -34.0,119.6 -34.4,118.0 #> -35.1,116.0 -34.8,115.0 -34.3,115.0 -33.5 #>  #> 147.8 -42.9,147.9 -42.6,148.2 -42.1,148.3 -42.3,148.3 -41.3,148.3 -41.0,148.0 -40.7,147.4 #> -41.0,146.7 -41.1,146.6 -41.2,146.5 -41.1,146.4 -41.2,145.3 -40.8,145.3 -40.7,145.2 -40.8,145.2 #> -40.8,145.2 -40.8,145.0 -40.8,144.7 -40.7,144.7 -41.2,145.2 -42.2,145.4 -42.2,145.5 -42.4,145.5 #> -42.5,145.2 -42.3,145.5 -43.0,146.0 -43.3,146.0 -43.6,146.9 -43.6,146.9 -43.5,147.1 -43.3,147.0 #> -43.1,147.2 -43.3,147.3 -42.8,147.4 -42.9,147.6 -42.8,147.5 -42.8,147.8 -42.9,147.9 -43.0,147.7 #> -43.0,147.8 -43.2,147.9 -43.2,147.9 -43.2,148.0 -43.2,148.0 -43.1,148.0 -42.9,147.8 -42.9 #>  #> 136.7 -13.8,136.7 -13.7,136.6 -13.7,136.6 -13.8,136.4 -13.8,136.4 -14.1,136.3 -14.2,136.9 #> -14.3,137.0 -14.2,136.9 -14.2,136.7 -14.1,136.9 -13.8,136.7 -13.8,136.7 -13.8 #>  #> 139.5 -16.6,139.7 -16.5,139.4 -16.5,139.2 -16.7,139.3 -16.7,139.5 -16.6 #>  #> 153.0 -25.2,153.0 -25.7,153.1 -25.8,153.4 -25.0,153.2 -24.7,153.2 -25.0,153.0 -25.2 #>  #> 137.5 -36.1,137.7 -35.9,138.1 -35.9,137.9 -35.7,137.6 -35.7,137.6 -35.6,136.6 -35.8,136.7 #> -36.1,137.2 -36.0,137.5 -36.1 #>  #> 143.9 -39.7,144.0 -39.6,144.1 -39.8,143.9 -40.2,143.9 -40.0,143.9 -39.7 #>  #> 148.0 -39.7,147.7 -39.9,147.9 -39.9,148.0 -40.1,148.1 -40.3,148.3 -40.2,148.3 -40.0,148.0 -39.7 #>  #> 148.1 -40.4,148.0 -40.4,148.4 -40.3,148.4 -40.5,148.1 -40.4 #>  #> 130.4 -11.3,130.4 -11.2,130.6 -11.3,130.7 -11.4,130.9 -11.3,131.0 -11.4,131.1 -11.3,131.2 #> -11.4,131.3 -11.2,131.5 -11.4,131.5 -11.5,131.0 -11.9,130.8 -11.8,130.6 -11.7,130.0 -11.8,130.1 #> -11.7,130.3 -11.7,130.1 -11.5,130.4 -11.3 #>  #> Data Currency Beginning date 1999-09-01 #>  #> Ending date 2001-03-31 #>  #> Dataset Status Progress COMPLETE #>  #> Maintenance and Update Frequency NOT PLANNED #>  #> Access Stored Data Format DIGITAL - ESRI Arc/Info integer GRID #>  #> Available Format Type DIGITAL - ESRI Arc/Info integer GRID #>  #> Access Constraint Subject to the terms & condition of the data access & management agreement #> between the National Land & Water Audit and ANZLIC parties #>  #> Data Quality Lineage The soil attribute surface was created using the following datasets 1. The #> digital polygon coverage of the Soil-Landforms of the Murray Darling Basis (MDBSIS)(Bui et al. #> 1998), classified as principal profile forms (PPF's) (Northcote 1979). 2. The digital Atlas of #> Australian Soils (Northcote et al.1960-1968)(Leahy, 1993). 3. Western Australia land systems #> coverage (Agriculture WA). 4. Western Australia sub-systems coverage (Agriculture WA). 5. Ord river #> catchment soils coverage (Agriculture WA). 6. Victoria soils coverage (Victorian Department of #> Natural Resources and Environment - NRE). 7. NSW Soil Landscapes and reconnaissance soil landscape #> mapping (NSW Department of Land and Water Conservation - DLWC). 8. New South Wales Land systems #> west (NSW Department of Land and Water Conservation - DLWC). 9. South Australia soil land-systems #> (Primary Industries and Resources South Australia - PIRSA). 10. Northern Territory soils coverage #> (Northern Territory Department of Lands, Planning and Environment). 11. A mosaic of Queensland #> soils coverages (Queensland Department of Natural Resources - QDNR). 12. A look-up table linking #> PPF values from the Atlas of Australian Soils with interpreted soil attributes (McKenzie et al. #> 2000). 13. Look_up tables provided by WA Agriculture linking WA soil groups with interpreted soil #> attributes. 14. Look_up tables provided by PIRSA linking SA soil groups with interpreted soil #> attributes. #>  #> The continuous raster surface representing Thickness of soil layer 1 was created by combining #> national and state level digitised land systems maps and soil surveys linked to look-up tables #> listing soil type and corresponding attribute values. #>  #> Because thickness is used sparingly in the Factual Key, estimations of thickness in the look-up #> tables were made using empirical correlations for particular soil types. #>  #> To estimate a soil attribute where more than one soil type was given for a polygon or map-unit, the #> soil attribute values related to each soil type in the look-up table were weighted according to the #> area occupied by that soil type within the polygon or map-unit. The final soil attribute values are #> an area weighted average for a polygon or map-unit.  The polygon data was then converted to a #> continuous raster surface using the soil attribute values calculated for each polygon. #>  #> The ASRIS soil attribute surfaces created using polygon attribution relied on a number of data sets #> from various state agencies.  Each polygon data set was turned into a continuous surface grid based #> on the calculated soil attribute value for that polygon.  The grids where then merged on the basis #> that, where available, state data replaced the Atlas of Australian Soils and MDBSIS.  MDBSIS #> derived soil attribute values were restricted to areas where MDBSIS was deemed to be more accurate #> that the Atlas of Australian Soils (see Carlile et al (2001a). #>  #> In cases where a soil type was missing from the look-up table or layer 2 did not exist for that #> soil type, the percent area of the soils remaining were adjusted prior to calculating the final #> soil attribute value. The method used to attribute polygons was dependent on the data supplied by #> individual State agencies. #>  #> The modelled grid was resampled from 0.0025 degree cells to 0.01 degree cells using bilinear #> interpolation #>  #> Positional Accuracy The predictive surface is a 0.01 X 0.01 degree grid and has a locational #> accurate of about 1m. #>  #> The positional accuracy of the defining polygons have variable positional accuracy most locations #> are expected to be within 100m of the recorded location.  The vertical accuracy is not relevant. #> The positional assessment has been made by considering the tools used to generate the locational #> information and contacting the data providers. #>  #> The other parameters used in the production of the led surface have a range of positional accuracy #> ranging from + - 50 m to + - kilometres.  This contribute to the loss of attribute accuracy in the #> surface. #>  #> Attribute Accuracy Input attribute accuracy for the areas is highly variable.  The predictive has a #> variable and much lower attribute accuracy due to the irregular distribution and the limited #> positional accuracy of the parameters used for modelling. #>  #> There are several sources of error in estimating soil depth and thickness of horizons for the #> look-up tables.  Because thickness is used sparingly in the Factual Key, estimations of thickness #> in the look-up tables were made using empirical correlations for particular soil types.  The #> quality of data on soil depth in existing soil profile datasets is questionable, in soil mapping, #> thickness of soil horizons varies locally with topography, so values for map units are general #> averages.  The definition of the depth of soil or regolith is imprecise and it can be difficult to #> determine the lower limit of soil. #>  #> The assumption made that an area weighted mean of soil attribute values based on soil type is a #> good estimation of a soil property is debatable, in that it does not supply the soil attribute #> value at any given location. Rather it is designed to show national and regional patterns in soil #> properties. The use of the surfaces at farm or catchment scale modelling may prove inaccurate. Also #> the use of look-up tables to attribute soil types is only as accurate as the number of observations #> used to estimate a attribute value for a soil type. Some soil types in the look-up tables may have #> few observations, yet the average attribute value is still taken as the attribute value for that #> soil type. Different states are using different taxonomic schemes making a national soil database #> difficult. Another downfall of the area weighted approach is that some soil types may not be listed #> in look-up tables. If a soil type is a dominant one within a polygon or map-unit, but is not listed #> within the look-up table or is not attributed within the look-up table then the final soil #> attribute value for that polygon will be biased towards the minor soil types that do exist. This #> may also happen when a large area is occupied by a soil type which has no B horizon. In this case #> the final soil attribute value will be area weighted on the soils with a B horizon, ignoring a #> major soil type within that polygon or map-unit. The layer 2 surfaces have large areas of no-data #> because all soils listed for a particular map-unit or polygon had no B horizon. #>  #> Logical Consistency Surface is fully logically consistent as only one parameter is shown, as #> predicted average Soil Thickness within each grid cell #>  #> Completeness Surface is nearly complete.  There are some areas (about %1 missing) for which #> insufficient parameters were known to provide a useful prediction and thus attributes are absent in #> these areas. #>  #> Contact Information Contact Organisation (s) CSIRO, Land & Water #>  #> Contact Position Project Leader #>  #> Mail Address ACLEP, GPO 1666 #>  #> Locality Canberra #>  #> State ACT #>  #> Country AUSTRALIA #>  #> Postcode 2601 #>  #> Telephone 02 6246 5922 #>  #> Facsimile 02 6246 5965 #>  #> Electronic Mail Address neil.mckenzie@cbr.clw.csiro.au #>  #> Metadata Date Metadata Date 2001-07-01 #>  #> Additional Metadata Additional Metadata #>  #> Entity and Attributes Entity Name Soil Thickness Layer 1 (derived from mapping) #>  #> Entity description Estimated Soil Thickness (mm) of Layer 1 on a cell by cell basis #>  #> Feature attribute name VALUE #>  #> Feature attribute definition Predicted average Thickness (mm) of soil layer 1 in the 0.01 X 0.01 #> degree quadrat #>  #> Data Type Spatial representation type RASTER #>  #> Projection Map projection GEOGRAPHIC #>  #> Datum WGS84 #>  #> Map units DECIMAL DEGREES #>  #> Scale Scale/ resolution 1:1 000 000 #>  #> Usage Purpose Estimates of soil depths are needed to calculate the amount of any soil constituent #> in either volume or mass terms (bulk density is also needed) - for example, the volume of water #> stored in the rooting zone potentially available for plant use, to assess total stores of soil #> carbon for Greenhouse inventory or to assess total stores of nutrients. #>  #> Provide indications of probable Thickness soil layer 1 in agricultural areas where soil thickness #> testing has not been carried out #>  #> Use Use Limitation This dataset is bound by the requirements set down by the National Land & Water #> Resources Audit library(read.abares) library(pander) x <- get_soil_thickness(cache = TRUE) y <- x$metadata pander(y)"},{"path":"https://adamhsparks.github.io/read.abares/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Adam H. Sparks. Maintainer, author. Jacob. Contributor.            Assisted troubleshooting formatting documentation display '<' '>' properly Curtin University Technology. Copyright holder.           Provided support Adam Sparks's time. Grains Research Development Corporation. Funder, copyright holder.           GRDC Project CUR2210-005OPX (AAGI-CU)","code":""},{"path":"https://adamhsparks.github.io/read.abares/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Sparks (????). read.abares: Simple downloading importing ABARES Data. R package version 1.0.0, https://adamhsparks.github.io/read.abares/.","code":"@Manual{,   title = {{read.abares}: Simple downloading and importing of ABARES Data},   author = {Adam H. Sparks},   note = {R package version 1.0.0},   url = {https://adamhsparks.github.io/read.abares/}, }"},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"readabares-simple-downloading-and-importing-of-abares-data-","dir":"","previous_headings":"","what":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"R package automated downloading ingestion data Australian Bureau Agricultural Resource Economics Sciences. ABARES data serviced. list hand-picked reasonably useful maintainable, .e., frequently updated values included , e.g., Australian crop reports. However, data set feel useful serviced {read.abares}, please feel free open issue details data set better yet, open pull request! Data serviced include: ABARES Estimates; Australian Gridded Farm Data (AGFD) set; Australian Agricultural Grazing Industries Survey (AAGIS) region mapping files; Historical Agricultural Forecast Database; Soil Thickness Australian areas intensive agriculture Layer 1 (Horizon - top-soil) (derived soil mapping) map ; trade data ; trade region data. files freely available CSV files, zip archives NetCDF files zip archives geospatial shape files. {read.abares} facilitates downloading, caching importing files R session choice class resulting object(s).","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"installation","dir":"","previous_headings":"Get Started","what":"Installation","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"{read.abares} available CRAN (yet). can install like :","code":"if (!require(\"remotes\"))   install.packages(\"remotes\") remotes::install_git(\"https://github.com/adamhsparks/read.abares\")"},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"caching","dir":"","previous_headings":"Features","what":"Caching","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"{read.abares} supports caching files using tools::R_user_dir(package = \"read.abares\", = \"cache\") save files standardised location across platforms don’t worry files went ’re still . requesting files, {read.abares} first check available locally either cached temporary storage. Caching mandatory, can just work downloaded files tempdir(), cleaned R session ends.","code":""},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"multiple-classes-supported","dir":"","previous_headings":"Features","what":"Multiple Classes Supported","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"{read.abares} supports multiple classes objects support workflow. Select spatial classes AGFD NetCDF files: {stars}, {terra} {tidync} data.frame (data.table) objects: {data.table}","code":""},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"metadata","dir":"","previous_headings":"","what":"Metadata","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"Please report issues bugs. License: MIT","code":""},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"citations","dir":"","previous_headings":"Metadata","what":"Citations","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"Citing data: Please refer ABARES website, https://www.agriculture.gov.au/abares/products/citations, cite data use . Citing {read.abares}: citing use package, please use,","code":"library(\"read.abares\") #>  #> Attaching package: 'read.abares' #> The following object is masked from 'package:graphics': #>  #>     plot #> The following object is masked from 'package:base': #>  #>     plot citation(\"read.abares\") #> To cite package 'read.abares' in publications use: #>  #>   Sparks A (????). _read.abares: Simple downloading and importing of #>   ABARES Data_. R package version 1.0.0, #>   <https://adamhsparks.github.io/read.abares/>. #>  #> A BibTeX entry for LaTeX users is #>  #>   @Manual{, #>     title = {{read.abares}: Simple downloading and importing of ABARES Data}, #>     author = {Adam H. Sparks}, #>     note = {R package version 1.0.0}, #>     url = {https://adamhsparks.github.io/read.abares/}, #>   }"},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"a-note-on-testing","dir":"","previous_headings":"Metadata > Contributing","what":"A Note on Testing","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"’ve aimed make testing package complete possible. files downloaded >1GB may take several minutes hour download due size, wish include package . Therefore, tests rely already downloaded locally cached files. wish work development {read.abares} please aware take time establish local cache testing somewhat faster. considering including pared examples tests data released CC 4.0 License, now opted just use locally cached data simplicity.","code":""},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"code-of-conduct","dir":"","previous_headings":"Metadata","what":"Code of Conduct","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"Please note {read.abares} project released Contributor Code Conduct. contributing project, agree abide terms.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/clear_cache.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove Files in Users' Cache Directory — clear_cache","title":"Remove Files in Users' Cache Directory — clear_cache","text":"Removes files read.abares cache exist.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/clear_cache.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove Files in Users' Cache Directory — clear_cache","text":"","code":"clear_cache()"},{"path":"https://adamhsparks.github.io/read.abares/reference/clear_cache.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove Files in Users' Cache Directory — clear_cache","text":"Nothing, called side-effects, clearing cached files","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/clear_cache.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Remove Files in Users' Cache Directory — clear_cache","text":"","code":"# not run because cached files shouldn't exist on CRAN or testing envs if (FALSE) { # \\dontrun{ clear_cache() } # }"},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Australian Gridded Farm Data for Local Use — get_agfd","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"Downloads Australian Gridded Farm Data (AGFD) data unzips compressed files NetCDF importing.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"","code":"get_agfd(fixed_prices = TRUE, cache = TRUE)"},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"Historical climate prices fixed – https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1036161/3, Historical climate prices – https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1036161/2","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"fixed_prices Boolean Download historical climate prices historical climate fixed prices described  (Hughes et al. 2022). Defaults TRUE downloads data historical climate fixed prices “isolate effects climate variability financial incomes broadacre farm businesses” (ABARES 2024). Using TRUE download simulations global output input price indexes fixed values recently completed financial year. cache Boolean Cache Australian Gridded Farm Data files download using tools::R_user_dir identify proper directory storing user data cache package. Defaults TRUE, caching files locally. FALSE, function uses tempdir() files deleted upon closing R session.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"read.abares.agfd.nc.files object, list NetCDF files containing Australian Gridded Farm Data","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"ABARES website: “Australian Gridded Farm Data (AGFD) set national scale maps containing simulated data historical broadacre farm business outcomes including farm profitability 0.05-degree (approximately 5 km) grid. data produced ABARES part ongoing Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data.Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data. maps provide estimates farm business profit, revenue, costs production location (grid cell) year period 1990-91 2022-23. data include actual observed outcomes rather model predicted outcomes representative ‘typical’ broadacre farm businesses location considering likely farm characteristics prevailing weather conditions commodity prices.” – ABARES, 2024-11-25 sets data large file size, .e., >1GB, require time download.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"historical-climate-fixed-prices-","dir":"Reference","previous_headings":"","what":"Historical climate (fixed prices)","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"Historical climate (fixed prices) scenario similar described Hughes et al. (2022) intended isolate effects climate variability financial incomes broadacre farm businesses. simulations, global output input price indexes fixed values recently completed financial year. However, scenarios spread domestic global grain (wheat, barley sorghum) prices, along Australian fodder prices allowed vary response climate data (capture domestic increases grain fodder prices drought years, see Hughes et al. 2022). 33-year historical climate sequence (including historical simulated crop pasture data AADI project) simulated grid cell (1990-91 2022-23).","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"historical-climate-and-prices","dir":"Reference","previous_headings":"","what":"Historical climate and prices","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"part AADI project additional scenario developed accounting changes climate conditions output input prices (.e., global commodity market variability). Historical climate prices scenario 33-year reference period allows variation \\ historical climate conditions historical prices. scenario, historical price indexes de-trended, account consistent long- term trends real commodity prices (particularly sheep lamb). resulting simulation results percentile indicators intended reflect combined impacts annual climate commodity price variability.\" – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"data-files","dir":"Reference","previous_headings":"","what":"Data files","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"Simulation output data saved multilayer NetCDF files, named using following convention: f<farm year>.c<climate year>.p<price year>.t<technology year>.nc : <farm year> = Financial year farm business data used simulations. <climate year> = Financial year climate data used simulations. <price year> = Financial year output input prices used simulations. <technology year> = Financial year farm ‘technology’ (equal farm year simulations) financial years referred closing calendar year (e.g., 2022 = 1 July 2021 30 June 2022). – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"data-layers","dir":"Reference","previous_headings":"","what":"Data layers","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"data layers downloaded NetCDF files described Table 2 seen Australian Bureau Agricultural Resource Economics Sciences (2024). Following copy Table 2 convenience, please refer full document methods metadata.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"Australian gridded farm data, Australian Bureau Agricultural Resource Economics Sciences, Canberra, July 2024, DOI: 10.25814/7n6z-ev41. CC 4.0. N. Hughes, W.Y. Soh, C. Boult, K. Lawson, Defining drought perspective Australian farmers, Climate Risk Management, Volume 35, 2022, 100420, ISSN 2212-0963, DOI: 10.1016/j.crm.2022.100420.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"","code":"if (FALSE) { # interactive() get_agfd() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"Get Soil Thickness Australian Areas Intensive Agriculture Layer 1 Local Use","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"","code":"get_soil_thickness(cache = TRUE)"},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"https://anrdl-integration-web-catalog-saxfirxkxt.s3-ap-southeast-2.amazonaws.com/warehouse/staiar9cl__059/staiar9cl__05911a01eg_geo___.zip","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"cache Boolean Cache soil thickness data files download using tools::R_user_dir() identify proper directory storing user data cache package. Defaults TRUE, caching files locally. FALSE, function uses tempdir() files deleted upon closing R session. custom print method provided print metadata associated data. Examples provided interacting metadata directly.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"read.abares.soil.thickness object, named list file path resulting ESRI Grid file text file metadata","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"https://data.agriculture.gov.au/geonetwork/srv/eng/catalog.search#/metadata/faa9f157-8e17-4b23-b6a7-37eb7920ead6","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"","code":"if (FALSE) { # interactive() x <- get_soil_thickness()  # View the metadata with pretty printing x  # Extract the metadata as an object in your R session and use it with # {pander}, useful for Markdown files  library(pander) y <- x$metadata pander(y) }"},{"path":"https://adamhsparks.github.io/read.abares/reference/inspect_cache.html","id":null,"dir":"Reference","previous_headings":"","what":"List the File Path to Users' Cache Directory — inspect_cache","title":"List the File Path to Users' Cache Directory — inspect_cache","text":"Check files exist read.abares file cache.  function always return full file names, .e., directory path prepended. See help file list.files() full.names argument. wish strip file path return directory file names, use basename(). See examples .","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/inspect_cache.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List the File Path to Users' Cache Directory — inspect_cache","text":"","code":"inspect_cache(recursive = FALSE)"},{"path":"https://adamhsparks.github.io/read.abares/reference/inspect_cache.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List the File Path to Users' Cache Directory — inspect_cache","text":"recursive Boolean value indicating whether list files subdirectories cache directory. Defaults FALSE returning top-level directories contained cache directory.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/inspect_cache.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List the File Path to Users' Cache Directory — inspect_cache","text":"list directories files cache","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/inspect_cache.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"List the File Path to Users' Cache Directory — inspect_cache","text":"","code":"# not run because cached files shouldn't exist on CRAN or testing envs if (FALSE) { # \\dontrun{ # list directories in cache only inspect_cache()  # list directory names, stripping the file path basename(inspect_cache)  # list all files in subdirectories of the cache inspect_cache(recursive = TRUE)  # list all files in subdirectories, stripping the file path basename(inspect_cache(recursive_true)) } # }"},{"path":"https://adamhsparks.github.io/read.abares/reference/print_agfd_nc_file_format.html","id":null,"dir":"Reference","previous_headings":"","what":"Prints File Format Information for the AGFD NetCDF Files — print_agfd_nc_file_format","title":"Prints File Format Information for the AGFD NetCDF Files — print_agfd_nc_file_format","text":"Print file format section 3.2 Australian Bureau Agricultural Resource Economics Sciences.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/print_agfd_nc_file_format.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prints File Format Information for the AGFD NetCDF Files — print_agfd_nc_file_format","text":"","code":"print_agfd_nc_file_format()"},{"path":"https://adamhsparks.github.io/read.abares/reference/print_agfd_nc_file_format.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Prints File Format Information for the AGFD NetCDF Files — print_agfd_nc_file_format","text":"https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1036161/0","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/print_agfd_nc_file_format.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Prints File Format Information for the AGFD NetCDF Files — print_agfd_nc_file_format","text":"Australian gridded farm data, Australian Bureau Agricultural Resource Economics Sciences, Canberra, July, DOI: <https://doi.org/10.25814/7n6z-ev41. CC 4.0.>","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/print_agfd_nc_file_format.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prints File Format Information for the AGFD NetCDF Files — print_agfd_nc_file_format","text":"","code":"print_agfd_nc_file_format() #> ──────────────────────────────────────────────────────────────────────────────── #> Each of the layers in simulation output data is represented as a 2D raster in #> NETCDF files, with the following grid format: #>  #> CRS: EPSG:4326 - WGS 84 - Geographic #> Extent: 111.975 -44.525 156.275 -9.975 #> Unit: Degrees #> Width: 886 #> Height: 691 #> Cell size: 0.05 degree x 0.05 degree #> ──────────────────────────────────────────────────────────────────────────────── #> For further details, see the ABARES website, #> <https://www.agriculture.gov.au/abares/research-topics/surveys/farm-survey-data/australian-gridded-farm-data>"},{"path":"https://adamhsparks.github.io/read.abares/reference/print_soil_thickness_metadata.html","id":null,"dir":"Reference","previous_headings":"","what":"Display Complete Metadata Associated with Soil Thickness Data in the R Console — print_soil_thickness_metadata","title":"Display Complete Metadata Associated with Soil Thickness Data in the R Console — print_soil_thickness_metadata","text":"Displays complete set metadata associated soil thickness data R console. including metadata documents methods outside R, see get_soil_thickness example using pander::pander print metadata.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/print_soil_thickness_metadata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Display Complete Metadata Associated with Soil Thickness Data in the R Console — print_soil_thickness_metadata","text":"","code":"print_soil_thickness_metadata(x)"},{"path":"https://adamhsparks.github.io/read.abares/reference/print_soil_thickness_metadata.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Display Complete Metadata Associated with Soil Thickness Data in the R Console — print_soil_thickness_metadata","text":"x read.abares.soil.thickness.files object","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/print_soil_thickness_metadata.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Display Complete Metadata Associated with Soil Thickness Data in the R Console — print_soil_thickness_metadata","text":"Nothing, called side effects, prints complete metadata file R console","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/print_soil_thickness_metadata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Display Complete Metadata Associated with Soil Thickness Data in the R Console — print_soil_thickness_metadata","text":"","code":"if (FALSE) { # interactive() get_soil_thickness(cache = TRUE) |> print_soil_thickness_metadata() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read.abares-package.html","id":null,"dir":"Reference","previous_headings":"","what":"read.abares: Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources — read.abares-package","title":"read.abares: Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources — read.abares-package","text":"Download import data Australian Bureau Agricultural Resource Economics Sciences (ABARES) https://www.agriculture.gov.au/abares.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read.abares-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"read.abares: Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources — read.abares-package","text":"Maintainer: Adam H. Sparks adamhsparks@gmail.com (ORCID) contributors: Jacob jacob@wujciak.de (ORCID) (Assisted troubleshooting formatting documentation display '<' '>' properly) [contributor] Curtin University Technology (Provided support Adam Sparks's time.) [copyright holder] Grains Research Development Corporation (GRDC Project CUR2210-005OPX (AAGI-CU)) [funder, copyright holder]","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":null,"dir":"Reference","previous_headings":"","what":"Read AAGIS Region Mapping Files — read_aagis_regions","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"Download, cache import Australian Agricultural Grazing Industries Survey (AAGIS regions geospatial shapefile. Upon import, geometries  automatically corrected fix invalid geometries present original shapefile.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"","code":"read_aagis_regions(cache = TRUE)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"https://www.agriculture.gov.au/sites/default/files/documents/aagis_asgs16v1_g5a.shp_.zip","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"cache Boolean Cache AAGIS regions' geospatial file downloading using tools::R_user_dir(\"read.abares\", \"cache\") identify proper directory storing user data cache package. Defaults TRUE, caching files locally Geopackage. FALSE, function uses tempdir() files deleted upon closing R session.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"sf object AAGIS regions","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"https://www.agriculture.gov.au/abares/research-topics/surveys/farm-definitions-methods#regions","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"","code":"if (FALSE) { # interactive() aagis <- read_aagis_regions()  plot(aagis) }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Data From the ABARES Trade Dashboard — read_abares_trade","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"Fetches imports  ABARES trade data.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"","code":"read_abares_trade(cache = TRUE)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1033841/0","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"cache Boolean Cache ABARES trade data download using tools::R_user_dir() identify proper directory storing user data cache package. Defaults TRUE, caching files locally native R object. FALSE, function uses tempdir() files deleted upon closing R session.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"data.table object ABARES trade data.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"Columns renamed consistency ABARES products serviced package using snake_case format ordered consistently.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"https://www.agriculture.gov.au/abares/research-topics/trade/dashboard","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"","code":"if (FALSE) { # interactive() trade <- read_abares_trade()  trade }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":null,"dir":"Reference","previous_headings":"","what":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"Fetches imports  ABARES trade regions data.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"","code":"read_abares_trade_regions(cache = TRUE)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1033841/2","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"cache Boolean Cache ABARES trade regions data download using tools::R_user_dir() identify proper directory storing user data cache package. Defaults TRUE, caching files locally native R object. FALSE, function uses tempdir() files deleted upon closing R session.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"data.table object ABARES trade data regions.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"Columns renamed consistency ABARES products serviced package using snake_case format ordered consistently.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1033841/0","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"","code":"if (FALSE) { # interactive() trade_regions <- read_abares_trade_regions()  trade_regions }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":null,"dir":"Reference","previous_headings":"","what":"Read AGFD NCDF Files as a data.table — read_agfd_dt","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"Read Australian Gridded Farm Data, (AGFD) data.table object.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"","code":"read_agfd_dt(files)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"files list AGFD NetCDF files import","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"data.table::data.table object Australian Gridded Farm Data","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"ABARES website: “Australian Gridded Farm Data (AGFD) set national scale maps containing simulated data historical broadacre farm business outcomes including farm profitability 0.05-degree (approximately 5 km) grid. data produced ABARES part ongoing Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data.Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data. maps provide estimates farm business profit, revenue, costs production location (grid cell) year period 1990-91 2022-23. data include actual observed outcomes rather model predicted outcomes representative ‘typical’ broadacre farm businesses location considering likely farm characteristics prevailing weather conditions commodity prices.” – ABARES, 2024-11-25 sets data large file size, .e., >1GB, require time download.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"historical-climate-fixed-prices-","dir":"Reference","previous_headings":"","what":"Historical climate (fixed prices)","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"Historical climate (fixed prices) scenario similar described Hughes et al. (2022) intended isolate effects climate variability financial incomes broadacre farm businesses. simulations, global output input price indexes fixed values recently completed financial year. However, scenarios spread domestic global grain (wheat, barley sorghum) prices, along Australian fodder prices allowed vary response climate data (capture domestic increases grain fodder prices drought years, see Hughes et al. 2022). 33-year historical climate sequence (including historical simulated crop pasture data AADI project) simulated grid cell (1990-91 2022-23).","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"historical-climate-and-prices","dir":"Reference","previous_headings":"","what":"Historical climate and prices","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"part AADI project additional scenario developed accounting changes climate conditions output input prices (.e., global commodity market variability). Historical climate prices scenario 33-year reference period allows variation \\ historical climate conditions historical prices. scenario, historical price indexes de-trended, account consistent long- term trends real commodity prices (particularly sheep lamb). resulting simulation results percentile indicators intended reflect combined impacts annual climate commodity price variability.\" – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"data-files","dir":"Reference","previous_headings":"","what":"Data files","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"Simulation output data saved multilayer NetCDF files, named using following convention: f<farm year>.c<climate year>.p<price year>.t<technology year>.nc : <farm year> = Financial year farm business data used simulations. <climate year> = Financial year climate data used simulations. <price year> = Financial year output input prices used simulations. <technology year> = Financial year farm ‘technology’ (equal farm year simulations) financial years referred closing calendar year (e.g., 2022 = 1 July 2021 30 June 2022). – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"data-layers","dir":"Reference","previous_headings":"","what":"Data layers","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"data layers downloaded NetCDF files described Table 2 seen Australian Bureau Agricultural Resource Economics Sciences (2024). Following copy Table 2 convenience, please refer full document methods metadata.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"Australian gridded farm data, Australian Bureau Agricultural Resource Economics Sciences, Canberra, July 2024, DOI: 10.25814/7n6z-ev41. CC 4.0. N. Hughes, W.Y. Soh, C. Boult, K. Lawson, Defining drought perspective Australian farmers, Climate Risk Management, Volume 35, 2022, 100420, ISSN 2212-0963, DOI: 10.1016/j.crm.2022.100420.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"","code":"if (FALSE) { # interactive()  # using piping, which can use the {read.abares} cache after the first DL  get_agfd(cache = TRUE) |>   read_agfd_dt() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":null,"dir":"Reference","previous_headings":"","what":"Read AGFD NCDF Files With stars — read_agfd_stars","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"Read Australian Gridded Farm Data, (AGFD) list stars objects.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"","code":"read_agfd_stars(files)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"files list AGFD NetCDF files import","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"list object stars objects Australian Gridded Farm Data file names list's objects' names","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"ABARES website: “Australian Gridded Farm Data (AGFD) set national scale maps containing simulated data historical broadacre farm business outcomes including farm profitability 0.05-degree (approximately 5 km) grid. data produced ABARES part ongoing Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data.Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data. maps provide estimates farm business profit, revenue, costs production location (grid cell) year period 1990-91 2022-23. data include actual observed outcomes rather model predicted outcomes representative ‘typical’ broadacre farm businesses location considering likely farm characteristics prevailing weather conditions commodity prices.” – ABARES, 2024-11-25 sets data large file size, .e., >1GB, require time download.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"historical-climate-fixed-prices-","dir":"Reference","previous_headings":"","what":"Historical climate (fixed prices)","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"Historical climate (fixed prices) scenario similar described Hughes et al. (2022) intended isolate effects climate variability financial incomes broadacre farm businesses. simulations, global output input price indexes fixed values recently completed financial year. However, scenarios spread domestic global grain (wheat, barley sorghum) prices, along Australian fodder prices allowed vary response climate data (capture domestic increases grain fodder prices drought years, see Hughes et al. 2022). 33-year historical climate sequence (including historical simulated crop pasture data AADI project) simulated grid cell (1990-91 2022-23).","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"historical-climate-and-prices","dir":"Reference","previous_headings":"","what":"Historical climate and prices","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"part AADI project additional scenario developed accounting changes climate conditions output input prices (.e., global commodity market variability). Historical climate prices scenario 33-year reference period allows variation \\ historical climate conditions historical prices. scenario, historical price indexes de-trended, account consistent long- term trends real commodity prices (particularly sheep lamb). resulting simulation results percentile indicators intended reflect combined impacts annual climate commodity price variability.\" – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"data-files","dir":"Reference","previous_headings":"","what":"Data files","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"Simulation output data saved multilayer NetCDF files, named using following convention: f<farm year>.c<climate year>.p<price year>.t<technology year>.nc : <farm year> = Financial year farm business data used simulations. <climate year> = Financial year climate data used simulations. <price year> = Financial year output input prices used simulations. <technology year> = Financial year farm ‘technology’ (equal farm year simulations) financial years referred closing calendar year (e.g., 2022 = 1 July 2021 30 June 2022). – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"data-layers","dir":"Reference","previous_headings":"","what":"Data layers","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"data layers downloaded NetCDF files described Table 2 seen Australian Bureau Agricultural Resource Economics Sciences (2024). Following copy Table 2 convenience, please refer full document methods metadata.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"Australian gridded farm data, Australian Bureau Agricultural Resource Economics Sciences, Canberra, July 2024, DOI: 10.25814/7n6z-ev41. CC 4.0. N. Hughes, W.Y. Soh, C. Boult, K. Lawson, Defining drought perspective Australian farmers, Climate Risk Management, Volume 35, 2022, 100420, ISSN 2212-0963, DOI: 10.1016/j.crm.2022.100420.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"","code":"if (FALSE) { # interactive()  # using piping, which can use the {read.abares} cache after the first DL  agfd <- get_agfd(cache = TRUE) |>   read_agfd_stars()  head(agfd)  plot(agfd[[1]]) }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":null,"dir":"Reference","previous_headings":"","what":"Read AGFD NCDF Files With terra — read_agfd_terra","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"Read Australian Gridded Farm Data, (AGFD) list terra::rast objects.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"","code":"read_agfd_terra(files)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"files list AGFD NetCDF files import","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"list object terra::rast objects Australian Gridded Farm Data file names list's objects' names","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"ABARES website: “Australian Gridded Farm Data (AGFD) set national scale maps containing simulated data historical broadacre farm business outcomes including farm profitability 0.05-degree (approximately 5 km) grid. data produced ABARES part ongoing Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data.Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data. maps provide estimates farm business profit, revenue, costs production location (grid cell) year period 1990-91 2022-23. data include actual observed outcomes rather model predicted outcomes representative ‘typical’ broadacre farm businesses location considering likely farm characteristics prevailing weather conditions commodity prices.” – ABARES, 2024-11-25 sets data large file size, .e., >1GB, require time download.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"historical-climate-fixed-prices-","dir":"Reference","previous_headings":"","what":"Historical climate (fixed prices)","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"Historical climate (fixed prices) scenario similar described Hughes et al. (2022) intended isolate effects climate variability financial incomes broadacre farm businesses. simulations, global output input price indexes fixed values recently completed financial year. However, scenarios spread domestic global grain (wheat, barley sorghum) prices, along Australian fodder prices allowed vary response climate data (capture domestic increases grain fodder prices drought years, see Hughes et al. 2022). 33-year historical climate sequence (including historical simulated crop pasture data AADI project) simulated grid cell (1990-91 2022-23).","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"historical-climate-and-prices","dir":"Reference","previous_headings":"","what":"Historical climate and prices","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"part AADI project additional scenario developed accounting changes climate conditions output input prices (.e., global commodity market variability). Historical climate prices scenario 33-year reference period allows variation \\ historical climate conditions historical prices. scenario, historical price indexes de-trended, account consistent long- term trends real commodity prices (particularly sheep lamb). resulting simulation results percentile indicators intended reflect combined impacts annual climate commodity price variability.\" – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"data-files","dir":"Reference","previous_headings":"","what":"Data files","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"Simulation output data saved multilayer NetCDF files, named using following convention: f<farm year>.c<climate year>.p<price year>.t<technology year>.nc : <farm year> = Financial year farm business data used simulations. <climate year> = Financial year climate data used simulations. <price year> = Financial year output input prices used simulations. <technology year> = Financial year farm ‘technology’ (equal farm year simulations) financial years referred closing calendar year (e.g., 2022 = 1 July 2021 30 June 2022). – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"data-layers","dir":"Reference","previous_headings":"","what":"Data layers","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"data layers downloaded NetCDF files described Table 2 seen Australian Bureau Agricultural Resource Economics Sciences (2024). Following copy Table 2 convenience, please refer full document methods metadata.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"Australian gridded farm data, Australian Bureau Agricultural Resource Economics Sciences, Canberra, July 2024, DOI: 10.25814/7n6z-ev41. CC 4.0. N. Hughes, W.Y. Soh, C. Boult, K. Lawson, Defining drought perspective Australian farmers, Climate Risk Management, Volume 35, 2022, 100420, ISSN 2212-0963, DOI: 10.1016/j.crm.2022.100420.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"","code":"if (FALSE) { # interactive()  # using piping, which can use the {read.abares} cache after the first DL  get_agfd(cache = TRUE) |>   read_agfd_terra() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":null,"dir":"Reference","previous_headings":"","what":"Read agfd NCDF Files With tidync — read_agfd_tidync","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"Read Australian Gridded Farm Data, (AGFD) list tidync objects","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"","code":"read_agfd_tidync(files)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"files list AGFD NetCDF files import","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"list object tidync tidync::tidync objects Australian Gridded Farm Data file names  list's objects' names.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"ABARES website: “Australian Gridded Farm Data (AGFD) set national scale maps containing simulated data historical broadacre farm business outcomes including farm profitability 0.05-degree (approximately 5 km) grid. data produced ABARES part ongoing Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data.Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data. maps provide estimates farm business profit, revenue, costs production location (grid cell) year period 1990-91 2022-23. data include actual observed outcomes rather model predicted outcomes representative ‘typical’ broadacre farm businesses location considering likely farm characteristics prevailing weather conditions commodity prices.” – ABARES, 2024-11-25 sets data large file size, .e., >1GB, require time download.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"historical-climate-fixed-prices-","dir":"Reference","previous_headings":"","what":"Historical climate (fixed prices)","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"Historical climate (fixed prices) scenario similar described Hughes et al. (2022) intended isolate effects climate variability financial incomes broadacre farm businesses. simulations, global output input price indexes fixed values recently completed financial year. However, scenarios spread domestic global grain (wheat, barley sorghum) prices, along Australian fodder prices allowed vary response climate data (capture domestic increases grain fodder prices drought years, see Hughes et al. 2022). 33-year historical climate sequence (including historical simulated crop pasture data AADI project) simulated grid cell (1990-91 2022-23).","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"historical-climate-and-prices","dir":"Reference","previous_headings":"","what":"Historical climate and prices","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"part AADI project additional scenario developed accounting changes climate conditions output input prices (.e., global commodity market variability). Historical climate prices scenario 33-year reference period allows variation \\ historical climate conditions historical prices. scenario, historical price indexes de-trended, account consistent long- term trends real commodity prices (particularly sheep lamb). resulting simulation results percentile indicators intended reflect combined impacts annual climate commodity price variability.\" – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"data-files","dir":"Reference","previous_headings":"","what":"Data files","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"Simulation output data saved multilayer NetCDF files, named using following convention: f<farm year>.c<climate year>.p<price year>.t<technology year>.nc : <farm year> = Financial year farm business data used simulations. <climate year> = Financial year climate data used simulations. <price year> = Financial year output input prices used simulations. <technology year> = Financial year farm ‘technology’ (equal farm year simulations) financial years referred closing calendar year (e.g., 2022 = 1 July 2021 30 June 2022). – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"data-layers","dir":"Reference","previous_headings":"","what":"Data layers","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"data layers downloaded NetCDF files described Table 2 seen Australian Bureau Agricultural Resource Economics Sciences (2024). Following copy Table 2 convenience, please refer full document methods metadata.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"Australian gridded farm data, Australian Bureau Agricultural Resource Economics Sciences, Canberra, July 2024, DOI: 10.25814/7n6z-ev41. CC 4.0. N. Hughes, W.Y. Soh, C. Boult, K. Lawson, Defining drought perspective Australian farmers, Climate Risk Management, Volume 35, 2022, 100420, ISSN 2212-0963, DOI: 10.1016/j.crm.2022.100420.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"","code":"if (FALSE) { # interactive()  # using piping, which can use the {read.abares} cache after the first DL  x <- get_agfd(cache = TRUE) |>   read_agfd_tidync() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_performance_category.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","title":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","text":"Read Estimates Size ABARES","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_performance_category.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","text":"","code":"read_estimates_by_performance_category()  read_est_by_perf_cat()"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_performance_category.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","text":"https://www.agriculture.gov.au/sites/default/files/documents/fdp-BySize-ByPerformance.csv","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_performance_category.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","text":"data.table::data.table object","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_performance_category.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","text":"https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_performance_category.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","text":"","code":"if (FALSE) { # interactive()   read_estimates_by_performance_category()   # or shorter  read_est_by_perf_cat() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Estimates by Size From ABARES — read_estimates_by_size","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"Read Estimates Size ABARES","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"","code":"read_estimates_by_size()  read_est_by_size()"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"https://www.agriculture.gov.au/sites/default/files/documents/fdp-national-historical.csv","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"data.table::data.table object Variable field key.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"Columns renamed reordered consistency.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"","code":"if (FALSE) { # interactive()  read_estimates_by_size()  # or shorter read_est_by_size() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"Read Historical Forecast Database ABARES","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"","code":"read_historical_forecast_database()  read_historical_forecast()"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1031941/0","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"data.table::data.table object","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"Columns renamed consistency ABARES products serviced package using snake_case format ordered consistently. \"Month_issued\" column converted character string numeric value representing month year, e.g., \"March\" converted 3.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"data-dictionary","dir":"Reference","previous_headings":"","what":"Data Dictionary","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"resulting object contain following fields.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"https://www.agriculture.gov.au/abares/research-topics/agricultural-outlook/historical-forecasts#:~:text=%20the%20historical%20agricultural%20forecast,relevant%20to%20Australian%20agricultural%20markets","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"","code":"if (FALSE) { # interactive()  read_historical_forecast_database()  # or shorter read_historical_forecast() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Historical National Estimates from ABARES — read_historical_national_estimates","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"Read Historical National Estimates ABARES","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"","code":"read_historical_national_estimates()  read_hist_nat_est()"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"https://www.agriculture.gov.au/sites/default/files/documents/fdp-national-historical.csv","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"data.table::data.table object Variable field key.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"Columns renamed consistency ABARES products serviced package using snake_case format ordered consistently.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"","code":"if (FALSE) { # interactive()   read_historical_national_estimates()   # or shorter  read_hist_nat_est() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"Read Historical Regional Estimates ABARES","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"","code":"read_historical_regional_estimates()  read_hist_reg_est()"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"https://www.agriculture.gov.au/sites/default/files/documents/fdp-regional-historical.csv","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"data.table::data.table object Variable field key.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"Columns renamed consistency ABARES products serviced package using snake_case format ordered consistently.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"","code":"if (FALSE) { # interactive()  read_historical_regional_estimates()   # or shorter  read_hist_reg_est() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Historical State Estimates from ABARES — read_historical_state_estimates","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"Read Historical State Estimates ABARES","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"","code":"read_historical_state_estimates()  read_hist_sta_est()"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"https://www.agriculture.gov.au/sites/default/files/documents/fdp-state-historical.csv","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"data.table::data.table object Variable field key.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"Columns renamed consistency ABARES products serviced package using snake_case format ordered consistently.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"","code":"if (FALSE) { # interactive()  read_historical_state_estimates()   # or shorter  read_hist_sta_est() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Soil Thickness File With stars — read_soil_thickness_stars","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"Read Soil Thickness Australian Areas Intensive Agriculture Layer 1 data stars object.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"","code":"read_soil_thickness_stars(files)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"https://anrdl-integration-web-catalog-saxfirxkxt.s3-ap-southeast-2.amazonaws.com/warehouse/staiar9cl__059/staiar9cl__05911a01eg_geo___.zip","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"files read.abares read.abares.soil.thickness object, list contains ESRI grid file import","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"stars object Soil Thickness Australian Areas Intensive Agriculture Layer 1","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"https://data.agriculture.gov.au/geonetwork/srv/eng/catalog.search#/metadata/faa9f157-8e17-4b23-b6a7-37eb7920ead6","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"","code":"if (FALSE) { # interactive() get_soil_thickness(cache = TRUE) |>   read_soil_thickness_stars() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Soil Thickness File With terra — read_soil_thickness_terra","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"Read Soil Thickness Australian Areas Intensive Agriculture Layer 1 data terra::rast object.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"","code":"read_soil_thickness_terra(files)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"https://anrdl-integration-web-catalog-saxfirxkxt.s3-ap-southeast-2.amazonaws.com/warehouse/staiar9cl__059/staiar9cl__05911a01eg_geo___.zip","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"files read.abares read.abares.soil.thickness object, list contains ESRI grid file import","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"terra::rast object Soil Thickness Australian Areas Intensive Agriculture Layer 1","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"https://data.agriculture.gov.au/geonetwork/srv/eng/catalog.search#/metadata/faa9f157-8e17-4b23-b6a7-37eb7920ead6","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"","code":"if (FALSE) { # interactive() x <- get_soil_thickness(cache = TRUE) |>   read_soil_thickness_terra()  # terra::plot() is reexported for convience plot(x) }"},{"path":"https://adamhsparks.github.io/read.abares/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. terra plot","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/news/index.html","id":"major-changes-1-0-0","dir":"Changelog","previous_headings":"","what":"Major changes","title":"read.abares 1.0.0","text":"Rename functions download read files active R session get_ read_ avoid confusion functions fetch data separate read_ functions Adds new function, print_agfd_nc_file_format() provide details AGFD NetCDF files’ contents Uses Geopackages {sf} objects rather .Rds, faster smaller file sizes caching Checks corrects geometries AAGIS Regions shapefile upon import applies cached object applicable","code":""},{"path":"https://adamhsparks.github.io/read.abares/news/index.html","id":"bug-fixes-1-0-0","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"read.abares 1.0.0","text":"longer checks length Boolean vector checking number files cache proceeding removing Fixes bugs get_agfd() creating directories saving downloaded file Fixes bug get_aagis_regions() creating cached object file Fixes “URL” field DESCRIPTION file, thanks @mpadge","code":""},{"path":"https://adamhsparks.github.io/read.abares/news/index.html","id":"minor-changes-1-0-0","dir":"Changelog","previous_headings":"","what":"Minor changes","title":"read.abares 1.0.0","text":"Improved documentation data sets now @source field points file provided data sets now @references field points references data Code linting thanks {flint} Use {httr2} handle downloads Increase timeout values deal stubborn long-running file downloads Uses {httr2}’s caching functionality simplify -session caching Use {brio} write downloads disk Use {httptest2} help test downloads Gracefully handle errors AGFD zip files corrupted download, provide user informative message remove corrupted download Tests run parallel quicker testing {sf} operations now quiet reading data possible","code":""},{"path":"https://adamhsparks.github.io/read.abares/news/index.html","id":"readabares-010","dir":"Changelog","previous_headings":"","what":"read.abares 0.1.0","title":"read.abares 0.1.0","text":"Submission rOpenSci peer code review","code":""}]
+[{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, caste, color, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://adamhsparks.github.io/read.abares/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement codeofconduct@posit.co. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://adamhsparks.github.io/read.abares/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.1, available https://www.contributor-covenant.org/version/2/1/code_of_conduct.html. Community Impact Guidelines inspired [Mozilla’s code conduct enforcement ladder][https://github.com/mozilla/inclusion]. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contributing to read.abares","title":"Contributing to read.abares","text":"outlines propose change read.abares. detailed discussion contributing tidyverse packages, please see development contributing guide code review principles.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"fixing-typos","dir":"","previous_headings":"","what":"Fixing typos","title":"Contributing to read.abares","text":"can fix typos, spelling mistakes, grammatical errors documentation directly using GitHub web interface, long changes made source file. generally means ’ll need edit roxygen2 comments .R, .Rd file. can find .R file generates .Rd reading comment first line.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"bigger-changes","dir":"","previous_headings":"","what":"Bigger changes","title":"Contributing to read.abares","text":"want make bigger change, ’s good idea first file issue make sure someone team agrees ’s needed. ’ve found bug, please file issue illustrates bug minimal reprex (also help write unit test, needed). See guide create great issue advice.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"Bigger changes","what":"Pull request process","title":"Contributing to read.abares","text":"Fork package clone onto computer. haven’t done , recommend using usethis::create_from_github(\"adamhsparks/read.abares\", fork = TRUE). Install development dependencies devtools::install_dev_deps(), make sure package passes R CMD check running devtools::check(). R CMD check doesn’t pass cleanly, ’s good idea ask help continuing. Create Git branch pull request (PR). recommend using usethis::pr_init(\"brief-description--change\"). Make changes, commit git, create PR running usethis::pr_push(), following prompts browser. title PR briefly describe change. body PR contain Fixes #issue-number. user-facing changes, add bullet top NEWS.md (.e. just first header). Follow style described https://style.tidyverse.org/news.html.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"code-style","dir":"","previous_headings":"Bigger changes","what":"Code style","title":"Contributing to read.abares","text":"New code follow tidyverse style guide. can use styler package apply styles, please don’t restyle code nothing PR. use roxygen2, Markdown syntax, documentation. use testthat unit tests. Contributions test cases included easier accept.","code":""},{"path":"https://adamhsparks.github.io/read.abares/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contributing to read.abares","text":"Please note read.abares project released Contributor Code Conduct. contributing project agree abide terms.","code":""},{"path":"https://adamhsparks.github.io/read.abares/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 read.abares authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://adamhsparks.github.io/read.abares/articles/read.abares.html","id":"working-with-agfd-data","dir":"Articles","previous_headings":"","what":"Working With AGFD Data","title":"read.abares","text":"can download files pipe directly class object desire Australian Farm Gridded Data (AGFD) data.","code":""},{"path":"https://adamhsparks.github.io/read.abares/articles/read.abares.html","id":"description-of-the-australian-farm-gridded-data","dir":"Articles","previous_headings":"Working With AGFD Data","what":"Description of the Australian Farm Gridded Data","title":"read.abares","text":"Directly DAFF website: Australian Gridded Farm Data set national scale maps containing simulated data historical broadacre farm business outcomes including farm profitability 0.05-degree (approximately 5 km) grid. data produced read.abares part ongoing Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using read.abares farmpredict model, turn based read.abares Agricultural Grazing Industries Survey (AAGIS) data. maps provide estimates farm business profit, revenue, costs production location (grid cell) year period 1990-91 2022-23. data include actual observed outcomes rather model predicted outcomes representative ‘typical’ broadacre farm businesses location considering likely farm characteristics prevailing weather conditions commodity prices. Australian Gridded Farm Data remain active development, considered experimental. – Australian Department Agriculture, Fisheries Forestry. Load {read.abares} library. Check file format information NetCDF files. Download load local cache read AGFD files list {stars} objects. Download load local cache read AGFD files terra::rast object. Download load local cache read AGFD files list {tidync} objects. Download load local cache read AGFD files {data.table} object.","code":"library(read.abares) print_agfd_nc_file_format() #> ──────────────────────────────────────────────────────────────────────────────────────────────────── #> Each of the layers in simulation output data is represented as a 2D raster in NETCDF files, with #> the following grid format: #> CRS: EPSG:4326 - WGS 84 – Geographic #> Extent: 111.975 -44.525 156.275 -9.975 #> Unit: Degrees #> Width: 886 #> Height: 691 #> Cell size: 0.05 degree x 0.05 degree #> ──────────────────────────────────────────────────────────────────────────────────────────────────── #> For further details, see the ABARES website, #> <https://www.agriculture.gov.au/abares/research-topics/surveys/farm-survey-data/australian-gridded-farm-data> ## A list of {stars} objects star <- get_agfd(cache = TRUE) |>   read_agfd_stars() #> Will return stars object with 612226 cells. #> No projection information found in nc file.  #>  Coordinate variable units found to be degrees,  #>  assuming WGS84 Lat/Lon.  head(star[[1]]) #> stars object with 2 dimensions and 6 attributes #> attribute(s): #>                         Min.         1st Qu.         Median           Mean        3rd Qu. #> farmno          15612.000000 233091.50000000 329567.0000000 324737.7187618 418508.5000000 #> R_total_hat_ha      2.954396      7.88312157     21.7520529    169.5139301    174.8553843 #> C_total_hat_ha      1.304440      4.34079101      9.9449849     93.2210542     95.7221857 #> FBP_fci_hat_ha   -143.759785      3.60529967     11.5796641     76.2928759     77.6748501 #> FBP_fbp_hat_ha   -349.521639      3.36599833     11.5074294     60.0750936     62.8596117 #> A_wheat_hat_ha      0.000000      0.04062786      0.1114289      0.1365683      0.2112845 #>                           Max.   NA's #> farmno          669706.0000000 443899 #> R_total_hat_ha    2415.7556059 443899 #> C_total_hat_ha    1853.5385298 443899 #> FBP_fci_hat_ha    1186.5830232 443899 #> FBP_fbp_hat_ha    1240.6003218 443899 #> A_wheat_hat_ha       0.5047761 565224 #> dimension(s): #>     from  to refsys              values x/y #> lon    1 886 WGS 84 [886] 112,...,156.2 [x] #> lat    1 691 WGS 84 [691] -44.5,...,-10 [y] ## A {terra} `rast` object terr <- get_agfd(cache = TRUE) |>   read_agfd_terra()  head(terr[[1]]) #> class       : SpatRaster  #> dimensions  : 6, 886, 41  (nrow, ncol, nlyr) #> resolution  : 0.05, 0.05  (x, y) #> extent      : 111.975, 156.275, -10.275, -9.975  (xmin, xmax, ymin, ymax) #> coord. ref. : lon/lat WGS 84 (CRS84) (OGC:CRS84)  #> source(s)   : memory #> names       : farmno, R_tot~at_ha, C_tot~at_ha, FBP_f~at_ha, FBP_f~at_ha, A_whe~at_ha, ...  #> min values  :    NaN,         NaN,         NaN,         NaN,         NaN,         NaN, ...  #> max values  :    NaN,         NaN,         NaN,         NaN,         NaN,         NaN, ... ## A list of {tidync} objects tdnc <- get_agfd(cache = TRUE) |>   read_agfd_tidync()  head(tdnc[[1]]) #> $source #> # A tibble: 1 × 2 #>   access              source                                                                         #>   <dttm>              <chr>                                                                          #> 1 2024-12-08 10:28:31 /Users/adamsparks/Library/Caches/org.R-project.R/R/read.abares/historical_cli… #>  #> $axis #> # A tibble: 84 × 3 #>     axis variable       dimension #>    <int> <chr>              <int> #>  1     1 lon                    0 #>  2     2 lat                    1 #>  3     3 farmno                 0 #>  4     4 farmno                 1 #>  5     5 R_total_hat_ha         0 #>  6     6 R_total_hat_ha         1 #>  7     7 C_total_hat_ha         0 #>  8     8 C_total_hat_ha         1 #>  9     9 FBP_fci_hat_ha         0 #> 10    10 FBP_fci_hat_ha         1 #> # ℹ 74 more rows #>  #> $grid #> # A tibble: 3 × 4 #>   grid  ndims variables         nvars #>   <chr> <int> <list>            <int> #> 1 D0,D1     2 <tibble [41 × 1]>    41 #> 2 D0        1 <tibble [1 × 1]>      1 #> 3 D1        1 <tibble [1 × 1]>      1 #>  #> $dimension #> # A tibble: 2 × 8 #>      id name  length unlim coord_dim active start count #>   <int> <chr>  <dbl> <lgl> <lgl>     <lgl>  <int> <int> #> 1     0 lon      886 FALSE TRUE      TRUE       1   886 #> 2     1 lat      691 FALSE TRUE      TRUE       1   691 #>  #> $variable #> # A tibble: 43 × 7 #>       id name            type      ndims natts dim_coord active #>    <int> <chr>           <chr>     <int> <int> <lgl>     <lgl>  #>  1     0 lon             NC_DOUBLE     1     2 TRUE      FALSE  #>  2     1 lat             NC_DOUBLE     1     2 TRUE      FALSE  #>  3     2 farmno          NC_DOUBLE     2     1 FALSE     TRUE   #>  4     3 R_total_hat_ha  NC_DOUBLE     2     1 FALSE     TRUE   #>  5     4 C_total_hat_ha  NC_DOUBLE     2     1 FALSE     TRUE   #>  6     5 FBP_fci_hat_ha  NC_DOUBLE     2     1 FALSE     TRUE   #>  7     6 FBP_fbp_hat_ha  NC_DOUBLE     2     1 FALSE     TRUE   #>  8     7 A_wheat_hat_ha  NC_DOUBLE     2     1 FALSE     TRUE   #>  9     8 H_wheat_dot_hat NC_DOUBLE     2     1 FALSE     TRUE   #> 10     9 A_barley_hat_ha NC_DOUBLE     2     1 FALSE     TRUE   #> # ℹ 33 more rows #>  #> $attribute #> # A tibble: 49 × 4 #>       id name       variable       value        #>    <int> <chr>      <chr>          <named list> #>  1     0 _FillValue lon            <dbl [1]>    #>  2     1 units      lon            <chr [1]>    #>  3     0 _FillValue lat            <dbl [1]>    #>  4     1 units      lat            <chr [1]>    #>  5     0 _FillValue farmno         <dbl [1]>    #>  6     0 _FillValue R_total_hat_ha <dbl [1]>    #>  7     0 _FillValue C_total_hat_ha <dbl [1]>    #>  8     0 _FillValue FBP_fci_hat_ha <dbl [1]>    #>  9     0 _FillValue FBP_fbp_hat_ha <dbl [1]>    #> 10     0 _FillValue A_wheat_hat_ha <dbl [1]>    #> # ℹ 39 more rows ## A {data.table} object get_agfd(cache = TRUE) |>   read_agfd_dt() |>   head() #>                            id farmno R_total_hat_ha C_total_hat_ha FBP_fci_hat_ha FBP_fbp_hat_ha #>                        <char>  <num>          <num>          <num>          <num>          <num> #> 1: f2022.c1991.p2022.t2022.nc  15612       7.636519       4.405228       3.231292       1.766127 #> 2: f2022.c1991.p2022.t2022.nc  21495      14.811169       9.165632       5.645538       6.178280 #> 3: f2022.c1991.p2022.t2022.nc  23418      24.874456      14.858595      10.015861      15.504923 #> 4: f2022.c1991.p2022.t2022.nc  24494      15.043653       9.326359       5.717294       7.212161 #> 5: f2022.c1991.p2022.t2022.nc  32429      23.630099      13.681063       9.949036       9.612778 #> 6: f2022.c1991.p2022.t2022.nc  32485      15.009926       9.815501       5.194425       6.582035 #>    A_wheat_hat_ha H_wheat_dot_hat A_barley_hat_ha H_barley_dot_hat A_sorghum_hat_ha #>             <num>           <num>           <num>            <num>            <num> #> 1:            NaN             NaN             NaN              NaN              NaN #> 2:            NaN             NaN             NaN              NaN              NaN #> 3:            NaN             NaN             NaN              NaN              NaN #> 4:            NaN             NaN             NaN              NaN              NaN #> 5:            NaN             NaN             NaN              NaN              NaN #> 6:            NaN             NaN             NaN              NaN              NaN #>    H_sorghum_dot_hat A_oilseeds_hat_ha H_oilseeds_dot_hat R_wheat_hat_ha R_sorghum_hat_ha #>                <num>             <num>              <num>          <num>            <num> #> 1:               NaN               NaN                NaN            NaN              NaN #> 2:               NaN               NaN                NaN            NaN              NaN #> 3:               NaN               NaN                NaN            NaN              NaN #> 4:               NaN               NaN                NaN            NaN              NaN #> 5:               NaN               NaN                NaN            NaN              NaN #> 6:               NaN               NaN                NaN            NaN              NaN #>    R_oilseeds_hat_ha R_barley_hat_ha Q_wheat_hat_ha Q_barley_hat_ha Q_sorghum_hat_ha #>                <num>           <num>          <num>           <num>            <num> #> 1:               NaN             NaN            NaN             NaN              NaN #> 2:               NaN             NaN            NaN             NaN              NaN #> 3:               NaN             NaN            NaN             NaN              NaN #> 4:               NaN             NaN            NaN             NaN              NaN #> 5:               NaN             NaN            NaN             NaN              NaN #> 6:               NaN             NaN            NaN             NaN              NaN #>    Q_oilseeds_hat_ha S_wheat_cl_hat_ha S_sheep_cl_hat_ha S_sheep_births_hat_ha #>                <num>             <num>             <num>                 <num> #> 1:               NaN               NaN    0.000046854152        0.000048411171 #> 2:               NaN               NaN    0.000066325878        0.000057753874 #> 3:               NaN               NaN    0.000007771546        0.000007320093 #> 4:               NaN               NaN    0.000070963917        0.000062521929 #> 5:               NaN               NaN    0.000007780997        0.000006834211 #> 6:               NaN               NaN    0.000059600116        0.000053976389 #>    S_sheep_deaths_hat_ha S_beef_cl_hat_ha S_beef_births_hat_ha S_beef_deaths_hat_ha Q_beef_hat_ha #>                    <num>            <num>                <num>                <num>         <num> #> 1:        0.000007187978       0.02034820          0.005212591          0.000989490   0.004790528 #> 2:        0.000009039695       0.02974461          0.007970856          0.001468278   0.009646485 #> 3:        0.000000000000       0.05393181          0.014745383          0.002867331   0.014401773 #> 4:        0.000009726773       0.03057606          0.008602196          0.001446424   0.009577272 #> 5:        0.000000000000       0.04944272          0.011527594          0.002491037   0.014668761 #> 6:        0.000008478467       0.03322463          0.008456550          0.001627910   0.009281578 #>    Q_sheep_hat_ha Q_lamb_hat_ha R_beef_hat_ha R_sheep_hat_ha R_lamb_hat_ha C_fodder_hat_ha #>             <num>         <num>         <num>          <num>         <num>           <num> #> 1:  0.00007117650             0      7.392679    0.010222802             0       0.3553107 #> 2:  0.00009448864             0     14.281910    0.014485890             0       0.7040333 #> 3:  0.00001299674             0     24.308574    0.001821158             0       0.9473936 #> 4:  0.00010191595             0     14.518771    0.015352095             0       0.7060111 #> 5:  0.00001283228             0     23.060943    0.001892115             0       1.0269189 #> 6:  0.00008869032             0     14.474964    0.013278806             0       0.7019839 #>    C_fert_hat_ha C_fuel_hat_ha C_chem_hat_ha A_total_cropped_ha FBP_pfe_hat_ha farmland_per_cell #>            <num>         <num>         <num>              <num>          <num>             <num> #> 1:  0.0007795925     0.4282799  0.0002169123     0.000001588013       2.142158          62.26270 #> 2:  0.0670951492     0.5663560  0.0212989625     0.000144292922       6.679382          61.71605 #> 3:  0.1475929946     0.9244438  0.0398376851     0.000296036096      16.185389          61.82964 #> 4:  0.0764850563     0.5688555  0.0223214940     0.000151675639       7.711993          72.85995 #> 5:  0.1592835324     0.8337981  0.0416492516     0.000316535762      10.294743          61.82964 #> 6:  0.0997758317     0.5575842  0.0293469147     0.000201161236       7.101658          61.71605 #>       lon    lat #>     <num>  <num> #> 1: 142.60 -10.75 #> 2: 136.75 -11.05 #> 3: 132.90 -11.15 #> 4: 136.70 -11.20 #> 5: 133.45 -11.60 #> 6: 136.25 -11.60"},{"path":"https://adamhsparks.github.io/read.abares/articles/read.abares.html","id":"working-with-the-soil-thickness-map","dir":"Articles","previous_headings":"","what":"Working With the Soil Thickness Map","title":"read.abares","text":"can download soil depth map import {stars} terra::rast() object. convenience, {read.abares} re-exports terra::plot(), can just use plot() {terra} objects {read.abares}.","code":"library(read.abares) get_soil_thickness(cache = TRUE) |>   read_soil_thickness_stars() #> stars object with 2 dimensions and 1 attribute #> attribute(s), summary of first 100000 cells: #>         Min. 1st Qu. Median Mean 3rd Qu. Max.   NA's #> thpk_1    NA      NA     NA  NaN      NA   NA 100000 #> dimension(s): #>   from   to offset delta refsys x/y #> x    1 4150  112.5  0.01 WGS 84 [x] #> y    1 3401 -9.995 -0.01 WGS 84 [y]  x <- get_soil_thickness(cache = TRUE) |>   read_soil_thickness_terra() plot(x)"},{"path":"https://adamhsparks.github.io/read.abares/articles/read.abares.html","id":"soil-thickness-metadata","dir":"Articles","previous_headings":"Working With the Soil Thickness Map","what":"Soil Thickness Metadata","title":"read.abares","text":"default, brief bit metadata printed console call soil thickness object R session. , {read.abares} provides function browse soil thickness metadata console. can also access directly use pander::pander() include document like vignette. Dataset ANZLIC ID ANZCW1202000149 Title Soil Thickness Australian areas intensive agriculture Layer 1 (Horizon - top-soil) (derived soil mapping) Custodian CSIRO, Land & Water Jurisdiction Australia Description Abstract Surface predicted Thickness soil layer 1 (Horizon - top-soil) surface intensive agricultural areas Australia. Data modelled area based observations made soil agencies State CSIRO presented .0.01 degree grid cells. Topsoils (horizons) defined surface soil layers organic matter accumulates, may include dominantly organic surface layers (O P horizons). depth topsoil important , higher organic matter contents, topsoils (horizon) generally suitable properties agriculture, including higher permeability higher levels soil nutrients. Estimates soil depths needed calculate amount soil constituent either volume mass terms (bulk density also needed) - example, volume water stored rooting zone potentially available plant use, assess total stores soil carbon Greenhouse inventory assess total stores nutrients. pattern soil depth strongly related topography - shape slope land. Deeper soils typically found river valleys soils accumulate floodplains footslopes ranges (zones deposition), soils hillslopes (zones erosion) tend shallow. Map thickness topsoil derived soil map data interpreted tables soil properties specific soil groups. quality data soil depth existing soil profile datasets questionable thickness soil horizons varies locally topography, values map units general averages. final ASRIS polygon attributed surfaces mosaic data obtained various state federal agencies. surfaces constructed best available soil survey information available time. surfaces also rely number assumptions. One area weighted mean good estimate soil attributes polygon map-unit. Another assumption made look-tables provided McKenzie et al. (2000), state territories accurately depict soil attribute values soil type. accuracy maps dependent scale original polygon data sets level soil survey taken place state. scale various soil maps used deriving map available accessing data-source grid, scale used assessment likely accuracy modelling. Atlas Australian Soils considered least accurate dataset therefore used state based data. state datasets Western Australian sub-systems, South Australian land systems NSW soil landscapes reconnaissance mapping reliable based scale. NSW soil landscapes reconnaissance mapping use one dominant soil type per polygon estimation attributes. South Australia Western Australia use several soil types per polygon map-unit. digital map data provided geographical coordinates based World Geodetic System 1984 (WGS84) datum. raster data set grid resolution 0.001 degrees (approximately equivalent 1.1 km). data set product National Land Water Resources Audit (NLWRA) base dataset. Search Word(s) AGRICULTURE SOIL Physics Models Geographic Extent Name(s) GEN Category GEN Custodial Jurisdiction GEN Name Geographic Bounding Box North Bounding Latitude -10.707149 South Bounding Latitude -43.516831 East Bounding Longitude 113.19673 West Bounding Longitude 153.990779 Geographic Extent Polygon(s) 115.0 -33.5,115.7 -33.3,115.7 -31.7,113.2 -26.2,113.5 -25.4,114.1 -26.4,114.3 -26.0,113.4 -24.3,114.1 -21.8,122.3 -18.2,122.2 -17.2,126.7 -13.6,129.1 -14.9,130.6 -12.3,132.6 -12.1,132.5 -11.6,131.9 -11.3,132.0 -11.1,137.0 -12.2,135.4 -14.7,140.0 -17.7,140.8 -17.4,141.7 -15.1,141.4 -13.7,142.2 -10.9,142.7 -10.7,143.9 -14.5,144.6 -14.1,145.3 -14.9,146.3 -18.8,148.9 -20.5,150.9 -22.6,153.2 -25.9,153.7 -28.8,153.0 -31.3,150.8 -34.8,150.0 -37.5,147.8 -37.9,146.3 -39.0,144.7 -38.4,143.5 -38.8,141.3 -38.4,139.7 -37.3,139.7 -36.9,139.9 -36.7,138.9 -35.5,138.1 -35.7,138.6 -34.7,138.1 -34.2,137.8 -35.1,136.9 -35.3,137.0 -34.9,137.5 -34.9,137.4 -34.0,137.9 -33.5,137.8 -32.6,137.3 -33.6,135.9 -34.7,136.1 -34.8,136.0 -35.0,135.1 -34.6,135.2 -34.5,135.4 -34.5,134.7 -33.3,134.0 -32.9,133.7 -32.1,133.3 -32.2,132.2 -32.0,131.3 -31.5,127.3 -32.3,126.0 -32.3,123.6 -33.9,123.2 -34.0,122.1 -34.0,121.9 -33.8,119.9 -34.0,119.6 -34.4,118.0 -35.1,116.0 -34.8,115.0 -34.3,115.0 -33.5 147.8 -42.9,147.9 -42.6,148.2 -42.1,148.3 -42.3,148.3 -41.3,148.3 -41.0,148.0 -40.7,147.4 -41.0,146.7 -41.1,146.6 -41.2,146.5 -41.1,146.4 -41.2,145.3 -40.8,145.3 -40.7,145.2 -40.8,145.2 -40.8,145.2 -40.8,145.0 -40.8,144.7 -40.7,144.7 -41.2,145.2 -42.2,145.4 -42.2,145.5 -42.4,145.5 -42.5,145.2 -42.3,145.5 -43.0,146.0 -43.3,146.0 -43.6,146.9 -43.6,146.9 -43.5,147.1 -43.3,147.0 -43.1,147.2 -43.3,147.3 -42.8,147.4 -42.9,147.6 -42.8,147.5 -42.8,147.8 -42.9,147.9 -43.0,147.7 -43.0,147.8 -43.2,147.9 -43.2,147.9 -43.2,148.0 -43.2,148.0 -43.1,148.0 -42.9,147.8 -42.9 136.7 -13.8,136.7 -13.7,136.6 -13.7,136.6 -13.8,136.4 -13.8,136.4 -14.1,136.3 -14.2,136.9 -14.3,137.0 -14.2,136.9 -14.2,136.7 -14.1,136.9 -13.8,136.7 -13.8,136.7 -13.8 139.5 -16.6,139.7 -16.5,139.4 -16.5,139.2 -16.7,139.3 -16.7,139.5 -16.6 153.0 -25.2,153.0 -25.7,153.1 -25.8,153.4 -25.0,153.2 -24.7,153.2 -25.0,153.0 -25.2 137.5 -36.1,137.7 -35.9,138.1 -35.9,137.9 -35.7,137.6 -35.7,137.6 -35.6,136.6 -35.8,136.7 -36.1,137.2 -36.0,137.5 -36.1 143.9 -39.7,144.0 -39.6,144.1 -39.8,143.9 -40.2,143.9 -40.0,143.9 -39.7 148.0 -39.7,147.7 -39.9,147.9 -39.9,148.0 -40.1,148.1 -40.3,148.3 -40.2,148.3 -40.0,148.0 -39.7 148.1 -40.4,148.0 -40.4,148.4 -40.3,148.4 -40.5,148.1 -40.4 130.4 -11.3,130.4 -11.2,130.6 -11.3,130.7 -11.4,130.9 -11.3,131.0 -11.4,131.1 -11.3,131.2 -11.4,131.3 -11.2,131.5 -11.4,131.5 -11.5,131.0 -11.9,130.8 -11.8,130.6 -11.7,130.0 -11.8,130.1 -11.7,130.3 -11.7,130.1 -11.5,130.4 -11.3 Data Currency Beginning date 1999-09-01 Ending date 2001-03-31 Dataset Status Progress COMPLETE Maintenance Update Frequency PLANNED Access Stored Data Format DIGITAL - ESRI Arc/Info integer GRID Available Format Type DIGITAL - ESRI Arc/Info integer GRID Access Constraint Subject terms & condition data access & management agreement National Land & Water Audit ANZLIC parties Data Quality Lineage soil attribute surface created using following datasets 1. digital polygon coverage Soil-Landforms Murray Darling Basis (MDBSIS)(Bui et al. 1998), classified principal profile forms (PPF’s) (Northcote 1979). 2. digital Atlas Australian Soils (Northcote et al.1960-1968)(Leahy, 1993). 3. Western Australia land systems coverage (Agriculture WA). 4. Western Australia sub-systems coverage (Agriculture WA). 5. Ord river catchment soils coverage (Agriculture WA). 6. Victoria soils coverage (Victorian Department Natural Resources Environment - NRE). 7. NSW Soil Landscapes reconnaissance soil landscape mapping (NSW Department Land Water Conservation - DLWC). 8. New South Wales Land systems west (NSW Department Land Water Conservation - DLWC). 9. South Australia soil land-systems (Primary Industries Resources South Australia - PIRSA). 10. Northern Territory soils coverage (Northern Territory Department Lands, Planning Environment). 11. mosaic Queensland soils coverages (Queensland Department Natural Resources - QDNR). 12. look-table linking PPF values Atlas Australian Soils interpreted soil attributes (McKenzie et al. 2000). 13. Look_up tables provided WA Agriculture linking WA soil groups interpreted soil attributes. 14. Look_up tables provided PIRSA linking SA soil groups interpreted soil attributes. continuous raster surface representing Thickness soil layer 1 created combining national state level digitised land systems maps soil surveys linked look-tables listing soil type corresponding attribute values. thickness used sparingly Factual Key, estimations thickness look-tables made using empirical correlations particular soil types. estimate soil attribute one soil type given polygon map-unit, soil attribute values related soil type look-table weighted according area occupied soil type within polygon map-unit. final soil attribute values area weighted average polygon map-unit. polygon data converted continuous raster surface using soil attribute values calculated polygon. ASRIS soil attribute surfaces created using polygon attribution relied number data sets various state agencies. polygon data set turned continuous surface grid based calculated soil attribute value polygon. grids merged basis , available, state data replaced Atlas Australian Soils MDBSIS. MDBSIS derived soil attribute values restricted areas MDBSIS deemed accurate Atlas Australian Soils (see Carlile et al (2001a). cases soil type missing look-table layer 2 exist soil type, percent area soils remaining adjusted prior calculating final soil attribute value. method used attribute polygons dependent data supplied individual State agencies. modelled grid resampled 0.0025 degree cells 0.01 degree cells using bilinear interpolation Positional Accuracy predictive surface 0.01 X 0.01 degree grid locational accurate 1m. positional accuracy defining polygons variable positional accuracy locations expected within 100m recorded location. vertical accuracy relevant. positional assessment made considering tools used generate locational information contacting data providers. parameters used production led surface range positional accuracy ranging + - 50 m + - kilometres. contribute loss attribute accuracy surface. Attribute Accuracy Input attribute accuracy areas highly variable. predictive variable much lower attribute accuracy due irregular distribution limited positional accuracy parameters used modelling. several sources error estimating soil depth thickness horizons look-tables. thickness used sparingly Factual Key, estimations thickness look-tables made using empirical correlations particular soil types. quality data soil depth existing soil profile datasets questionable, soil mapping, thickness soil horizons varies locally topography, values map units general averages. definition depth soil regolith imprecise can difficult determine lower limit soil. assumption made area weighted mean soil attribute values based soil type good estimation soil property debatable, supply soil attribute value given location. Rather designed show national regional patterns soil properties. use surfaces farm catchment scale modelling may prove inaccurate. Also use look-tables attribute soil types accurate number observations used estimate attribute value soil type. soil types look-tables may observations, yet average attribute value still taken attribute value soil type. Different states using different taxonomic schemes making national soil database difficult. Another downfall area weighted approach soil types may listed look-tables. soil type dominant one within polygon map-unit, listed within look-table attributed within look-table final soil attribute value polygon biased towards minor soil types exist. may also happen large area occupied soil type B horizon. case final soil attribute value area weighted soils B horizon, ignoring major soil type within polygon map-unit. layer 2 surfaces large areas -data soils listed particular map-unit polygon B horizon. Logical Consistency Surface fully logically consistent one parameter shown, predicted average Soil Thickness within grid cell Completeness Surface nearly complete. areas (%1 missing) insufficient parameters known provide useful prediction thus attributes absent areas. Contact Information Contact Organisation (s) CSIRO, Land & Water Contact Position Project Leader Mail Address ACLEP, GPO 1666 Locality Canberra State ACT Country AUSTRALIA Postcode 2601 Telephone 02 6246 5922 Facsimile 02 6246 5965 Electronic Mail Address neil.mckenzie@cbr.clw.csiro.au Metadata Date Metadata Date 2001-07-01 Additional Metadata Additional Metadata Entity Attributes Entity Name Soil Thickness Layer 1 (derived mapping) Entity description Estimated Soil Thickness (mm) Layer 1 cell cell basis Feature attribute name VALUE Feature attribute definition Predicted average Thickness (mm) soil layer 1 0.01 X 0.01 degree quadrat Data Type Spatial representation type RASTER Projection Map projection GEOGRAPHIC Datum WGS84 Map units DECIMAL DEGREES Scale Scale/ resolution 1:1 000 000 Usage Purpose Estimates soil depths needed calculate amount soil constituent either volume mass terms (bulk density also needed) - example, volume water stored rooting zone potentially available plant use, assess total stores soil carbon Greenhouse inventory assess total stores nutrients. Provide indications probable Thickness soil layer 1 agricultural areas soil thickness testing carried ","code":"library(read.abares) get_soil_thickness(cache = TRUE) #>  #> ── Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - top-soil) ── #>  #> ── Dataset ANZLIC ID ANZCW1202000149 ── #>  #> Feature attribute definition Predicted average Thickness (mm) of soil layer 1 in the 0.01 X 0.01 #> degree quadrat. #>  #> Custodian: CSIRO Land & Water #>  #> Jurisdiction Australia #>  #> Short Description The digital map data is provided in geographical coordinates based on the World #> Geodetic System 1984 (WGS84) datum. This raster data set has a grid resolution of 0.001 degrees #> (approximately equivalent to 1.1 km). #>  #> The data set is a product of the National Land and Water Resources Audit (NLWRA) as a base dataset. #>  #> Data Type: Spatial representation type RASTER #>  #> Projection Map: projection GEOGRAPHIC #>  #> Datum: WGS84 #>  #> Map Units: DECIMAL DEGREES #>  #> Scale: Scale/ resolution 1:1 000 000 #>  #> Usage Purpose Estimates of soil depths are needed to calculate the amount of any soil constituent #> in either volume or mass terms (bulk density is also needed) - for example, the volume of water #> stored in the rooting zone potentially available for plant use, to assess total stores of soil #> carbon for greenhouse inventory or to assess total stores of nutrients. #>  #> Provide indications of probable thickness soil layer 1 in agricultural areas where soil thickness #> testing has not been carried out. #>  #> Use Limitation: This dataset is bound by the requirements set down by the National Land & Water #> Resources Audit #> To see the full metadata, call `print_soil_thickness_metadata()` on a soil thickness object in your #> R session. library(read.abares) get_soil_thickness(cache = TRUE) |>   print_soil_thickness_metadata() #>  #> ── Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - top-soil) ── #>  #> ── Dataset ANZLIC ID ANZCW1202000149 ── #>  #> Dataset ANZLIC ID ANZCW1202000149 #>  #> Title Soil Thickness for Australian areas of intensive agriculture of Layer 1 (A Horizon - #> top-soil) (derived from soil mapping) #>  #> Custodian CSIRO, Land & Water #>  #> Jurisdiction Australia #>  #> Description Abstract Surface of predicted Thickness of soil layer 1 (A Horizon - top-soil) surface #> for the intensive agricultural areas of Australia.  Data modelled from area based observations made #> by soil agencies both State and CSIRO and presented as .0.01 degree grid cells. #>  #> Topsoils (A horizons) are defined as the surface soil layers in which organic matter accumulates, #> and may include dominantly organic surface layers (O and P horizons). #>  #> The depth of topsoil is important because, with their higher organic matter contents, topsoils (A #> horizon) generally have more suitable properties for agriculture, including higher permeability and #> higher levels of soil nutrients. #>  #> Estimates of soil depths are needed to calculate the amount of any soil constituent in either #> volume or mass terms (bulk density is also needed) - for example, the volume of water stored in the #> rooting zone potentially available for plant use, to assess total stores of soil carbon for #> Greenhouse inventory or to assess total stores of nutrients. #>  #> The pattern of soil depth is strongly related to topography - the shape and slope of the land. #> Deeper soils are typically found in the river valleys where soils accumulate on floodplains and at #> the footslopes of ranges (zones of deposition), while soils on hillslopes (zones of erosion) tend #> to be shallow.  Map of thickness of topsoil was derived from soil map data and interpreted tables #> of soil properties for specific soil groups. #>  #> The quality of data on soil depth in existing soil profile datasets is questionable and as the #> thickness of soil horizons varies locally with topography, values for map units are general #> averages. #>  #> The final ASRIS polygon attributed surfaces are a mosaic of all of the data obtained from various #> state and federal agencies. The surfaces have been constructed with the best available soil survey #> information available at the time. The surfaces also rely on a number of assumptions. One being #> that an area weighted mean is a good estimate of the soil attributes for that polygon or map-unit. #> Another assumption made is that the look-up tables provided by McKenzie et al. (2000), state and #> territories accurately depict the soil attribute values for each soil type. #>  #> The accuracy of the maps is most dependent on the scale of the original polygon data sets and the #> level of soil survey that has taken place in each state.  The scale of the various soil maps used #> in deriving this map is available by accessing the data-source grid, the scale is used as an #> assessment of the likely accuracy of the modelling.  The Atlas of Australian Soils is considered to #> be the least accurate dataset and has therefore only been used where there is no state based data. #> Of the state datasets Western Australian sub-systems, South Australian land systems and NSW soil #> landscapes and reconnaissance mapping would be the most reliable based on scale. NSW soil #> landscapes and reconnaissance mapping use only one dominant soil type per polygon in the estimation #> of attributes.  South Australia and Western Australia use several soil types per polygon or #> map-unit. #>  #> The digital map data is provided in geographical coordinates based on the World Geodetic System #> 1984 (WGS84) datum. This raster data set has a grid resolution of 0.001 degrees (approximately #> equivalent to 1.1 km). #>  #> The data set is a product of the National Land and Water Resources Audit (NLWRA) as a base dataset. #>  #> Search Word(s) AGRICULTURE SOIL Physics Models #>  #> Geographic Extent Name(s) GEN Category #>  #> GEN Custodial Jurisdiction #>  #> GEN Name #>  #> Geographic Bounding Box North Bounding Latitude -10.707149 South Bounding Latitude -43.516831 East #> Bounding Longitude 113.19673 West Bounding Longitude 153.990779 #>  #> Geographic Extent Polygon(s) 115.0 -33.5,115.7 -33.3,115.7 -31.7,113.2 -26.2,113.5 -25.4,114.1 #> -26.4,114.3 -26.0,113.4 -24.3,114.1 -21.8,122.3 -18.2,122.2 -17.2,126.7 -13.6,129.1 -14.9,130.6 #> -12.3,132.6 -12.1,132.5 -11.6,131.9 -11.3,132.0 -11.1,137.0 -12.2,135.4 -14.7,140.0 -17.7,140.8 #> -17.4,141.7 -15.1,141.4 -13.7,142.2 -10.9,142.7 -10.7,143.9 -14.5,144.6 -14.1,145.3 -14.9,146.3 #> -18.8,148.9 -20.5,150.9 -22.6,153.2 -25.9,153.7 -28.8,153.0 -31.3,150.8 -34.8,150.0 -37.5,147.8 #> -37.9,146.3 -39.0,144.7 -38.4,143.5 -38.8,141.3 -38.4,139.7 -37.3,139.7 -36.9,139.9 -36.7,138.9 #> -35.5,138.1 -35.7,138.6 -34.7,138.1 -34.2,137.8 -35.1,136.9 -35.3,137.0 -34.9,137.5 -34.9,137.4 #> -34.0,137.9 -33.5,137.8 -32.6,137.3 -33.6,135.9 -34.7,136.1 -34.8,136.0 -35.0,135.1 -34.6,135.2 #> -34.5,135.4 -34.5,134.7 -33.3,134.0 -32.9,133.7 -32.1,133.3 -32.2,132.2 -32.0,131.3 -31.5,127.3 #> -32.3,126.0 -32.3,123.6 -33.9,123.2 -34.0,122.1 -34.0,121.9 -33.8,119.9 -34.0,119.6 -34.4,118.0 #> -35.1,116.0 -34.8,115.0 -34.3,115.0 -33.5 #>  #> 147.8 -42.9,147.9 -42.6,148.2 -42.1,148.3 -42.3,148.3 -41.3,148.3 -41.0,148.0 -40.7,147.4 #> -41.0,146.7 -41.1,146.6 -41.2,146.5 -41.1,146.4 -41.2,145.3 -40.8,145.3 -40.7,145.2 -40.8,145.2 #> -40.8,145.2 -40.8,145.0 -40.8,144.7 -40.7,144.7 -41.2,145.2 -42.2,145.4 -42.2,145.5 -42.4,145.5 #> -42.5,145.2 -42.3,145.5 -43.0,146.0 -43.3,146.0 -43.6,146.9 -43.6,146.9 -43.5,147.1 -43.3,147.0 #> -43.1,147.2 -43.3,147.3 -42.8,147.4 -42.9,147.6 -42.8,147.5 -42.8,147.8 -42.9,147.9 -43.0,147.7 #> -43.0,147.8 -43.2,147.9 -43.2,147.9 -43.2,148.0 -43.2,148.0 -43.1,148.0 -42.9,147.8 -42.9 #>  #> 136.7 -13.8,136.7 -13.7,136.6 -13.7,136.6 -13.8,136.4 -13.8,136.4 -14.1,136.3 -14.2,136.9 #> -14.3,137.0 -14.2,136.9 -14.2,136.7 -14.1,136.9 -13.8,136.7 -13.8,136.7 -13.8 #>  #> 139.5 -16.6,139.7 -16.5,139.4 -16.5,139.2 -16.7,139.3 -16.7,139.5 -16.6 #>  #> 153.0 -25.2,153.0 -25.7,153.1 -25.8,153.4 -25.0,153.2 -24.7,153.2 -25.0,153.0 -25.2 #>  #> 137.5 -36.1,137.7 -35.9,138.1 -35.9,137.9 -35.7,137.6 -35.7,137.6 -35.6,136.6 -35.8,136.7 #> -36.1,137.2 -36.0,137.5 -36.1 #>  #> 143.9 -39.7,144.0 -39.6,144.1 -39.8,143.9 -40.2,143.9 -40.0,143.9 -39.7 #>  #> 148.0 -39.7,147.7 -39.9,147.9 -39.9,148.0 -40.1,148.1 -40.3,148.3 -40.2,148.3 -40.0,148.0 -39.7 #>  #> 148.1 -40.4,148.0 -40.4,148.4 -40.3,148.4 -40.5,148.1 -40.4 #>  #> 130.4 -11.3,130.4 -11.2,130.6 -11.3,130.7 -11.4,130.9 -11.3,131.0 -11.4,131.1 -11.3,131.2 #> -11.4,131.3 -11.2,131.5 -11.4,131.5 -11.5,131.0 -11.9,130.8 -11.8,130.6 -11.7,130.0 -11.8,130.1 #> -11.7,130.3 -11.7,130.1 -11.5,130.4 -11.3 #>  #> Data Currency Beginning date 1999-09-01 #>  #> Ending date 2001-03-31 #>  #> Dataset Status Progress COMPLETE #>  #> Maintenance and Update Frequency NOT PLANNED #>  #> Access Stored Data Format DIGITAL - ESRI Arc/Info integer GRID #>  #> Available Format Type DIGITAL - ESRI Arc/Info integer GRID #>  #> Access Constraint Subject to the terms & condition of the data access & management agreement #> between the National Land & Water Audit and ANZLIC parties #>  #> Data Quality Lineage The soil attribute surface was created using the following datasets 1. The #> digital polygon coverage of the Soil-Landforms of the Murray Darling Basis (MDBSIS)(Bui et al. #> 1998), classified as principal profile forms (PPF's) (Northcote 1979). 2. The digital Atlas of #> Australian Soils (Northcote et al.1960-1968)(Leahy, 1993). 3. Western Australia land systems #> coverage (Agriculture WA). 4. Western Australia sub-systems coverage (Agriculture WA). 5. Ord river #> catchment soils coverage (Agriculture WA). 6. Victoria soils coverage (Victorian Department of #> Natural Resources and Environment - NRE). 7. NSW Soil Landscapes and reconnaissance soil landscape #> mapping (NSW Department of Land and Water Conservation - DLWC). 8. New South Wales Land systems #> west (NSW Department of Land and Water Conservation - DLWC). 9. South Australia soil land-systems #> (Primary Industries and Resources South Australia - PIRSA). 10. Northern Territory soils coverage #> (Northern Territory Department of Lands, Planning and Environment). 11. A mosaic of Queensland #> soils coverages (Queensland Department of Natural Resources - QDNR). 12. A look-up table linking #> PPF values from the Atlas of Australian Soils with interpreted soil attributes (McKenzie et al. #> 2000). 13. Look_up tables provided by WA Agriculture linking WA soil groups with interpreted soil #> attributes. 14. Look_up tables provided by PIRSA linking SA soil groups with interpreted soil #> attributes. #>  #> The continuous raster surface representing Thickness of soil layer 1 was created by combining #> national and state level digitised land systems maps and soil surveys linked to look-up tables #> listing soil type and corresponding attribute values. #>  #> Because thickness is used sparingly in the Factual Key, estimations of thickness in the look-up #> tables were made using empirical correlations for particular soil types. #>  #> To estimate a soil attribute where more than one soil type was given for a polygon or map-unit, the #> soil attribute values related to each soil type in the look-up table were weighted according to the #> area occupied by that soil type within the polygon or map-unit. The final soil attribute values are #> an area weighted average for a polygon or map-unit.  The polygon data was then converted to a #> continuous raster surface using the soil attribute values calculated for each polygon. #>  #> The ASRIS soil attribute surfaces created using polygon attribution relied on a number of data sets #> from various state agencies.  Each polygon data set was turned into a continuous surface grid based #> on the calculated soil attribute value for that polygon.  The grids where then merged on the basis #> that, where available, state data replaced the Atlas of Australian Soils and MDBSIS.  MDBSIS #> derived soil attribute values were restricted to areas where MDBSIS was deemed to be more accurate #> that the Atlas of Australian Soils (see Carlile et al (2001a). #>  #> In cases where a soil type was missing from the look-up table or layer 2 did not exist for that #> soil type, the percent area of the soils remaining were adjusted prior to calculating the final #> soil attribute value. The method used to attribute polygons was dependent on the data supplied by #> individual State agencies. #>  #> The modelled grid was resampled from 0.0025 degree cells to 0.01 degree cells using bilinear #> interpolation #>  #> Positional Accuracy The predictive surface is a 0.01 X 0.01 degree grid and has a locational #> accurate of about 1m. #>  #> The positional accuracy of the defining polygons have variable positional accuracy most locations #> are expected to be within 100m of the recorded location.  The vertical accuracy is not relevant. #> The positional assessment has been made by considering the tools used to generate the locational #> information and contacting the data providers. #>  #> The other parameters used in the production of the led surface have a range of positional accuracy #> ranging from + - 50 m to + - kilometres.  This contribute to the loss of attribute accuracy in the #> surface. #>  #> Attribute Accuracy Input attribute accuracy for the areas is highly variable.  The predictive has a #> variable and much lower attribute accuracy due to the irregular distribution and the limited #> positional accuracy of the parameters used for modelling. #>  #> There are several sources of error in estimating soil depth and thickness of horizons for the #> look-up tables.  Because thickness is used sparingly in the Factual Key, estimations of thickness #> in the look-up tables were made using empirical correlations for particular soil types.  The #> quality of data on soil depth in existing soil profile datasets is questionable, in soil mapping, #> thickness of soil horizons varies locally with topography, so values for map units are general #> averages.  The definition of the depth of soil or regolith is imprecise and it can be difficult to #> determine the lower limit of soil. #>  #> The assumption made that an area weighted mean of soil attribute values based on soil type is a #> good estimation of a soil property is debatable, in that it does not supply the soil attribute #> value at any given location. Rather it is designed to show national and regional patterns in soil #> properties. The use of the surfaces at farm or catchment scale modelling may prove inaccurate. Also #> the use of look-up tables to attribute soil types is only as accurate as the number of observations #> used to estimate a attribute value for a soil type. Some soil types in the look-up tables may have #> few observations, yet the average attribute value is still taken as the attribute value for that #> soil type. Different states are using different taxonomic schemes making a national soil database #> difficult. Another downfall of the area weighted approach is that some soil types may not be listed #> in look-up tables. If a soil type is a dominant one within a polygon or map-unit, but is not listed #> within the look-up table or is not attributed within the look-up table then the final soil #> attribute value for that polygon will be biased towards the minor soil types that do exist. This #> may also happen when a large area is occupied by a soil type which has no B horizon. In this case #> the final soil attribute value will be area weighted on the soils with a B horizon, ignoring a #> major soil type within that polygon or map-unit. The layer 2 surfaces have large areas of no-data #> because all soils listed for a particular map-unit or polygon had no B horizon. #>  #> Logical Consistency Surface is fully logically consistent as only one parameter is shown, as #> predicted average Soil Thickness within each grid cell #>  #> Completeness Surface is nearly complete.  There are some areas (about %1 missing) for which #> insufficient parameters were known to provide a useful prediction and thus attributes are absent in #> these areas. #>  #> Contact Information Contact Organisation (s) CSIRO, Land & Water #>  #> Contact Position Project Leader #>  #> Mail Address ACLEP, GPO 1666 #>  #> Locality Canberra #>  #> State ACT #>  #> Country AUSTRALIA #>  #> Postcode 2601 #>  #> Telephone 02 6246 5922 #>  #> Facsimile 02 6246 5965 #>  #> Electronic Mail Address neil.mckenzie@cbr.clw.csiro.au #>  #> Metadata Date Metadata Date 2001-07-01 #>  #> Additional Metadata Additional Metadata #>  #> Entity and Attributes Entity Name Soil Thickness Layer 1 (derived from mapping) #>  #> Entity description Estimated Soil Thickness (mm) of Layer 1 on a cell by cell basis #>  #> Feature attribute name VALUE #>  #> Feature attribute definition Predicted average Thickness (mm) of soil layer 1 in the 0.01 X 0.01 #> degree quadrat #>  #> Data Type Spatial representation type RASTER #>  #> Projection Map projection GEOGRAPHIC #>  #> Datum WGS84 #>  #> Map units DECIMAL DEGREES #>  #> Scale Scale/ resolution 1:1 000 000 #>  #> Usage Purpose Estimates of soil depths are needed to calculate the amount of any soil constituent #> in either volume or mass terms (bulk density is also needed) - for example, the volume of water #> stored in the rooting zone potentially available for plant use, to assess total stores of soil #> carbon for Greenhouse inventory or to assess total stores of nutrients. #>  #> Provide indications of probable Thickness soil layer 1 in agricultural areas where soil thickness #> testing has not been carried out #>  #> Use Use Limitation This dataset is bound by the requirements set down by the National Land & Water #> Resources Audit library(read.abares) library(pander) x <- get_soil_thickness(cache = TRUE) y <- x$metadata pander(y)"},{"path":"https://adamhsparks.github.io/read.abares/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Adam H. Sparks. Maintainer, author. Jacob. Contributor.            Assisted troubleshooting formatting documentation display '<' '>' properly Curtin University Technology. Copyright holder.           Provided support Adam Sparks's time. Grains Research Development Corporation. Funder, copyright holder.           GRDC Project CUR2210-005OPX (AAGI-CU)","code":""},{"path":"https://adamhsparks.github.io/read.abares/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Sparks (????). read.abares: Simple downloading importing ABARES Data. R package version 1.0.0, https://adamhsparks.github.io/read.abares/.","code":"@Manual{,   title = {{read.abares}: Simple downloading and importing of ABARES Data},   author = {Adam H. Sparks},   note = {R package version 1.0.0},   url = {https://adamhsparks.github.io/read.abares/}, }"},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"readabares-simple-downloading-and-importing-of-abares-data-","dir":"","previous_headings":"","what":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"R package automated downloading ingestion data Australian Bureau Agricultural Resource Economics Sciences. ABARES data serviced. list hand-picked reasonably useful maintainable, .e., frequently updated values included , e.g., Australian crop reports. However, data set feel useful serviced {read.abares}, please feel free open issue details data set better yet, open pull request! Data serviced include: ABARES Estimates; Australian Gridded Farm Data (AGFD) set; Australian Agricultural Grazing Industries Survey (AAGIS) region mapping files; Historical Agricultural Forecast Database; Soil Thickness Australian areas intensive agriculture Layer 1 (Horizon - top-soil) (derived soil mapping) map ; trade data ; trade region data. files freely available CSV files, zip archives NetCDF files zip archives geospatial shape files. {read.abares} facilitates downloading, caching importing files R session choice class resulting object(s).","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"installation","dir":"","previous_headings":"Get Started","what":"Installation","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"{read.abares} available CRAN (yet). can install like :","code":"if (!require(\"remotes\"))   install.packages(\"remotes\") remotes::install_git(\"https://github.com/adamhsparks/read.abares\")"},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"caching","dir":"","previous_headings":"Features","what":"Caching","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"{read.abares} supports caching files using tools::R_user_dir(package = \"read.abares\", = \"cache\") save files standardised location across platforms don’t worry files went ’re still . requesting files, {read.abares} first check available locally either cached temporary storage. Caching mandatory, can just work downloaded files tempdir(), cleaned R session ends.","code":""},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"multiple-classes-supported","dir":"","previous_headings":"Features","what":"Multiple Classes Supported","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"{read.abares} supports multiple classes objects support workflow. Select spatial classes AGFD NetCDF files: {stars}, {terra} {tidync} data.frame (data.table) objects: {data.table}","code":""},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"metadata","dir":"","previous_headings":"","what":"Metadata","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"Please report issues bugs. License: MIT","code":""},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"citations","dir":"","previous_headings":"Metadata","what":"Citations","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"Citing data: Please refer ABARES website, https://www.agriculture.gov.au/abares/products/citations, cite data use . Citing {read.abares}: citing use package, please use,","code":"library(\"read.abares\") #>  #> Attaching package: 'read.abares' #> The following object is masked from 'package:graphics': #>  #>     plot #> The following object is masked from 'package:base': #>  #>     plot citation(\"read.abares\") #> To cite package 'read.abares' in publications use: #>  #>   Sparks A (????). _read.abares: Simple downloading and importing of #>   ABARES Data_. R package version 1.0.0, #>   <https://adamhsparks.github.io/read.abares/>. #>  #> A BibTeX entry for LaTeX users is #>  #>   @Manual{, #>     title = {{read.abares}: Simple downloading and importing of ABARES Data}, #>     author = {Adam H. Sparks}, #>     note = {R package version 1.0.0}, #>     url = {https://adamhsparks.github.io/read.abares/}, #>   }"},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"a-note-on-testing","dir":"","previous_headings":"Metadata > Contributing","what":"A Note on Testing","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"’ve aimed make testing package complete possible. files downloaded >1GB may take several minutes hour download due size, wish include package . Therefore, tests rely already downloaded locally cached files. wish work development {read.abares} please aware take time establish local cache testing somewhat faster. considering including pared examples tests data released CC 4.0 License, now opted just use locally cached data simplicity.","code":""},{"path":"https://adamhsparks.github.io/read.abares/index.html","id":"code-of-conduct","dir":"","previous_headings":"Metadata","what":"Code of Conduct","title":"Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources","text":"Please note {read.abares} project released Contributor Code Conduct. contributing project, agree abide terms.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/clear_cache.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove Files in Users' Cache Directory — clear_cache","title":"Remove Files in Users' Cache Directory — clear_cache","text":"Removes files read.abares cache exist.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/clear_cache.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove Files in Users' Cache Directory — clear_cache","text":"","code":"clear_cache()"},{"path":"https://adamhsparks.github.io/read.abares/reference/clear_cache.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove Files in Users' Cache Directory — clear_cache","text":"Nothing, called side-effects, clearing cached files","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/clear_cache.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Remove Files in Users' Cache Directory — clear_cache","text":"","code":"# not run because cached files shouldn't exist on CRAN or testing envs if (FALSE) { # \\dontrun{ clear_cache() } # }"},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Australian Gridded Farm Data for Local Use — get_agfd","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"Downloads Australian Gridded Farm Data (AGFD) data unzips compressed files NetCDF importing.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"","code":"get_agfd(fixed_prices = TRUE, cache = TRUE)"},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"Historical climate prices fixed – https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1036161/3, Historical climate prices – https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1036161/2","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"fixed_prices Boolean Download historical climate prices historical climate fixed prices described  (Hughes et al. 2022). Defaults TRUE downloads data historical climate fixed prices “isolate effects climate variability financial incomes broadacre farm businesses” (ABARES 2024). Using TRUE download simulations global output input price indexes fixed values recently completed financial year. cache Boolean Cache Australian Gridded Farm Data files download using tools::R_user_dir identify proper directory storing user data cache package. Defaults TRUE, caching files locally. FALSE, function uses tempdir() files deleted upon closing R session.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"read.abares.agfd.nc.files object, list NetCDF files containing Australian Gridded Farm Data","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"ABARES website: “Australian Gridded Farm Data (AGFD) set national scale maps containing simulated data historical broadacre farm business outcomes including farm profitability 0.05-degree (approximately 5 km) grid. data produced ABARES part ongoing Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data.Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data. maps provide estimates farm business profit, revenue, costs production location (grid cell) year period 1990-91 2022-23. data include actual observed outcomes rather model predicted outcomes representative ‘typical’ broadacre farm businesses location considering likely farm characteristics prevailing weather conditions commodity prices.” – ABARES, 2024-11-25 sets data large file size, .e., >1GB, require time download.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"historical-climate-fixed-prices-","dir":"Reference","previous_headings":"","what":"Historical climate (fixed prices)","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"Historical climate (fixed prices) scenario similar described Hughes et al. (2022) intended isolate effects climate variability financial incomes broadacre farm businesses. simulations, global output input price indexes fixed values recently completed financial year. However, scenarios spread domestic global grain (wheat, barley sorghum) prices, along Australian fodder prices allowed vary response climate data (capture domestic increases grain fodder prices drought years, see Hughes et al. 2022). 33-year historical climate sequence (including historical simulated crop pasture data AADI project) simulated grid cell (1990-91 2022-23).","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"historical-climate-and-prices","dir":"Reference","previous_headings":"","what":"Historical climate and prices","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"part AADI project additional scenario developed accounting changes climate conditions output input prices (.e., global commodity market variability). Historical climate prices scenario 33-year reference period allows variation \\ historical climate conditions historical prices. scenario, historical price indexes de-trended, account consistent long- term trends real commodity prices (particularly sheep lamb). resulting simulation results percentile indicators intended reflect combined impacts annual climate commodity price variability.\" – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"data-files","dir":"Reference","previous_headings":"","what":"Data files","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"Simulation output data saved multilayer NetCDF files, named using following convention: f<farm year>.c<climate year>.p<price year>.t<technology year>.nc : <farm year> = Financial year farm business data used simulations. <climate year> = Financial year climate data used simulations. <price year> = Financial year output input prices used simulations. <technology year> = Financial year farm ‘technology’ (equal farm year simulations) financial years referred closing calendar year (e.g., 2022 = 1 July 2021 30 June 2022). – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"data-layers","dir":"Reference","previous_headings":"","what":"Data layers","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"data layers downloaded NetCDF files described Table 2 seen Australian Bureau Agricultural Resource Economics Sciences (2024). Following copy Table 2 convenience, please refer full document methods metadata.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"Australian gridded farm data, Australian Bureau Agricultural Resource Economics Sciences, Canberra, July 2024, DOI: 10.25814/7n6z-ev41. CC 4.0. N. Hughes, W.Y. Soh, C. Boult, K. Lawson, Defining drought perspective Australian farmers, Climate Risk Management, Volume 35, 2022, 100420, ISSN 2212-0963, DOI: 10.1016/j.crm.2022.100420.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/get_agfd.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Australian Gridded Farm Data for Local Use — get_agfd","text":"","code":"if (FALSE) { # interactive() get_agfd() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"Get Soil Thickness Australian Areas Intensive Agriculture Layer 1 Local Use","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"","code":"get_soil_thickness(cache = TRUE)"},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"https://anrdl-integration-web-catalog-saxfirxkxt.s3-ap-southeast-2.amazonaws.com/warehouse/staiar9cl__059/staiar9cl__05911a01eg_geo___.zip","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"cache Boolean Cache soil thickness data files download using tools::R_user_dir() identify proper directory storing user data cache package. Defaults TRUE, caching files locally. FALSE, function uses tempdir() files deleted upon closing R session. custom print method provided print metadata associated data. Examples provided interacting metadata directly.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"read.abares.soil.thickness object, named list file path resulting ESRI Grid file text file metadata","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"https://data.agriculture.gov.au/geonetwork/srv/eng/catalog.search#/metadata/faa9f157-8e17-4b23-b6a7-37eb7920ead6","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/get_soil_thickness.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Soil Thickness for Australian Areas of Intensive Agriculture of Layer 1 for Local Use — get_soil_thickness","text":"","code":"if (FALSE) { # interactive() x <- get_soil_thickness()  # View the metadata with pretty printing x  # Extract the metadata as an object in your R session and use it with # {pander}, useful for Markdown files  library(pander) y <- x$metadata pander(y) }"},{"path":"https://adamhsparks.github.io/read.abares/reference/inspect_cache.html","id":null,"dir":"Reference","previous_headings":"","what":"List the File Path to Users' Cache Directory — inspect_cache","title":"List the File Path to Users' Cache Directory — inspect_cache","text":"Check files exist read.abares file cache.  function always return full file names, .e., directory path prepended. See help file list.files() full.names argument. wish strip file path return directory file names, use basename(). See examples .","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/inspect_cache.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List the File Path to Users' Cache Directory — inspect_cache","text":"","code":"inspect_cache(recursive = FALSE)"},{"path":"https://adamhsparks.github.io/read.abares/reference/inspect_cache.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List the File Path to Users' Cache Directory — inspect_cache","text":"recursive Boolean value indicating whether list files subdirectories cache directory. Defaults FALSE returning top-level directories contained cache directory.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/inspect_cache.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List the File Path to Users' Cache Directory — inspect_cache","text":"list directories files cache","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/inspect_cache.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"List the File Path to Users' Cache Directory — inspect_cache","text":"","code":"# not run because cached files shouldn't exist on CRAN or testing envs if (FALSE) { # \\dontrun{ # list directories in cache only inspect_cache()  # list directory names, stripping the file path basename(inspect_cache)  # list all files in subdirectories of the cache inspect_cache(recursive = TRUE)  # list all files in subdirectories, stripping the file path basename(inspect_cache(recursive_true)) } # }"},{"path":"https://adamhsparks.github.io/read.abares/reference/print_agfd_nc_file_format.html","id":null,"dir":"Reference","previous_headings":"","what":"Prints File Format Information for the AGFD NetCDF Files — print_agfd_nc_file_format","title":"Prints File Format Information for the AGFD NetCDF Files — print_agfd_nc_file_format","text":"Print file format section 3.2 Australian Bureau Agricultural Resource Economics Sciences.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/print_agfd_nc_file_format.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prints File Format Information for the AGFD NetCDF Files — print_agfd_nc_file_format","text":"","code":"print_agfd_nc_file_format()"},{"path":"https://adamhsparks.github.io/read.abares/reference/print_agfd_nc_file_format.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Prints File Format Information for the AGFD NetCDF Files — print_agfd_nc_file_format","text":"https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1036161/0","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/print_agfd_nc_file_format.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Prints File Format Information for the AGFD NetCDF Files — print_agfd_nc_file_format","text":"Australian gridded farm data, Australian Bureau Agricultural Resource Economics Sciences, Canberra, July, DOI: <https://doi.org/10.25814/7n6z-ev41. CC 4.0.>","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/print_agfd_nc_file_format.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prints File Format Information for the AGFD NetCDF Files — print_agfd_nc_file_format","text":"","code":"print_agfd_nc_file_format() #> ──────────────────────────────────────────────────────────────────────────────── #> Each of the layers in simulation output data is represented as a 2D raster in #> NETCDF files, with the following grid format: #>  #> CRS: EPSG:4326 - WGS 84 - Geographic #> Extent: 111.975 -44.525 156.275 -9.975 #> Unit: Degrees #> Width: 886 #> Height: 691 #> Cell size: 0.05 degree x 0.05 degree #> ──────────────────────────────────────────────────────────────────────────────── #> For further details, see the ABARES website, #> <https://www.agriculture.gov.au/abares/research-topics/surveys/farm-survey-data/australian-gridded-farm-data>"},{"path":"https://adamhsparks.github.io/read.abares/reference/print_soil_thickness_metadata.html","id":null,"dir":"Reference","previous_headings":"","what":"Display Complete Metadata Associated with Soil Thickness Data in the R Console — print_soil_thickness_metadata","title":"Display Complete Metadata Associated with Soil Thickness Data in the R Console — print_soil_thickness_metadata","text":"Displays complete set metadata associated soil thickness data R console. including metadata documents methods outside R, see get_soil_thickness example using pander::pander print metadata.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/print_soil_thickness_metadata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Display Complete Metadata Associated with Soil Thickness Data in the R Console — print_soil_thickness_metadata","text":"","code":"print_soil_thickness_metadata(x)"},{"path":"https://adamhsparks.github.io/read.abares/reference/print_soil_thickness_metadata.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Display Complete Metadata Associated with Soil Thickness Data in the R Console — print_soil_thickness_metadata","text":"x read.abares.soil.thickness.files object","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/print_soil_thickness_metadata.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Display Complete Metadata Associated with Soil Thickness Data in the R Console — print_soil_thickness_metadata","text":"Nothing, called side effects, prints complete metadata file R console","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/print_soil_thickness_metadata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Display Complete Metadata Associated with Soil Thickness Data in the R Console — print_soil_thickness_metadata","text":"","code":"if (FALSE) { # interactive() get_soil_thickness(cache = TRUE) |>   print_soil_thickness_metadata() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read.abares-package.html","id":null,"dir":"Reference","previous_headings":"","what":"read.abares: Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources — read.abares-package","title":"read.abares: Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources — read.abares-package","text":"Download import data Australian Bureau Agricultural Resource Economics Sciences (ABARES) https://www.agriculture.gov.au/abares.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read.abares-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"read.abares: Provides simple downloading, parsing and importing of Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) data sources — read.abares-package","text":"Maintainer: Adam H. Sparks adamhsparks@gmail.com (ORCID) contributors: Jacob jacob@wujciak.de (ORCID) (Assisted troubleshooting formatting documentation display '<' '>' properly) [contributor] Curtin University Technology (Provided support Adam Sparks's time.) [copyright holder] Grains Research Development Corporation (GRDC Project CUR2210-005OPX (AAGI-CU)) [funder, copyright holder]","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":null,"dir":"Reference","previous_headings":"","what":"Read AAGIS Region Mapping Files — read_aagis_regions","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"Download, cache import Australian Agricultural Grazing Industries Survey (AAGIS regions geospatial shapefile. Upon import, geometries  automatically corrected fix invalid geometries present original shapefile.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"","code":"read_aagis_regions(cache = TRUE)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"https://www.agriculture.gov.au/sites/default/files/documents/aagis_asgs16v1_g5a.shp_.zip","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"cache Boolean Cache AAGIS regions' geospatial file downloading using tools::R_user_dir(\"read.abares\", \"cache\") identify proper directory storing user data cache package. Defaults TRUE, caching files locally Geopackage. FALSE, function uses tempdir() files deleted upon closing R session.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"sf object AAGIS regions","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"https://www.agriculture.gov.au/abares/research-topics/surveys/farm-definitions-methods#regions","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_aagis_regions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read AAGIS Region Mapping Files — read_aagis_regions","text":"","code":"if (FALSE) { # interactive() aagis <- read_aagis_regions()  plot(aagis) }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Data From the ABARES Trade Dashboard — read_abares_trade","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"Fetches imports  ABARES trade data.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"","code":"read_abares_trade(cache = TRUE)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1033841/0","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"cache Boolean Cache ABARES trade data download using tools::R_user_dir() identify proper directory storing user data cache package. Defaults TRUE, caching files locally native R object. FALSE, function uses tempdir() files deleted upon closing R session.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"data.table object ABARES trade data.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"Columns renamed consistency ABARES products serviced package using snake_case format ordered consistently.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"https://www.agriculture.gov.au/abares/research-topics/trade/dashboard","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Data From the ABARES Trade Dashboard — read_abares_trade","text":"","code":"if (FALSE) { # interactive() trade <- read_abares_trade()  trade }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":null,"dir":"Reference","previous_headings":"","what":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"Fetches imports  ABARES trade regions data.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"","code":"read_abares_trade_regions(cache = TRUE)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1033841/2","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"cache Boolean Cache ABARES trade regions data download using tools::R_user_dir() identify proper directory storing user data cache package. Defaults TRUE, caching files locally native R object. FALSE, function uses tempdir() files deleted upon closing R session.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"data.table object ABARES trade data regions.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"Columns renamed consistency ABARES products serviced package using snake_case format ordered consistently.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1033841/0","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_abares_trade_regions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read ABARES Trade Data Regions From the ABARES Trade Dashboard — read_abares_trade_regions","text":"","code":"if (FALSE) { # interactive() trade_regions <- read_abares_trade_regions()  trade_regions }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":null,"dir":"Reference","previous_headings":"","what":"Read AGFD NCDF Files as a data.table — read_agfd_dt","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"Read Australian Gridded Farm Data, (AGFD) data.table object.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"","code":"read_agfd_dt(files)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"files list AGFD NetCDF files import","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"data.table::data.table object Australian Gridded Farm Data","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"ABARES website: “Australian Gridded Farm Data (AGFD) set national scale maps containing simulated data historical broadacre farm business outcomes including farm profitability 0.05-degree (approximately 5 km) grid. data produced ABARES part ongoing Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data.Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data. maps provide estimates farm business profit, revenue, costs production location (grid cell) year period 1990-91 2022-23. data include actual observed outcomes rather model predicted outcomes representative ‘typical’ broadacre farm businesses location considering likely farm characteristics prevailing weather conditions commodity prices.” – ABARES, 2024-11-25 sets data large file size, .e., >1GB, require time download.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"historical-climate-fixed-prices-","dir":"Reference","previous_headings":"","what":"Historical climate (fixed prices)","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"Historical climate (fixed prices) scenario similar described Hughes et al. (2022) intended isolate effects climate variability financial incomes broadacre farm businesses. simulations, global output input price indexes fixed values recently completed financial year. However, scenarios spread domestic global grain (wheat, barley sorghum) prices, along Australian fodder prices allowed vary response climate data (capture domestic increases grain fodder prices drought years, see Hughes et al. 2022). 33-year historical climate sequence (including historical simulated crop pasture data AADI project) simulated grid cell (1990-91 2022-23).","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"historical-climate-and-prices","dir":"Reference","previous_headings":"","what":"Historical climate and prices","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"part AADI project additional scenario developed accounting changes climate conditions output input prices (.e., global commodity market variability). Historical climate prices scenario 33-year reference period allows variation \\ historical climate conditions historical prices. scenario, historical price indexes de-trended, account consistent long- term trends real commodity prices (particularly sheep lamb). resulting simulation results percentile indicators intended reflect combined impacts annual climate commodity price variability.\" – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"data-files","dir":"Reference","previous_headings":"","what":"Data files","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"Simulation output data saved multilayer NetCDF files, named using following convention: f<farm year>.c<climate year>.p<price year>.t<technology year>.nc : <farm year> = Financial year farm business data used simulations. <climate year> = Financial year climate data used simulations. <price year> = Financial year output input prices used simulations. <technology year> = Financial year farm ‘technology’ (equal farm year simulations) financial years referred closing calendar year (e.g., 2022 = 1 July 2021 30 June 2022). – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"data-layers","dir":"Reference","previous_headings":"","what":"Data layers","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"data layers downloaded NetCDF files described Table 2 seen Australian Bureau Agricultural Resource Economics Sciences (2024). Following copy Table 2 convenience, please refer full document methods metadata.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"Australian gridded farm data, Australian Bureau Agricultural Resource Economics Sciences, Canberra, July 2024, DOI: 10.25814/7n6z-ev41. CC 4.0. N. Hughes, W.Y. Soh, C. Boult, K. Lawson, Defining drought perspective Australian farmers, Climate Risk Management, Volume 35, 2022, 100420, ISSN 2212-0963, DOI: 10.1016/j.crm.2022.100420.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_dt.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read AGFD NCDF Files as a data.table — read_agfd_dt","text":"","code":"if (FALSE) { # interactive()  # using piping, which can use the {read.abares} cache after the first DL  get_agfd(cache = TRUE) |>   read_agfd_dt() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":null,"dir":"Reference","previous_headings":"","what":"Read AGFD NCDF Files With stars — read_agfd_stars","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"Read Australian Gridded Farm Data, (AGFD) list stars objects.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"","code":"read_agfd_stars(files)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"files list AGFD NetCDF files import","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"list object stars objects Australian Gridded Farm Data file names list's objects' names","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"ABARES website: “Australian Gridded Farm Data (AGFD) set national scale maps containing simulated data historical broadacre farm business outcomes including farm profitability 0.05-degree (approximately 5 km) grid. data produced ABARES part ongoing Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data.Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data. maps provide estimates farm business profit, revenue, costs production location (grid cell) year period 1990-91 2022-23. data include actual observed outcomes rather model predicted outcomes representative ‘typical’ broadacre farm businesses location considering likely farm characteristics prevailing weather conditions commodity prices.” – ABARES, 2024-11-25 sets data large file size, .e., >1GB, require time download.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"historical-climate-fixed-prices-","dir":"Reference","previous_headings":"","what":"Historical climate (fixed prices)","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"Historical climate (fixed prices) scenario similar described Hughes et al. (2022) intended isolate effects climate variability financial incomes broadacre farm businesses. simulations, global output input price indexes fixed values recently completed financial year. However, scenarios spread domestic global grain (wheat, barley sorghum) prices, along Australian fodder prices allowed vary response climate data (capture domestic increases grain fodder prices drought years, see Hughes et al. 2022). 33-year historical climate sequence (including historical simulated crop pasture data AADI project) simulated grid cell (1990-91 2022-23).","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"historical-climate-and-prices","dir":"Reference","previous_headings":"","what":"Historical climate and prices","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"part AADI project additional scenario developed accounting changes climate conditions output input prices (.e., global commodity market variability). Historical climate prices scenario 33-year reference period allows variation \\ historical climate conditions historical prices. scenario, historical price indexes de-trended, account consistent long- term trends real commodity prices (particularly sheep lamb). resulting simulation results percentile indicators intended reflect combined impacts annual climate commodity price variability.\" – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"data-files","dir":"Reference","previous_headings":"","what":"Data files","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"Simulation output data saved multilayer NetCDF files, named using following convention: f<farm year>.c<climate year>.p<price year>.t<technology year>.nc : <farm year> = Financial year farm business data used simulations. <climate year> = Financial year climate data used simulations. <price year> = Financial year output input prices used simulations. <technology year> = Financial year farm ‘technology’ (equal farm year simulations) financial years referred closing calendar year (e.g., 2022 = 1 July 2021 30 June 2022). – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"data-layers","dir":"Reference","previous_headings":"","what":"Data layers","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"data layers downloaded NetCDF files described Table 2 seen Australian Bureau Agricultural Resource Economics Sciences (2024). Following copy Table 2 convenience, please refer full document methods metadata.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"Australian gridded farm data, Australian Bureau Agricultural Resource Economics Sciences, Canberra, July 2024, DOI: 10.25814/7n6z-ev41. CC 4.0. N. Hughes, W.Y. Soh, C. Boult, K. Lawson, Defining drought perspective Australian farmers, Climate Risk Management, Volume 35, 2022, 100420, ISSN 2212-0963, DOI: 10.1016/j.crm.2022.100420.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_stars.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read AGFD NCDF Files With stars — read_agfd_stars","text":"","code":"if (FALSE) { # interactive()  # using piping, which can use the {read.abares} cache after the first DL  agfd <- get_agfd(cache = TRUE) |>   read_agfd_stars()  head(agfd)  plot(agfd[[1]]) }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":null,"dir":"Reference","previous_headings":"","what":"Read AGFD NCDF Files With terra — read_agfd_terra","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"Read Australian Gridded Farm Data, (AGFD) list terra::rast objects.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"","code":"read_agfd_terra(files)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"files list AGFD NetCDF files import","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"list object terra::rast objects Australian Gridded Farm Data file names list's objects' names","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"ABARES website: “Australian Gridded Farm Data (AGFD) set national scale maps containing simulated data historical broadacre farm business outcomes including farm profitability 0.05-degree (approximately 5 km) grid. data produced ABARES part ongoing Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data.Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data. maps provide estimates farm business profit, revenue, costs production location (grid cell) year period 1990-91 2022-23. data include actual observed outcomes rather model predicted outcomes representative ‘typical’ broadacre farm businesses location considering likely farm characteristics prevailing weather conditions commodity prices.” – ABARES, 2024-11-25 sets data large file size, .e., >1GB, require time download.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"historical-climate-fixed-prices-","dir":"Reference","previous_headings":"","what":"Historical climate (fixed prices)","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"Historical climate (fixed prices) scenario similar described Hughes et al. (2022) intended isolate effects climate variability financial incomes broadacre farm businesses. simulations, global output input price indexes fixed values recently completed financial year. However, scenarios spread domestic global grain (wheat, barley sorghum) prices, along Australian fodder prices allowed vary response climate data (capture domestic increases grain fodder prices drought years, see Hughes et al. 2022). 33-year historical climate sequence (including historical simulated crop pasture data AADI project) simulated grid cell (1990-91 2022-23).","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"historical-climate-and-prices","dir":"Reference","previous_headings":"","what":"Historical climate and prices","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"part AADI project additional scenario developed accounting changes climate conditions output input prices (.e., global commodity market variability). Historical climate prices scenario 33-year reference period allows variation \\ historical climate conditions historical prices. scenario, historical price indexes de-trended, account consistent long- term trends real commodity prices (particularly sheep lamb). resulting simulation results percentile indicators intended reflect combined impacts annual climate commodity price variability.\" – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"data-files","dir":"Reference","previous_headings":"","what":"Data files","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"Simulation output data saved multilayer NetCDF files, named using following convention: f<farm year>.c<climate year>.p<price year>.t<technology year>.nc : <farm year> = Financial year farm business data used simulations. <climate year> = Financial year climate data used simulations. <price year> = Financial year output input prices used simulations. <technology year> = Financial year farm ‘technology’ (equal farm year simulations) financial years referred closing calendar year (e.g., 2022 = 1 July 2021 30 June 2022). – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"data-layers","dir":"Reference","previous_headings":"","what":"Data layers","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"data layers downloaded NetCDF files described Table 2 seen Australian Bureau Agricultural Resource Economics Sciences (2024). Following copy Table 2 convenience, please refer full document methods metadata.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"Australian gridded farm data, Australian Bureau Agricultural Resource Economics Sciences, Canberra, July 2024, DOI: 10.25814/7n6z-ev41. CC 4.0. N. Hughes, W.Y. Soh, C. Boult, K. Lawson, Defining drought perspective Australian farmers, Climate Risk Management, Volume 35, 2022, 100420, ISSN 2212-0963, DOI: 10.1016/j.crm.2022.100420.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_terra.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read AGFD NCDF Files With terra — read_agfd_terra","text":"","code":"if (FALSE) { # interactive()  # using piping, which can use the {read.abares} cache after the first DL  get_agfd(cache = TRUE) |>   read_agfd_terra() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":null,"dir":"Reference","previous_headings":"","what":"Read agfd NCDF Files With tidync — read_agfd_tidync","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"Read Australian Gridded Farm Data, (AGFD) list tidync objects","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"","code":"read_agfd_tidync(files)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"files list AGFD NetCDF files import","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"list object tidync tidync::tidync objects Australian Gridded Farm Data file names  list's objects' names.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"ABARES website: “Australian Gridded Farm Data (AGFD) set national scale maps containing simulated data historical broadacre farm business outcomes including farm profitability 0.05-degree (approximately 5 km) grid. data produced ABARES part ongoing Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data.Australian Agricultural Drought Indicator (AADI) project (previously known Drought Early Warning System Project) derived using ABARES farmpredict model, turn based ABARES Agricultural Grazing Industries Survey (AAGIS) data. maps provide estimates farm business profit, revenue, costs production location (grid cell) year period 1990-91 2022-23. data include actual observed outcomes rather model predicted outcomes representative ‘typical’ broadacre farm businesses location considering likely farm characteristics prevailing weather conditions commodity prices.” – ABARES, 2024-11-25 sets data large file size, .e., >1GB, require time download.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"historical-climate-fixed-prices-","dir":"Reference","previous_headings":"","what":"Historical climate (fixed prices)","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"Historical climate (fixed prices) scenario similar described Hughes et al. (2022) intended isolate effects climate variability financial incomes broadacre farm businesses. simulations, global output input price indexes fixed values recently completed financial year. However, scenarios spread domestic global grain (wheat, barley sorghum) prices, along Australian fodder prices allowed vary response climate data (capture domestic increases grain fodder prices drought years, see Hughes et al. 2022). 33-year historical climate sequence (including historical simulated crop pasture data AADI project) simulated grid cell (1990-91 2022-23).","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"historical-climate-and-prices","dir":"Reference","previous_headings":"","what":"Historical climate and prices","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"part AADI project additional scenario developed accounting changes climate conditions output input prices (.e., global commodity market variability). Historical climate prices scenario 33-year reference period allows variation \\ historical climate conditions historical prices. scenario, historical price indexes de-trended, account consistent long- term trends real commodity prices (particularly sheep lamb). resulting simulation results percentile indicators intended reflect combined impacts annual climate commodity price variability.\" – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"data-files","dir":"Reference","previous_headings":"","what":"Data files","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"Simulation output data saved multilayer NetCDF files, named using following convention: f<farm year>.c<climate year>.p<price year>.t<technology year>.nc : <farm year> = Financial year farm business data used simulations. <climate year> = Financial year climate data used simulations. <price year> = Financial year output input prices used simulations. <technology year> = Financial year farm ‘technology’ (equal farm year simulations) financial years referred closing calendar year (e.g., 2022 = 1 July 2021 30 June 2022). – Taken  Australian Bureau Agricultural Resource Economics Sciences (2024)","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"data-layers","dir":"Reference","previous_headings":"","what":"Data layers","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"data layers downloaded NetCDF files described Table 2 seen Australian Bureau Agricultural Resource Economics Sciences (2024). Following copy Table 2 convenience, please refer full document methods metadata.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"Australian gridded farm data, Australian Bureau Agricultural Resource Economics Sciences, Canberra, July 2024, DOI: 10.25814/7n6z-ev41. CC 4.0. N. Hughes, W.Y. Soh, C. Boult, K. Lawson, Defining drought perspective Australian farmers, Climate Risk Management, Volume 35, 2022, 100420, ISSN 2212-0963, DOI: 10.1016/j.crm.2022.100420.","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_agfd_tidync.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read agfd NCDF Files With tidync — read_agfd_tidync","text":"","code":"if (FALSE) { # interactive()  # using piping, which can use the {read.abares} cache after the first DL  x <- get_agfd(cache = TRUE) |>   read_agfd_tidync() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_performance_category.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","title":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","text":"Read Estimates Size ABARES","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_performance_category.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","text":"","code":"read_estimates_by_performance_category()  read_est_by_perf_cat()"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_performance_category.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","text":"https://www.agriculture.gov.au/sites/default/files/documents/fdp-BySize-ByPerformance.csv","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_performance_category.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","text":"data.table::data.table object","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_performance_category.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","text":"https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_performance_category.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Estimates by Size From ABARES — read_estimates_by_performance_category","text":"","code":"if (FALSE) { # interactive()  read_estimates_by_performance_category()  # or shorter read_est_by_perf_cat() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Estimates by Size From ABARES — read_estimates_by_size","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"Read Estimates Size ABARES","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"","code":"read_estimates_by_size()  read_est_by_size()"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"https://www.agriculture.gov.au/sites/default/files/documents/fdp-national-historical.csv","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"data.table::data.table object Variable field key.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"Columns renamed reordered consistency.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_estimates_by_size.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Estimates by Size From ABARES — read_estimates_by_size","text":"","code":"if (FALSE) { # interactive()  read_estimates_by_size()  # or shorter read_est_by_size() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"Read Historical Forecast Database ABARES","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"","code":"read_historical_forecast_database()  read_historical_forecast()"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"https://daff.ent.sirsidynix.net.au/client/en_AU/search/asset/1031941/0","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"data.table::data.table object","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"Columns renamed consistency ABARES products serviced package using snake_case format ordered consistently. \"Month_issued\" column converted character string numeric value representing month year, e.g., \"March\" converted 3.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"data-dictionary","dir":"Reference","previous_headings":"","what":"Data Dictionary","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"resulting object contain following fields.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"https://www.agriculture.gov.au/abares/research-topics/agricultural-outlook/historical-forecasts#:~:text=%20the%20historical%20agricultural%20forecast,relevant%20to%20Australian%20agricultural%20markets","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_forecast_database.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Historical Forecast Database From ABARES — read_historical_forecast_database","text":"","code":"if (FALSE) { # interactive()  read_historical_forecast_database()  # or shorter read_historical_forecast() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Historical National Estimates from ABARES — read_historical_national_estimates","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"Read Historical National Estimates ABARES","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"","code":"read_historical_national_estimates()  read_hist_nat_est()"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"https://www.agriculture.gov.au/sites/default/files/documents/fdp-national-historical.csv","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"data.table::data.table object Variable field key.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"Columns renamed consistency ABARES products serviced package using snake_case format ordered consistently.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_national_estimates.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Historical National Estimates from ABARES — read_historical_national_estimates","text":"","code":"if (FALSE) { # interactive()  read_historical_national_estimates()  # or shorter read_hist_nat_est() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"Read Historical Regional Estimates ABARES","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"","code":"read_historical_regional_estimates()  read_hist_reg_est()"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"https://www.agriculture.gov.au/sites/default/files/documents/fdp-regional-historical.csv","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"data.table::data.table object Variable field key.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"Columns renamed consistency ABARES products serviced package using snake_case format ordered consistently.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_regional_estimates.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Historical Regional Estimates from ABARES — read_historical_regional_estimates","text":"","code":"if (FALSE) { # interactive() read_historical_regional_estimates()  # or shorter read_hist_reg_est() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Historical State Estimates from ABARES — read_historical_state_estimates","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"Read Historical State Estimates ABARES","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"","code":"read_historical_state_estimates()  read_hist_sta_est()"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"https://www.agriculture.gov.au/sites/default/files/documents/fdp-state-historical.csv","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"data.table::data.table object Variable field key.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"Columns renamed consistency ABARES products serviced package using snake_case format ordered consistently.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"https://www.agriculture.gov.au/abares/data/farm-data-portal#data-download","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_historical_state_estimates.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Historical State Estimates from ABARES — read_historical_state_estimates","text":"","code":"if (FALSE) { # interactive() read_historical_state_estimates()  # or shorter read_hist_sta_est() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Soil Thickness File With stars — read_soil_thickness_stars","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"Read Soil Thickness Australian Areas Intensive Agriculture Layer 1 data stars object.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"","code":"read_soil_thickness_stars(files)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"https://anrdl-integration-web-catalog-saxfirxkxt.s3-ap-southeast-2.amazonaws.com/warehouse/staiar9cl__059/staiar9cl__05911a01eg_geo___.zip","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"files read.abares read.abares.soil.thickness object, list contains ESRI grid file import","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"stars object Soil Thickness Australian Areas Intensive Agriculture Layer 1","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"https://data.agriculture.gov.au/geonetwork/srv/eng/catalog.search#/metadata/faa9f157-8e17-4b23-b6a7-37eb7920ead6","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_stars.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Soil Thickness File With stars — read_soil_thickness_stars","text":"","code":"if (FALSE) { # interactive() get_soil_thickness(cache = TRUE) |>   read_soil_thickness_stars() }"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Soil Thickness File With terra — read_soil_thickness_terra","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"Read Soil Thickness Australian Areas Intensive Agriculture Layer 1 data terra::rast object.","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"","code":"read_soil_thickness_terra(files)"},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"https://anrdl-integration-web-catalog-saxfirxkxt.s3-ap-southeast-2.amazonaws.com/warehouse/staiar9cl__059/staiar9cl__05911a01eg_geo___.zip","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"files read.abares read.abares.soil.thickness object, list contains ESRI grid file import","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"terra::rast object Soil Thickness Australian Areas Intensive Agriculture Layer 1","code":""},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"https://data.agriculture.gov.au/geonetwork/srv/eng/catalog.search#/metadata/faa9f157-8e17-4b23-b6a7-37eb7920ead6","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/reference/read_soil_thickness_terra.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Soil Thickness File With terra — read_soil_thickness_terra","text":"","code":"if (FALSE) { # interactive() x <- get_soil_thickness(cache = TRUE) |>   read_soil_thickness_terra()  # terra::plot() is reexported for convience plot(x) }"},{"path":"https://adamhsparks.github.io/read.abares/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. terra plot","code":""},{"path":[]},{"path":"https://adamhsparks.github.io/read.abares/news/index.html","id":"breaking-changes-1-0-0","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"read.abares 1.0.0","text":"Rename functions download read files active R session get_ read_ avoid confusion functions fetch data separate read_ functions Adds new function, print_agfd_nc_file_format() provide details AGFD NetCDF files’ contents Uses Geopackages {sf} objects rather .Rds, faster smaller file sizes caching Checks corrects geometries AAGIS Regions shapefile upon import applies cached object applicable","code":""},{"path":"https://adamhsparks.github.io/read.abares/news/index.html","id":"new-features-1-0-0","dir":"Changelog","previous_headings":"","what":"New features","title":"read.abares 1.0.0","text":"Improved documentation data sets now @source field points file provided data sets now @references field points references data Code linting thanks {flint} Use {httr2} handle downloads Increase timeout values deal stubborn long-running file downloads Uses {httr2}’s caching functionality simplify -session caching Use {brio} write downloads disk Use {httptest2} help test downloads Gracefully handle errors AGFD zip files corrupted download, provide user informative message remove corrupted download Tests run parallel quicker testing {sf} operations now quiet reading data possible","code":""},{"path":"https://adamhsparks.github.io/read.abares/news/index.html","id":"minor-improvements-and-fixes-1-0-0","dir":"Changelog","previous_headings":"","what":"Minor improvements and fixes","title":"read.abares 1.0.0","text":"longer checks length Boolean vector checking number files cache proceeding removing Fixes bugs get_agfd() creating directories saving downloaded file Fixes bug get_aagis_regions() creating cached object file Fixes “URL” field DESCRIPTION file (@mpadge https://github.com/adamhsparks/read.abares/issues/1)","code":""},{"path":"https://adamhsparks.github.io/read.abares/news/index.html","id":"readabares-010","dir":"Changelog","previous_headings":"","what":"read.abares 0.1.0","title":"read.abares 0.1.0","text":"Submission rOpenSci peer code review","code":""}]
diff --git a/sitemap.xml b/sitemap.xml
index 3ad85b1..dc20e01 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -1,5 +1,6 @@
 <urlset xmlns = 'http://www.sitemaps.org/schemas/sitemap/0.9'>
 <url><loc>https://adamhsparks.github.io/read.abares/404.html</loc></url>
+<url><loc>https://adamhsparks.github.io/read.abares/CODE_OF_CONDUCT.html</loc></url>
 <url><loc>https://adamhsparks.github.io/read.abares/CONTRIBUTING.html</loc></url>
 <url><loc>https://adamhsparks.github.io/read.abares/LICENSE-text.html</loc></url>
 <url><loc>https://adamhsparks.github.io/read.abares/LICENSE.html</loc></url>
