Copy_of_exploration.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Copy of exploration.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/simonm3/published/blob/master/Copy_of_exploration.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vajgKCRqmfcT",
        "colab_type": "code",
        "outputId": "817400e7-03d4-4cbd-a2f2-c0be7872ad83",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 598
        }
      },
      "source": [
        "#https://developers.google.com/earth-engine/python_install\n",
        "#You 1st need to sign up your Google account here: https://earthengine.google.com/ (it takes a couple of hours to get accepted. The API won't work before.)\n",
        "import ee\n",
        "import folium\n",
        "from IPython.display import Image\n",
        "!pip install earthengine-api\n",
        "ee.Authenticate()\n",
        "ee.Initialize()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: earthengine-api in /usr/local/lib/python3.6/dist-packages (0.1.204)\n",
            "Requirement already satisfied: google-auth>=1.4.1 in /usr/local/lib/python3.6/dist-packages (from earthengine-api) (1.4.2)\n",
            "Requirement already satisfied: google-auth-httplib2>=0.0.3 in /usr/local/lib/python3.6/dist-packages (from earthengine-api) (0.0.3)\n",
            "Requirement already satisfied: future in /usr/local/lib/python3.6/dist-packages (from earthengine-api) (0.16.0)\n",
            "Requirement already satisfied: httplib2<1dev,>=0.9.2 in /usr/local/lib/python3.6/dist-packages (from earthengine-api) (0.11.3)\n",
            "Requirement already satisfied: google-cloud-storage in /usr/local/lib/python3.6/dist-packages (from earthengine-api) (1.16.2)\n",
            "Requirement already satisfied: google-api-python-client in /usr/local/lib/python3.6/dist-packages (from earthengine-api) (1.7.11)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from earthengine-api) (1.12.0)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.6/dist-packages (from google-auth>=1.4.1->earthengine-api) (0.2.7)\n",
            "Requirement already satisfied: rsa>=3.1.4 in /usr/local/lib/python3.6/dist-packages (from google-auth>=1.4.1->earthengine-api) (4.0)\n",
            "Requirement already satisfied: cachetools>=2.0.0 in /usr/local/lib/python3.6/dist-packages (from google-auth>=1.4.1->earthengine-api) (3.1.1)\n",
            "Requirement already satisfied: google-cloud-core<2.0dev,>=1.0.0 in /usr/local/lib/python3.6/dist-packages (from google-cloud-storage->earthengine-api) (1.0.3)\n",
            "Requirement already satisfied: google-resumable-media<0.5.0dev,>=0.3.1 in /usr/local/lib/python3.6/dist-packages (from google-cloud-storage->earthengine-api) (0.4.1)\n",
            "Requirement already satisfied: uritemplate<4dev,>=3.0.0 in /usr/local/lib/python3.6/dist-packages (from google-api-python-client->earthengine-api) (3.0.0)\n",
            "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.6/dist-packages (from pyasn1-modules>=0.2.1->google-auth>=1.4.1->earthengine-api) (0.4.7)\n",
            "Requirement already satisfied: google-api-core<2.0.0dev,>=1.14.0 in /usr/local/lib/python3.6/dist-packages (from google-cloud-core<2.0dev,>=1.0.0->google-cloud-storage->earthengine-api) (1.14.3)\n",
            "Requirement already satisfied: pytz in /usr/local/lib/python3.6/dist-packages (from google-api-core<2.0.0dev,>=1.14.0->google-cloud-core<2.0dev,>=1.0.0->google-cloud-storage->earthengine-api) (2018.9)\n",
            "Requirement already satisfied: protobuf>=3.4.0 in /usr/local/lib/python3.6/dist-packages (from google-api-core<2.0.0dev,>=1.14.0->google-cloud-core<2.0dev,>=1.0.0->google-cloud-storage->earthengine-api) (3.10.0)\n",
            "Requirement already satisfied: requests<3.0.0dev,>=2.18.0 in /usr/local/lib/python3.6/dist-packages (from google-api-core<2.0.0dev,>=1.14.0->google-cloud-core<2.0dev,>=1.0.0->google-cloud-storage->earthengine-api) (2.21.0)\n",
            "Requirement already satisfied: googleapis-common-protos<2.0dev,>=1.6.0 in /usr/local/lib/python3.6/dist-packages (from google-api-core<2.0.0dev,>=1.14.0->google-cloud-core<2.0dev,>=1.0.0->google-cloud-storage->earthengine-api) (1.6.0)\n",
            "Requirement already satisfied: setuptools>=34.0.0 in /usr/local/lib/python3.6/dist-packages (from google-api-core<2.0.0dev,>=1.14.0->google-cloud-core<2.0dev,>=1.0.0->google-cloud-storage->earthengine-api) (41.4.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2.0.0dev,>=1.14.0->google-cloud-core<2.0dev,>=1.0.0->google-cloud-storage->earthengine-api) (2019.9.11)\n",
            "Requirement already satisfied: urllib3<1.25,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2.0.0dev,>=1.14.0->google-cloud-core<2.0dev,>=1.0.0->google-cloud-storage->earthengine-api) (1.24.3)\n",
            "Requirement already satisfied: idna<2.9,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2.0.0dev,>=1.14.0->google-cloud-core<2.0dev,>=1.0.0->google-cloud-storage->earthengine-api) (2.8)\n",
            "Requirement already satisfied: chardet<3.1.0,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2.0.0dev,>=1.14.0->google-cloud-core<2.0dev,>=1.0.0->google-cloud-storage->earthengine-api) (3.0.4)\n",
            "To authorize access needed by Earth Engine, open the following URL in a web browser and follow the instructions. If the web browser does not start automatically, please manually browse the URL below.\n",
            "\n",
            "    https://accounts.google.com/o/oauth2/auth?client_id=517222506229-vsmmajv00ul0bs7p89v5m89qs8eb9359.apps.googleusercontent.com&scope=https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fearthengine+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdevstorage.full_control&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob&response_type=code\n",
            "\n",
            "The authorization workflow will generate a code, which you should paste in the box below. \n",
            "Enter verification code: 4/swEUlvLrGM6rzT2QogtQMPp0oXBl7YiuDte1HDOl28gTRBf4cNarnyM\n",
            "\n",
            "Successfully saved authorization token.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lqkM3Ki6sza3",
        "colab_type": "text"
      },
      "source": [
        "### Generates an interactive Map (tutorial code)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xOyjdSWPmgdN",
        "colab_type": "code",
        "outputId": "9c5be9af-c03d-4aee-a221-44b12fa6e728",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        }
      },
      "source": [
        "# Import libraries.\n",
        "import ee\n",
        "import folium\n",
        "\n",
        "# Initialize the Earth Engine library.\n",
        "ee.Initialize()\n",
        "\n",
        "# Define a method for displaying Earth Engine image tiles to folium map.\n",
        "def add_ee_layer(self, eeImageObject, visParams, name):\n",
        "  mapID = ee.Image(eeImageObject).getMapId(visParams)\n",
        "  folium.raster_layers.TileLayer(\n",
        "    tiles = \"https://earthengine.googleapis.com/map/\"+mapID['mapid']+\n",
        "      \"/{z}/{x}/{y}?token=\"+mapID['token'],\n",
        "    attr = \"Map Data © Google Earth Engine\",\n",
        "    name = name,\n",
        "    overlay = True,\n",
        "    control = True\n",
        "  ).add_to(self)\n",
        "\n",
        "# Add EE drawing method to folium.\n",
        "folium.Map.add_ee_layer = add_ee_layer\n",
        "\n",
        "# Fetch an elevation model.\n",
        "# dem = ee.Image('USGS/SRTMGL1_003')\n",
        "dem = ee.Image('USGS/SRTMGL1_003')\n",
        "\n",
        "# Set visualization parameters.\n",
        "visParams = {'min':0, 'max':3000, 'palette':['225ea8','41b6c4','a1dab4','ffffcc']}\n",
        "\n",
        "# Create a folium map object.\n",
        "myMap = folium.Map(location=[20, 0], zoom_start=3, height=500)\n",
        "\n",
        "# Add the elevation model to the map object.\n",
        "# myMap.add_ee_layer(dem, visParams, 'DEM')\n",
        "\n",
        "nighttimeLights = dem.select('avg_vis')\n",
        "nighttimeLightsVis = {min: 3.0,max: 60.0}\n",
        "myMap.add_ee_layer(nighttimeLights, nighttimeLightsVis, 'Nighttime Lights');\n",
        "\n",
        "# Add a layer control panel to the map.\n",
        "myMap.add_child(folium.LayerControl())\n",
        "\n",
        "# Display the map.\n",
        "display(myMap)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "error",
          "ename": "EEException",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mEEException\u001b[0m                               Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-27-31885d4bfbf4>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     35\u001b[0m \u001b[0mnighttimeLights\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdem\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mselect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'avg_vis'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     36\u001b[0m \u001b[0mnighttimeLightsVis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0mmin\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;36m3.0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mmax\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;36m60.0\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 37\u001b[0;31m \u001b[0mmyMap\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_ee_layer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnighttimeLights\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnighttimeLightsVis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'Nighttime Lights'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m;\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     38\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     39\u001b[0m \u001b[0;31m# Add a layer control panel to the map.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-27-31885d4bfbf4>\u001b[0m in \u001b[0;36madd_ee_layer\u001b[0;34m(self, eeImageObject, visParams, name)\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0;31m# Define a method for displaying Earth Engine image tiles to folium map.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0madd_ee_layer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0meeImageObject\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvisParams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m   \u001b[0mmapID\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mee\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mImage\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0meeImageObject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetMapId\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvisParams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     10\u001b[0m   folium.raster_layers.TileLayer(\n\u001b[1;32m     11\u001b[0m     \u001b[0mtiles\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"https://earthengine.googleapis.com/map/\"\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mmapID\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'mapid'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/ee/image.py\u001b[0m in \u001b[0;36mgetMapId\u001b[0;34m(self, vis_params)\u001b[0m\n\u001b[1;32m    129\u001b[0m     \u001b[0mvis_image\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrequest\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_apply_visualization\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvis_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    130\u001b[0m     \u001b[0mrequest\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'image'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvis_image\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 131\u001b[0;31m     \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetMapId\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    132\u001b[0m     \u001b[0mresponse\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'image'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    133\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/ee/data.py\u001b[0m in \u001b[0;36mgetMapId\u001b[0;34m(params)\u001b[0m\n\u001b[1;32m    575\u001b[0m     \u001b[0mparams\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'image'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'image'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mserialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    576\u001b[0m   \u001b[0mparams\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'json_format'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'v2'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 577\u001b[0;31m   \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msend_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/mapid'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    578\u001b[0m   url_format = '%s/map/%s/{z}/{x}/{y}?token=%s' % (\n\u001b[1;32m    579\u001b[0m       _tile_base_url, result['mapid'], result['token'])\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/ee/data.py\u001b[0m in \u001b[0;36msend_\u001b[0;34m(path, params, opt_method, opt_raw)\u001b[0m\n\u001b[1;32m   1776\u001b[0m       \u001b[0;32mraise\u001b[0m \u001b[0mee_exception\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mEEException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Invalid JSON: %s'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mcontent\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1777\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;34m'error'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mjson_content\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1778\u001b[0;31m       \u001b[0;32mraise\u001b[0m \u001b[0mee_exception\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mEEException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjson_content\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'error'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'message'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1779\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;34m'data'\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mcontent\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1780\u001b[0m       \u001b[0;32mraise\u001b[0m \u001b[0mee_exception\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mEEException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Malformed response: '\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcontent\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mEEException\u001b[0m: Image.select: Pattern 'avg_vis' did not match any bands."
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tqLvMATjJVaC",
        "colab_type": "text"
      },
      "source": [
        "Night lights Nigeria"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h9CJfCuhJUF0",
        "colab_type": "code",
        "outputId": "03efdd39-028a-48eb-c8c7-8b49a1cdbce7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "#I found the JS code here: https://github.com/google/earthengine-api\n",
        "# Create a folium map object.\n",
        "myMap = folium.Map(location=[9.0820, 8.6753], zoom_start=6, height=1000)\n",
        "\n",
        "# Adds a band containing image date as years since 1991.\n",
        "def createTimeBand(img):\n",
        "  year = ee.Date(img.get('system:time_start')).get('year').subtract(1991)\n",
        "  return ee.Image(year).byte().addBands(img)\n",
        "\n",
        "\n",
        "# Map the time band creation helper over the night-time lights collection.\n",
        "# https://developers.google.com/earth-engine/datasets/catalog/NOAA_DMSP-OLS_NIGHTTIME_LIGHTS\n",
        "collection = ee.ImageCollection('NOAA/DMSP-OLS/NIGHTTIME_LIGHTS').select('stable_lights').map(createTimeBand)\n",
        "\n",
        "# Compute a linear fit over the series of values at each pixel, visualizing\n",
        "# the y-intercept in green, and positive/negative slopes as red/blue.\n",
        "myMap.add_ee_layer(collection.reduce(ee.Reducer.linearFit()),{'bands':['scale', 'offset', 'scale'], 'min': 0, 'max': [0.18, 20, -0.18]},'stable lights trend')\n",
        "\n",
        "# Add a layer control panel to the map.\n",
        "myMap.add_child(folium.LayerControl())\n",
        "\n",
        "# Display the map.\n",
        "display(myMap)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><iframe src=\"data:text/html;charset=utf-8;base64,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\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
            ],
            "text/plain": [
              "<folium.folium.Map at 0x7f288b67ea58>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Tbf7CiCQj9Op",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "collection.reduce?"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Bn_0IxqhNGLF",
        "colab_type": "text"
      },
      "source": [
        "Air Temperature"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SqQAeaw3LxED",
        "colab_type": "code",
        "outputId": "0ea37859-7873-40d0-ee01-154aea985909",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "# Create a folium map object.\n",
        "myMap = folium.Map(location=[9.0820, 8.6753], zoom_start=6, height=1000)\n",
        "\n",
        "# Adds a band containing image date as years since 1991.\n",
        "def createTimeBand(img):\n",
        "  year = ee.Date(img.get('system:time_start')).get('year').subtract(1991)\n",
        "  return ee.Image(year).byte().addBands(img)\n",
        "\n",
        "\n",
        "# Map the time band creation helper over the night-time lights collection.\n",
        "# https://developers.google.com/earth-engine/datasets/catalog/NOAA_DMSP-OLS_NIGHTTIME_LIGHTS\n",
        "collection = ee.ImageCollection('ECMWF/ERA5/DAILY').select('maximum_2m_air_temperature').filter(ee.Filter.date('2019-07-01', '2019-07-31'))\n",
        "\n",
        "# Compute a linear fit over the series of values at each pixel, visualizing\n",
        "# the y-intercept in green, and positive/negative slopes as red/blue.\n",
        "visParams = {\n",
        "  'min': 250,\n",
        "  'max': 320,\n",
        "  'palette': [\n",
        "    '#000080', '#0000D9', '#4000FF', '#8000FF', '#0080FF', '#00FFFF', '#00FF80',\n",
        "    '#80FF00', '#DAFF00', '#FFFF00', '#FFF500', '#FFDA00', '#FFB000', '#FFA400',\n",
        "    '#FF4F00', '#FF2500', '#FF0A00', '#FF00FF'\n",
        "  ]\n",
        "}\n",
        "myMap.add_ee_layer(collection.reduce(ee.Reducer.median()),visParams,'mean 2m air temperature')\n",
        "\n",
        "# Add a layer control panel to the map.\n",
        "myMap.add_child(folium.LayerControl())\n",
        "\n",
        "# Display the map.\n",
        "display(myMap)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><iframe src=\"data:text/html;charset=utf-8;base64,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\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
            ],
            "text/plain": [
              "<folium.folium.Map at 0x7f288b7615c0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rHx3tI0EKAjM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "collection.reduce?"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lRAxStFNs7WZ",
        "colab_type": "text"
      },
      "source": [
        "Generates a satelite video evolution of the selected region (currently not working)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jsEQqpI3kfhP",
        "colab_type": "code",
        "outputId": "a9a99efc-dec8-4d77-d48d-62aa3b9130ad",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "#initial snippet found here: https://geoscripting-wur.github.io/Earth_Engine/\n",
        "import ee\n",
        "from ee import batch\n",
        "## Initialize connection to server\n",
        "ee.Initialize()\n",
        "## Define your image collection\n",
        "#collection = ee.ImageCollection('LANDSAT/LC8_L1T_TOA')\n",
        "collection = ee.ImageCollection('ECMWF/ERA5/DAILY')\n",
        "## Define time range\n",
        "collection_time = collection.filterDate('2013-04-11', '2018-01-01') #YYYY-MM-DD\n",
        "## Select location based on location of tile\n",
        "path = collection_time.filter(ee.Filter.eq('WRS_PATH', 198))\n",
        "pathrow = path.filter(ee.Filter.eq('WRS_ROW', 24))\n",
        "# or via geographical location:\n",
        "#point_geom = ee.Geometry.Point(5, 52) #longitude, latitude\n",
        "#pathrow = collection_time.filterBounds(point_geom)\n",
        "## Select imagery with less then 5% of image covered by clouds\n",
        "clouds = pathrow.filter(ee.Filter.lt('CLOUD_COVER', 5))\n",
        "## Select bands\n",
        "bands = clouds.select(['B4', 'B3', 'B2'])\n",
        "## Make 8 bit data\n",
        "def convertBit(image):\n",
        "    return image.multiply(512).uint8()  \n",
        "## Convert bands to output video  \n",
        "outputVideo = bands.map(convertBit)\n",
        "print(\"Starting to create a video\")\n",
        "## Export video to Google Drive\n",
        "out = batch.Export.video.toDrive(outputVideo, description='Nigeria_video_region_L8_time', dimensions = 720, framesPerSecond = 2, region=([8.6753,9.0820], [8.6753, 9.0820],[8.6753, 9.0820],[8.6753, 9.0820]), maxFrames=10000)\n",
        "## Process the image\n",
        "process = batch.Task\n",
        "process.start(out)\n",
        "print(\"Process sent to cloud\")"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Starting to create a video\n",
            "Process sent to cloud\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NEKEWDCWx71p",
        "colab_type": "code",
        "outputId": "9e27f7fd-69b6-46ef-b264-886c3a1046a3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        }
      },
      "source": [
        "process.status(out)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'creation_timestamp_ms': 1572961002177,\n",
              " 'description': 'Nigeria_video_region_L8_time',\n",
              " 'id': 'ZZUHXBEJBUXCELJ4DHLNHQFO',\n",
              " 'state': 'READY',\n",
              " 'task_type': 'EXPORT_VIDEO',\n",
              " 'update_timestamp_ms': 1572961002177}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 79
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nY2UsiP6u623",
        "colab_type": "code",
        "outputId": "a5d37d2e-37ae-44f3-ae2e-d184cb06fcc3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        }
      },
      "source": [
        "process.list()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<Task EXPORT_VIDEO: Nigeria_video_region_L8_time (FAILED)>,\n",
              " <Task EXPORT_VIDEO: Nigeria_video_region_L8_time (FAILED)>,\n",
              " <Task EXPORT_VIDEO: Nigeria_video_region_L8_time (FAILED)>,\n",
              " <Task EXPORT_VIDEO: Nigeria_video_region_L8_time (FAILED)>,\n",
              " <Task EXPORT_VIDEO: Nigeria_video_region_L8_time (FAILED)>,\n",
              " <Task EXPORT_VIDEO: Netherlands_video_region_L8_time (COMPLETED)>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V_K89Qzsk8_C",
        "colab_type": "code",
        "outputId": "7b7d6430-cd68-471e-dc6b-60f136fbbe5d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "print(outputVideo)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ee.ImageCollection({\n",
            "  \"type\": \"Invocation\",\n",
            "  \"arguments\": {\n",
            "    \"collection\": {\n",
            "      \"type\": \"Invocation\",\n",
            "      \"arguments\": {\n",
            "        \"collection\": {\n",
            "          \"type\": \"Invocation\",\n",
            "          \"arguments\": {\n",
            "            \"collection\": {\n",
            "              \"type\": \"Invocation\",\n",
            "              \"arguments\": {\n",
            "                \"collection\": {\n",
            "                  \"type\": \"Invocation\",\n",
            "                  \"arguments\": {\n",
            "                    \"collection\": {\n",
            "                      \"type\": \"Invocation\",\n",
            "                      \"arguments\": {\n",
            "                        \"collection\": {\n",
            "                          \"type\": \"Invocation\",\n",
            "                          \"arguments\": {\n",
            "                            \"id\": \"LANDSAT/LC8_L1T_TOA\"\n",
            "                          },\n",
            "                          \"functionName\": \"ImageCollection.load\"\n",
            "                        },\n",
            "                        \"filter\": {\n",
            "                          \"type\": \"Invocation\",\n",
            "                          \"arguments\": {\n",
            "                            \"rightField\": \"system:time_start\",\n",
            "                            \"leftValue\": {\n",
            "                              \"type\": \"Invocation\",\n",
            "                              \"arguments\": {\n",
            "                                \"start\": \"2013-04-11\",\n",
            "                                \"end\": \"2018-01-01\"\n",
            "                              },\n",
            "                              \"functionName\": \"DateRange\"\n",
            "                            }\n",
            "                          },\n",
            "                          \"functionName\": \"Filter.dateRangeContains\"\n",
            "                        }\n",
            "                      },\n",
            "                      \"functionName\": \"Collection.filter\"\n",
            "                    },\n",
            "                    \"filter\": {\n",
            "                      \"type\": \"Invocation\",\n",
            "                      \"arguments\": {\n",
            "                        \"leftField\": \"WRS_PATH\",\n",
            "                        \"rightValue\": 198\n",
            "                      },\n",
            "                      \"functionName\": \"Filter.equals\"\n",
            "                    }\n",
            "                  },\n",
            "                  \"functionName\": \"Collection.filter\"\n",
            "                },\n",
            "                \"filter\": {\n",
            "                  \"type\": \"Invocation\",\n",
            "                  \"arguments\": {\n",
            "                    \"leftField\": \"WRS_ROW\",\n",
            "                    \"rightValue\": 24\n",
            "                  },\n",
            "                  \"functionName\": \"Filter.equals\"\n",
            "                }\n",
            "              },\n",
            "              \"functionName\": \"Collection.filter\"\n",
            "            },\n",
            "            \"filter\": {\n",
            "              \"type\": \"Invocation\",\n",
            "              \"arguments\": {\n",
            "                \"leftField\": \"CLOUD_COVER\",\n",
            "                \"rightValue\": 5\n",
            "              },\n",
            "              \"functionName\": \"Filter.lessThan\"\n",
            "            }\n",
            "          },\n",
            "          \"functionName\": \"Collection.filter\"\n",
            "        },\n",
            "        \"baseAlgorithm\": {\n",
            "          \"type\": \"Function\",\n",
            "          \"argumentNames\": [\n",
            "            \"_MAPPING_VAR_0_0\"\n",
            "          ],\n",
            "          \"body\": {\n",
            "            \"type\": \"Invocation\",\n",
            "            \"arguments\": {\n",
            "              \"input\": {\n",
            "                \"type\": \"ArgumentRef\",\n",
            "                \"value\": \"_MAPPING_VAR_0_0\"\n",
            "              },\n",
            "              \"bandSelectors\": [\n",
            "                \"B4\",\n",
            "                \"B3\",\n",
            "                \"B2\"\n",
            "              ]\n",
            "            },\n",
            "            \"functionName\": \"Image.select\"\n",
            "          }\n",
            "        }\n",
            "      },\n",
            "      \"functionName\": \"Collection.map\"\n",
            "    },\n",
            "    \"baseAlgorithm\": {\n",
            "      \"type\": \"Function\",\n",
            "      \"argumentNames\": [\n",
            "        \"_MAPPING_VAR_0_0\"\n",
            "      ],\n",
            "      \"body\": {\n",
            "        \"type\": \"Invocation\",\n",
            "        \"arguments\": {\n",
            "          \"value\": {\n",
            "            \"type\": \"Invocation\",\n",
            "            \"arguments\": {\n",
            "              \"image1\": {\n",
            "                \"type\": \"ArgumentRef\",\n",
            "                \"value\": \"_MAPPING_VAR_0_0\"\n",
            "              },\n",
            "              \"image2\": {\n",
            "                \"type\": \"Invocation\",\n",
            "                \"arguments\": {\n",
            "                  \"value\": 512\n",
            "                },\n",
            "                \"functionName\": \"Image.constant\"\n",
            "              }\n",
            "            },\n",
            "            \"functionName\": \"Image.multiply\"\n",
            "          }\n",
            "        },\n",
            "        \"functionName\": \"Image.uint8\"\n",
            "      }\n",
            "    }\n",
            "  },\n",
            "  \"functionName\": \"Collection.map\"\n",
            "})\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IOuOyTBSkg_0",
        "colab_type": "code",
        "outputId": "c8182145-eabd-4517-c8db-768554817b8b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        }
      },
      "source": [
        "print(dem)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ee.Image({\n",
            "  \"type\": \"Invocation\",\n",
            "  \"arguments\": {\n",
            "    \"id\": \"USGS/SRTMGL1_003\"\n",
            "  },\n",
            "  \"functionName\": \"Image.load\"\n",
            "})\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i6Jr6_UhvauF",
        "colab_type": "code",
        "outputId": "730af235-a8fb-40a1-c5a4-87b760e7a8dd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 969
        }
      },
      "source": [
        "print(pathrow)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ee.ImageCollection({\n",
            "  \"type\": \"Invocation\",\n",
            "  \"arguments\": {\n",
            "    \"collection\": {\n",
            "      \"type\": \"Invocation\",\n",
            "      \"arguments\": {\n",
            "        \"collection\": {\n",
            "          \"type\": \"Invocation\",\n",
            "          \"arguments\": {\n",
            "            \"collection\": {\n",
            "              \"type\": \"Invocation\",\n",
            "              \"arguments\": {\n",
            "                \"id\": \"LANDSAT/LC8_L1T_TOA\"\n",
            "              },\n",
            "              \"functionName\": \"ImageCollection.load\"\n",
            "            },\n",
            "            \"filter\": {\n",
            "              \"type\": \"Invocation\",\n",
            "              \"arguments\": {\n",
            "                \"rightField\": \"system:time_start\",\n",
            "                \"leftValue\": {\n",
            "                  \"type\": \"Invocation\",\n",
            "                  \"arguments\": {\n",
            "                    \"start\": \"2013-04-11\",\n",
            "                    \"end\": \"2018-01-01\"\n",
            "                  },\n",
            "                  \"functionName\": \"DateRange\"\n",
            "                }\n",
            "              },\n",
            "              \"functionName\": \"Filter.dateRangeContains\"\n",
            "            }\n",
            "          },\n",
            "          \"functionName\": \"Collection.filter\"\n",
            "        },\n",
            "        \"filter\": {\n",
            "          \"type\": \"Invocation\",\n",
            "          \"arguments\": {\n",
            "            \"leftField\": \"WRS_PATH\",\n",
            "            \"rightValue\": 198\n",
            "          },\n",
            "          \"functionName\": \"Filter.equals\"\n",
            "        }\n",
            "      },\n",
            "      \"functionName\": \"Collection.filter\"\n",
            "    },\n",
            "    \"filter\": {\n",
            "      \"type\": \"Invocation\",\n",
            "      \"arguments\": {\n",
            "        \"leftField\": \"WRS_ROW\",\n",
            "        \"rightValue\": 24\n",
            "      },\n",
            "      \"functionName\": \"Filter.equals\"\n",
            "    }\n",
            "  },\n",
            "  \"functionName\": \"Collection.filter\"\n",
            "})\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KRs3sViXmrJL",
        "colab_type": "code",
        "outputId": "46b01fbb-4c31-49bb-8f26-512200d50efa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "source": [
        "# Import libraries.\n",
        "import ee\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Initialize the Earth Engine module.\n",
        "ee.Initialize()\n",
        "\n",
        "# Fetch a Landsat image.\n",
        "img = ee.Image('LANDSAT/LT05/C01/T1_SR/LT05_034033_20000913')\n",
        "\n",
        "# Select Red and NIR bands, scale them, and sample 500 points.\n",
        "sampFC = img.select(['B3','B4']).divide(10000).sample(scale=30, numPixels=500)\n",
        "\n",
        "# Arrange the sample as a list of lists.\n",
        "sampDict = sampFC.reduceColumns(ee.Reducer.toList().repeat(2), ['B3', 'B4'])\n",
        "sampList = ee.List(sampDict.get('list'))\n",
        "\n",
        "# Save server-side ee.List as a client-side Python list.\n",
        "sampData = sampList.getInfo()\n",
        "\n",
        "# Display a scatter plot of Red-NIR sample pairs using matplotlib.\n",
        "plt.scatter(sampData[0], sampData[1], alpha=0.2)\n",
        "plt.xlabel('Red', fontsize=12)\n",
        "plt.ylabel('NIR', fontsize=12)\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYsAAAEJCAYAAABlmAtYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\neRUO37wAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pBh9kMYggz-G",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}