landsat8_ndvi_viz.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Landsat-8 NDVI visualization\n",
    "\n",
    "### Import required files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Image\n",
    "import ee, folium\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "# from pylab import *\n",
    "from matplotlib.pylab import rcParams\n",
    "\n",
    "ee.Initialize()\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Select area of interest and the collection to be used"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Polygon selected is a site near Yosemite\n",
    "roi = ee.Geometry.Polygon([[-120.3066492132134, 37.68165381501888],\n",
    "          [-120.3066492132134, 37.528794431827464],\n",
    "          [-119.9331140569634, 37.528794431827464],\n",
    "          [-119.9331140569634, 37.68165381501888]])\n",
    "l8 = ee.ImageCollection(\"LANDSAT/LC08/C01/T1_TOA\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize region of interest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f0b4bdec8e0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vis_params = {'bands':['B4','B3','B2'], 'max':0.3, 'min':0}\n",
    "filtered = l8.filterDate('2016-01-01','2017-01-01').filterBounds(roi);\n",
    "\n",
    "mapid = filtered.getMapId(vis_params)\n",
    "\n",
    "map = folium.Map(location=[37.61, -120.12],zoom_start=9, height=500,width=700)\n",
    "folium.TileLayer(\n",
    "    tiles=mapid['tile_fetcher'].url_format,\n",
    "    attr='Map Data &copy; <a href=\"https://earthengine.google.com/\">Google Earth Engine</a>',\n",
    "    overlay=True,\n",
    "    name='Landsat 8 ',\n",
    "  ).add_to(map)\n",
    "\n",
    "map.add_child(folium.LayerControl())\n",
    "map"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The output is a leaflet map, link to a screenshot of it:\n",
    "https://github.com/theadityasam/geepecan/blob/master/Images/yosemite_tcc.png\n",
    "![yosemitetcc](https://github.com/theadityasam/geepecan/blob/master/Images/yosemite_tcc.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Function for returning NDVI\n",
    "\n",
    "def retNDVI(image):\n",
    "  return image.normalizedDifference(['B5', 'B4'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize NDVI plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f0b4bdecb50>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndvi = retNDVI(l8.min())\n",
    "\n",
    "image = ndvi.clip(roi)\n",
    "vis_ndvi = {'min':-1,'max':1,'size':'800',\n",
    "           'region':roi}\n",
    "\n",
    "mapid = image.getMapId(vis_ndvi)\n",
    "\n",
    "map = folium.Map(location=[37.61, -120.12],zoom_start=11, height=500,width=700)\n",
    "folium.TileLayer(\n",
    "    tiles=mapid['tile_fetcher'].url_format,\n",
    "    attr='Map Data &copy; <a href=\"https://earthengine.google.com/\">Google Earth Engine</a>',\n",
    "    overlay=True,\n",
    "    name='NDVI',\n",
    "  ).add_to(map)\n",
    "\n",
    "map.add_child(folium.LayerControl())\n",
    "map"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The output is a leaflet map, link to a screenshot of it:\n",
    "https://github.com/theadityasam/geepecan/blob/master/Images/yosemite_fcc.png)\n",
    "![yosemitefcc](https://github.com/theadityasam/geepecan/blob/master/Images/yosemite_fcc.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### NDVI created with greenest pixel composite "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f0b4bd82610>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating ndvi collection\n",
    "ndvi_collection = l8.map(retNDVI)\n",
    "# Selecting greenest pixels of collection\n",
    "greenest = ndvi_collection.qualityMosaic('nd')\n",
    "\n",
    "#Visualizing\n",
    "greenest_vis = {'bands':'nd','min':0,'max':1}\n",
    "\n",
    "mapid = greenest.getMapId(greenest_vis)\n",
    "map = folium.Map(location=[37.61, -120.12],zoom_start=9, height=500,width=700)\n",
    "folium.TileLayer(\n",
    "    tiles=mapid['tile_fetcher'].url_format,\n",
    "    attr='Map Data &copy; <a href=\"https://earthengine.google.com/\">Google Earth Engine</a>',\n",
    "    overlay=True,\n",
    "    name='Landsat 8 ',\n",
    "  ).add_to(map)\n",
    "\n",
    "map.add_child(folium.LayerControl())\n",
    "What map"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The output is a leaflet map, link to a screenshot of it:https://github.com/theadityasam/geepecan/blob/master/Images/yosemite_green_colour_composite.png)\n",
    "![yosemite_green_colour_composite](https://github.com/theadityasam/geepecan/blob/master/Images/yosemite_green_colour_composite.png)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}