{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[](https://colab.research.google.com/github/gee-community/geemap/blob/master/examples/notebooks/tn_surface_water.ipynb)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Automated mapping of surface water in the state of Tennessee using Google Earth Engine cloud computing\n",
"\n",
"Author: Qiusheng Wu ([Website](https://wetlands.io) - [GitHub](https://github.com/giswqs))"
]
},
{
"cell_type": "markdown",
"metadata": {
"toc": true
},
"source": [
"Contents
\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Install geemap"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Installs geemap package\n",
"import subprocess\n",
"\n",
"try:\n",
" import geemap\n",
"except ImportError:\n",
" print('geemap package not installed. Installing ...')\n",
" subprocess.check_call([\"python\", '-m', 'pip', 'install', 'geemap'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import ee\n",
"import geemap"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create an interactive map"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"Map = geemap.Map()\n",
"Map"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Define region of interest (ROI)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"roi = ee.FeatureCollection('TIGER/2018/States').filter(\n",
" ee.Filter.eq('NAME', 'Tennessee')\n",
")\n",
"Map.addLayer(roi, {}, \"TN\")\n",
"Map.centerObject(roi, 7)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create Landsat timeseries"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"images = geemap.landsat_timeseries(\n",
" roi=roi, start_year=1984, end_year=2020, start_date='01-01', end_date='12-31'\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"first = images.first()\n",
"\n",
"vis_params = {'bands': ['NIR', 'Red', 'Green'], 'min': 0, 'max': 3000}\n",
"\n",
"Map.addLayer(first, vis_params, 'First image')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Calculate Normalized Difference Water Index (NDWI)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ndwi_images = images.map(\n",
" lambda img: img.normalizedDifference(['Green', 'SWIR1']).rename('ndwi')\n",
")\n",
"\n",
"ndwi_palette = [\n",
" '#ece7f2',\n",
" '#d0d1e6',\n",
" '#a6bddb',\n",
" '#74a9cf',\n",
" '#3690c0',\n",
" '#0570b0',\n",
" '#045a8d',\n",
" '#023858',\n",
"]\n",
"\n",
"first_ndwi = ndwi_images.first()\n",
"\n",
"Map.addLayer(first_ndwi, {'palette': ndwi_palette}, 'First NDWI')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Extract surface water extent"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"water_images = ndwi_images.map(lambda img: img.gt(0).selfMask())\n",
"\n",
"first_water = water_images.first()\n",
"\n",
"Map.addLayer(first_water, {'palette': ['blue']}, 'First Water')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Calculate surface water areas"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def cal_area(img):\n",
" pixel_area = img.multiply(ee.Image.pixelArea()).divide(1e6)\n",
" img_area = pixel_area.reduceRegion(\n",
" **{\n",
" 'geometry': roi.geometry(),\n",
" 'reducer': ee.Reducer.sum(),\n",
" 'scale': 1000,\n",
" 'maxPixels': 1e12,\n",
" }\n",
" )\n",
" return img.set({'water_area': img_area})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"water_areas = water_images.map(cal_area)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"water_stats = water_areas.aggregate_array('water_area').getInfo()\n",
"water_stats"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot temporal trend"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"x = list(range(1984, 2021))\n",
"y = [item.get('ndwi') for item in water_stats]\n",
"\n",
"plt.bar(x, y, align='center', alpha=0.5)\n",
"# plt.xticks(y_pos, objects)\n",
"plt.ylabel('Area (km2)')\n",
"plt.title('Surface water dynamics in Tennessee')\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"Map.addLayerControl()\n",
"Map"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}