examples/notebooks/tn_surface_water.ipynb

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            "source": [
                "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/gee-community/geemap/blob/master/examples/notebooks/tn_surface_water.ipynb)"
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            "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": {
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            "source": [
                "<h1>Contents<span class=\"tocSkip\"></span></h1>\n",
                "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Install-geemap\" data-toc-modified-id=\"Install-geemap-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Install geemap</a></span></li><li><span><a href=\"#Create-an-interactive-map\" data-toc-modified-id=\"Create-an-interactive-map-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Create an interactive map</a></span></li><li><span><a href=\"#Define-region-of-interest-(ROI)\" data-toc-modified-id=\"Define-region-of-interest-(ROI)-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Define region of interest (ROI)</a></span></li><li><span><a href=\"#Create-Landsat-timeseries\" data-toc-modified-id=\"Create-Landsat-timeseries-4\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Create Landsat timeseries</a></span></li><li><span><a href=\"#Calculate-Normalized-Difference-Water-Index-(NDWI)\" data-toc-modified-id=\"Calculate-Normalized-Difference-Water-Index-(NDWI)-5\"><span class=\"toc-item-num\">5&nbsp;&nbsp;</span>Calculate Normalized Difference Water Index (NDWI)</a></span></li><li><span><a href=\"#Extract-surface-water-extent\" data-toc-modified-id=\"Extract-surface-water-extent-6\"><span class=\"toc-item-num\">6&nbsp;&nbsp;</span>Extract surface water extent</a></span></li><li><span><a href=\"#Calculate-surface-water-areas\" data-toc-modified-id=\"Calculate-surface-water-areas-7\"><span class=\"toc-item-num\">7&nbsp;&nbsp;</span>Calculate surface water areas</a></span></li><li><span><a href=\"#Plot-temporal-trend\" data-toc-modified-id=\"Plot-temporal-trend-8\"><span class=\"toc-item-num\">8&nbsp;&nbsp;</span>Plot temporal trend</a></span></li></ul></div>"
            ]
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        {
            "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"
            ]
        }
    ],
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