{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "<a href=\"https://githubtocolab.com/gee-community/geemap/blob/master/examples/notebooks/108_image_zonal_stats.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\"/></a>\n",
                "\n",
                "Uncomment the following line to install [geemap](https://geemap.org) if needed."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "# !pip install geemap"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Import libraries."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "import ee\n",
                "import geemap\n",
                "import geemap.colormaps as cm"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Create an interactive map."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "Map = geemap.Map(center=[40, -100], zoom=4)\n",
                "Map"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Add a DEM to the map."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "dem = ee.Image('USGS/3DEP/10m')\n",
                "vis = {'min': 0, 'max': 4000, 'palette': cm.palettes.dem}"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "Map.addLayer(dem, vis, 'DEM')"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Add NLCD land cover data and legend to the map."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "landcover = ee.Image(\"USGS/NLCD_RELEASES/2019_REL/NLCD/2019\").select('landcover')"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "Map.addLayer(landcover, {}, 'NLCD 2019')\n",
                "Map.add_legend(builtin_legend='NLCD')"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Calculate image zonal statistics by zone. In this case, we are going to calculate the mean elevation by each land cover type. The result can be returned as a Panda DataFrame or saved as a CSV."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "stats = geemap.image_stats_by_zone(dem, landcover, reducer='MEAN')\n",
                "stats"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Save the resulting Pandas DataFrame as a CSV."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "stats.to_csv('mean.csv', index=False)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Calculate the standard deviation of elevation by each land cover type and save the result as a CSV."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "geemap.image_stats_by_zone(dem, landcover, out_csv=\"std.csv\", reducer='STD')"
            ]
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "Python 3",
            "language": "python",
            "name": "python3"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 5
}