examples/notebooks/30_image_props_stats.ipynb

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    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "<a href=\"https://githubtocolab.com/gee-community/geemap/blob/master/examples/notebooks/30_image_props_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": [
                "# How to get image basic properties and descriptive statistics"
            ]
        },
        {
            "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": [
                "## Add images to the map"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "centroid = ee.Geometry.Point([-122.4439, 37.7538])\n",
                "\n",
                "landsat = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR').filterBounds(centroid).first()\n",
                "\n",
                "landsat_vis = {'min': 0, 'max': 3000, 'bands': ['B5', 'B4', 'B3']}\n",
                "\n",
                "Map.centerObject(centroid, 8)\n",
                "Map.addLayer(landsat, landsat_vis, \"Landsat-8\")"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "naip = ee.ImageCollection('USDA/NAIP/DOQQ').filterBounds(centroid).first()\n",
                "\n",
                "naip_vis = {'bands': ['N', 'R', 'G']}\n",
                "\n",
                "Map.addLayer(naip, naip_vis, 'NAIP')"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Get image property names"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "landsat.propertyNames().getInfo()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "landsat.get('CLOUD_COVER').getInfo()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "# The number of milliseconds since 1970-01-01T00:00:00Z.\n",
                "landsat.get('system:time_start').getInfo()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "ee.Date(landsat.get('system:time_start')).format('YYYY-MM-dd').getInfo()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Get image properties all at once"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "landsat_props = geemap.image_props(landsat)\n",
                "landsat_props.getInfo()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "landsat_props.get('IMAGE_DATE').getInfo()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "naip_props = geemap.image_props(naip)\n",
                "naip_props.getInfo()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "naip_props.get('NOMINAL_SCALE').getInfo()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Get image descriptive statistics\n",
                "\n",
                "Including minimum, maximum, mean, standard deviation, and sum."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "landsat_stats = geemap.image_stats(landsat, scale=90)\n",
                "landsat_stats.getInfo()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "naip_stats = geemap.image_stats(naip, scale=10)\n",
                "naip_stats.getInfo()"
            ]
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "Python 3",
            "language": "python",
            "name": "python3"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 5
}