{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "<a href=\"https://githubtocolab.com/gee-community/geemap/blob/master/examples/notebooks/35_geemap_colab.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 geemap library\n",
                "\n",
                "The [geemap](https://github.com/gee-community/geemap) Python package has two plotting backends: [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet) and [folium](https://github.com/python-visualization/folium). A key difference between folium and ipyleaflet is that ipyleaflet is built upon ipywidgets and allows bidirectional communication between the front-end and the backend enabling the use of the map to capture user input, while folium is meant for displaying static data only ([source](https://blog.jupyter.org/interactive-gis-in-jupyter-with-ipyleaflet-52f9657fa7a)). Note that Google Colab currently does not support ipyleaflet ([source](https://github.com/googlecolab/colabtools/issues/60#issuecomment-596225619)). Therefore, if you are using geemap with Google Colab, geemap will automatically use the folium plotting backend."
            ]
        },
        {
            "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()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Add Earth Engine data"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "# Add Earth Engine dataset\n",
                "image = ee.Image('USGS/SRTMGL1_003')\n",
                "\n",
                "# Set visualization parameters.\n",
                "vis_params = {\n",
                "    'min': 0,\n",
                "    'max': 4000,\n",
                "    'palette': ['006633', 'E5FFCC', '662A00', 'D8D8D8', 'F5F5F5'],\n",
                "}\n",
                "\n",
                "# Print the elevation of Mount Everest.\n",
                "xy = ee.Geometry.Point([86.9250, 27.9881])\n",
                "elev = image.sample(xy, 30).first().get('elevation').getInfo()\n",
                "print('Mount Everest elevation (m):', elev)\n",
                "\n",
                "# Add Earth Engine layers to Map\n",
                "Map.addLayer(image, vis_params, 'DEM')\n",
                "Map.addLayer(xy, {'color': 'red'}, 'Mount Everest')\n",
                "\n",
                "# Center the map based on an Earth Engine object or coordinates (longitude, latitude)\n",
                "# Map.centerObject(xy, 4)\n",
                "Map.setCenter(86.9250, 27.9881, 4)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Display the map"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "Map"
            ]
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "Python 3",
            "language": "python",
            "name": "python3"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 5
}