examples/notebooks/24_publish_maps.ipynb

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    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "<a href=\"https://githubtocolab.com/gee-community/geemap/blob/master/examples/notebooks/24_publish_maps.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": [
                "To follow this tutorial, you will need to [sign up](https://datapane.com/accounts/signup/) for an account with <https://datapane.com>, then install and authenticate the `datapane` Python package. More information can be found [here](https://docs.datapane.com/tutorials/tut-getting-started). \n",
                "\n",
                "- `pip install datapane`\n",
                "- `datapane login`\n",
                "- `datapane ping`"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "import ee\n",
                "import geemap.foliumap as geemap"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "# Create a map centered at (lat, lon).\n",
                "Map = geemap.Map(center=[40, -100], zoom=4)\n",
                "\n",
                "# Use an elevation dataset and terrain functions to create\n",
                "# a custom visualization of topography.\n",
                "\n",
                "# Load a global elevation image.\n",
                "elev = ee.Image('USGS/GMTED2010')\n",
                "\n",
                "# Zoom to an area of interest.\n",
                "Map.setCenter(-121.069, 50.709, 6)\n",
                "\n",
                "# Add the elevation to the map.\n",
                "Map.addLayer(elev, {}, 'elev')\n",
                "\n",
                "# Use the terrain algorithms to compute a hillshade with 8-bit values.\n",
                "shade = ee.Terrain.hillshade(elev)\n",
                "Map.addLayer(shade, {}, 'hillshade', False)\n",
                "\n",
                "# Create a \"sea\" variable to be used for cartographic purposes\n",
                "sea = elev.lte(0)\n",
                "Map.addLayer(sea.mask(sea), {'palette': '000022'}, 'sea', False)\n",
                "\n",
                "# Create a custom elevation palette from hex strings.\n",
                "elevationPalette = ['006600', '002200', 'fff700', 'ab7634', 'c4d0ff', 'ffffff']\n",
                "# Use these visualization parameters, customized by location.\n",
                "visParams = {'min': 1, 'max': 3000, 'palette': elevationPalette}\n",
                "\n",
                "# Create a mosaic of the sea and the elevation data\n",
                "visualized = ee.ImageCollection(\n",
                "    [\n",
                "        # Mask the elevation to get only land\n",
                "        elev.mask(sea.Not()).visualize(**visParams),\n",
                "        # Use the sea mask directly to display sea.\n",
                "        sea.mask(sea).visualize(**{'palette': '000022'}),\n",
                "    ]\n",
                ").mosaic()\n",
                "\n",
                "# Note that the visualization image doesn't require visualization parameters.\n",
                "Map.addLayer(visualized, {}, 'elev palette', False)\n",
                "\n",
                "# Convert the visualized elevation to HSV, first converting to [0, 1] data.\n",
                "hsv = visualized.divide(255).rgbToHsv()\n",
                "# Select only the hue and saturation bands.\n",
                "hs = hsv.select(0, 1)\n",
                "# Convert the hillshade to [0, 1] data, as expected by the HSV algorithm.\n",
                "v = shade.divide(255)\n",
                "# Create a visualization image by converting back to RGB from HSV.\n",
                "# Note the cast to byte in order to export the image correctly.\n",
                "rgb = hs.addBands(v).hsvToRgb().multiply(255).byte()\n",
                "Map.addLayer(rgb, {}, 'styled')\n",
                "\n",
                "states = ee.FeatureCollection('TIGER/2018/States')\n",
                "Map.addLayer(ee.Image().paint(states, 0, 2), {}, \"US States\")"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "# Display the map.\n",
                "Map"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "Map.publish(\n",
                "    name='Terrain Visualization',\n",
                "    description='A folium map with Earth Engine data layers',\n",
                ")"
            ]
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "Python 3",
            "language": "python",
            "name": "python3"
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    "nbformat": 4,
    "nbformat_minor": 5
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