examples/notebooks/99_landsat_9.ipynb

{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "<a href=\"https://githubtocolab.com/gee-community/geemap/blob/master/examples/notebooks/99_landsat_9.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.\n",
                "\n",
                "[Landsat 9](https://landsat.gsfc.nasa.gov/satellites/landsat-9) was successfully launched on Sept. 27, 2021. USGS has been providing Landsat data to the public since Feb. 10, 2022. Landsat 9 data can be downloaded from [EarthExplorer](https://earthexplorer.usgs.gov). The Earth Engine team has been ingesting Landsat 9 into the Public Data Catalog. As of Feb. 14, 2022, although Landsat 9 data have not been publicly listed on the [Earth Engine Datasets](https://developers.google.com/earth-engine/datasets) page, you can access the data through `ee.ImageCollection('LANDSAT/LC09/C02/T1_L2')` ."
            ]
        },
        {
            "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"
            ]
        },
        {
            "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": [
                "Find out how many Landsat imgaes are available."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "collection = ee.ImageCollection('LANDSAT/LC09/C02/T1_L2')\n",
                "print(collection.size().getInfo())"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Create a median composite."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "median = collection.median()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Apply scaling factors. See https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_L2#bands"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "def apply_scale_factors(image):\n",
                "    opticalBands = image.select('SR_B.').multiply(0.0000275).add(-0.2)\n",
                "    thermalBands = image.select('ST_B.*').multiply(0.00341802).add(149.0)\n",
                "    return image.addBands(opticalBands, None, True).addBands(thermalBands, None, True)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "tags": []
            },
            "outputs": [],
            "source": [
                "dataset = apply_scale_factors(median)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Specify visualization parameters."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "vis_natural = {\n",
                "    'bands': ['SR_B4', 'SR_B3', 'SR_B2'],\n",
                "    'min': 0.0,\n",
                "    'max': 0.3,\n",
                "}\n",
                "\n",
                "vis_nir = {\n",
                "    'bands': ['SR_B5', 'SR_B4', 'SR_B3'],\n",
                "    'min': 0.0,\n",
                "    'max': 0.3,\n",
                "}"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Add data layers to the map."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "Map.addLayer(dataset, vis_natural, 'True color (432)')\n",
                "Map.addLayer(dataset, vis_nir, 'Color infrared (543)')\n",
                "Map"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "![](https://i.imgur.com/USPMXzw.png)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Create linked maps for visualizing images with different band combinations. For more information on common band combinations of Landsat 8/9, see https://gisgeography.com/landsat-8-bands-combinations/"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Specify visualization parameters."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "vis_params = [\n",
                "    {'bands': ['SR_B4', 'SR_B3', 'SR_B2'], 'min': 0, 'max': 0.3},\n",
                "    {'bands': ['SR_B5', 'SR_B4', 'SR_B3'], 'min': 0, 'max': 0.3},\n",
                "    {'bands': ['SR_B7', 'SR_B6', 'SR_B4'], 'min': 0, 'max': 0.3},\n",
                "    {'bands': ['SR_B6', 'SR_B5', 'SR_B2'], 'min': 0, 'max': 0.3},\n",
                "]"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Specify labels for each layers."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "labels = [\n",
                "    'Natural Color (4, 3, 2)',\n",
                "    'Color Infrared (5, 4, 3)',\n",
                "    'Short-Wave Infrared (7, 6 4)',\n",
                "    'Agriculture (6, 5, 2)',\n",
                "]"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Create linked maps."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "geemap.linked_maps(\n",
                "    rows=2,\n",
                "    cols=2,\n",
                "    height=\"400px\",\n",
                "    center=[40, -100],\n",
                "    zoom=4,\n",
                "    ee_objects=[dataset],\n",
                "    vis_params=vis_params,\n",
                "    labels=labels,\n",
                "    label_position=\"topright\",\n",
                ")"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "![](https://i.imgur.com/c4FsGBI.png)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Create a split-panel map for comparing Landsat 8 and 9 images.\n",
                "\n",
                "Retrieve two sample images."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "landsat8 = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_015043_20130402')\n",
                "landsat9 = ee.Image('LANDSAT/LC09/C02/T1_L2/LC09_015043_20211231')"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Apply scaling factors."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "landsat8 = apply_scale_factors(landsat8)\n",
                "landsat9 = apply_scale_factors(landsat9)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Generate Earth Engine layers."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "left_layer = geemap.ee_tile_layer(landsat8, vis_natural, 'Landsat 8')\n",
                "right_layer = geemap.ee_tile_layer(landsat9, vis_natural, 'Landsat 9')"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Create a split-panel map."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "Map = geemap.Map()\n",
                "Map.split_map(left_layer, right_layer)\n",
                "Map"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "![](https://i.imgur.com/i6lUYHF.png)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": []
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "Python 3",
            "language": "python",
            "name": "python3"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 5
}