examples/notebooks/100_numpy_to_cog.ipynb

{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "[![image](https://colab.research.google.com/assets/colab-badge.svg)](https://githubtocolab.com/gee-community/geemap/blob/master/examples/notebooks/100_numpy_to_cog.ipynb)\n",
                "\n",
                "Create a fresh conda env to run this example if needed.\n",
                "\n",
                "```\n",
                "conda create -n cog python=3.9\n",
                "conda install mamba -c conda-forge\n",
                "mamba install geemap rio-cogeo -c conda-forge\n",
                "```"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "# !pip install geemap rio-cogeo"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "import geemap"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "url = 'https://github.com/giswqs/leafmap/raw/master/examples/data/cog.tif'\n",
                "in_cog = 'cog.tif'\n",
                "out_cog = \"ndvi.tif\""
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Download a sample dataset."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "geemap.download_from_url(url, in_cog)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Convert image to numpy array."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "arr = geemap.image_to_numpy(in_cog)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "arr.shape"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Computer NDVI."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "ndvi = (arr[3] - arr[0]) / (arr[3] + arr[0])"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "ndvi.shape"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Convert numpy array to COG."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "geemap.numpy_to_cog(ndvi, out_cog, profile=in_cog)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "m = geemap.Map()\n",
                "m.add_raster(in_cog, band=[4, 1, 2], layer_name=\"Color infrared\")\n",
                "m.add_raster(out_cog, palette=\"Greens\", layer_name=\"NDVI\")\n",
                "m"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "![](https://i.imgur.com/OVaTyP3.gif)"
            ]
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "Python 3",
            "language": "python",
            "name": "python3"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 5
}