{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0",
   "metadata": {},
   "source": [
    "<a href=\"https://githubtocolab.com/gee-community/geemap/blob/master/examples/notebooks/11_export_image.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,
   "id": "1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install geemap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee\n",
    "import geemap\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3",
   "metadata": {},
   "outputs": [],
   "source": [
    "geemap.show_youtube(\"_6JOA-iiEGU\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4",
   "metadata": {},
   "outputs": [],
   "source": [
    "Map = geemap.Map()\n",
    "Map"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5",
   "metadata": {},
   "source": [
    "## Download an ee.Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6",
   "metadata": {},
   "outputs": [],
   "source": [
    "image = ee.Image(\"LANDSAT/LE7_TOA_5YEAR/1999_2003\")\n",
    "\n",
    "landsat_vis = {\"bands\": [\"B4\", \"B3\", \"B2\"], \"gamma\": 1.4}\n",
    "Map.addLayer(image, landsat_vis, \"LE7_TOA_5YEAR/1999_2003\", True, 0.7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Draw any shapes on the map using the Drawing tools before executing this code block\n",
    "feature = Map.draw_last_feature\n",
    "\n",
    "if feature is None:\n",
    "    geom = ee.Geometry.Polygon(\n",
    "        [\n",
    "            [\n",
    "                [-115.413031, 35.889467],\n",
    "                [-115.413031, 36.543157],\n",
    "                [-114.034328, 36.543157],\n",
    "                [-114.034328, 35.889467],\n",
    "                [-115.413031, 35.889467],\n",
    "            ]\n",
    "        ]\n",
    "    )\n",
    "    feature = ee.Feature(geom, {})\n",
    "\n",
    "roi = feature.geometry()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8",
   "metadata": {},
   "outputs": [],
   "source": [
    "out_dir = os.path.join(os.path.expanduser(\"~\"), \"Downloads\")\n",
    "filename = os.path.join(out_dir, \"landsat.tif\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9",
   "metadata": {},
   "source": [
    "### Exporting all bands as one single image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10",
   "metadata": {},
   "outputs": [],
   "source": [
    "image = image.clip(roi).unmask()\n",
    "geemap.ee_export_image(\n",
    "    image, filename=filename, scale=90, region=roi, file_per_band=False\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11",
   "metadata": {},
   "source": [
    "### Exporting each band as one image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "12",
   "metadata": {},
   "outputs": [],
   "source": [
    "geemap.ee_export_image(\n",
    "    image, filename=filename, scale=90, region=roi, file_per_band=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13",
   "metadata": {},
   "source": [
    "### Export an image to Google Drive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "14",
   "metadata": {},
   "outputs": [],
   "source": [
    "geemap.ee_export_image_to_drive(\n",
    "    image, description=\"landsat\", folder=\"export\", region=roi, scale=30\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15",
   "metadata": {},
   "source": [
    "## Download an ee.ImageCollection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "16",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee\n",
    "import geemap\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "17",
   "metadata": {},
   "outputs": [],
   "source": [
    "loc = ee.Geometry.Point(-99.2222, 46.7816)\n",
    "collection = (\n",
    "    ee.ImageCollection(\"USDA/NAIP/DOQQ\")\n",
    "    .filterBounds(loc)\n",
    "    .filterDate(\"2008-01-01\", \"2020-01-01\")\n",
    "    .filter(ee.Filter.listContains(\"system:band_names\", \"N\"))\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18",
   "metadata": {},
   "outputs": [],
   "source": [
    "out_dir = os.path.join(os.path.expanduser(\"~\"), \"Downloads\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "19",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(collection.aggregate_array(\"system:index\").getInfo())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20",
   "metadata": {},
   "outputs": [],
   "source": [
    "geemap.ee_export_image_collection(collection, out_dir=out_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21",
   "metadata": {},
   "outputs": [],
   "source": [
    "geemap.ee_export_image_collection_to_drive(collection, folder=\"export\", scale=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22",
   "metadata": {},
   "source": [
    "## Extract pixels as a Numpy array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "23",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee\n",
    "import geemap\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "img = ee.Image(\"LANDSAT/LC08/C01/T1_SR/LC08_038029_20180810\").select([\"B4\", \"B5\", \"B6\"])\n",
    "\n",
    "aoi = ee.Geometry.Polygon(\n",
    "    [[[-110.8, 44.7], [-110.8, 44.6], [-110.6, 44.6], [-110.6, 44.7]]], None, False\n",
    ")\n",
    "\n",
    "rgb_img = geemap.ee_to_numpy(img, region=aoi)\n",
    "print(rgb_img.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "24",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Scale the data to [0, 255] to show as an RGB image.\n",
    "# Adapted from https://bit.ly/2XlmQY8. Credits to Justin Braaten\n",
    "rgb_img_test = (255 * ((rgb_img[:, :, 0:3] - 100) / 3500)).astype(\"uint8\")\n",
    "plt.imshow(rgb_img_test)\n",
    "plt.show()"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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