{
 "cells": [
  {
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   "id": "6b55717a",
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   "source": [
    "# Downloading Images and Collections\n",
    "In this tutorial, we'll look at how we can use `wxee` and the `wx` accesor to quickly and easily download images and image collections from Earth Engine to a local drive. \n",
    "\n",
    "`wxee` isn't designed to replace Earth Engine's native downloading functionality--if you need high resolution images or large areas, downloading to a Drive using ee is probably the best option. What `wxee`'s downloading system is great for is quickly pulling small regions or mesoscale images for further processing in Python without the hassle of intermediate steps."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3081bca9",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "656935bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install wxee"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "739f74b7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-09-12T04:09:14.626266Z",
     "start_time": "2021-09-12T04:09:11.263266Z"
    }
   },
   "outputs": [],
   "source": [
    "import ee\n",
    "import wxee\n",
    "\n",
    "ee.Authenticate()\n",
    "wxee.Initialize()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1d076fd",
   "metadata": {},
   "source": [
    "## Downloading an Image"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ff1a78d",
   "metadata": {},
   "source": [
    "Load an image from MODIS. For convenience, we'll select just the red, green, and blue bands."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a2491f50",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-09-12T04:09:14.630624Z",
     "start_time": "2021-09-12T04:09:14.627974Z"
    }
   },
   "outputs": [],
   "source": [
    "img = ee.Image(\"MODIS/006/MOD09GA/2021_06_01\").select([\"sur_refl_b01\", \"sur_refl_b04\" ,\"sur_refl_b03\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fde849d1",
   "metadata": {},
   "source": [
    "Set the download parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9a4ef628",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-09-12T04:09:16.743925Z",
     "start_time": "2021-09-12T04:09:16.739648Z"
    }
   },
   "outputs": [],
   "source": [
    "# The file name to save\n",
    "description = \"modis_img\"\n",
    "# The coordinate reference system to use (NAD83 Albers CONUS)\n",
    "crs = \"EPSG:5070\"\n",
    "# Spatial resolution in CRS units (meters)\n",
    "scale = 500\n",
    "# The region to download the image within.\n",
    "region = ee.Geometry.Polygon(\n",
    "    [[[-120.0576549852371, 46.185091976777684],\n",
    "      [-120.0576549852371, 45.577074504710005],\n",
    "      [-118.91782344226834, 45.577074504710005],\n",
    "      [-118.91782344226834, 46.185091976777684]]]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09a996a2",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Warning:</b> If an image download fails due to size limits, try using a smaller region or a coarser scale.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39659dfa",
   "metadata": {},
   "source": [
    "Download the image to GeoTIFF. The `ee.Image.wx.to_tif` method returns a path to the downloaded image(s). `wxee` always saves files with the name format `{id}.{dimension}.{coordinate}`. If no `description` is passed, the `system:id` property of the image will determine the file ID."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e65b0d91",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-09-12T04:09:21.037621Z",
     "start_time": "2021-09-12T04:09:18.859951Z"
    }
   },
   "outputs": [
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      "text/plain": [
       "Downloading:   0%|          | 0.00/139k [00:00<?, ?iB/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
      "text/plain": [
       "['data/modis_img.time.20210601T000000.tif']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file = img.wx.to_tif(out_dir='data', description=description, region=region, scale=scale, crs=crs)\n",
    "file"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72dc019d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-26T05:46:50.204388Z",
     "start_time": "2021-07-26T05:46:50.192595Z"
    }
   },
   "source": [
    "Above, we downloaded 1 three-band image, but we could also download it as 3 one-band images by setting `file_per_band` to True."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3da21b76",
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    "ExecuteTime": {
     "end_time": "2021-09-12T04:09:24.954769Z",
     "start_time": "2021-09-12T04:09:23.169210Z"
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   },
   "outputs": [
    {
     "data": {
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       "model_id": "e20a0b7d9e4d4f1789f3654655c449c4",
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      "text/plain": [
       "Downloading:   0%|          | 0.00/159k [00:00<?, ?iB/s]"
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    {
     "data": {
      "text/plain": [
       "['data/modis_img.time.20210601T000000.sur_refl_b01.tif',\n",
       " 'data/modis_img.time.20210601T000000.sur_refl_b04.tif',\n",
       " 'data/modis_img.time.20210601T000000.sur_refl_b03.tif']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
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   ],
   "source": [
    "file = img.wx.to_tif(\n",
    "    out_dir='data', \n",
    "    description=description, \n",
    "    region=region, \n",
    "    scale=scale, \n",
    "    crs=crs, \n",
    "    file_per_band=True\n",
    ")\n",
    "\n",
    "file"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e104110",
   "metadata": {},
   "source": [
    "## Downloading an Image Collection"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dbb4b2a2",
   "metadata": {},
   "source": [
    "Load the MODIS collection, choose a date range with 4 images, and select the red, green, and blue bands."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8da1370b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-09-12T04:09:27.800354Z",
     "start_time": "2021-09-12T04:09:27.796681Z"
    }
   },
   "outputs": [],
   "source": [
    "collection = (ee.ImageCollection(\"MODIS/006/MOD09GA\")\n",
    "    .filterDate(\"2021-06-01\", \"2021-06-05\")\n",
    "    .select([\"sur_refl_b01\", \"sur_refl_b04\" ,\"sur_refl_b03\"])\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66b5b5d6",
   "metadata": {},
   "source": [
    "Download each image in the collection to GeoTIFF. We'll use the same parameters as above except for `description`. `ee.ImageCollection.wx.to_tif` doesn't take a `description` parameter, but it does take a `prefix` that can be added to the beginning of each file name. File names are based on the `system:id` property of each image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "03bd3c81",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-09-12T04:09:32.634975Z",
     "start_time": "2021-09-12T04:09:29.259865Z"
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   "outputs": [
    {
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      "text/plain": [
       "Requesting:   0%|          | 0/4 [00:00<?, ?it/s]"
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       "Downloading:   0%|          | 0/4 [00:00<?, ?it/s]"
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    {
     "data": {
      "text/plain": [
       "['data/wx_MODIS_006_MOD09GA_2021_06_02.time.20210602T000000.tif',\n",
       " 'data/wx_MODIS_006_MOD09GA_2021_06_01.time.20210601T000000.tif',\n",
       " 'data/wx_MODIS_006_MOD09GA_2021_06_04.time.20210604T000000.tif',\n",
       " 'data/wx_MODIS_006_MOD09GA_2021_06_03.time.20210603T000000.tif']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "files = collection.wx.to_tif(\n",
    "    out_dir=\"data\", \n",
    "    prefix=\"wx_\", \n",
    "    region=region, \n",
    "    scale=scale, \n",
    "    crs=crs\n",
    ")\n",
    "\n",
    "files"
   ]
  }
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