1.1_sampling_training_files.ipynb

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      "provenance": [],
      "authorship_tag": "ABX9TyNXtY7NVP/iqiqkz7agpKu1",
      "include_colab_link": true
    },
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      "name": "python3",
      "display_name": "Python 3"
    },
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      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/Drfengze/ANN-CBIR/blob/main/1.1_sampling_training_files.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# -*- coding: utf-8 -*-\n",
        "\"\"\"1.2_training_dataset_corn_sentinelonly_june1_julyend.ipynb\n",
        "\n",
        "Automatically generated by Colaboratory.\n",
        "\n",
        "Original file is located at\n",
        "    https://colab.research.google.com/github/Hydrometeorological-Remote-Sensing/cropmapping/blob/sw_ww_test/1.2_training_dataset_corn_sentinelonly_june1_julyend.ipynb\n",
        "\n",
        "## Data preparation\n",
        "\"\"\"\n",
        "import ee\n",
        "import numpy as np\n",
        "import random\n",
        "import pandas as pd\n",
        "from datetime import datetime, timedelta, date\n",
        "from google.colab import drive\n",
        "\n",
        "ee.Authenticate()\n",
        "ee.Initialize()\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "qeKZwkd2fKRd",
        "outputId": "011d17b9-1e54-4e00-ba22-4729dd1be152",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "To authorize access needed by Earth Engine, open the following URL in a web browser and follow the instructions. If the web browser does not start automatically, please manually browse the URL below.\n",
            "\n",
            "    https://code.earthengine.google.com/client-auth?scopes=https%3A//www.googleapis.com/auth/earthengine%20https%3A//www.googleapis.com/auth/devstorage.full_control&request_id=72M0sNHPKot1WXkao5DIAO5UAv4ltZly8kWGedrVMEU&tc=Q8zkTN19WhWYGVpzHCV2-IgxiYRGRjwD1NPFwFi3lu4&cc=pU1Yj_IXKN1H7p62rnaH0NVhrNIfoqA4qSB9-zGBHrQ\n",
            "\n",
            "The authorization workflow will generate a code, which you should paste in the box below.\n",
            "Enter verification code: 4/1Adeu5BUMb5Q2YE9dykd02xrxkYW3SM-3oiuu1tNcDqUYx5i1Rc6Ko3kUNT0\n",
            "\n",
            "Successfully saved authorization token.\n",
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "wJXzhQe8fIx0"
      },
      "outputs": [],
      "source": [
        "# Constants\n",
        "BAND_NAMES_L8 = [\"SR_B2\", \"SR_B3\", \"SR_B4\", \"SR_B5\", \"SR_B6\", \"SR_B7\"]\n",
        "BAND_NAMES_OUT = [\"blue\", \"green\", \"red\", \"nir\", \"swir1\", \"swir2\"]\n",
        "BAND_NAMES_S2 = [\"B2\", \"B3\", \"B4\", \"B8\", \"B11\", \"B12\"]\n",
        "BANDS = [\"blue\", \"green\", \"red\", \"nir\", \"swir1\", \"swir2\", \"ndvi\", \"nirv\"]\n",
        "RESPONSE = \"cropland\"\n",
        "FEATURES = BANDS + [RESPONSE]\n",
        "KERNEL_SIZE = 128\n",
        "KERNEL_SHAPE = [KERNEL_SIZE, KERNEL_SIZE]\n",
        "MAX_CLOUD_PROBABILITY = 65\n",
        "FOLDER = \"Corn_Soybean_United_States_of_America_True\"\n",
        "\n",
        "\n",
        "list1 = ee.List.repeat(1, KERNEL_SIZE)\n",
        "lists = ee.List.repeat(list1, KERNEL_SIZE)\n",
        "kernel = ee.Kernel.fixed(KERNEL_SIZE, KERNEL_SIZE, lists)\n",
        "\n",
        "# Functions\n",
        "def mask_l8_sr(image):\n",
        "    cloud_shadow_bit_mask = ee.Number(2).pow(4).int()\n",
        "    clouds_bit_mask = ee.Number(2).pow(3).int()\n",
        "    qa = image.select(\"QA_PIXEL\")\n",
        "    mask1 = (\n",
        "        qa.bitwiseAnd(cloud_shadow_bit_mask).eq(0).And(qa.bitwiseAnd(clouds_bit_mask).eq(0))\n",
        "    )\n",
        "    mask2 = image.mask().reduce(\"min\")\n",
        "    mask = mask1.And(mask2)\n",
        "    return image.updateMask(mask)\n",
        "\n",
        "def mask_edges(s2_img):\n",
        "    return s2_img.updateMask(s2_img.select('B8A').mask().updateMask(s2_img.select('B9').mask()))\n",
        "\n",
        "def mask_clouds(img):\n",
        "    clouds = ee.Image(img.get('cloud_mask')).select('probability')\n",
        "    is_not_cloud = clouds.lt(MAX_CLOUD_PROBABILITY)\n",
        "    return img.updateMask(is_not_cloud)\n",
        "\n",
        "def merge_s2_l8(s2, l8):\n",
        "    merged = ee.ImageCollection([s2, l8]).mean()\n",
        "    return merged\n",
        "\n",
        "def img_vi(img):\n",
        "    img = img.addBands(img.normalizedDifference([\"nir\", \"red\"]).rename(\"ndvi\"))\n",
        "    img = img.addBands(img.select([\"ndvi\"]).multiply(img.select([\"nir\"])).rename(\"nirv\"))\n",
        "    return img\n",
        "\n",
        "class DATA_EXPORTER:\n",
        "  def __init__(self, image, cdl, kernel, binary,scale,FOLDER):\n",
        "      self.image = image\n",
        "      self.cdl = cdl\n",
        "      self.kernel = kernel\n",
        "      self.binary = binary\n",
        "      self.folder = FOLDER\n",
        "      self.scale = scale\n",
        "\n",
        "  def filter_type(self):\n",
        "    return self.cdl.eq(1).selfMask().multiply(1).unmask().add(self.cdl.eq(5).selfMask().multiply(2).unmask())\n",
        "\n",
        "  def export(self):\n",
        "      wheat_lc = self.filter_type()\n",
        "      mask = wheat_lc.neq(0)\n",
        "      if self.binary:\n",
        "          featureStack = ee.Image.cat([self.image, wheat_lc.select(\"cropland\")]).float()\n",
        "          # self.cdl_export(wheat_lc,self.description,self.trainingPoly)\n",
        "      else:\n",
        "          featureStack = ee.Image.cat([self.image, self.cdl.select(\"cropland\")]).float()\n",
        "          # self.cdl_export(self.cdl,self.description,self.trainingPoly)\n",
        "      arrays = featureStack.neighborhoodToArray(self.kernel)\n",
        "      arrays_masked = arrays.updateMask(mask)\n",
        "      return arrays,wheat_lc\n",
        "\n",
        "  def train_export(self,trainingPoly,desc,n=200):\n",
        "      '''\n",
        "      arrays: image collection\n",
        "      trainingPoly: polygon to sample\n",
        "      n: number of samples\n",
        "      folder: folder to save to\n",
        "      desc: description of task\n",
        "      i: seed\n",
        "      '''\n",
        "      arrays,_ = self.export()\n",
        "      trainingPoly = trainingPoly.geometry().simplify(1)\n",
        "      geomSample = ee.FeatureCollection([])\n",
        "      for j in np.arange(n):\n",
        "          sample = arrays.sample(\n",
        "              region=trainingPoly,\n",
        "              numPixels=20,  # Size of the shard.\n",
        "              seed=random.randint(0, 10*n),\n",
        "              scale=self.scale,\n",
        "              tileScale=8,\n",
        "          )\n",
        "          geomSample = geomSample.merge(sample)\n",
        "\n",
        "      task = ee.batch.Export.table.toDrive(\n",
        "          folder=self.folder,\n",
        "          collection=geomSample,\n",
        "          description='train_'+desc,\n",
        "          fileFormat=\"TFRecord\",\n",
        "      )\n",
        "      task.start()\n",
        "\n",
        "def process_date_range(start_date, end_date, s2Sr, l8sr,l8=False):\n",
        "    s2_criteria = ee.Filter.date(start_date.strftime(\"%Y-%m-%d\"), end_date.strftime(\"%Y-%m-%d\"))\n",
        "    l8_criteria = ee.Filter.date(start_date.strftime(\"%Y-%m-%d\"), end_date.strftime(\"%Y-%m-%d\"))\n",
        "\n",
        "    s2_reduced = s2Sr.filter(s2_criteria).median().divide(10000).float()\n",
        "    l8_reduced = l8sr.filter(l8_criteria).median().multiply(0.0000275).add(-0.2).float()\n",
        "    if l8:\n",
        "      image = merge_s2_l8(s2_reduced, l8_reduced)\n",
        "    else:\n",
        "      image = s2_reduced\n",
        "    return img_vi(image).float()  # 需要定义img_vi函数\n",
        "\n",
        "# def get_date_range(YEAR, month, half):\n",
        "#     start_date = date(YEAR, month, 1 + 15 * half)\n",
        "#     if half == 0:\n",
        "#         end_date = date(YEAR, month, 15)\n",
        "#     else:\n",
        "#         end_date = date(YEAR, month, 30) if month == 6 else date(YEAR, 8, 1)\n",
        "#     return start_date, end_date\n",
        "\n",
        "# def handle_year(YEAR, s2Sr, l8sr):\n",
        "#     image_combined = None\n",
        "\n",
        "#     for month in [6, 7]:\n",
        "#         for half in range(2):\n",
        "#             start_date, end_date = get_date_range(YEAR, month, half)\n",
        "#             image = process_date_range(start_date, end_date, s2Sr, l8sr)\n",
        "#             if image_combined is None:\n",
        "#                 image_combined = image\n",
        "#             else:\n",
        "#                 image_combined = image_combined.addBands(image)\n",
        "\n",
        "#     return image_combined\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "l8sr = ee.ImageCollection(\"LANDSAT/LC08/C02/T1_L2\").map(mask_l8_sr)\n",
        "l8sr = l8sr.select(BAND_NAMES_L8, BAND_NAMES_OUT)\n",
        "\n",
        "s2_sr = ee.ImageCollection(\"COPERNICUS/S2_SR_HARMONIZED\").map(mask_edges)\n",
        "s2_clouds = ee.ImageCollection('COPERNICUS/S2_CLOUD_PROBABILITY')\n",
        "s2_sr_with_cloud_mask = ee.Join.saveFirst('cloud_mask').apply(\n",
        "    primary=s2_sr,\n",
        "    secondary=s2_clouds,\n",
        "    condition=ee.Filter.equals(leftField='system:index', rightField='system:index')\n",
        ")\n",
        "s2_cloud_masked = ee.ImageCollection(s2_sr_with_cloud_mask).map(mask_clouds)\n",
        "s2_sr = s2_cloud_masked.select(BAND_NAMES_S2, BAND_NAMES_OUT)\n",
        "\n",
        "# df = pd.read_csv('/content/drive/MyDrive/RDA/model_and_env/calendar.csv')\n",
        "country = 'United States of America'\n",
        "crop = 'Corn Soybean'\n",
        "# calendar = df.loc[(df['Country'] == country) & (df['Crop'] == crop)].to_dict(orient='records')[0]\n",
        "us = ee.FeatureCollection(\"FAO/GAUL_SIMPLIFIED_500m/2015/level1\").filter(\n",
        "    'ADM0_NAME == \"{}\"'.format(country)\n",
        ")\n",
        "states = ['Iowa', 'Illinois', 'Indiana', 'Michigan', 'Ohio', 'Nebraska', 'Kansas', 'Minnesota', 'Missouri'，'South Dakota','North Dakota','Kentucky​']\n",
        "trainingPolys = us.filter(ee.Filter.inList(\"ADM1_NAME\", states))"
      ],
      "metadata": {
        "id": "GpzB1HPwN8F9"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "\n",
        "\"\"\"# Data Preparation\"\"\"\n",
        "binary = True\n",
        "FOLDER = \"{}_{}_{}\".format(crop,country,str(binary)).replace(' ','_')\n",
        "\n",
        "for YEAR in range(2019, 2023):\n",
        "    image = process_date_range(date(YEAR, 6, 1), date(YEAR, 8, 1), s2_sr, l8sr,l8=True)\n",
        "    start_year = date(YEAR, 1, 1).strftime(\"%Y-%m-%d\")\n",
        "    end_year = '2022-12-31'\n",
        "    cdl = ee.ImageCollection('USDA/NASS/CDL').filterDate(start_year, end_year).first().select('cropland')\n",
        "    n = 200  # Number of shards in each polygon.\n",
        "    N = 1000  # Total sample size in each polygon.\n",
        "    # crop_code = int(calendar['Crop Code'])\n",
        "    i = random.randint(0, 100)\n",
        "    data_export = DATA_EXPORTER(image, cdl, kernel, binary,30,FOLDER)\n",
        "    for g in states:\n",
        "        trainingPoly = us.filter(ee.Filter.eq(\"ADM1_NAME\", g))\n",
        "        # run_task(arrays,trainingPoly,desc,i)\n",
        "        if binary:\n",
        "            desc = 'binary_{}_{}_{}'.format(crop,g,YEAR).replace(' ','_')\n",
        "            data_export.train_export(trainingPoly,desc)\n",
        "        else:\n",
        "            desc = 'multiclass_{}_{}_{}'.format(crop,g,YEAR).replace(' ','_')\n",
        "            data_export.train_export(trainingPoly,desc)\n",
        "\n",
        "\"\"\"## Export task\"\"\"\n",
        "\n",
        "from pprint import pprint\n",
        "\n",
        "pprint(ee.batch.Task.list())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "baBscZhhfTMV",
        "outputId": "f2fe6fc3-977c-4dd5-bba9-36134794b662"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[<Task R3SG5SDNSLEAEHE63P7LH4FC EXPORT_FEATURES: train_binary_Corn_Soybean_Missouri_2022 (READY)>,\n",
            " <Task YIX73JDE7MQ5QTEKGAEGLXDC EXPORT_FEATURES: train_binary_Corn_Soybean_Minnesota_2022 (READY)>,\n",
            " <Task VX5OTFAKFBT7SAE7QXQPMHD3 EXPORT_FEATURES: train_binary_Corn_Soybean_Kansas_2022 (READY)>,\n",
            " <Task MCOFOSM4JG3QWUV6JTDDUUKA EXPORT_FEATURES: train_binary_Corn_Soybean_Nebraska_2022 (READY)>,\n",
            " <Task BSS4JTDHEIOLVBU5U6NX6O3S EXPORT_FEATURES: train_binary_Corn_Soybean_Ohio_2022 (READY)>,\n",
            " <Task XPPDBSAET3CHDXYHGZJAJSKM EXPORT_FEATURES: train_binary_Corn_Soybean_Michigan_2022 (READY)>,\n",
            " <Task DW3UUQZRGOAJV5POM6JO4IBD EXPORT_FEATURES: train_binary_Corn_Soybean_Indiana_2022 (READY)>,\n",
            " <Task D5WUUZBJB2WBM6CTJAO2GF6K EXPORT_FEATURES: train_binary_Corn_Soybean_Illinois_2022 (READY)>,\n",
            " <Task U7LGE77DHYQ2EWPPNCGL6D2A EXPORT_FEATURES: train_binary_Corn_Soybean_Iowa_2022 (READY)>,\n",
            " <Task QZLFQCKHGMAVQEJRJMXGEIF4 EXPORT_FEATURES: train_binary_Corn_Soybean_Missouri_2021 (READY)>,\n",
            " <Task AM7K2J5BGKWS2FPR6CUL4EDS EXPORT_FEATURES: train_binary_Corn_Soybean_Minnesota_2021 (READY)>,\n",
            " <Task WFANXR4F7QVM2YFW2BMBEO6V EXPORT_FEATURES: train_binary_Corn_Soybean_Kansas_2021 (READY)>,\n",
            " <Task 564RPCKEREWH6Q3OS6KAYLOC EXPORT_FEATURES: train_binary_Corn_Soybean_Nebraska_2021 (READY)>,\n",
            " <Task V5J6BUULUTJB3XYYAEN7CFWX EXPORT_FEATURES: train_binary_Corn_Soybean_Ohio_2021 (READY)>,\n",
            " <Task FHKGS5NWKSE33ETLUHGG6574 EXPORT_FEATURES: train_binary_Corn_Soybean_Michigan_2021 (READY)>,\n",
            " <Task 4SBCOWVTBQHAX3X6KGELO3WB EXPORT_FEATURES: train_binary_Corn_Soybean_Indiana_2021 (READY)>,\n",
            " <Task 4H55GI2POHAEFCQHF53W2EYG EXPORT_FEATURES: train_binary_Corn_Soybean_Illinois_2021 (READY)>,\n",
            " <Task H33CE4IHBTTNI3V6ZHDRHWPH EXPORT_FEATURES: train_binary_Corn_Soybean_Iowa_2021 (READY)>,\n",
            " <Task 2MWB2SZTED44BHHRECZ7ZMZG EXPORT_FEATURES: train_binary_Corn_Soybean_Missouri_2020 (READY)>,\n",
            " <Task 5X3WZXI77U46G234OLT4QO4S EXPORT_FEATURES: train_binary_Corn_Soybean_Minnesota_2020 (READY)>,\n",
            " <Task SAAZ2H3KTJEAPSLUWSY3Y6OF EXPORT_FEATURES: train_binary_Corn_Soybean_Kansas_2020 (READY)>,\n",
            " <Task SRT5QKWFG2NVDMTVYGBDEBLV EXPORT_FEATURES: train_binary_Corn_Soybean_Nebraska_2020 (READY)>,\n",
            " <Task 5MCDQPTIAZDINXFVMQTVYS6W EXPORT_FEATURES: train_binary_Corn_Soybean_Ohio_2020 (READY)>,\n",
            " <Task NWFHU2EP2LFPNRMKKNRX2QRI EXPORT_FEATURES: train_binary_Corn_Soybean_Michigan_2020 (READY)>,\n",
            " <Task LFDO6GCETVJZYH4ZKODWVMQV EXPORT_FEATURES: train_binary_Corn_Soybean_Indiana_2020 (READY)>,\n",
            " <Task PYO72MBZEN2WM56Q3ZNPO2NU EXPORT_FEATURES: train_binary_Corn_Soybean_Illinois_2020 (READY)>,\n",
            " <Task 4PFTC4PRTMLH2PYJPPHK2H7S EXPORT_FEATURES: train_binary_Corn_Soybean_Iowa_2020 (READY)>,\n",
            " <Task 2TN54MFGD4DNNM6W3BDFVWKE EXPORT_FEATURES: train_binary_Corn_Soybean_Missouri_2019 (READY)>,\n",
            " <Task JEOXY2PBGLE5FVN5IWTA4L55 EXPORT_FEATURES: train_binary_Corn_Soybean_Minnesota_2019 (READY)>,\n",
            " <Task XHZBIU275FFW4YOZDITCZY62 EXPORT_FEATURES: train_binary_Corn_Soybean_Kansas_2019 (READY)>,\n",
            " <Task RYHFYOYWRUXIIAH2YDT4EOTN EXPORT_FEATURES: train_binary_Corn_Soybean_Nebraska_2019 (READY)>,\n",
            " <Task B2VZ5NTD3I6NDNKACX7WGYVY EXPORT_FEATURES: train_binary_Corn_Soybean_Ohio_2019 (READY)>,\n",
            " <Task KYHL2Z4KXDL4OZJWJPYKSQL4 EXPORT_FEATURES: train_binary_Corn_Soybean_Michigan_2019 (RUNNING)>,\n",
            " <Task 7XBPPULBWP3FERPKOZ2AOGCY EXPORT_FEATURES: train_binary_Corn_Soybean_Indiana_2019 (RUNNING)>,\n",
            " <Task UJCFH6DKXIQ4UCTNAEUOY7QG EXPORT_FEATURES: train_binary_Corn_Soybean_Illinois_2019 (RUNNING)>,\n",
            " <Task NXZZNDLBLGX7EMNWIFJG4SQN EXPORT_FEATURES: train_binary_Corn_Soybean_Iowa_2019 (RUNNING)>,\n",
            " <Task WUGJVDXOWUYZLRXA7BX3GTTJ EXPORT_IMAGE: cdl_Corn_Soybean_Illinois (COMPLETED)>,\n",
            " <Task KEJQ2HDH5PTCFQTC3JSRH2OA EXPORT_IMAGE: cdl_Corn_Soybean_Iowa (COMPLETED)>,\n",
            " <Task SZB4EVMIRC27QTGYNY3Y64JY EXPORT_FEATURES: train_binary_Corn_Soybean_Missouri_2022 (COMPLETED)>,\n",
            " <Task ZK36FSFEO4GIEUYN3YMQ65LR EXPORT_FEATURES: train_binary_Corn_Soybean_Minnesota_2022 (COMPLETED)>,\n",
            " <Task LQ67BVQ5NCVU2JIGQ52PAZT3 EXPORT_FEATURES: train_binary_Corn_Soybean_Kansas_2022 (COMPLETED)>,\n",
            " <Task PEB65MLTAXGPLCBF4TVHFZKR EXPORT_FEATURES: train_binary_Corn_Soybean_Nebraska_2022 (COMPLETED)>,\n",
            " <Task 7HDVVESJPN2EFLANEPETLTGJ EXPORT_FEATURES: train_binary_Corn_Soybean_Ohio_2022 (COMPLETED)>,\n",
            " <Task SRMGLJQK7RPUBKZNCA33FOY4 EXPORT_FEATURES: train_binary_Corn_Soybean_Michigan_2022 (COMPLETED)>,\n",
            " <Task URVAYR4BOF2O3M677DNFPIYJ EXPORT_FEATURES: train_binary_Corn_Soybean_Indiana_2022 (COMPLETED)>,\n",
            " <Task PLIVL5M3NBCPHVWN2CM7AA2Q EXPORT_FEATURES: train_binary_Corn_Soybean_Illinois_2022 (COMPLETED)>,\n",
            " <Task 5Q2MXRZVRSXW25HOOQKVY5CM EXPORT_FEATURES: train_binary_Corn_Soybean_Iowa_2022 (COMPLETED)>,\n",
            " <Task CZXZB7FQCPTOVCO26DSGR25P EXPORT_FEATURES: train_binary_Corn_Soybean_Missouri_2021 (COMPLETED)>,\n",
            " <Task 5KDDJYMG52YO5DX3MIAJU7R2 EXPORT_FEATURES: train_binary_Corn_Soybean_Minnesota_2021 (COMPLETED)>,\n",
            " <Task Z2XX6SMEBUBMBEA3MYHUCWU5 EXPORT_FEATURES: train_binary_Corn_Soybean_Kansas_2021 (COMPLETED)>,\n",
            " <Task 3JDCNBCCY22DVOVSVDHW4JPX EXPORT_FEATURES: train_binary_Corn_Soybean_Nebraska_2021 (COMPLETED)>,\n",
            " <Task WI4WBCZOIUYMXZSXTJ77MOOQ EXPORT_FEATURES: train_binary_Corn_Soybean_Ohio_2021 (COMPLETED)>,\n",
            " <Task LNIERHHACMZI3TPN67BZYQ3H EXPORT_FEATURES: train_binary_Corn_Soybean_Michigan_2021 (COMPLETED)>,\n",
            " <Task REONLGGMXK4DY3OKKRJGI7RL EXPORT_FEATURES: train_binary_Corn_Soybean_Indiana_2021 (COMPLETED)>,\n",
            " <Task 3SN5RVRY2P7UVRMXXH7KS5S3 EXPORT_FEATURES: train_binary_Corn_Soybean_Illinois_2021 (COMPLETED)>,\n",
            " <Task CBKPHEVM2GHWWIWZWM4J5GTB EXPORT_FEATURES: train_binary_Corn_Soybean_Iowa_2021 (COMPLETED)>,\n",
            " <Task LZG75PRA2OCOTSXOAKR6QFKW EXPORT_FEATURES: train_binary_Corn_Soybean_Missouri_2020 (COMPLETED)>,\n",
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            " <Task X247M6UGMBBRRU63FSOLXHX6 EXPORT_FEATURES: training_patches_Iowa_2021_128 (CANCELLED)>,\n",
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            " <Task 4YJSGJ3F7MZTQBI542EMYMFU EXPORT_FEATURES: training_patches_Kansas_2020_128 (CANCELLED)>,\n",
            " <Task 57CSO3QRV2CG2LXONKN7EJUM EXPORT_FEATURES: training_patches_Nebraska_2020_128 (CANCELLED)>,\n",
            " <Task QQOASP2RQ6RLPD7ENEAZSM2N EXPORT_FEATURES: training_patches_Ohio_2020_128 (CANCELLED)>,\n",
            " <Task 32DKV77EFU2WOBPEMA55S6UA EXPORT_FEATURES: training_patches_Michigan_2020_128 (CANCELLED)>,\n",
            " <Task MMOU6NKNXJBGO5SQJFSUSPV6 EXPORT_FEATURES: training_patches_Indiana_2020_128 (CANCELLED)>,\n",
            " <Task MGPWFURXPBRTW62OI73JKU4P EXPORT_FEATURES: training_patches_Illinois_2020_128 (CANCELLED)>,\n",
            " <Task WHVJAWE6NFLCLB7BAXZARHUU EXPORT_FEATURES: training_patches_Iowa_2020_128 (CANCELLED)>,\n",
            " <Task O7PQU5MDK37JA5XHJ2LX4DSH EXPORT_FEATURES: training_patches_Missouri_2019_128 (CANCELLED)>,\n",
            " <Task GODMRK44ATA52TO7CMIQOBQ3 EXPORT_FEATURES: training_patches_Minnesota_2019_128 (CANCELLED)>,\n",
            " <Task HDCY4KWAGHO63CWYZZFXOHLR EXPORT_FEATURES: training_patches_Kansas_2019_128 (CANCELLED)>,\n",
            " <Task A7D6T5KQZF4HJBNVDYERSZUE EXPORT_FEATURES: training_patches_Nebraska_2019_128 (CANCELLED)>,\n",
            " <Task LYJVZ5CT3WX4YMY2D7XOMWCK EXPORT_FEATURES: training_patches_Ohio_2019_128 (FAILED)>,\n",
            " <Task IJF3O7RNRRZQJF75K4DYVSDI EXPORT_FEATURES: training_patches_Michigan_2019_128 (CANCELLED)>,\n",
            " <Task NMDUSDIASCGA2L5VGNOS5CMN EXPORT_FEATURES: training_patches_Indiana_2019_128 (FAILED)>,\n",
            " <Task ITKFBCX7O7FHU3SKKEPWFH73 EXPORT_FEATURES: training_patches_Illinois_2019_128 (FAILED)>,\n",
            " <Task RADBUWED3QHZY3NFY4BKTCN5 EXPORT_FEATURES: training_patches_Iowa_2019_128 (FAILED)>,\n",
            " <Task DBUWFW7L52YWE4DPTFV7B6KP EXPORT_FEATURES: training_patches_Missouri_2018_128 (FAILED)>,\n",
            " <Task 7BKDKKSGX7NQCSKQGNWNVBZM EXPORT_FEATURES: training_patches_Minnesota_2018_128 (COMPLETED)>,\n",
            " <Task AYWZDGXE6CUL63KMHZNXJKQH EXPORT_FEATURES: training_patches_Kansas_2018_128 (COMPLETED)>,\n",
            " <Task SSCLLLVOGDAS6JX25KQF4SRS EXPORT_FEATURES: training_patches_Nebraska_2018_128 (COMPLETED)>,\n",
            " <Task SMHTRAMIN4KI2LSKUJ76DDMQ EXPORT_FEATURES: training_patches_Ohio_2018_128 (COMPLETED)>,\n",
            " <Task W465LR4GMYNUYZ2YRKPTYHBF EXPORT_FEATURES: training_patches_Michigan_2018_128 (COMPLETED)>,\n",
            " <Task EEPWHUPCOUV6QMR5VLNOL73H EXPORT_FEATURES: training_patches_Indiana_2018_128 (COMPLETED)>,\n",
            " <Task RNIKHH7ZCNGH5XUULZWOFI7F EXPORT_FEATURES: training_patches_Illinois_2018_128 (COMPLETED)>,\n",
            " <Task K4SEOJOHJJLH4O4N7JTZWSNR EXPORT_FEATURES: training_patches_Iowa_2018_128 (COMPLETED)>,\n",
            " <Task 7PJQPXP2RZ5MAXSXVAI3JEXP EXPORT_FEATURES: training_patches_Missouri_2017_128 (COMPLETED)>,\n",
            " <Task DFNUJ25AFFN5IMGSKMJ4V2RK EXPORT_FEATURES: training_patches_Minnesota_2017_128 (COMPLETED)>,\n",
            " <Task IOUJULXJCXO26MOQG4W33TCT EXPORT_FEATURES: training_patches_Kansas_2017_128 (COMPLETED)>,\n",
            " <Task CUO66SWMTZDO3WDKIIKXGBVM EXPORT_FEATURES: training_patches_Nebraska_2017_128 (COMPLETED)>,\n",
            " <Task FT644I5QNOM76BDM3UJOBNVA EXPORT_FEATURES: training_patches_Ohio_2017_128 (COMPLETED)>,\n",
            " <Task UONAANR7DJVGRGGK4L4GHQAS EXPORT_FEATURES: training_patches_Michigan_2017_128 (COMPLETED)>,\n",
            " <Task 2ROI7F5Q3L26OXEENR26FM55 EXPORT_FEATURES: training_patches_Indiana_2017_128 (COMPLETED)>,\n",
            " <Task DVBFHJ2EOFCA6QDKRAO3BMJ4 EXPORT_FEATURES: training_patches_Illinois_2017_128 (COMPLETED)>,\n",
            " <Task ZPLTK5R7YXBXJQV2SYGMA2HL EXPORT_FEATURES: training_patches_Iowa_2017_128 (COMPLETED)>]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def doExport(image,out_image_base, kernel_buffer, region,folder):\n",
        "  \"\"\"Run the image export task.  Block until complete.\n",
        "  \"\"\"\n",
        "  task = ee.batch.Export.image.toDrive(\n",
        "    image = image,\n",
        "    folder = folder,\n",
        "    description = out_image_base,\n",
        "    fileNamePrefix = out_image_base,\n",
        "    region = region.geometry(),#.getInfo()['coordinates'],\n",
        "    scale = 30,\n",
        "    fileFormat = 'TFRecord',\n",
        "    maxPixels = 1e10,\n",
        "    formatOptions = {\n",
        "      'patchDimensions': KERNEL_SHAPE,\n",
        "      'kernelSize': kernel_buffer,\n",
        "      'compressed': True,\n",
        "      'maxFileSize': 104857600\n",
        "    }\n",
        "  )\n",
        "  print('Running image export to Cloud Storage...')\n",
        "  task.start()"
      ],
      "metadata": {
        "id": "LENqwrCAPDry"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# states = ['Iowa', 'Illinois']\n",
        "kernel_buffer = [64, 64]\n",
        "year = 2023\n",
        "image = process_date_range(date(year, 6, 1), date(year, 8, 1), s2_sr, l8sr,l8=True)\n",
        "for state in states:\n",
        "  folder = 'prediction_{}_{}'.format(year,state).replace(' ','_')\n",
        "  image_base = 'cdl_{}_{}'.format(crop,state).replace(' ','_')\n",
        "  region = us.filter(ee.Filter.eq(\"ADM1_NAME\", state))\n",
        "  doExport(image,image_base, kernel_buffer, region,folder)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zKGxrTfZlA-I",
        "outputId": "ffa46aee-a291-4e6a-aa2f-ff1a9f13c9aa"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Running image export to Cloud Storage...\n",
            "Running image export to Cloud Storage...\n",
            "Running image export to Cloud Storage...\n",
            "Running image export to Cloud Storage...\n",
            "Running image export to Cloud Storage...\n",
            "Running image export to Cloud Storage...\n",
            "Running image export to Cloud Storage...\n",
            "Running image export to Cloud Storage...\n",
            "Running image export to Cloud Storage...\n"
          ]
        }
      ]
    }
  ]
}