SML_v4_GHS_built_pop_smod.ipynb

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  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z1a1YvqQMYwq",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!pip install gdal\n",
        "!pip install rasterio\n",
        "!pip install sentinelsat"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RFoYRRBraO35",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sentinelsat.sentinel import SentinelAPI, read_geojson, geojson_to_wkt\n",
        "import gdal\n",
        "from gdalconst import GA_ReadOnly \n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline \n",
        "import cv2\n",
        "import numpy as np\n",
        "from collections import Counter\n",
        "from tqdm import tqdm_notebook as tqdm\n",
        "IMG_SIZE=1031\n",
        "import rasterio\n",
        "from rasterio.plot import show\n",
        "import subprocess\n",
        "import os\n",
        "import math\n",
        "from sklearn.preprocessing import minmax_scale\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H8AocvjjPhJv",
        "colab_type": "text"
      },
      "source": [
        "# **GHS BUILT-UP**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mc5cUgbQMsgh",
        "colab_type": "text"
      },
      "source": [
        "**DOWNLOAD CLC REFERENCE DATA**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cMkDlUdYMcms",
        "colab_type": "code",
        "outputId": "fde6a02d-2aa7-4978-bdf7-4f15ba3dca92",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        }
      },
      "source": [
        "subprocess.run(['wget', 'https://land.copernicus.eu/land-files/7ac95361f9ac3cecdf37785bc183ff02dd765a16.zip'])\n",
        "subprocess.run(['unzip' ,'7ac95361f9ac3cecdf37785bc183ff02dd765a16.zip'])\n",
        "subprocess.run(['unzip' ,'clc2018_clc2018_v2018_20_raster100m.zip'])\n",
        "subprocess.run(['gdalwarp','-co','COMPRESS=DEFLATE','-t_srs','EPSG:32632','clc2018_clc2018_v2018_20_raster100m/CLC2018_CLC2018_V2018_20.tif','europe.tif'])\n"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "CompletedProcess(args=['gdalwarp', '-co', 'COMPRESS=DEFLATE', '-t_srs', 'EPSG:32632', 'clc2018_clc2018_v2018_20_raster100m/CLC2018_CLC2018_V2018_20.tif', 'europe.tif'], returncode=0)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3TibEqxG3UVr",
        "colab_type": "text"
      },
      "source": [
        "**STEP 1 : DATA PREPROCESSING**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7eprcUOi3EDs",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def download_scene(file_id):\n",
        "  api = SentinelAPI('uname', 'pwd',api_url='https://scihub.copernicus.eu/apihub')\n",
        "  api.download(file_id)\n",
        "\n",
        "def unzip_scene(file_name):\n",
        "  subprocess.call('unzip '+file_name,shell=True)\n",
        "\n",
        "def jp2_to_tif(input_file,output_file):\n",
        "  subprocess.call('gdal_translate ' +input_file+' '+output_file,shell=True)\n",
        "\n",
        "def clip_ref_scene(input_file,output_file):\n",
        "  data=gdal.Open(input_file,GA_ReadOnly) \n",
        "  geoTransform=data.GetGeoTransform() \n",
        "  minx=geoTransform[0] \n",
        "  maxy=geoTransform[3] \n",
        "  maxx = minx + geoTransform[1] * data.RasterXSize \n",
        "  miny = maxy + geoTransform[5] * data.RasterYSize \n",
        "  subprocess.call('gdal_translate -projwin ' + ' '.join([str(x) for x in [minx, maxy, maxx, miny]]) + ' -of GTiff europe.tif ' +output_file, shell=True) \n",
        "\n",
        "def resize_scene(input_file,output_file):\n",
        "  subprocess.call('gdal_translate -co QUALITY=100 -co PROGRESSIVE=ON -outsize '+str(IMG_SIZE)+' '+str(IMG_SIZE)+' -r bilinear '+input_file+' '+output_file,shell=True)\n",
        "\n",
        "\n",
        "\n",
        "def clip_ref_scene_pop(input_file,output_file):\n",
        "  data=gdal.Open(input_file,GA_ReadOnly) \n",
        "  geoTransform=data.GetGeoTransform() \n",
        "  minx=geoTransform[0] \n",
        "  maxy=geoTransform[3] \n",
        "  maxx = minx + geoTransform[1] * data.RasterXSize \n",
        "  miny = maxy + geoTransform[5] * data.RasterYSize \n",
        "  subprocess.call('gdal_translate -projwin ' + ' '.join([str(x) for x in [minx, maxy, maxx, miny]]) + ' -of GTiff world-population.tif ' +output_file, shell=True) "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wNm3vAoqGJ3w",
        "colab_type": "code",
        "outputId": "c386e526-35a0-45ce-bc83-6d0c5e62d651",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 151
        }
      },
      "source": [
        "#download_scene('742eb824-df10-4402-866e-0d92e8575aa4')\n",
        "download_scene('cbb628b9-8399-4a24-aaeb-b5d5bdc49be0')\n",
        "unzip_scene('/content/S2A_MSIL1C_20190926T105811_N0208_R094_T30TVK_20190926T130550.zip')\n",
        "jp2_to_tif('/content/S2A_MSIL1C_20190926T105811_N0208_R094_T30TVK_20190926T130550.SAFE/GRANULE/L1C_T30TVK_A022256_20190926T110642/IMG_DATA/T30TVK_20190926T105811_TCI.jp2','test-full-temp.tif')\n",
        "!gdalwarp -co  COMPRESS=DEFLATE -t_srs EPSG:32632 'test-full-temp.tif' 'test-full.tif'\n",
        "clip_ref_scene('test-full.tif','test-y.tif')\n",
        "resize_scene('test-full.tif','test.tif')\n",
        "jp2_to_tif('/content/S2A_MSIL1C_20190926T105811_N0208_R094_T30TVK_20190926T130550.SAFE/GRANULE/L1C_T30TVK_A022256_20190926T110642/IMG_DATA/T30TVK_20190926T105811_B08.jp2','test-b8-full-temp.tif')\n",
        "!gdalwarp -co  COMPRESS=DEFLATE -t_srs EPSG:32632 'test-b8-full-temp.tif' 'test-b8-full.tif'\n",
        "clip_ref_scene('test-b8-full.tif','test-b8-y.tif')\n",
        "resize_scene('test-b8-full.tif','test-b8.tif')\n"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading: 100%|██████████| 900M/900M [00:30<00:00, 29.1MB/s]\n",
            "MD5 checksumming: 100%|██████████| 900M/900M [00:02<00:00, 437MB/s]\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Creating output file that is 12371P x 12371L.\n",
            "Processing input file test-full-temp.tif.\n",
            "0...10...20...30...40...50...60...70...80...90...100 - done.\n",
            "Creating output file that is 12371P x 12371L.\n",
            "Processing input file test-b8-full-temp.tif.\n",
            "0...10...20...30...40...50...60...70...80...90...100 - done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0oyqqoewN1Pq",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "jPMzARDeN1pE"
      },
      "source": [
        "**DOWNLOAD GPW DATA**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "t_oZDcf9N1pI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 151
        },
        "outputId": "94a4ab6b-e521-4b05-fb43-dab72c64e29f"
      },
      "source": [
        "!unzip '/content/drive/My Drive/Colab_Notebooks/gpw-v4-population-count-rev11_2015_30_sec_tif.zip'\n",
        "!gdalwarp -co  COMPRESS=DEFLATE -t_srs EPSG:32632 '/content/gpw_v4_population_count_rev11_2015_30_sec.tif' 'world-population.tif'\n",
        "clip_ref_scene_pop('test-full.tif','test-pop-full.tif')\n",
        "resize_scene('test-pop-full.tif','test-pop.tif')\n"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Archive:  /content/drive/My Drive/Colab_Notebooks/gpw-v4-population-count-rev11_2015_30_sec_tif.zip\n",
            "  inflating: gpw_v4_population_count_rev11_2015_30_sec.tif  \n",
            "  inflating: gpw_v4_population_count_rev11_2015_30_sec_tif_readme.txt  \n",
            "Creating output file that is 31049P x 36997L.\n",
            "Processing input file /content/gpw_v4_population_count_rev11_2015_30_sec.tif.\n",
            "Using internal nodata values (e.g. -3.40282e+38) for image /content/gpw_v4_population_count_rev11_2015_30_sec.tif.\n",
            "Copying nodata values from source /content/gpw_v4_population_count_rev11_2015_30_sec.tif to destination world-population.tif.\n",
            "0...10...20...30...40...50...60...70...80...90...100 - done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ltZFj9WoNM6B",
        "colab_type": "code",
        "outputId": "8e3e2198-04f7-4b1d-beee-2b2dca102e12",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        }
      },
      "source": [
        "download_scene('4f07815d-5709-4b0b-8fdd-7e12c78e6546')\n",
        "unzip_scene('S2A_MSIL1C_20190629T103031_N0207_R108_T32UMV_20190629T124358.zip')\n",
        "jp2_to_tif('/content/S2A_MSIL1C_20190629T103031_N0207_R108_T32UMV_20190629T124358.SAFE/GRANULE/L1C_T32UMV_A020983_20190629T103537/IMG_DATA/T32UMV_20190629T103031_TCI.jp2','s1-full.tif')\n",
        "clip_ref_scene('s1-full.tif','s1-y.tif')\n",
        "resize_scene('s1-full.tif','s1.tif')\n",
        "jp2_to_tif('/content/S2A_MSIL1C_20190629T103031_N0207_R108_T32UMV_20190629T124358.SAFE/GRANULE/L1C_T32UMV_A020983_20190629T103537/IMG_DATA/T32UMV_20190629T103031_B08.jp2','s1-b8-full.tif')\n",
        "clip_ref_scene('s1-b8-full.tif','s1-b8-y.tif')\n",
        "resize_scene('s1-b8-full.tif','s1-b8.tif')"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading: 100%|██████████| 854M/854M [00:28<00:00, 30.3MB/s]\n",
            "MD5 checksumming: 100%|██████████| 854M/854M [00:01<00:00, 431MB/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_aXVnyDdPP5_",
        "colab_type": "code",
        "outputId": "40c5dfc7-1cd1-4093-dfdc-89b8a58d0810",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        }
      },
      "source": [
        "download_scene('03cf3314-1b05-46f1-af1b-cee2652edf2b')\n",
        "unzip_scene('S2B_MSIL1C_20190724T103029_N0208_R108_T32UMV_20190724T122822.zip')\n",
        "jp2_to_tif('/content/S2B_MSIL1C_20190724T103029_N0208_R108_T32UMV_20190724T122822.SAFE/GRANULE/L1C_T32UMV_A012432_20190724T103030/IMG_DATA/T32UMV_20190724T103029_TCI.jp2','s2-full.tif')\n",
        "clip_ref_scene('s2-full.tif','s2-y.tif')\n",
        "resize_scene('s2-full.tif','s2.tif')\n",
        "jp2_to_tif('/content/S2B_MSIL1C_20190724T103029_N0208_R108_T32UMV_20190724T122822.SAFE/GRANULE/L1C_T32UMV_A012432_20190724T103030/IMG_DATA/T32UMV_20190724T103029_B08.jp2','s2-b8-full.tif')\n",
        "clip_ref_scene('s2-b8-full.tif','s2-b8-y.tif')\n",
        "resize_scene('s2-b8-full.tif','s2-b8.tif')"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading: 100%|██████████| 840M/840M [00:27<00:00, 30.1MB/s]\n",
            "MD5 checksumming: 100%|██████████| 840M/840M [00:01<00:00, 437MB/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "theSLX7TCzWm",
        "colab_type": "code",
        "outputId": "8fb73209-d801-4f26-fb45-f590990a5dd4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 151
        }
      },
      "source": [
        "download_scene('67a87302-2ff4-4c81-9e5e-792367578f6d')\n",
        "unzip_scene('S2B_MSIL1C_20190921T105739_N0208_R094_T30UYC_20190921T131721.zip')\n",
        "jp2_to_tif('/content/S2B_MSIL1C_20190921T105739_N0208_R094_T30UYC_20190921T131721.SAFE/GRANULE/L1C_T30UYC_A013276_20190921T110218/IMG_DATA/T30UYC_20190921T105739_TCI.jp2','s3-full-temp.tif')\n",
        "!gdalwarp -co  COMPRESS=DEFLATE -t_srs EPSG:32632 's3-full-temp.tif' 's3-full.tif'\n",
        "clip_ref_scene('s3-full.tif','s3-y.tif')\n",
        "resize_scene('s3-full.tif','s3.tif')\n",
        "jp2_to_tif('/content/S2B_MSIL1C_20190921T105739_N0208_R094_T30UYC_20190921T131721.SAFE/GRANULE/L1C_T30UYC_A013276_20190921T110218/IMG_DATA/T30UYC_20190921T105739_B08.jp2','s3-b8-full-temp.tif')\n",
        "!gdalwarp -co  COMPRESS=DEFLATE -t_srs EPSG:32632 's3-b8-full-temp.tif' 's3-b8-full.tif'\n",
        "clip_ref_scene('s3-b8-full.tif','s3-b8-y.tif')\n",
        "resize_scene('s3-b8-full.tif','s3-b8.tif')"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading: 100%|██████████| 818M/818M [00:27<00:00, 30.0MB/s]\n",
            "MD5 checksumming: 100%|██████████| 818M/818M [00:01<00:00, 437MB/s]\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Creating output file that is 12634P x 12634L.\n",
            "Processing input file s3-full-temp.tif.\n",
            "0...10...20...30...40...50...60...70...80...90...100 - done.\n",
            "Creating output file that is 12634P x 12634L.\n",
            "Processing input file s3-b8-full-temp.tif.\n",
            "0...10...20...30...40...50...60...70...80...90...100 - done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZQxGlIB8I14v",
        "colab_type": "code",
        "outputId": "d9d90789-077c-4a8c-a79e-d4f2b2c21359",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 151
        }
      },
      "source": [
        "download_scene('c04d2ba0-4880-4dcf-a733-879231478aa3')\n",
        "unzip_scene('S2B_MSIL1C_20190724T103029_N0208_R108_T31TGN_20190724T122822.zip')\n",
        "jp2_to_tif('/content/S2B_MSIL1C_20190724T103029_N0208_R108_T31TGN_20190724T122822.SAFE/GRANULE/L1C_T31TGN_A012432_20190724T103030/IMG_DATA/T31TGN_20190724T103029_TCI.jp2','s4-full-temp.tif')\n",
        "!gdalwarp -co  COMPRESS=DEFLATE -t_srs EPSG:32632 's4-full-temp.tif' 's4-full.tif'\n",
        "clip_ref_scene('s4-full.tif','s4-y.tif')\n",
        "resize_scene('s4-full.tif','s4.tif')\n",
        "jp2_to_tif('/content/S2B_MSIL1C_20190724T103029_N0208_R108_T31TGN_20190724T122822.SAFE/GRANULE/L1C_T31TGN_A012432_20190724T103030/IMG_DATA/T31TGN_20190724T103029_B08.jp2','s4-b8-full-temp.tif')\n",
        "!gdalwarp -co  COMPRESS=DEFLATE -t_srs EPSG:32632 's4-b8-full-temp.tif' 's4-b8-full.tif'\n",
        "clip_ref_scene('s4-b8-full.tif','s4-b8-y.tif')\n",
        "resize_scene('s4-b8-full.tif','s4-b8.tif')"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading: 100%|██████████| 824M/824M [00:27<00:00, 30.0MB/s]\n",
            "MD5 checksumming: 100%|██████████| 824M/824M [00:01<00:00, 435MB/s]\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Creating output file that is 11792P x 11792L.\n",
            "Processing input file s4-full-temp.tif.\n",
            "0...10...20...30...40...50...60...70...80...90...100 - done.\n",
            "Creating output file that is 11792P x 11792L.\n",
            "Processing input file s4-b8-full-temp.tif.\n",
            "0...10...20...30...40...50...60...70...80...90...100 - done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eIxGrcIFQYar",
        "colab_type": "code",
        "outputId": "58d42b9e-ae97-42e0-e92b-53ecd62df9ac",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        }
      },
      "source": [
        "download_scene('4557d038-7f7e-4356-b410-5c6e7d741e7f')\n",
        "unzip_scene('/content/S2A_MSIL1C_20190904T102021_N0208_R065_T32TNT_20190904T123501.zip')\n",
        "jp2_to_tif('/content/S2A_MSIL1C_20190904T102021_N0208_R065_T32TNT_20190904T123501.SAFE/GRANULE/L1C_T32TNT_A021941_20190904T102045/IMG_DATA/T32TNT_20190904T102021_TCI.jp2','s5-full.tif')\n",
        "clip_ref_scene('s5-full.tif','s5-y.tif')\n",
        "resize_scene('s5-full.tif','s5.tif')\n",
        "jp2_to_tif('/content/S2A_MSIL1C_20190904T102021_N0208_R065_T32TNT_20190904T123501.SAFE/GRANULE/L1C_T32TNT_A021941_20190904T102045/IMG_DATA/T32TNT_20190904T102021_B08.jp2','s5-b8-full.tif')\n",
        "clip_ref_scene('s5-b8-full.tif','s5-b8-y.tif')\n",
        "resize_scene('s5-b8-full.tif','s5-b8.tif')"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading: 100%|██████████| 847M/847M [00:28<00:00, 30.0MB/s]\n",
            "MD5 checksumming: 100%|██████████| 847M/847M [00:01<00:00, 431MB/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Nk8gd31NQYeh",
        "colab_type": "code",
        "outputId": "ffa98f51-64cf-45e8-b325-ae7b54f9c3ee",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 151
        }
      },
      "source": [
        "download_scene('336a6ef0-784a-4a90-8333-02ed7ae93b85')\n",
        "unzip_scene('/content/S2B_MSIL1C_20190913T100029_N0208_R122_T33TVJ_20190913T134222.zip')\n",
        "jp2_to_tif('/content/S2B_MSIL1C_20190913T100029_N0208_R122_T33TVJ_20190913T134222.SAFE/GRANULE/L1C_T33TVJ_A013161_20190913T100548/IMG_DATA/T33TVJ_20190913T100029_TCI.jp2','s6-full-temp.tif')\n",
        "!gdalwarp -co  COMPRESS=DEFLATE -t_srs EPSG:32632 's6-full-temp.tif' 's6-full.tif'\n",
        "clip_ref_scene('s6-full.tif','s6-y.tif')\n",
        "resize_scene('s6-full.tif','s6.tif')\n",
        "jp2_to_tif('/content/S2B_MSIL1C_20190913T100029_N0208_R122_T33TVJ_20190913T134222.SAFE/GRANULE/L1C_T33TVJ_A013161_20190913T100548/IMG_DATA/T33TVJ_20190913T100029_B08.jp2','s6-b8-full-temp.tif')\n",
        "!gdalwarp -co  COMPRESS=DEFLATE -t_srs EPSG:32632 's6-b8-full-temp.tif' 's6-b8-full.tif'\n",
        "clip_ref_scene('s6-b8-full.tif','s6-b8-y.tif')\n",
        "resize_scene('s6-b8-full.tif','s6-b8.tif')"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading: 100%|██████████| 555M/555M [00:18<00:00, 29.5MB/s]\n",
            "MD5 checksumming: 100%|██████████| 555M/555M [00:01<00:00, 435MB/s]\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Creating output file that is 11747P x 11747L.\n",
            "Processing input file s6-full-temp.tif.\n",
            "0...10...20...30...40...50...60...70...80...90...100 - done.\n",
            "Creating output file that is 11747P x 11747L.\n",
            "Processing input file s6-b8-full-temp.tif.\n",
            "0...10...20...30...40...50...60...70...80...90...100 - done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ixJUkrMgcU8L",
        "colab_type": "text"
      },
      "source": [
        "**VISUALIZE TEST SET - MADRID REGION - SPAIN**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yZyfQIfccjHl",
        "colab_type": "code",
        "outputId": "16fa38aa-650d-4b37-904c-25e957d098ac",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        }
      },
      "source": [
        "dataset = rasterio.open('test.tif')\n",
        "show(dataset.read([1,2,3]))"
      ],
      "execution_count": 176,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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pgobvUeQl+9MAU9dxdI1xmqEjcC0TQxNouk6WzoxeB2HEh979ECj4/FdepWIYVKoerj4L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+0UIn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\nAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fad3850e710>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 176
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i__Huo409P2W",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "tif1=gdal.Open('s1.tif')\n",
        "s1r = tif1.GetRasterBand(1).ReadAsArray()\n",
        "s1g = tif1.GetRasterBand(2).ReadAsArray()\n",
        "s1b = tif1.GetRasterBand(3).ReadAsArray()\n",
        "tif1=gdal.Open('s1-b8.tif')\n",
        "s1b8=tif1.GetRasterBand(1).ReadAsArray()\n",
        "\n",
        "\n",
        "tif1=gdal.Open('s2.tif')\n",
        "s2r = tif1.GetRasterBand(1).ReadAsArray()\n",
        "s2g = tif1.GetRasterBand(2).ReadAsArray()\n",
        "s2b = tif1.GetRasterBand(3).ReadAsArray()\n",
        "tif1=gdal.Open('s2-b8.tif')\n",
        "s2b8=tif1.GetRasterBand(1).ReadAsArray()\n",
        "\n",
        "\n",
        "tif1=gdal.Open('s3.tif')\n",
        "s3r = tif1.GetRasterBand(1).ReadAsArray()\n",
        "s3g = tif1.GetRasterBand(2).ReadAsArray()\n",
        "s3b = tif1.GetRasterBand(3).ReadAsArray()\n",
        "tif1=gdal.Open('s3-b8.tif')\n",
        "s3b8=tif1.GetRasterBand(1).ReadAsArray()\n",
        "\n",
        "\n",
        "tif1=gdal.Open('s4.tif')\n",
        "s4r = tif1.GetRasterBand(1).ReadAsArray()\n",
        "s4g = tif1.GetRasterBand(2).ReadAsArray()\n",
        "s4b = tif1.GetRasterBand(3).ReadAsArray()\n",
        "tif1=gdal.Open('s4-b8.tif')\n",
        "s4b8=tif1.GetRasterBand(1).ReadAsArray()\n",
        "\n",
        "\n",
        "tif1=gdal.Open('s5.tif')\n",
        "s5r = tif1.GetRasterBand(1).ReadAsArray()\n",
        "s5g = tif1.GetRasterBand(2).ReadAsArray()\n",
        "s5b = tif1.GetRasterBand(3).ReadAsArray()\n",
        "tif1=gdal.Open('s5-b8.tif')\n",
        "s5b8=tif1.GetRasterBand(1).ReadAsArray()\n",
        "\n",
        "\n",
        "tif1=gdal.Open('s6.tif')\n",
        "s6r = tif1.GetRasterBand(1).ReadAsArray()\n",
        "s6g = tif1.GetRasterBand(2).ReadAsArray()\n",
        "s6b = tif1.GetRasterBand(3).ReadAsArray()\n",
        "tif1=gdal.Open('s6-b8.tif')\n",
        "s6b8=tif1.GetRasterBand(1).ReadAsArray()\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UeXgX8gGJ1zr",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "tif2=gdal.Open('test-y.tif')\n",
        "Y_raster_test= tif2.GetRasterBand(1).ReadAsArray()\n",
        "Y_raster_test[Y_raster_test < 100] = 999\n",
        "Y_raster_test[(Y_raster_test > 100)&(Y_raster_test <= 150)] = 0\n",
        "Y_raster_test[Y_raster_test > 150] = 255"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DhVGgAwsDE1W",
        "colab_type": "code",
        "outputId": "eccb9b7b-8f69-481c-d791-8af22d58cb53",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "tif2=gdal.Open('s1-y.tif')\n",
        "Y_raster_s1 = tif2.GetRasterBand(1).ReadAsArray()\n",
        "Y_raster_s1[Y_raster_s1 < 100] = 999\n",
        "Y_raster_s1[(Y_raster_s1 > 100)&(Y_raster_s1 <= 150)] = 0\n",
        "Y_raster_s1[Y_raster_s1 > 150] = 255\n",
        "Y_list=Y_raster_s1.flatten().tolist()\n",
        "print(len(Y_list))"
      ],
      "execution_count": 179,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1062961\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Cm0pI9wdDbU2",
        "colab_type": "code",
        "outputId": "995b0df5-cb46-4fbe-9f75-277f042498c5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        }
      },
      "source": [
        "tif2=gdal.Open('s2-y.tif')\n",
        "Y_raster_s2 = tif2.GetRasterBand(1).ReadAsArray()\n",
        "print(np.unique(Y_raster_s2))\n",
        "Y_raster_s2[Y_raster_s2 < 100] = 999\n",
        "Y_raster_s2[(Y_raster_s2 > 100)&(Y_raster_s2 <= 150)] = 0\n",
        "Y_raster_s2[Y_raster_s2 > 150] = 255\n",
        "\n",
        "Y_list=Y_list+(Y_raster_s2.flatten().tolist())"
      ],
      "execution_count": 180,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[111 112 121 122 123 124 131 132 133 141 142 211 221 222 231 242 243 311\n",
            " 312 313 321 322 324 411 412 511 512]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4P6PAl0xDdJn",
        "colab_type": "code",
        "outputId": "be7b374f-7a0e-40d9-c583-884ff533f51b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84
        }
      },
      "source": [
        "tif2=gdal.Open('s3-y.tif')\n",
        "Y_raster_s3 = tif2.GetRasterBand(1).ReadAsArray()\n",
        "print(np.unique(Y_raster_s3))\n",
        "Y_raster_s3[Y_raster_s3 < 100] = 999\n",
        "Y_raster_s3[(Y_raster_s3 > 100)&(Y_raster_s3 <= 150)] = 0\n",
        "Y_raster_s3[Y_raster_s3 > 150] = 255\n",
        "\n",
        "Y_list=Y_list+(Y_raster_s3.flatten().tolist())"
      ],
      "execution_count": 181,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[-32768    111    112    121    122    123    124    131    132    133\n",
            "    141    142    211    222    231    242    243    311    312    313\n",
            "    321    322    324    331    411    421    423    511    512    522\n",
            "    523]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fUYhZKvLR6UL",
        "colab_type": "code",
        "outputId": "ac94e7ac-4878-4f5c-9b85-33a7b756a4f4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 67
        }
      },
      "source": [
        "tif2=gdal.Open('s4-y.tif')\n",
        "Y_raster_s4 = tif2.GetRasterBand(1).ReadAsArray()\n",
        "print(np.unique(Y_raster_s4))\n",
        "Y_raster_s4[Y_raster_s4 < 100] = 999\n",
        "Y_raster_s4[(Y_raster_s4 > 100)&(Y_raster_s4 <= 150)] = 0\n",
        "Y_raster_s4[Y_raster_s4 > 150] = 255\n",
        " \n",
        "Y_list=Y_list+(Y_raster_s4.flatten().tolist())\n",
        "\n",
        "print(len(Y_list))"
      ],
      "execution_count": 182,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[111 112 121 122 124 131 132 133 141 142 211 221 222 231 242 243 311 312\n",
            " 313 321 322 324 411 412 511 512]\n",
            "4769852\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zecGHKZnl6lE",
        "colab_type": "code",
        "outputId": "81528d24-c5ac-4802-cbce-8da6948263cc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        }
      },
      "source": [
        "tif2=gdal.Open('s5-y.tif')\n",
        "Y_raster_s5 = tif2.GetRasterBand(1).ReadAsArray()\n",
        "print(np.unique(Y_raster_s5))\n",
        "Y_raster_s5[Y_raster_s5 < 100] = 999\n",
        "Y_raster_s5[(Y_raster_s5 > 100)&(Y_raster_s5 <= 150)] = 0\n",
        "Y_raster_s5[Y_raster_s5 > 150] = 255\n",
        " \n",
        "Y_list=Y_list+(Y_raster_s5.flatten().tolist())"
      ],
      "execution_count": 183,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[111 112 121 122 124 131 132 133 141 142 211 221 222 231 242 243 311 312\n",
            " 313 321 322 324 331 332 333 335 411 412 511 512]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8gj9Q5FNryY-",
        "colab_type": "code",
        "outputId": "21176462-1a44-4401-e135-700a3004a9ef",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 67
        }
      },
      "source": [
        "tif2=gdal.Open('s6-y.tif')\n",
        "Y_raster_s6 = tif2.GetRasterBand(1).ReadAsArray()\n",
        "print(np.unique(Y_raster_s6))\n",
        "Y_raster_s6[Y_raster_s6 < 100] = 999\n",
        "Y_raster_s6[(Y_raster_s6 > 100)&(Y_raster_s6 <= 150)] = 0\n",
        "Y_raster_s6[Y_raster_s6 > 150] = 255\n",
        " \n",
        "Y_list=Y_list+(Y_raster_s6.flatten().tolist())"
      ],
      "execution_count": 184,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[-32768    112    121    122    123    142    211    221    223    231\n",
            "    242    243    311    312    313    321    323    324    331    333\n",
            "    421    422    512    523]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fje5-W0HDzrv",
        "colab_type": "code",
        "outputId": "28489d65-eee3-4df9-f49d-ae3cca379257",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "print(np.unique(Y_list))"
      ],
      "execution_count": 185,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[  0 255]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eQz8Q81IEHjN",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#CONVERT RGB BANDS AS INPUT FEATURE SEQUENCES\n",
        "#QUANTIZATION\n",
        "\n",
        "rband_list=s1r.flatten().tolist()\n",
        "rband_list=rband_list+(s2r.flatten().tolist())\n",
        "rband_list=rband_list+(s3r.flatten().tolist())\n",
        "rband_list=rband_list+(s4r.flatten().tolist())\n",
        "rband_list=rband_list+(s5r.flatten().tolist())\n",
        "rband_list=rband_list+(s6r.flatten().tolist())\n",
        "\n",
        "\n",
        "\n",
        "gband_list=s1g.flatten().tolist()\n",
        "gband_list=gband_list+(s2g.flatten().tolist())\n",
        "gband_list=gband_list+(s3g.flatten().tolist())\n",
        "gband_list=gband_list+(s4g.flatten().tolist())\n",
        "gband_list=gband_list+(s5g.flatten().tolist())\n",
        "gband_list=gband_list+(s6g.flatten().tolist())\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "bband_list=s1b.flatten().tolist()\n",
        "bband_list=bband_list+(s2b.flatten().tolist())\n",
        "bband_list=bband_list+(s3b.flatten().tolist())\n",
        "bband_list=bband_list+(s4b.flatten().tolist())\n",
        "bband_list=bband_list+(s5b.flatten().tolist())\n",
        "bband_list=bband_list+(s6b.flatten().tolist())\n",
        "\n",
        "\n",
        "\n",
        "band8_list=s1b8.flatten().tolist()\n",
        "band8_list=band8_list+(s2b8.flatten().tolist())\n",
        "band8_list=band8_list+(s3b8.flatten().tolist())\n",
        "band8_list=band8_list+(s4b8.flatten().tolist())\n",
        "band8_list=band8_list+(s5b8.flatten().tolist())\n",
        "band8_list=band8_list+(s6b8.flatten().tolist())\n",
        "\n",
        "\n",
        "q1=max(rband_list)/16\n",
        "q2=max(gband_list)/16\n",
        "q3=max(bband_list)/16\n",
        "q4=max(band8_list)/18\n",
        "\n",
        "\n",
        "rband_list = [round(math.floor(x+0.5)/q1) for x in rband_list]\n",
        "gband_list = [round(math.floor(x+0.5)/q2) for x in gband_list]\n",
        "bband_list = [round(math.floor(x+0.5)/q3) for x in bband_list]\n",
        "band8_list = [round(math.floor(x+0.5)/q4) for x in band8_list]\n",
        "\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iyaKFSYjTXGE",
        "colab_type": "code",
        "outputId": "43e90c23-7130-4440-9060-9ef6c9eaa300",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "print(len(rband_list))"
      ],
      "execution_count": 187,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "6377766\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G6x9yhlajJ8M",
        "colab_type": "text"
      },
      "source": [
        "***SEQUENCE LIST AND ANTECEDENT-CONSEQUENT LIST(X->Y)***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZsgmJ8Kew52V",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "sequences_list=[]\n",
        "ante_consq_list=[]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mgDj_gvvthgO",
        "colab_type": "code",
        "outputId": "25073d3f-1219-488b-d261-2b07cbaf0662",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 82,
          "referenced_widgets": [
            "1f627b2d91134d08a280f52c5f4e1342",
            "d8045827f2404b0ba2090ceb60f6abe7",
            "92ecf0f496f249ebad2e0cfaa8c1dec2",
            "5bee379c395d4c8ca97bf9b104fa69be",
            "202e14ca4ba24338bb8a27e4fe269776",
            "c36f9f9586eb4640a54057fce9794603",
            "8420dc538411429a94133a8b259951e8",
            "94c572a04dc54b0197ef1bd12bfb22de"
          ]
        }
      },
      "source": [
        "for i in tqdm(range(len(rband_list))):\n",
        "  sequences_list.append((rband_list[i],gband_list[i],bband_list[i],band8_list[i]))\n",
        "  ante_consq_list.append((rband_list[i],gband_list[i],bband_list[i],band8_list[i],Y_list[i]))\n",
        "\n",
        "print('BUILDING DATA DONE')\n"
      ],
      "execution_count": 189,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "1f627b2d91134d08a280f52c5f4e1342",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=6377766), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "BUILDING DATA DONE\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iCVRyjESjwwL",
        "colab_type": "text"
      },
      "source": [
        "***RANDOM EXAMPLE - DATA STRUCTURE (R, G, B, B8, CLASS_LABEL)***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HrJF9PIIthju",
        "colab_type": "code",
        "outputId": "788ed1ce-f549-489a-ebbc-71ebb361fdd1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "print ((ante_consq_list[56]))"
      ],
      "execution_count": 190,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(3, 4, 4, 4, 255)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O843PnPQj9p_",
        "colab_type": "text"
      },
      "source": [
        "***FIND UNIQUE SEQUENCES(X-cap) AND COUNT***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W32qBvF1thnU",
        "colab_type": "code",
        "outputId": "86853cc7-5a46-4141-dd5b-1609054cc6eb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        }
      },
      "source": [
        "print('UNIQUE SEQUENCES COUNT: ')\n",
        "print(len(list(set(sequences_list))))\n",
        "unique_X_sequences=list(set(sequences_list))"
      ],
      "execution_count": 191,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "UNIQUE SEQUENCES COUNT: \n",
            "909\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6u71bdBBsWU9",
        "colab_type": "text"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9tfHuR7ckert",
        "colab_type": "text"
      },
      "source": [
        "***STEP 2:***\n",
        "\n",
        "*   ***ASSOCIATION ANALYSIS***\n",
        "*   ***EVIDENCE BASED NORMALIZED DIFFERENTIAL INDEX(ENDI) MEASURE***\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CDwyOG-sluFT",
        "colab_type": "text"
      },
      "source": [
        "***HELPER FUNCTIONS:***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PBmN7nsvxTGb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#ONE VARIATION OF ENDI INTERESTINGNESS MEASURE\n",
        "def calculate_ENDI(positive,negative):\n",
        "  if (positive==0) and (negative==0) : return 0\n",
        "  return (positive-negative)/(positive+negative)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q5DdKX6Z51Jm",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#POSITIVE EVIDENCES\n",
        "def positive_count(sequence,class_name):\n",
        "  item = list(sequence)\n",
        "  item.append(class_name)\n",
        "  c=counter[tuple(item)]\n",
        "  return c\n",
        "\n",
        "\n",
        "#NEGATIVE EVIDENCES\n",
        "def negative_count(sequence, class_list):\n",
        "  negative_classcount=0\n",
        "  for c in  class_list:\n",
        "    item = list(sequence)\n",
        "    item.append(c)\n",
        "    negative_classcount=negative_classcount+counter[tuple(item)]\n",
        "\n",
        "  return negative_classcount\n",
        "\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GqVeHx5El9b7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#COUNT FREQUENCIES OF EACH UNIQUE SEQUENCE\n",
        "counter=Counter(ante_consq_list)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "N6c40R8gtgYA",
        "colab_type": "text"
      },
      "source": [
        "***CALCULATE ENDI MEASURE FOR ALL THE CLASSES PER SEQUENCE DATA***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BHa17NbP4P6R",
        "colab_type": "code",
        "outputId": "6391907c-43e2-490b-f0c3-c8eb0942d799",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 82,
          "referenced_widgets": [
            "6ceeb4b0930e4bd9b3dc636e1d807bef",
            "50171239cdef4a99960595b68e431098",
            "95f5687cbca94fef99752bfc9723eba4",
            "4a0a6b1ab60f4264a6fc4a3c0da85f11",
            "d6714349621a44eb9d78a2e6a98c6436",
            "87744452783f4c5e831bedca0a79a1cf",
            "0918f4e43f504dc28b580ffa15398c81",
            "6bad974e2545448680daae39cdeefa8b"
          ]
        }
      },
      "source": [
        "#GENERATE A DICTIONARY OF THE FORM : {(unique sequence) : [ENDI MEASURE-CLASS 0, ENDI MEASURE-CLASS 1]}\n",
        "ENDI_table_dictionary={}\n",
        "\n",
        "for i in tqdm(range(len(unique_X_sequences))):\n",
        "  seq=unique_X_sequences[i]\n",
        "  ENDI_class_0=calculate_ENDI(positive_count(seq,0),negative_count(seq,[255]))\n",
        "  ENDI_class_1=calculate_ENDI(positive_count(seq,255),negative_count(seq,[0]))\n",
        "  ENDI_table_dictionary[seq]=[ENDI_class_0,ENDI_class_1]\n",
        "\n",
        "print('BUILDING DICTIONARY DONE')\n",
        "\n",
        "#PRINT RANDOM DATA POINT\n",
        "#print(ENDI_table_dictionary[unique_X_sequences[5000]])\n"
      ],
      "execution_count": 195,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "6ceeb4b0930e4bd9b3dc636e1d807bef",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=909), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "BUILDING DICTIONARY DONE\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n84ur78SsZ-z",
        "colab_type": "text"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "goD_JtMTtgo7",
        "colab_type": "text"
      },
      "source": [
        "***STEP 3 : CLASSIFICATION AND VISUALIZATION***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8kntNAM6gcPn",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def classification(file_name,band8filename):\n",
        "          new_image=gdal.Open(file_name)\n",
        "          rband_new = new_image.GetRasterBand(1).ReadAsArray()\n",
        "          gband_new = new_image.GetRasterBand(2).ReadAsArray()\n",
        "          bband_new = new_image.GetRasterBand(3).ReadAsArray()\n",
        "          tif1=gdal.Open(band8filename)\n",
        "          band8_new=tif1.GetRasterBand(1).ReadAsArray()\n",
        "\n",
        "          rband_list_new=rband_new.flatten().tolist()\n",
        "          gband_list_new=gband_new.flatten().tolist()\n",
        "          bband_list_new=bband_new.flatten().tolist()\n",
        "          band8_list_new=band8_new.flatten().tolist()\n",
        "\n",
        "          q1=max(rband_list_new)/16\n",
        "          q2=max(gband_list_new)/16\n",
        "          q3=max(bband_list_new)/16\n",
        "          q4=max(band8_list_new)/18\n",
        "\n",
        "          rband_list_new = [round(math.floor(x+0.5)/q1) for x in rband_list_new]\n",
        "          gband_list_new = [round(math.floor(x+0.5)/q2) for x in gband_list_new]\n",
        "          bband_list_new = [round(math.floor(x+0.5)/q3) for x in bband_list_new]\n",
        "          band8_list_new = [round(math.floor(x+0.5)/q4) for x in band8_list_new]\n",
        "\n",
        "\n",
        "          final_pred_list=[]\n",
        "          final_confidence_list=[]\n",
        "\n",
        "          for i in tqdm(range(len(rband_list_new))):\n",
        "\n",
        "            if ((rband_list_new[i],gband_list_new[i],bband_list_new[i],band8_list_new[i])) in ENDI_table_dictionary:\n",
        "                  ENDI_vals=ENDI_table_dictionary[(rband_list_new[i],gband_list_new[i],bband_list_new[i],band8_list_new[i])]\n",
        "                  max_val = max(ENDI_vals)\n",
        "                  index_max = ENDI_vals.index(max_val)\n",
        "                  final_pred_list.append(index_max)\n",
        "                  final_confidence_list.append(ENDI_vals[0])   \n",
        "            else:\n",
        "              final_pred_list.append(1)\n",
        "              final_confidence_list.append(-1)\n",
        "\n",
        "          final_confidence_list_scaled = minmax_scale(final_confidence_list, feature_range=(0,100))\n",
        "          return final_pred_list,final_confidence_list_scaled\n",
        "\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wq6E1HhJhfi2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def visualization(any_list,size,title,outputfile,colormap):\n",
        "  numpy_array=np.asarray(any_list)\n",
        "  #numpy_array[numpy_array == 1] = 255\n",
        "  final_image_array=numpy_array.reshape((size,size))\n",
        "  fig, ax = plt.subplots()\n",
        "  ax.set_title(title)\n",
        "  img = ax.imshow(final_image_array,cmap=plt.get_cmap(colormap))\n",
        "  fig.colorbar(img, ax=ax)\n",
        "  fig.savefig(outputfile+'.png')\n",
        "  cv2.imwrite(outputfile+\".tif\", final_image_array)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "72cxX4heaE5W",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def metrics(y_actual, y_pred_original):\n",
        "    numpy_array=np.asarray(y_pred_original)\n",
        "    numpy_array[numpy_array == 1] = 255\n",
        "    y_pred=numpy_array.tolist()\n",
        "    class_id = set(y_actual).union(set(y_pred))\n",
        "    TP = []\n",
        "    FP = []\n",
        "    TN = []\n",
        "    FN = []\n",
        "\n",
        "    for index ,_id in enumerate(class_id):\n",
        "        TP.append(0)\n",
        "        FP.append(0)\n",
        "        TN.append(0)\n",
        "        FN.append(0)\n",
        "        for i in tqdm(range(len(y_pred))):\n",
        "            if y_actual[i] == y_pred[i] == _id:\n",
        "                TP[index] += 1\n",
        "            if y_pred[i] == _id and y_actual[i] != y_pred[i]:\n",
        "                FP[index] += 1\n",
        "            if y_actual[i] == y_pred[i] != _id:\n",
        "                TN[index] += 1\n",
        "            if y_pred[i] != _id and y_actual[i] != y_pred[i]:\n",
        "                FN[index] += 1\n",
        "\n",
        "\n",
        "    return class_id,TP, FP, TN, FN"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RqZ2C_ow04Ij",
        "colab_type": "text"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JCK5RsYA05Ld",
        "colab_type": "text"
      },
      "source": [
        "**VISUALIZATION OF RESULTS AND METRICS - MADRID AREA(SPAIN)**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iPhSuhjw1S5y",
        "colab_type": "text"
      },
      "source": [
        "1) MADRID CLASSIFICATION RESULTS"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3zzrNttfg4p-",
        "colab_type": "code",
        "outputId": "733d5a34-2fe1-4cef-8a15-931954991b82",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 66,
          "referenced_widgets": [
            "cb7a68d186c34328a06147d6ad426a4a",
            "7556f263a20f430d856dbe52e5d56b5f",
            "de62f736573240acbffa09a799b51cd4",
            "8cbdb1508e9547519497ca9a30ff498d",
            "b7144714d5ec4e69bf9b2309ceba0074",
            "a655bd6d0d204aa09f2ebc429205e228",
            "775bcaddad454549bef6e99e164065fc",
            "1c0df33c78f04e8eb5394310025feffe"
          ]
        }
      },
      "source": [
        "prediction_list,confidence_list=classification('test.tif','test-b8.tif')\n"
      ],
      "execution_count": 199,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "cb7a68d186c34328a06147d6ad426a4a",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=1062961), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JJYgfo6zWVj2",
        "colab_type": "code",
        "outputId": "8767ff6d-ed29-466c-e64e-385fc5c6cfbc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        }
      },
      "source": [
        "visualization(prediction_list,  IMG_SIZE, 'Classification-Madrid Region, Spain','predictions-madrid',colormap='binary')"
      ],
      "execution_count": 200,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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pcEm7S7pa0u3h727hXEn6gKQNkr4m6aB2bqGR/ZWvqVrhm04GboNJQjvNylc0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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lJSm-m30qk3a",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "outputId": "a725bf19-a79f-41d3-fc17-e47f9143a175"
      },
      "source": [
        "visualization(confidence_list,  IMG_SIZE,'Confidence-Madrid Region, Spain','confidence-madrid',colormap='Greens')"
      ],
      "execution_count": 201,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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wgpoKdRAykviu63sHlV1ItzXKhNSJelv/rpg0Kv+fmwuN1SpfVpNufYSZIYS4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\nRK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H8YwFJ2lbXdk",
        "colab_type": "code",
        "outputId": "adc623fd-4290-4e99-efee-a2aa44966251",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 114,
          "referenced_widgets": [
            "4055a008ab054f4598e27ff158f26b2f",
            "12f2c4971b7946c19d12e632d65211c3",
            "bd4491e4051f4561887c6092f9ffde8c",
            "5ca2dced08c34e00803cec511230c089",
            "9f1d7158c2d94d1884cc1e92cc3f1fcf",
            "1b45b8713c434b2ba692cec1d40da0e0",
            "57d148453e714cea9d2cb495fd9ccd59",
            "d664e86ddd024b649fcf006f1085646b",
            "bb9579dbb6654f5d85a3e3a8893681d4",
            "29647bb75494416dbc5af0682a53bb86",
            "d21b93d8357c4774bc96341dd28e9a43",
            "ce57b93169c742d7a917804ba8e1df8a",
            "31efd801aca544448855fa2683676fa9",
            "aef377dc560e4e6eae39bd99954a4143",
            "056120f0c73f47d994b0e1fbcab11285",
            "4d8906c461034bbaa4d7574d5b9aeb6d"
          ]
        }
      },
      "source": [
        "m=metrics(Y_raster_test.flatten().tolist(),prediction_list)"
      ],
      "execution_count": 202,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "4055a008ab054f4598e27ff158f26b2f",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=1062961), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "bb9579dbb6654f5d85a3e3a8893681d4",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=1062961), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mbjXWoqsjQ_d",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "unique, counts = np.unique(Y_raster_test.flatten().tolist(), return_counts=True)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WskaAi3ghsiH",
        "colab_type": "code",
        "outputId": "e398e3c1-3ba1-45a9-99e3-991c51893f66",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84
        }
      },
      "source": [
        "for i in range(0,2):\n",
        "  TP=m[1][i]\n",
        "  FP=m[2][i]\n",
        "  TN=m[3][i]\n",
        "  FN=m[4][i]\n",
        "  P=counts[i]\n",
        "  N=len(Y_list)-P\n",
        "  TPR=TP/P\n",
        "  TNR=TN/N\n",
        "  bal_measure = (TPR+TNR)/2\n",
        "  inf_accuracy=TPR-TNR\n",
        "  print('BALANCED ACCURACY FOR CLASS '+str(i)+\" is \"+ str(bal_measure))\n",
        "  print('INFORMEDNESS FOR CLASS '+str(i)+\" is \"+str(inf_accuracy))\n"
      ],
      "execution_count": 204,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "BALANCED ACCURACY FOR CLASS 0 is 0.08182210162870895\n",
            "INFORMEDNESS FOR CLASS 0 is -0.10021403591198473\n",
            "BALANCED ACCURACY FOR CLASS 1 is 0.3643016883644962\n",
            "INFORMEDNESS FOR CLASS 1 is 0.7271509196183651\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "unQkKXcY1RAe",
        "colab_type": "text"
      },
      "source": [
        "2)ORIGINAL RGB IMAGE"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wCHf3Rrg0J5J",
        "colab_type": "code",
        "outputId": "1985ad88-32d7-44a9-987f-1d4bf6d1455b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        }
      },
      "source": [
        "dataset = rasterio.open('test.tif')\n",
        "show(dataset.read([1,2,3]))"
      ],
      "execution_count": 205,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ooOG7VByHmqVz/uwySxWLi8fanFtq8zvPXkUTJYUq+dyVDfamAeeWOxxECaUG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+0UIn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\nAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fad6816a668>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 205
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kahuQs5RQke_",
        "colab_type": "text"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wi0eQgxbQc-Z",
        "colab_type": "text"
      },
      "source": [
        "# **GHS-POP**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V_x38xXZvfRw",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "outputId": "140766a7-272a-4be2-9ad0-c532b71e33c7"
      },
      "source": [
        "pop1=gdal.Open('test-pop.tif')\n",
        "pop2d = pop1.GetRasterBand(1).ReadAsArray()\n",
        "pop2d[pop2d < 0] = 0\n",
        "fig, ax = plt.subplots()\n",
        "img = ax.imshow((pop2d),cmap=plt.get_cmap('Purples'))\n",
        "fig.colorbar(img, ax=ax)\n",
        "ax.set_title('GHS POP')"
      ],
      "execution_count": 206,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'GHS POP')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 206
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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OOLZTDognJi3N90yA9zBm56hLq21uqaODPvfvHdNq+WzvdKzNrZoHnOd1ojfZ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\ncRzAxdBxHAdwMXQcxwHg/2f+eNN/NyM+AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mvZV26J1PRtM",
        "colab_type": "text"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1ZzqcPLVPSkn",
        "colab_type": "text"
      },
      "source": [
        "# **GHS S-MOD**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bboKeNp8hoEC",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def classify_urban_area(i,j,d,arr):\n",
        "  n = arr[i-d:i+d+1, j-d:j+d+1].flatten()\n",
        "  return n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nT2V_oR7kubq",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "confidence2d=np.asarray(confidence_list).reshape((IMG_SIZE,IMG_SIZE))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zKvjUXZgQEGI",
        "colab_type": "text"
      },
      "source": [
        "CLASSIFY URBAN CENTRE, URBAN CLUSTER, RURAL AREA AND OTHER REGIONS"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NxHaEnLJjxbf",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 66,
          "referenced_widgets": [
            "4fe6ab92ee3c4fc888f725c7cfc90de6",
            "71ce979bdd964af180b6ec0e63df1317",
            "a5c8b9f01d97419a83f58f4c2c5b5343",
            "e18d214a622849248e65f74b5f132040",
            "1e81f7c856e746fd99dd1fc2e6015bde",
            "24583eb23db04d37840baa3612390e63",
            "ab8fad30bf65436891e5fcc400a131f3",
            "1d7f8d19c16c4f85858ab51f9ea9de95"
          ]
        },
        "outputId": "b9f7d004-7184-4dc0-de3b-00b8e7547e2d"
      },
      "source": [
        "urban_array=np.zeros((IMG_SIZE, IMG_SIZE))\n",
        "\n",
        "for ix,iy in tqdm(np.ndindex(pop2d.shape)):\n",
        "    popcellvalue=pop2d[ix,iy]\n",
        "    confidencecellvalue=confidence2d[ix,iy]\n",
        "\n",
        "    if((popcellvalue>1500 or confidencecellvalue>50) and (np.sum(classify_urban_area(ix,iy,2,pop2d))>50000)):\n",
        "      urban_array[ix,iy]=3\n",
        "    elif (popcellvalue>300 and (np.sum(classify_urban_area(ix,iy,8,pop2d))>5000)):\n",
        "      urban_array[ix,iy]=2\n",
        "    elif(popcellvalue>1 and (np.sum(classify_urban_area(ix,iy,3,pop2d))<5000)):\n",
        "      urban_array[ix,iy]=1"
      ],
      "execution_count": 227,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "4fe6ab92ee3c4fc888f725c7cfc90de6",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ny5DJDt_ozxY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "outputId": "8085a372-0abd-47a1-c38b-e98bffffde04"
      },
      "source": [
        "from matplotlib import colors\n",
        "import matplotlib.patches as mpatches\n",
        "fig, ax = plt.subplots()\n",
        "black_patch = mpatches.Patch(color='black', label='Urban Centre')\n",
        "dark_grey_patch=mpatches.Patch(color='grey', label='Urban Cluster')\n",
        "grey_patch = mpatches.Patch(color='lightgray', label='Others')\n",
        "white_patch = mpatches.Patch(color='white', label='Rural')\n",
        "\n",
        "ax.legend(handles=[black_patch,dark_grey_patch,white_patch, grey_patch], loc='lower right')\n",
        "img = ax.imshow(urban_array,cmap=plt.get_cmap('binary'))\n",
        "ax.set_title('GHS-SMOD')"
      ],
      "execution_count": 228,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'GHS-SMOD')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 228
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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SpEmccsopXHzxxVkF4fbbb+fWW2/NOqw+nfQxNIsXL+bSSy8FYNGiRZx22mkM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\n60Wa64VdmQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0Uj7CmWs1DfC",
        "colab_type": "text"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    }
  ]
}