Dataset Open Access

High-resolution inundation dataset for coastal India and Bangladesh

Mondal, Pinki; Dutta, Trishna; Qadir, Abdul; Sharma, Sandeep

This collection of gridded data layers provides the extent of inundation in May 2020 resulting from the cyclone Amphan in 39 coastal districts in India and Bangladesh.

Input data:

These geospatial data layers are derived from Sentinel-1 dual-polarization C-band Synthetic Aperture Radar (SAR) data for pre-Amphan (May 5-18, 2020) and post-Amphan (May 22-30, 2020) periods. We accessed ready-to-use SAR data on Google Earth Engine (GEE). These input data were preprocessed using Ground Range Detected (GRD) border-noise removal, thermal noise removal, radiometric calibration, and terrain correction, to derive backscatter coefficients (σ°) in decibels (dB). We used VH polarisation instead of VV, since the latter is known to be affected by windy conditions as compared to VH.

Methods:

We developed a binary water/non-water classification scheme for the pre- and post-Amphan images using the automated Otsu thresholding approach that finds optimum threshold values based on clusters found in the histograms of pixel values. This analysis resulted in eight images: four each for pre-Amphan and post-Amphan periods (one each for coastal districts of Odisha and West Bengal and two for Bangladesh for each period). The pixels in these images have two values: 0 for non-water and 1 for water.

We then used a decision rule to identify areas that changed from ‘non-water’ to ‘water’ after the cyclone. The decision rule generated the ‘inundation layer’ with the permanent water bodies such as river, lakes, oceans and aquaculture masked out. This analysis resulted in four images, each with pixels with a value of 1 for inundated regions.

Data set format:

The spatial resolution of all the derived datasets is 10m. These georeferenced datasets are distributed in GEOTIFF format, and are compatible with GIS and/or image processing software, such as R and ArcGIS. The GIS-ready raster files can be used directly in mapping and geospatial analysis.

Data set for download:

A. Three data layers for Odisha, India:

  1. OD_pre_binary.tif
  2. OD_post_binary.tif
  3. OD_inundation.tif

These data layers cover 10 districts: Baleshwar, Bhadrak, Cuttack, Jagatsinghpur, Jajpur, Kendrapara, Keonjhar, Khordha, Mayurbhanj and Puri.

B. Three data layers for West Bengal, India:

  1. WB_pre_binary.tif
  2. WB_post_binary.tif
  3. WB_inundation.tif

These data layers cover 9 districts: Barddhaman, East Midnapore, Haora, Hugli, Kolkata, Nadia, North 24 Parganas, South 24 Parganas, and West Midnapore.

C. Six data layers for Bangladesh – three each for lower (L) region and upper (U) region.

  1. BNG_L_pre_binary.tif
  2. BNG_L_post_binary.tif
  3. BNG_L_inundation.tif
  4. BNG_U_pre_binary.tif
  5. BNG_U_post_binary.tif
  6. BNG_U_inundation.tif

The data layers for the lower region cover 11 districts: Bagerhat, Barguna, Barisal, Bhola, Jhalokati, Khulna, Lakshmipur, Noakhali, Patuakhali, Pirojpur, and Satkhira.

The data layers for the upper region cover 9 districts: Chuadanga, Jessore, Jhenaidah, Kushtia, Meherpur, Naogaon, Natore, Pabna, and Rajshahi.

Files (168.3 MB)
Name Size
BNG_L_inundation.tif
md5:9c2977c4695113b3edf9d5eeadd7b1c7
7.5 MB Download
BNG_L_post_binary.tif
md5:441a51d0d25dc55bcb4e39b28ac65cf0
9.8 MB Download
BNG_L_pre_binary.tif
md5:c50daedc697caaf71c6837f304c1f31d
8.1 MB Download
BNG_U_inundation.tif
md5:9798d6158a7acb75ca9e48b098365587
7.0 MB Download
BNG_U_post_binary.tif
md5:d3064ceeb60493524a1e24cfad7c4479
12.9 MB Download
BNG_U_pre_binary.tif
md5:e44ec454ccfd0a541c8ee815669325e2
14.4 MB Download
OD_inundation.tif
md5:15470a51f722c78e20aaf6cb25ee93d9
21.0 MB Download
OD_post_binary.tif
md5:cf2879e8a55f30ae33cafb2cb39b8cab
24.5 MB Download
OD_pre_binary.tif
md5:ef0327867ceebe24b709a5b22cc61abb
27.4 MB Download
WB_inundation.tif
md5:477f4111cffb371bee209d0b814a89ad
12.6 MB Download
WB_post_binary.tif
md5:b89889b52f6f1a78b8e0043e53006db5
13.5 MB Download
WB_pre_binary.tif
md5:458460ebd9c4dfa87d61eb12a212044e
9.7 MB Download
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