Satellite detected water extent over Chittagong division, Bangladesh as of 8 August 2021

Date of Images: May 5, 2024, August 9, 2024, August 21, 2024 Summary: The Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at NASA's Jet Propulsion Laboratory and California Institute of Technology derived the surface water extent maps from Sentinel-1. The results posted here are preliminary and unvalidated results, primarily intended to aid the field response and people who wanted to have a rough first look at the inundation extent. The ARIA-share website has always focused on posting preliminary results as fast as possible for disaster response. Suggested Use: The OPERA DSWx-S1 products classifies the OPERA Radiometric Terrain Corrected SAR backscatter from Sentinel-1 (RTC-S1) input imagery into: not water, water, and inundated vegetation with the masks such as layover/shadow mask and HAND mask. The WTR layer includes all classes. Open water and inundated vegetation are represented in blue and green in WTR. Areas with masks are gray. The masks include the layover/shadow mask and HAND mask. Areas with no water detected are transparent. Transparent: Not Water Blue: Water Green: Inundated Vegetation Gray: Layover/Shadow/Hand Masks Satellite/Sensor: Synthetic Aperture Radar (SAR) instrument on European Space Agency's (ESA) Sentinel-1A satellite Harmonized Landsat Sentinel-2 (HLS): MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites and Operational Land Imager (OLI) on the NASA/USGS Landsat 8 satellite Resolution: 30 meters The DSWx-S1 products have these flags: 250 (light gray) and 251 (dark gray) represent HAND and layover/shadow masks, respectively. HAND mask (light gray, value 250) delineates regions where the terrain's elevation exceeds a specified threshold relative to the height above the nearest drainage point, indicating areas less likely to be subject to direct inundation. Layover/shadow mask (dark gray, value 251) identifies zones that are either occluded by topographic features taller than the surrounding landscape (layover) or are not illuminated by the radar signal due to obstruction by these elevated features (shadow), leading to potential data voids in SAR imagery. Credits: NASA JPL-Caltech ARIA/OPERA Team Sentinel-1 data were accessed through the Copernicus Open Hub and the Alaska Satellite Facility server. The product contains modified Copernicus Sentinel data (2024), processed by the European Space Agency and analyzed by the NASA-JPL/Caltech ARIA and OPERA team. The products are produced as part of the OPERA project, which is funded by NASA to address remote sensing needs identified by the Satellite Needs Working Group, and managed by NASA's Jet Propulsion Laboratory. The OPERA DSWx products have been in production since September 2024, are freely distributed to the public via NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC), and can be downloaded through NASA's Earthdata search. For more information about the Dynamic Surface Water eXtent product suite, please refer to the DSWx Product page: https://www.jpl.nasa.gov/go/opera/products/dswx-product-suite. For more information about the Caltech-JPL ARIA project, visit https://aria.jpl.nasa.gov. For more information about the JPL OPERA project, visit https://www.jpl.nasa.gov/go/opera. Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=feb8ab36293f4bcfa20ca61e54fa1298 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202408_FLOOD_BANGLADESH/2423_opera_dswx_s1/ImageServer/WMSServer

Includes a binary GeoTIFF where 0 values are non-flooded and 1 values are flooded. Included a metadata file that describes a summary and methods for the data.

**UNOSAT code: FL20200713BGD** This map illustrates satellite-detected surface waters over the Eastern part of the Sylhet division of Bangladesh as observed from a TerraSAR-X image acquired on 18 July 2020 due to the current monsoon rains. Within the analyzed area of about 8,600 km2, a total of about 2,200 km2 of lands appear to be flooded. This is a preliminary analysis and has not yet been validated in the field. Based on WorldPop population data and the detected surface waters, about 2,000,000 people area potentially exposed or living close to flooded areas. Please send ground feedback to UNITAR - UNOSAT. Important Note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

**UNOSAT code: FL20200713BGD** This map illustrates satellite-detected surface waters over Khulna, Rajshahi and Rangpur Division of Bangladesh of Bangladesh as observed from a Sentinel-1 image acquired on 9 July 2020 and 21 July 2020. Within the analyzed area of about 15,000 km2, a total of about 3,600 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 2,507,000 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT. Important Note: Flood analysis from Sentinel-1 image acquired on 9 July 2020 and 21 July 2020 may underestimate the presence of standing

**UNOSAT code: FL20200713BGD** This map illustrates satellite-detected surface waters over Chittagong, Dhaka, Mymensingh and Sylhet Divisions of Bangladesh as observed from a Sentinel-1 image acquired on 20 July 2020 due to the current monsoon rains. Within the analyzed area of about 14,250 km2, a total of about 7,120 km2 of lands appear to be flooded. Based on WorldPop population data and the detected surface waters, about 6,700,000 people area potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT. Important Note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

**UNOSAT code: FL20220525BGD** This map illustrates satellite-detected surface waters in Sylhet, Mymensingh, Dhaka, and Chattogram Divisions, Bangladesh observed from a RCM-1 images acquired on 19 Jun. 2022 at 18:02 local time. Within the analyzed area of about 22,300 km2, about 9,500 km2 of lands appear to be flooded. In this area, about 7,860 km2 of croplands and 1,340 km2 of herbaceous wetland appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters, about 7,334,000 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.