Bangladesh water data

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

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

**UNOSAT code: FL20210729BGD** This map illustrates satellite-detected surface waters in Chittagong division, Bangladesh as observed from a Sentinel-1 image acquired on 8 August 2021 at 17:55 local time. Within the analyzed area of about 18,700 km2 and, about 873 km2 of lands appear to be flooded. The water extent appears to have increased of about 21 km2 since 30 July 2021. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Cox's Bazar with ~393,240 people, Chittagong with ~358,320 people. 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.

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.

**UNOSAT code: FL20220525BGD** This map illustrates satellite-detected surface waters and impact in Sylhet and Sunamganj Districts, Sylhet Division, Bangladesh as observed from a RCM-1 image acquired on 18 Jun 2022 at 17:54 local time. Within the analyzed area of about 1,325 km2, about 840 km2 of lands appear to be flooded. In this area, about 140 km of roads and 1 km of railway appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters, about 839,000 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.

This map illustrates satellite-detected surface water extent around Maheshkhali, Chakaria and Cox'S Bazar Sadar Upazilas in the District of Cox's Bazar, Chittagong Division in the south eastern part of Bangladesh as detected by a TerraSAR-X image acquired on the 1st June 2017. A total of ~20,000 ha of lands seem to be affected with flood waters. Some of the affected lands are mainly agricultural fields. The analysis of this satellite image reveals also that about 100 km of roads with mainly tertiary roads seem to be also potentially affected. We can also estimate, within this map extent and using the WorldPop data, about 265,000 people living in flood affected zones. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

This map illustrates satellite-detected surface water extent in the District of Cox's Bazar, Chittagong Division, located in the southeastern part of Bangladesh after the tropical cyclone Mora-17 using a Sentinel-1 satellite image acquired on the 30 May 2017. A total of 23,058 ha surface waters were observed. In many zones, the affected lands are mainly agricultural. The analysis of this image reveals also that about 234 km of roads mainly tertiary roads seem to be potentially affected. The population exposure analysis using WorldPop data shows that ~267,000 people are potentially affected by floods within map extent. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

This map illustrates the satellite-detected water extent in the District of Chittagong, Chittagong Division, in the southeastern part of Bangladesh after the tropical cyclone Mora-17. The UNITAR-UNOSAT analysis used a Sentinel-1 satellite image acquired on the 30 May 2017 and detected several areas with standing waters. In the district of Chittagong ~4,790 ha are likely flooded and almost 12 km of the local roads seem to be affected. The population exposure analysis using WorldPop data shows that ~70,000 people are potentially affected by floods within map extent. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

**UNOSAT code: FL20240502BGD, GDACS ID: 1001064** This map illustrates satellite-detected surface waters in Barisal, Dhaka and Khulna Divisions, Bangladesh as observed from a Sentinel-1 images acquired on 1 June 2024 at 05:56 local time and using an automated analysis with machine learning method. Within the analyzed area of about 52,000 km2, about 1,000 km2 of land appears to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Bagerhat, Khulna Division with ~96,000 people, and Barguna, Barisal Division with ~74,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the 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.

**UNOSAT code: FL20240502BGD, GDACS ID: 1001064** This map illustrates satellite-detected surface waters in Satkhira and Khulna Districts, Khulna Divisions, Bangladesh as observed from TANDEM_X images acquired on 1 June 2024 at 18:01 local time. Within the analyzed area of about 1,100 km2, about 200 km2 of land appears to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, 124,000 people are potentially exposed or living close to the affected areas. UNITAR-UNOSAT identified 76,000 structures potentially exposed to floods in the analyzed area. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the 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 the backscattering properties of the radar signal.

**UNOSAT code: FL20240502BGD, GDACS ID: 1001064** This map illustrates cumulative satellite-detected surface waters in Sylhet Division, Bangladesh as observed from Sentinel-1 images acquired on the 19th and 22nd June 2024 and using an automated analysis with machine learning method. Within the analysed area of about 12,000 km2, about 2,600 km2 of land appears to be flooded. Based on Worldpop population data and the detected surface waters in the analysed area, the potentially exposed population is mainly located in the district of Sylhet with ~1 million people, Habiganj with ~530,000 people, Sunamganj with ~420,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the 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.

**UNOSAT code: FL20240502BGD, GDACS ID: 1102700** This map illustrates the aggregated floods using Sentinel-1 images acquired between 22 to 29 June 2024 and between 4 to 11 July 2024 using an automated analysis with machine learning method. Within the analysed area of about 140,000 km², a total of about 8,700 km² of land appear to be affected by flood waters. Based on Worldpop spatial demographic data, about 7.7 million people are exposed or living close to flooded areas. Between these two periods, the floodwaters have increased about 2,900 km2. The increase has been mainly observed within Rangpur and Rajshahi divisions accordingly. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the 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 the backscattering properties of the radar signal.

**UNOSAT code: FL20240502BGD, GDACS ID: 1102700** This map illustrates the aggregated floods using Sentinel-1 images acquired between 16 to 23 July 2024 and between 4 to 11 July 2024 using an automated analysis with a machine learning method. Within the analysed area of about 140,000 km², a total of about 8,530 km² of land appears to be affected by flood waters. Based on Worldpop spatial demographic data, about 8 million people are exposed or living close to flooded areas. Between these two periods, the floodwaters have increased about 130 km2. The increase has been mainly observed within the Rajshahi, Sylhet, Rangpur and Dhaka divisions accordingly. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the 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 the backscattering properties of the radar signal.

**UNOSAT code: FL20240825BGD** This map illustrates the aggregated floods using Sentinel-1 images acquired between 18 to 26 August 2024 and between 28 August & 4 September 2024 using an automated analysis with a machine learning method. Within the analysed area of about 140,000 km², a total of about 8,100 km² of land appears to be affected by flood waters. Based on Worldpop spatial demographic data, about 6.2 million people are exposed or living close to flooded areas. Over these two periods, floodwaters receded by approximately 8,700 km². This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the 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 the backscattering properties of the radar signal.

**UNOSAT code: FL20220525BGD** This map illustrates satellite-detected surface waters in Rangpur Division, Bangladesh as observed from a Sentinel-1 images acquired on 21 Jun. 2022 at 18:05 local time and using an automated analysis with machine learning method. Within the analyzed area of about 12,400 km2, about 1,200 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Kurigram with ~537,000 people, and Gaibandha with ~355,000 people. 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.

**UNOSAT code: FL20220525BGD** This map illustrates satellite-detected surface waters in Sylhet and Sunamganj Districts, Sylhet Division, Bangladesh as observed from a Chaohu-1 image acquired on 25 May 2022 at 22:23 local time. Within the analyzed area of about 730 km2, about 420 km2 of lands appear to be flooded. In this area, about 300 km2 of croplands and 70 km2 of herbaceous wetland appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters, about 307,000 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.

**UNOSAT code: FL20210729BGD** This map illustrates satellite-detected surface waters in Chittagong division, Bangladesh as observed from a Sentinel-1 image acquired on 30 July 2021 at 05:33 local time Within the analyzed area of about 18,700 km2 and, about 852 km2 of lands appear to be flooded. The water extent appears to have decreased of about 18km2 since 27 July 2021. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Cox's Bazar with ~425,000 people, Chittagong with ~392,300 people. 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.

**UNOSAT code: FL20220525BGD** This map illustrates satellite-detected surface waters in Sylhet, Mymensingh, Dhaka, and Chattogram Divisions, Bangladesh as observed from a Sentinel-1 images acquired on 28 May 2022 at 18:04 local time and using an automated analysis with machine learning method. Within the analyzed area of about 12,000 km2, about 4,500 km2 of lands appear to be flooded. In this area, about 3,400 km2 of croplands and 1,000 km2 of herbaceous wetland appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Sunamganj with ~935,000 people and Kishoreganj with ~779,000 people. 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.

**UNOSAT code: FL20220525BGD** This map illustrates satellite-detected surface waters in Rajshahi, Rangur, Mymensingh, Dhaka and Khulna Divisions, Bangladesh as observed from a Sentinel-1 images acquired on 21 Jun. 2022 at 18:05 local time and using an automated analysis with machine learning method. Within the analyzed area of about 20,400 km2, about 2,950 km2 of lands appear to be flooded. Water extent appears to have increased of about 2,360 km2 since 9 Jun. 2022. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the division of Rajshahi with ~1,335,000 people, Dhaka with 674,000 people,and Mymensingh with ~ 640,000 people. 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.

**UNOSAT code: FL20220525BGD** This map illustrates satellite-detected surface waters in Sylhet, Mymensingh, Dhaka, and Chattogram Divisions, Bangladesh as 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. Water extent appears to have increased of about 2,150 km2 since the period between 25 to 28 May 2022. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Sunamganj with ~1,822,000 people and Sylhet with ~1,550,000 people. 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.

**UNOSAT code: FL20220525BGD** This map illustrates satellite-detected surface waters in Sylhet, Mymensingh, Dhaka, and Chattogram Divisions, Bangladesh as observed from a Sentinel-1 images acquired on 26 May 2022 at 05:47 local time and using an automated analysis with machine learning method. Within the analyzed area of about 16,000 km2, about 6,800 km2 of lands appear to be flooded. In this area, about 5,400 km2 of croplands and 1,270 km2 of herbaceous wetland appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Sunamganj with ~1,700,000 people and Sylhet with ~1,400,000 people. 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.

**UNOSAT code: FL20210729BGD** This map illustrates satellite-detected surface waters in Chittagong division, Bangladesh as observed from a Sentinel-1 image acquired on 11 August 2021 at 05:48 local time. Within the analyzed area of about 18,700 km2 and, about 754 km2 of lands appear to be flooded. The water extent appears to have decreased of about 119 km2 since 8 August 2021. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Chittagong with ~ 342,690 people. and Cox's Bazar with ~ 244,000 people. 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.