Satellite detected waters over Cochabamba department, Bolivia
About this dataset
Documentation
Related datasets
✦ Suggested by OrionAIThis map illustrates satellite-detected standing water over the El Beni department in Bolivia, as of the 12 February 2018, following heavy rainfalls that caused severe flooding in the area. The analysis was conducted using Radarsat-2 image from 12 February 2018. UNITAR-UNOSAT identified in the analyzed area of the El Beni Department around 52,670 Ha of land that seem to be inundated, most of which are agricultural fields and swamps. The Rio Mamore has expanded along the banks. According to the analysis, the most affected province is Moxos, where more than 35,500 Ha are submerged. In the municipality of Trinidad 6,900 Ha are detected as inundated. 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 central and southern parts of Bangladesh using a Sentinel-1 satellite image acquired on the 22 August 2017. In the analysed area; 608,747 ha of lands are likely affected. These lands are mainly cropland irrigated and rainfed areas and estimated to 475,000 ha. The population exposure analysis using WorldPop data shows that ~6,400,000 people are potentially affected by floods in the analysed zone: ~2,300,000 are located in Chittagong Division and ~2,170,000 in Dhaka Division. Please note that for visualization purposesanalyzed area is wider than the extent of this map. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
**UNOSAT code: TC20240313MOZ, GDACS ID: 1001053** This map illustrates satellite detected surface waters in Maputo province, Mozambique, as observed from a Sentinel-1 images acquired on 23 March 2024 at 05:19 local time (03:19 UTC). Within the analyzed areas of about 950 km², a total of about 10 km² of lands appear to be flooded. 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).
This map illustrates satellite-detected surface water extent in the central and northern parts of Bangladesh using a Sentinel-1 satellite image acquired on the 22 August 2017. The total analysed area is about 4,284,431 ha. In this analysed area; 1,099,369 ha (39%) of lands are likely affected. These lands are mainly cropland irrigated and rainfed areas and estimated to 1,039,350 ha. The population exposure analysis using WorldPop data shows that ~10,000,000 people are potentially affected by floods in the analysed zone: ~5,400,000 are located in Dhaka Division and ~2,750,000 in Rajshahi Division. Please note that for visualization purposes the analyzed area is wider than the extent of this map.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 Maguindanao and Cotabato provinces, Phillipines. The UNITAR-UNOSAT analysis used a Sentinel-1 satellite image acquired on the 07 June 2017 and could observe areas with standing waters mainly affecting agricultural fields. Within the map extent, the UNITAR-UNOSAT analysis identified ~34,000 ha of those areas and ~127 km of potentially affected road mainly local roads. 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 surface waters extent in the southern provinces of kien Giang, An Giang, Dong Thap & Can tho as observed from the Sentinel-1 SAR images acquired on 16 & 28 August 2018. In the analysed area, an increase of surface waters is observed mainly in agricultural and paddy fields areas. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
Indexed by OrionGIS from Humanitarian Data Exchange (HDX). Data is loaded from the publisher's own server when you use it. Permanent link