UN Operational Satellite Applications Programme (UNOSAT)
Last updated on August 11, 2020
Refine your search: Clear all
Featured:
Locations:
More
Formats:
More
Tags:
More
Licenses:
  • UNOSAT code: FL20200713BGD This map illustrates potentially exposed population to floods (cumulative) aggregated by district using NOAA20-VIIRS in Bangladesh between the 12th and the 21st of July 2020 and Worldpop spatial demographic data. About 34 million people were exposed or living close to flooded areas. The most exposed districts mainly located in Sylhet, Mymensingh and Rajshahi divisions.
  • 10+ Downloads
    Updated August 8, 2020 | Dataset date: Aug 6, 2015
    This dataset updates: Never
    This is "Flood vectors - TerraSAR-X (06 August 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 21,970 satellite detected water bodies with a spatial extent of 1,066.81 square kilometers derived from the TerraSAR-X image a...
  • Updated August 8, 2020 | Dataset date: Aug 6, 2015
    This dataset updates: Never
    This is "Flood vectors - Sentinel-1 (06 August 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 48,899 satellite detected water bodies with a spatial extent of 1,140.54 square kilometers derived from the Sentinel-1 image a...
  • 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: FL20200713BGD This map illustrates satellite-detected surface waters in the central parts of Bangladesh as observed from a Sentinel-1 image acquired on 19 July 2020 and 13 July 2020. Within the analyzed area of about 40,000 km2, a total of about 8,700 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 UNITAR - UNOSAT. Important Note: Flood analysis from Sentinel-1 imagery acquired on 19 July 2020 and 13 July 2020 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 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: FL20200708NPL This map illustrates satellite-detected surface waters in Province 2 of Nepal as observed from a Radarsat-2 image acquired on 14 July 2020 due to the current monsoon rains. Within the analyzed area of about 2,000 km2, a total of about 50 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 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: FL20200708NPL This map illustrates satellite-detected surface waters in Province 2 of Nepal as observed from a Sentinel-1 image acquired on 13 July 2020 due to the current monsoon rains. Within the analyzed area of about 2,300 km2, a total of about 200 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 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: FL20200708NPL This map illustrates satellite-detected surface waters in Province 1 and 2 of Nepal as observed from a Radarsat-2 image acquired on 12 July 2020 due to the current monsoon rains. Within the analyzed area of about 3,000 km2, a total of about 475 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 UNITAR - UNOSAT. Important Note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas due to backscattering properties of the radar signal.
  • UNOSAT code: FL20200708NPL This map illustrates satellite-detected surface waters in Province 2 of Nepal as observed from a TerraSAR-X image acquired on 12 July 2020 due to the current monsoon rains. Within the analyzed area of about 900 km2, a total of about 35 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 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: FL20200708NPL This map illustrates satellite-detected surface waters in Province 1 and 2 of Nepal as observed from a Sentinel-1 image acquired on 6 July 2020. Within the analyzed area of about 2,700 km2, a total of a bout 76 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 UNITAR - UNOSAT. Important Note: Flood analysis from Sentinel-1 imagery acquired on 6 July 2020 may seriously underestimate presence of standing flood water in built up areas due to backscattering properties
  • UNOSAT code: FL20200713BGD This map illustrates satellite-detected surface waters over Mymensingh, Rajshahi and Rangpur Division of Bangladesh as observed from a TerraSAR-X image acquired on 18 July 2020. Within the analyzed area of about 9,000 km2, a total of about 2,860 km2 of lands appear to be flooded. This is a preliminary analysis and has not yet been validated in the field. Please sendground 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 Bangladesh as observed from a TanDEM-X image acquired on 19 July 2020 due to the current monsoon rains. Within the analyzed area of about 14,000 km2, a total of about 6,800 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 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: FL20200626UKR This map illustrates satellite-detected surface waters in Ivano-Frankivska and Ternopilska Oblastof Ukraine as observed from a Sentinel-1 image acquired on 24 June 2020. Within the ana lyzed area of about 642 km2, a total of a bout 35 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 UNITAR-UNOSAT .
  • UNOSAT code: TC20200518BGD This map illustrates satellite-detected surface waters in Bagerhat, Jessore, Khulna, Narail, and Satkhira district of Khulna division, Bangladesh as observed from a Sentinel-1 image acquired on 31 May 2020. Within the analyzed area of about 8,320 km2, a total of about 462 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 UNITAR - UNOSAT.
  • Updated June 3, 2020 | Dataset date: May 26, 2020
    This dataset updates: Never
    UNOSAT code: TC20200518BGD This map illustrates satellite-detected surface waters in Bagerhat, Jessore, Khulna, Narail, and Satkhira district of Khulna division, Bangladesh as observed from a Sentinel-1 image acquired on 25 May 2020. Within the analyzed area of about 8,320 km2, a total of about 1,000 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 UNITAR - UNOSAT.
  • Updated June 3, 2020 | Dataset date: May 18, 2020
    This dataset updates: Never
    UNOSAT code: FL20200428SOM This map illustrates the flood-affected sectors of Beletweyne town in Hiraan Region, Somalia as detected from the analysis of an ICEYE satellite image acquired on 16 May 2020. Within the analysed area of about 30 km2, a total of 8 km2 of land appear to be flooded in BeletWeyne town and surroundings. This is a preliminary analysis and has not been validated in the field yet. Please send ground feedback to UNITAR-UNOSAT.
  • UNOSAT code: FL20200428SOM This map illustrates the flood-affected sectors of Beletweyne town in Hiiran Region, Somalia as detected from the analysis of a satellite Worldview-2 images acquired on the 13 May 2020. Belet Weyne is heavily affected by floods and about 50% of the town and its vicinity is largely inundated; the sectors called Kutimbo, Radar, and Lamagalay Regional Military Base appear to be the most affected by floodwaters as of 13 May 2020. More than 110 IDP sites are located inside of the town and 25% of them are located within the completely flooded areas. This is a preliminary analysis and has not been validated in the field yet. Please send ground feedback to UNITAR-UNOSAT.
  • Updated June 3, 2020 | Dataset date: Apr 28, 2020
    This dataset updates: Never
    UNOSAT code: TC20200403VUT This map illustrates potentially damaged structures and buildings in Meawo Island, Penama Province, Vanuatu as detected by satellite image acquired after landfall of the Tropical Cyclone Harold-20 on 6 April 2020. UNITAR-UNOSAT analysis used a Pleiades image acquired on 21 and 27 April 2020 as post event images, Within the island boundary, UNITAR-UNOSAT identified in the cloud free zones about 20 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 2% of the total number of structures within the analyzed cloud free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • UNOSAT code: TC20200403VUT This map illustrates potentially damaged structures and buildings in West Santo and South Santo Municipality, Sanma Province, Vanuatu as detected using WorldView-2 satellite images acquired on 17 and 19 April 2020 and a Pleiades satellite image acquired on 27 April 2020. Within the analyzed zone, UNITAR-UNOSAT identified in the cloud-free zones about 3,650 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 63 % of the total number of structures within the analyzed cloud-free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • Updated June 3, 2020 | Dataset date: Apr 27, 2020
    This dataset updates: Never
    UNOSAT code: TC20200403VUT This map illustrates potentially damaged structures and buildings in Ambae Island, Penama Province, Vanuatu as detected by satellite image acquired after landfall of the Tropical Cyclone Harold-20 on 6 April 2020. UNITAR-UNOSAT analysis used a WorldView-2 image acquired on 20 April 2020 and Pleiades image acquired on 21 April 2020 as post event images, Within the Island extent, UNITAR-UNOSAT identified in the cloud free zones about 60 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 1% of the total number of structures within the analyzed cloud free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • Updated June 3, 2020 | Dataset date: Apr 24, 2020
    This dataset updates: Never
    UNOSAT code: TC20200403VUT This map illustrates potentially damaged structures and buildings in Paama Island, Malampa Province, Vanuatu as detected by satellite image acquired after landfall of the Tropical Cyclone Harold-20 on 6 April 2020. UNITAR-UNOSAT analysis used a Pleiades image acquired on 21 April 2020 as post event images, Within the island boundary, UNITAR-UNOSAT identified in the cloud free zones about 100 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 30% of the total number of structures within the analyzed cloud free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • UNOSAT code: TC20200408FJI This map illustrates potentially damaged structures, buildings and their related density in Kadavu Province, Eastern Division, Republic of Fiji as detected by satellite images acquired on 12 April 2020. Within the Kadavu Province, UNITAR-UNOSAT identified in the cloud free zones 1,003 potentially damaged structures. Taking into account the pre-building footprints provided by OpenStreetMap, this represents about 22% of the total number of structures within the analyzed cloud free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • UNOSAT code: TC20200403VUT This map illustrates potentially damaged structures and buildings in south of Sanma Province, Vanuatu as detected by satellite image acquired after landfall of the Tropical Cyclone Harold-20 on 6 April 2020. UNITAR-UNOSAT analysis identified about 5,200 potentially damaged structures in the analysis extent across the south of Sanma province within the cloud free areas. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 33% of the total number of structures/buildings within the analyzed cloud free areas. Please note that some areas could not be analyzed due to the cloud cover. Total and final estimates by municipality are summarized in the table below. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.