UNOSAT is a technology-intensive programme delivering imagery analysis and satellite solutions to relief and development organisations within and outside the UN system to help make a difference in critical areas such as humanitarian relief, human security, strategic territorial and development planning. UNOSAT develops applied research solutions keeping in sight the needs of the beneficiaries at the end of the process.
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Updated
November 25, 2020
| Dataset date: Nov 19, 2020
This dataset updates: Never
UNOSAT code: TC20201116HND This map illustrates satellite-detected surface waters in Atlantida and Yoro Departments of Honduras as observed from a Sentinel-1 image acquired on 18 November 2020 at 05:37 Local time. Within the analyzed area of about 3,000 km2, a total of about 40 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 1,200 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 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.
Updated
November 25, 2020
| Dataset date: Nov 19, 2020
This dataset updates: Never
UNOSAT code: TC20201116HND This map illustrates satellite-detected surface waters in Olancho Department of Honduras as observed from a Sentinel-1 image acquired on 18 November 2020 at 05:37 Local time. Within the analyzed area of about 4,400 km2, a total of about 32 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 900 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 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.
Updated
November 25, 2020
| Dataset date: Nov 19, 2020
This dataset updates: Never
UNOSAT code: TC20201116HND This map illustrates satellite-detected surface waters in Colon and Yoro Departments of Honduras as observed from a Sentinel-1 image acquired on 18 November 2020 at 05:37 Local time. Within the analyzed area of about 12,000 km2, a total of about 80 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 4,000 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 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.
Updated
November 25, 2020
| Dataset date: Nov 20, 2020
This dataset updates: Never
UNOSAT code: TC20201116HND This map illustrates satellite-detected surface waters in Colon and Yoro Departments of Honduras as observed from a Sentinel-1 image acquired on 18 November 2020 at 18:06 Local time. Within the analyzed area of about 5,200 km2, a total of about 220 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 82,000 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 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.
Updated
November 25, 2020
| Dataset date: Nov 20, 2020
This dataset updates: Never
UNOSAT code: TC20201119GTM This map illustrates satellite-detected surface waters in Alta Verapaz, Izabal and Zacapa departments of Guatemala as observed from a Sentinel-1 image acquired on 18 November 2020 at 18:06 local time. Within the analyzed area of about 15,000 km2, a total of about 170 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 17,500 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 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.
Updated
November 25, 2020
| Dataset date: Nov 20, 2020
This dataset updates: Never
UNOSAT code: TC20201119GTM This map illustrates satellite-detected surface waters in Petรฉn department of Guatemala as observed from a Sentinel-1 image acquired on 18 November 2020 at 18:06 local time. Within the analyzed area of about 3,400 km2, a total of about 100 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 4,200 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 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.
Updated
November 25, 2020
| Dataset date: Nov 23, 2020
This dataset updates: Never
UNOSAT code: TC20201119GTM This map illustrates satellite-detected surface waters in Peten, Alta Verapaz and Quiche departments of Guatemala & Chiapas state of Mexico as observed from a Sentinel-1 image acquired on 22 November 2020 at 05:53 Local time. Within the analyzed area of about 10,000 km2, a total of about 380 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 24,000 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 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.
Updated
November 25, 2020
| Dataset date: Nov 24, 2020
This dataset updates: Never
UNOSAT code: TC20201123COL This map illustrates potentially damaged structures and buildings in Providencia Island, Providencia and Santa Catalina Department of Colombia as detected by satellite image acquired after landfall of the Tropical Cyclone IOTA on 17 November 2020.
UNITAR-UNOSAT analysis used a WorldView-2 image acquired on 21 November 2020 as a post-event image. Within the Island boundary, UNITAR-UNOSAT identified in the cloud-free zones 1,110 damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 90% of the total number of structures within the analyzed cloud-free areas.
Updated
November 25, 2020
| Dataset date: Nov 24, 2020
This dataset updates: Never
UNOSAT code: TC20201123COL This map illustrates potentially damaged structures and buildings in San Andres Island, Providencia and Santa Catalina department of Colombia as detected by satellite image acquired after landfall of the Tropical Cyclone IOTA on 17 November 2020.
UNITAR-UNOSAT analysis used a WorldView-2 image acquired on 18 November 2020 as a post-event image. Within the Island boundary, UNITAR-UNOSAT identified in the cloud-free zones 220 Potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 6% of the total number of structures within the analyzed cloud-free areas.
Updated
November 25, 2020
| Dataset date: Nov 25, 2020
This dataset updates: Never
UNOSAT code: TC20201116HND This map illustrates satellite-detected surface waters in Cortes, Atlantida, and Yoro departments of Honduras as observed from a Sentinel-1 image acquired on 23 November 2020 at 05:45 Local time. Within the analyzed area of about 3,500 km2, a total of about 170 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 35,000 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 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.
Updated
November 25, 2020
| Dataset date: Nov 25, 2020
This dataset updates: Never
UNOSAT code: TC20201119GTM This map illustrates satellite-detected surface waters in Izabal department of Guatemala as observed from a Sentinel-1 image acquired on 23 November 2020 at 05:45 Local time. Within the analyzed area of about 6,000 km2, a total of about 150 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 8,600 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 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.
Updated
September 10, 2019
| Dataset date: Sep 3, 2019
This dataset updates: Never
UNOSAT code: FL20190815SDN This map illustrates satellite-detected surface water over Aljammalab region, White Nile State in Sudan as observed from Pleiades imagery acquired on 28 August 2019. Within the analysed area of about 14,000 ha, a total of 7,200 ha of lands appear to be flooded as of 28 August 2019. Waters seem to have retracted from the settlement as of 28 August 2019. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
Updated
December 10, 2015
| Dataset date: Dec 8, 2015
This dataset updates: Never
This map illustrates satellite-detected shelters and other buildings at the Al Zaatari refugee camp in Mafraq Governorate, Jordan. As of 12 October 2015 a total of 26,963 shelters were detected as well as 2,130 infrastructure and support buildings within the 534.4 hectares of the camp. Between 26 April 2015 and 12 October 2015, a total of 4,310 shelters closed or were moved, and a total of 2,296 shelters were constructed, and the number of shelters has thus decreased by about 2,268 since the previous UNITAR-UNOSAT assessment. This indicates an approximate 7.76% decrease in the number of shelters between 26 April 2015 and 12 October 2015. This is a preliminary analysis and has not yet been validated in the field; structure locations subject to a spatial error margin of +/- three meters. Shelters grouped under plastic sheeting were estimated by average household size and may be a source of error. Please send ground feedback to UNITAR-UNOSAT.
Updated
November 14, 2018
| Dataset date: Aug 10, 2015
This dataset updates: Never
This is "Flood vectors - TerraSAR-X (10 August 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 36,947 satellite detected water bodies with a spatial extent of 1,398.96 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 - 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
December 14, 2018
| Dataset date: Jul 18, 2015
This dataset updates: Never
This is "Flood vectors - Sentinel-1 (18 July 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 106,050 satellite detected water bodies with a spatial extent of 1,623.93 square kilometers derived from the Sentinel-1 image ac...
Updated
December 14, 2018
| Dataset date: Jul 11, 2015
This dataset updates: Never
This is "Flood vectors - Sentinel-1 (11 July 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 18,990 satellite detected water bodies with a spatial extent of 6,593.12 square kilometers derived from the Sentinel-1 image acq...
Updated
November 14, 2018
| Dataset date: Aug 11, 2015
This dataset updates: Never
This is "Flood vectors - Sentinel-1 (11 August 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 54,800 satellite detected water bodies with a spatial extent of 2,939.48 square kilometers derived from the Sentinel-1 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...
Updated
December 14, 2018
| Dataset date: Jul 30, 2015
This dataset updates: Never
This is "Flood vectors - Radarsat-2 (30 July 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 8,573 satellite detected water bodies with a spatial extent of 747.03 square kilometers derived from the Radarsat-2 image acquir...
Updated
November 14, 2018
| Dataset date: Aug 17, 2015
This dataset updates: Never
This is "Flood vectors - Radarsat-2 (17 August 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 17,249 satellite detected water bodies with a spatial extent of 1,052.18 square kilometers derived from the Radarsat-2 image a...
Updated
November 14, 2018
| Dataset date: Jul 10, 2015
This dataset updates: Never
This is "Flood vectors - Radarsat-2 (10 July 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 41,369 satellite detected water bodies with a spatial extent of 690,073.54 square kilometers derived from the Radarsat-2 image a...
Updated
August 31, 2020
| Dataset date: Aug 9, 2015
This dataset updates: Never
This is "Flood vectors - Radarsat-2 (09 August 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 38,793 satellite detected water bodies with a spatial extent of 1,374.71 square kilometers derived from the Radarsat-2 image a...
Updated
August 31, 2020
| Dataset date: Aug 6, 2015
This dataset updates: Never
This is "Flood vectors - Radarsat-2 (06 August 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 21,526 satellite detected water bodies with a spatial extent of 1,187.49 square kilometers derived from the Radarsat-2 image a...
