UN Operational Satellite Applications Programme (UNOSAT)

Satellite-detected flood waters, as of 29 November 2019, over Loukoléla, Cuve...

Updated January 9, 2020 | Dataset date: Dec 10, 2019

This dataset updates: Never

UNOSAT code: FL20191205COG This map illustrates satellite-detected flood waters along the Congo River over, Loukoléla, Loukoléla District, Cuvette Department in Republic of Congo as observed from Pleiades-1 imagery acquired on 29 November 2019. 136 ha of potential flood waters and 168 potentially flooded structures have been identified in Loukoléla and its vicinity. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR -UNOSAT.

Satellite-detected water extents, as of 5 November 2019 over Basse-Kotto Pref...

UN Operational Satellite Applications Programme (UNOSAT)

Updated December 18, 2019 | Dataset date: Nov 13, 2019

This dataset updates: Never

UNOSAT code: FL20191028CAF This map illustrates satellite-detected surface water in Ouaka and Basse-Kotto Prefectures of the Central African Republic, as observed from Sentinel-1 imagery acquired on 5 November 2019. Within the analysed extent of about 970 km2, a total about 9 km2 of land 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 with Sentinel-1 imagery may notably underestimate the presence of standing water in built up areas due to backscattering of the radar signal.

Satellite-detected water extents, as of 5 November 2019 over Basse-Kotto Pref...

UN Operational Satellite Applications Programme (UNOSAT)

Updated December 18, 2019 | Dataset date: Nov 13, 2019

This dataset updates: Never

UNOSAT code: FL20191028CAF This map illustrates satellite-detected surface waters in Basse-Kotto Prefecture of the Central African Republic, as observed from Sentinel-1 imagery acquired on 5 November 2019. Within the analysed extent of about 390 km2, a total of about 7 km2 of land 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 with Sentinel-1 imagery may notably underestimate the presence of standing water in built up areas due to backscattering of the radar signal.

Satellite detected waters extents, as of 5 November 2019 over Ouaka Prefectur...

UN Operational Satellite Applications Programme (UNOSAT)

Updated December 18, 2019 | Dataset date: Nov 13, 2019

This dataset updates: Never

UNOSAT code: FL20191028CAF This map illustrates satellite-detected surface water in Ouaka Prefecture of Central African Republic, as observed from Sentinel-1 imagery acquired on 5 November 2019. Within the analysed extent of about 2,000 km2, a total about 10 km2 of land 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 with Sentinel-1 imagery may notably underestimate the presence of standing water in built up areas due to backscattering of the radar signal.

Landslides assessment in Pokot South and Sigor Sub Counties West Pokot County...

UN Operational Satellite Applications Programme (UNOSAT)

Updated December 10, 2019 | Dataset date: Nov 29, 2019

This dataset updates: Never

UNOSAT code: LS20191125KEN This map illustrates satellite-detected landslides in Pokot South and Sigor Sub counties located in West Pokot county (Kenya) as detected from a Pleiades-1 image acquired on 28 November 2019. Several roads in the valley have been affected and at least 5 bridges were destroyed. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

Satellite detected waters extents, as of 18 November 2019 over Basse-Kotto Pr...

UN Operational Satellite Applications Programme (UNOSAT)

Updated November 22, 2019 | Dataset date: Nov 22, 2019

This dataset updates: Never

UNOSAT code: FL20191028CAF This map illustrates satellite-detected water surface in Central African Republic and Democratic Republic of The Congo as observed from Sentinel-1 imagery acquired on 18 November 2019. Within the analysed extent of about 760 km2, a total about 6 km2 of land appear to be flooded in Basse-Kotto Prefecture of Central African Republic and about 1 km2 of land appear to be flooded in Nord-Ubangi Province of Democratic Republic of The Congo. 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 SAR Sentinel-1 images may significantly underestimate the presence of standing waters in built up and/or densely vegetated areas due to backscattering of the radar signal.

Satellite detected waters extents, as of 23 October 2019 over Unity, Jonglei ...

UN Operational Satellite Applications Programme (UNOSAT)

10+ Downloads

Updated December 6, 2019 | Dataset date: Oct 25, 2019

This dataset updates: Never

UNOSAT code: FL20191023SSD This map illustrates satellite-detected surface water in Unity, Jonglei and Lakes State of South Sudan as observed from Sentinel-1 imagery acquired on 23 October 2019. Within the analysed extent of about 85,000 km2, a total about 1,180 km2 of land 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 23 October 2019 may seriously underestimate the presence of standing floodwater in built-up areas due to backscattering of the radar signal

Satellite-detected water extents as of 30 October 2019, over Beled Weyne Dist...

UN Operational Satellite Applications Programme (UNOSAT)

Updated December 6, 2019 | Dataset date: Oct 31, 2019

This dataset updates: Never

UNOSAT code: FL20191030SOM This map illustrates satellite-detected surface water in Beled Weyne District, Hiraan Region in Somalia analyzed with Sentinel-1 imagery acquired on 30 October 2019. Within the analysed extent of about 2,500 km2, a total of about 155 km2 of land 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 based on Sentinel-1 imagery may significantly underestimate the presence of standing floodwater in dense built-up areas due to backscattering of the radar signal.

Satellite-detected flood waters over Mobayi-Mbongo, Nord-Ubangi Province, Dem...

UN Operational Satellite Applications Programme (UNOSAT)

Updated November 22, 2019 | Dataset date: Nov 21, 2019

This dataset updates: Never

UNOSAT code: FL20191118COD This map illustrates satellite-detected flooded waters along the Ubangui River over Mobayi-Mbongo,Mobayi-Mbongo Territory, Nord-Ubangi Province in Democratic Republic of the Congo as observed from SPOT 7 imagery acquired on 16 November 2019. UNITAR-UNOSAT has identified about 60 buildings/houses likely surrounded by waters. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR -UNOSAT.

Satellite-detected flood waters, as of 15 November 2019, Libenge, Libenge Ter...

UN Operational Satellite Applications Programme (UNOSAT)

Updated November 22, 2019 | Dataset date: Nov 20, 2019

This dataset updates: Never

UNOSAT code: FL20191118COD This map illustrates satellite-detected flood waters along the Ubangi River over Libenge, Libenge Territory, Sud-Ubangi Province in Democratic Republic of the Congo as observed from Pleiades imagery acquired on 15 November 2019. 90 ha of potential flood waters have been identified in Libenge and its vicinity. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR -UNOSAT.

Satellite detected waters extents, as of 17 November 2019 over Ouaka Prefectu...

UN Operational Satellite Applications Programme (UNOSAT)

Updated November 22, 2019 | Dataset date: Nov 20, 2019

This dataset updates: Never

UNOSAT code: FL20191028CAF This map illustrates satellite-detected surface water in Ouaka Prefecture of Central African Republic as observed from Sentinel-1 imagery acquired on 17 November 2019. Within the analysed extent of about 1,950 km2, a total about 4 km2 of land 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 SAR Sentinel-1 images may significantly underestimate the presence of standing waters in built up and/or densely vegetated areas due to backscattering of the radar signal.

Satellite detected waters extents, as of 17 November 2019 over Ouaka and Bass...

UN Operational Satellite Applications Programme (UNOSAT)

Updated November 22, 2019 | Dataset date: Nov 20, 2019

This dataset updates: Never

UNOSAT code: FL20191028CAF This map illustrates satellite-detected surface water in Ouaka and Basse-Kotto Prefecture of Central African Republic as observed from Sentinel-1 imagery acquired on 17 November 2019. Within the analysed extent of about 940 km2, a total about 3 km2 of land 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 SAR Sentinel-1 images may significantly underestimate the presence of standing waters in built up and/or densely vegetated areas due to backscattering of the radar signal.

Satellite detected waters extents, as of 17 November 2019 over Basse-Kotto Pr...

UN Operational Satellite Applications Programme (UNOSAT)

Updated November 22, 2019 | Dataset date: Nov 20, 2019

This dataset updates: Never

UNOSAT code: FL20191028CAF This map illustrates satellite-detected surface water in Basse-Kotto Prefecture of Central African Republic as observed from Sentinel-1 imagery acquired on 17 November 2019. Within the analysed extent of about 425 km2, a total about 2 km2 of land 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 SAR Sentinel-1 images may significantly underestimate the presence of standing waters in built up and/or densely vegetated areas due to backscattering of the radar signal.

Satellite-detected flood waters, as of 12 November 2019, over Zongo, Democrat...

UN Operational Satellite Applications Programme (UNOSAT)

Updated November 22, 2019 | Dataset date: Nov 19, 2019

This dataset updates: Never

UNOSAT code: FL20191118COD This map illustrates satellite-detected floodedwaters along the Ubangui River over Zongo, Libenge Territory, Sud-Ubangi Territory in Democratic Republic of the Congo as observed from GeoEye-1 imagery acquired on 12 November 2019. UNITAR-UNOSAT has identified 58 ha of potentially flood waters north-west of Zongo. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

Satellite-detected flooded structures, as of 15 November 2019, over Libenge, ...

UN Operational Satellite Applications Programme (UNOSAT)

Updated November 22, 2019 | Dataset date: Nov 19, 2019

This dataset updates: Never

UNOSAT code: FL20191118COD This map illustrates satellite-detected flooded structures along the Ubangui River over Libenge, Libenge Territory, Sud-Ubangui Territory in Democratic Republic of the Congo as observed from Pleiades imagery acquired on 15 November 2019. UNITAR-UNOSAT identified 22 potentially flooded structures west of Libenge, within 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.

Satellite-detected flooded structures, as of 12 November 2019, over Zongo, De...

UN Operational Satellite Applications Programme (UNOSAT)

Updated November 22, 2019 | Dataset date: Nov 18, 2019

This dataset updates: Never

UNOSAT code: FL20191118COD This map illustrates satellite-detected flooded structures along the Ubangui River over Zongo, Libenge Territory, Sud-Ubangui Territory in Democratic Republic of the Congo as observed from GeoEye-1 imagery acquired on 12 November 2019. UNITAR-UNOSAT has identified within the extent of this map 276 potentially flooded structures north-west of Zongo. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

Damage Assessment in Anguilla Island as of 8 September 2017

UN Operational Satellite Applications Programme (UNOSAT)

70+ Downloads

Updated September 10, 2017 | Dataset date: Sep 8, 2017

This dataset updates: Every day

This dataset illustrates satellite-detected potential damaged buildings in Anguilla Island, following the landfall of Tropical Cyclone IRMA-17 on September 6, 2017. The UNITAR-UNOSAT analysis used a Kompsat-3 satellite image acquired on 9 February 2017 and WorldView-2 image acquired on 5 July 2017 as pre-imagery and Pleiades satellite imagery acquired on the 7 & 8 September 2017 as a post-imagery. The UNITAR-UNOSAT analysis identified 2,147 potentially damaged structures within the analyzed area that was not covered by clouds. According to the pre-building footprints, inside the area free of clouds, provided by Humanitarian Open Street Map, this represents 42% of potentially affected structures in Anguilla.

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Damage Assessment in Barbuda Island as of 8 September 2017

UN Operational Satellite Applications Programme (UNOSAT)

70+ Downloads

Updated September 10, 2017 | Dataset date: Sep 8, 2017

This dataset updates: Every day

This dataset illustrates satellite-detected potential damaged buildings in Barbuda Island following the landfall of Tropical Cyclone IRMA-17 on September 6, 2017. The UNITAR-UNOSAT analysis used a Pleiades satellite image acquired on 8 September 2017 as post imagery. The UNITAR-UNOSAT analysis identified 1,071 potentially damaged structures within Codrington town in Barbuda. According to the pre-building footprints provided by Humanitarian Open Street Map, this represents 89% of potentially affected structures in Codrington town. The analysis could have been underestimated due to cloud cover. This is a preliminary analysis and has not yet been validated in the field.

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Cumulative Satellite detected waters extent overview between 13 & 26 March 20...

UN Operational Satellite Applications Programme (UNOSAT)

30+ Downloads

Updated April 10, 2019 | Dataset date: Apr 4, 2019

This dataset updates: Never

This map illustrates the cumulative satellite-detected surface waters in central provinces of Mozambique and particularly the Sofala province and its surroundings, as observed from the Sentinel-1 imagery acquired between 13 & 26 March 2019. Within the analysis extent. over Sofala and Manica provinces, a total of 170,000 km2 of surface imagery were analyzed and about 10,000 km2 of lands experienced floods within this period. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT. Satellite data : Sentinel-1 Imagery date: 13-14-19-20-26 March 2019 Resolution: 10 m Copyright: Copernicus 2019/ESA Source:ESA Boundary data: OCHA ROSEA Water body & waterway: COD Analysis : UNITAR-UNOSAT Production:UNITAR - UNOSAT

Tropical Cyclone IRMA-17 : Population Exposure estimates

UN Operational Satellite Applications Programme (UNOSAT)

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Updated September 9, 2017 | Dataset date: Sep 7, 2017

This dataset updates: Every week

Population exposure estimates based on tropical cyclone IRMA-17 path observed and predicted at 7 September 2017.

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Tropical Cyclone IRMA-17 : Path and Wind Speed Zones as of 7 September 2017

UN Operational Satellite Applications Programme (UNOSAT)

100+ Downloads

Updated September 8, 2017 | Dataset date: Sep 7, 2017

This dataset updates: Every day

This dataset illustrates the tropical cyclone IRMA-17 path with low, medium and strong wind impact zones observed and predicted at 7 September 2017. The tropical cyclone path and wind speed zones were derived from Joint Research Centre data (Warning 33 issued the 07 th September 2017 at 09:00 UTC). This is a preliminary analysis and has not yet been validated in the field.