Updated
27 January 2020
| Dataset date: January 01, 2019-December 31, 2019
This layer contains information about the final classification deriving from the Integrated Context Analysis (ICA) run in Afghanistan in 2019, showing the areas of convergence between recurrence of total food insecurity and propensity to natural shocks (floods, landslides and drought).
Original dataset title: ICA Afghanistan, 2019 - ICA Categories & Areas
Updated
9 January 2020
| Dataset date: December 10, 2019-December 10, 2019
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.
Updated
18 December 2019
| Dataset date: November 13, 2019-November 13, 2019
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.
Updated
18 December 2019
| Dataset date: November 13, 2019-November 13, 2019
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.
Updated
18 December 2019
| Dataset date: November 13, 2019-November 13, 2019
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.
Updated
6 December 2019
| Dataset date: October 31, 2019-October 31, 2019
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.
Updated
6 December 2019
| Dataset date: October 25, 2019-October 25, 2019
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
Updated
22 November 2019
| Dataset date: November 22, 2019-November 22, 2019
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.
Updated
22 November 2019
| Dataset date: November 21, 2019-November 21, 2019
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.
Updated
22 November 2019
| Dataset date: November 20, 2019-November 20, 2019
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.
Updated
22 November 2019
| Dataset date: November 20, 2019-November 20, 2019
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.
Updated
22 November 2019
| Dataset date: November 20, 2019-November 20, 2019
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.
Updated
22 November 2019
| Dataset date: November 20, 2019-November 20, 2019
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.
Updated
22 November 2019
| Dataset date: November 19, 2019-November 19, 2019
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.
Updated
22 November 2019
| Dataset date: November 19, 2019-November 19, 2019
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.
Updated
22 November 2019
| Dataset date: November 18, 2019-November 18, 2019
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.
Updated
14 November 2019
| Dataset date: November 13, 2019-November 13, 2019
UNOSAT code: FL20191030SOM This map illustrates the extent of surface waters detected over Hiraan, Middle Shabelle and Lower Shabelle Region in Somalia as detect by VIIRS-NOAA satellite between 2 & 6 November 2019. In the analysed area, a total of about 830 km2 are likely flooded and about 74,000 people might be exposed by taking into account WorldPop population estimates. About 10 km of the roads seem to be affected. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
Updated
14 November 2019
| Dataset date: November 13, 2019-November 13, 2019
UNOSAT code: FL20191023SSD This map illustrates the 5-day cumulative, day-time surface water extent detected over Luakpiny/Nasir, Pibor and neighbouring counties in South Sudan. The extent was derived from VIIRS-NOAA satellite imagery between 2 and 6 November 2019 and includes all pixels with 0-100% open water.
In the two counties of interest, about 9% of the population in Luakpiny/Nasir and 7% in Pibor may be affected by taking into account WorldPop population estimates. This is a preliminary analysis that has not yet been validated in the field. Please send any fieldbased comments to UNITAR-UNOSAT.
Updated
14 November 2019
| Dataset date: November 05, 2019-November 05, 2019
UNOSAT code: FL20191030SOM This map illustrates the satellite-detected flood water extent and IDP distribution within the town of Belet Weyne in Belet Weyne District, Hiiran Region, Somalia. The analysis was conducted by analyzing WorldView-1 images acquired on the 1 November 2019. As observed from the satellite image, the town of Belet Weyne is heavily affected by floods. Around 60% of the vicinity of the town is completely inundated; the districts of Hawa tako, Kutimbo, and the Lamagalay Regional Millitary Base completely submerged in water. More than 110 IDP sites are located inside of the town and 40% of them are located within 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
13 November 2019
| Dataset date: November 05, 2019-November 05, 2019
UNOSAT code: FL20191030SOM This map illustrates the extent of surface waters detected over Jowhar District, Middle Shabelle Region located in Somalia, as detect by VIIRS-NOAA satellite between 30 October & 3 November 2019. In the analysed area, a total of about 700 km2 are likely flooded and about 70,000 people may be affected, based on WorldPop population estimates. The 10 km of roads seem to be affected. This is a preliminary analysis and has not been validated in the field yet. Please send ground feedback to UNITAR-UNOSAT.
Updated
13 November 2019
| Dataset date: November 04, 2019-November 04, 2019
UNOSAT code: FL20191031KEN This map illustrates satellite-detected surface water in Garsen Sub County, Tana River County of Kenya as observed from Sentinel-2 imagery acquired on 28 October 2019. Within the analysed extent of about 150 km2, a total about 12 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.
Updated
13 November 2019
| Dataset date: November 04, 2019-November 04, 2019
UNOSAT code: FL20191031KEN This map illustrates satellite-detected surface water in Wajir East Sub County, Wajir County of Kenya as observed from Sentinel-2 imagery acquired on 2 November 2019. Within the analysed extent of about 200 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.
Updated
13 November 2019
| Dataset date: November 02, 2019-November 02, 2019
UNOSAT code: FL20191031KEN This map illustrates satellite-detected surface water in Wajir East Sub County, Wajir County of Kenya as observed from Sentinel-2 imagery acquired on 28 October 2019. Within the analysed extent of about 450 km2, a total of about 25 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.
