Satellite-detected water extents, as of 10 December 2019, over Epéna District, Likouala Department, Republic of Congo
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✦ Suggested by OrionAI**UNOSAT code: FL20211208COG** This map illustrates cumulative satellite-detected water using VIIRS in Republic of Congo between 03 to 07 December 2021 compared with the period between 26 to 30 November 2021. Within the cloud free analyzed areas of about 335,000 km2, a total of about 3,500 km2 of lands appear to be affected with flood waters. Water extent appears to have decreased of about 300 km2 since the period between 26 to 30 November 2021. Based on HRSL population data and the detected surface waters, the potentially exposed population of ~190,000 people is mainly located in department of Likouala with ~ 94,000 people, Brazzaville with ~ 70,000 people and Plateaux with ~10,000 people. 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).
**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.
**UNOSAT code: FL20200305ZMB** This map illustrates satellite-detected waters in Chitambo, Lunga, Samfya, Lavushimanda and Chilubi District; Central, Luapula, Muchinga and Northern Province of Zambia as observed from Sentinel-1 imagery acquired on 4 March 2020. Within the analysed area of 10,000 km2, a total of about 705 km2 of land appear to be flooded. Based on Worldpop population data and the detected surface waters, about 7,000 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 UNITARUNOSAT.
**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.
**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.
**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.
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