Satellite detected water over Wajir county, Kenya

**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.

**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.

This map illustrates potentially affected population by flooding in the eastern sub counties of Kenya. The analysis was conducted by analyzing Sentinel-1 imagery acquired on the 4 May 2018. Within the analysis extent, more than 200,000 people are potentially affected by the floods. Magarini sub county in Kilifi County, is the one with more than 40,000 people living inside flood affected areas, followed by Dadaab, Wajir South, Garsen and Malindi sub counties. Note that some sub counties have been partially analyzed depending on the area covered by satellite imagery. It is likely that flood waters have been systematically underestimated along highly vegetated areas, along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.

This map illustrates satellite-detected flood water extent over Garsen, Magarini, Malindi and Lamu West Sub Counties, Kenya. The analysis was conducted analyzing Sentinel-1 image acquired on the 4 May 2018. Within the extent of the map more than 25,000 ha of land appear to be inundated and around 20,000 people are living inside this flood water extent. Within the map extent, around 13,000 ha of inundated land are located inside Garsen sub county, potentially affecting 5,000 people. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.

This map illustrates satellite-detected flood water extent along Tana River, Bura Sub County, Kenya. The analysis was conducted analyzing Sentinel-1 image acquired on the 4 May 2018. The analysis extent is focused on the river bed of Tana and the surrounding land between the primary road and the limit of the Tana River boundary, specifically were the population is concentrated. Within the analysis extent, more than 9,100 ha of land appear to be inundated and more than 9,800 people are living inside this flood water extent. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.

This map illustrates satellite-detected flood water extent over Dadaab & Lagdera Sub Counties, Garissa County, Kenya. The analysis was conducted analyzing Sentinel-1 image acquired on the 4 May 2018. Within the analysis extent, ~ 43,300 ha of land appear to be inundated and around 23,000 people are living inside this flood water extent. Within the analysis extent, around 23,300 ha of inundated land are located inside Dabaad Sub County, potentially affecting 18,200 people. Several refugee camps, specially the ones located inside Dadaab Sub County, seem to be affected by the floods, being Ifo 2 Refugee Camp the most affected one. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.