• 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.
    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.
    This dataset updates: Never
  • 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.
    10+ Downloads
    This dataset updates: Never
  • 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.
    This dataset updates: Never
  • 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.
    10+ Downloads
    This dataset updates: Never
  • 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.
    10+ Downloads
    This dataset updates: Never
  • 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.
    10+ Downloads
    This dataset updates: Never
  • 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.
    This dataset updates: Never
  • 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 dataset updates: Never
  • Updated 10 November 2019 | Dataset date: January 01, 2017-December 31, 2017
    1) Natural disaster events include avalanches, earthquakes, flooding, heavy rainfall & snowfall, and landslides & mudflows as recorded by OCHA field offices based on assessments in the field. 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) people, who may or may not require humanitarian assistance. 3) The information includes assessment figures from OCHA, ANDMA, IOM, Red Crescent Societies, national NGOs, international NGOs, and ERM. 4) The number of affected people and houses damaged or destroyed are based on the reports received. These figures may change as updates are received.
    1900+ Downloads
    This dataset updates: Every year
  • UNOSAT code: FL20191029TGO Cette carte illustre l'étendue des eaux de surface détectées par images satellite (Sentinel-1, image du 26 Octobre 2019) à dans la préfecture de Lacs et alentours, Région Maritime, Togo. Dans la zone analysée d'environs 250,000 ha, environ 8,000 personnes sont potentiellement exposées aux 4060 ha d'eaux de surface détectées le 26 Octobre 2019. Ceci est une image préliminaite qui n'a pas été validée sur le terrain. Merci d'envoyer vos commentaires à UNITAR-UNOSAT.
    10+ Downloads
    This dataset updates: Never
  • UNOSAT code: FL20191017CMR This map illustrates satellite-detected surface water in Mayo-Danay and Logone-et-Chari Department, Far-North Region of Cameroon as observed from Sentinel-2 imagery acquired on 16 October 2019. Within the analysed extent of about 2,500 km2, a total about 211 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.
    10+ Downloads
    This dataset updates: Never
  • UNOSAT code: FL20191017CMR This map illustrates satellite-detected surface water in Mayo-Danay and Logone-et-Chari Department, Far-North Region of Cameroon as observed from Sentinel-2 imagery acquired on 11 October 2019. Within the analysed extent of about 7,200 km2, a total about 1,500 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.
    10+ Downloads
    This dataset updates: Never
  • Updated 31 October 2019 | Dataset date: October 29, 2019-October 29, 2019
    South Sudan flood locations as per end of October 2019
    200+ Downloads
    This dataset updates: As needed
  • UNOSAT code: FL20190905LAO This map illustrates satellite-detected surface water in Champasak province of Lao PDR as observed from Sentinel-1 imagery acquired on 10 September 2019. Within the analysed extent of about 14,400 km2, a total about 53 km2 of land appear to be flooded as of 10 September 2019. 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 10 September 2019 may seriously underestimate presence of standing flood water in built up areas due to backscattering of the radar signal
    10+ Downloads
    This dataset updates: Never
  • UNOSAT code: FL20190905LAO This map illustrates satellite-detected surface water in Attapeu provinces of Lao PDR as observed from Sentinel-1 imagery acquired on 10 September 2019. Within the analysed extent of about 6,000 km2, a total about 14 km2 of land appear to be flooded as of 10 September 2019. 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 10 September 2019 may seriously underestimate presence of standing flood water in built up areas due to backscattering of the radar signal
    This dataset updates: Never
  • Updated 24 April 2019 | Dataset date: December 31, 2010-December 31, 2010
    This data is from Darthmouth Flood Observatory (DFO) Global Active Archive of Large Flood Events. It contains more than 4000 records of flooding events globally from 1985 - 2010.
    100+ Downloads
    This dataset updates: As needed
  • Updated 22 April 2019 | Dataset date: March 13, 2019-March 20, 2019
    This data illustrates the satellite detected surface waters in Manica, Sofala, and Tete Provinces in Mozambique, as observed from Sentinel-1 imagery acquired on 13, 14, 19 and 20 March 2019.
    200+ Downloads
    This dataset updates: As needed
  • Data produced under hydrological forecasting strategy where National Directorate of Water Resource Management (DNGRH) is one of the main actors of the Disaster Risk Reduction system, whose fundamental and prime task is the monitoring, forecasting and issuing early warnings about the risks ahead, resulting in the safeguarding of lives and property
    90+ Downloads
    This dataset updates: Live
  • This map illustrates the satellite detected surface waters in Manicaland Province, Zimbabwe, as observed from the Sentinel-1 data imagery acquired on 12 and 24 March 2019. Within the analysis extent, over Manicaland Province, 164,130 ha of surface waters were observed the 12 March 2019. and about of 406,600 ha of surface waters were observed the 24 March 2019. It represents an increase of 40 %. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT. Satellite data (pre-event) : Sentinel-1 Imagery date: 12 March 2019 Resolution: 10 m Copyright: Copernicus 2019 / ESA Source: ESA Satellite data (post-event) : Sentinel-1 Imagery date: 24 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
    30+ Downloads
    This dataset updates: Never
  • Updated 22 March 2019 | Dataset date: March 21, 2019-March 21, 2019
    This dataset is a compilation of various sources such as Copernicus, Sentinel-1 and Atmospheric and Environmental Research, A Verisk Business, & African Risk Capacity using several days to calculate the maximum flood extent for the whole event.
    300+ Downloads
    This dataset updates: As needed
  • Updated 6 February 2019 | Dataset date: January 31, 2019-January 31, 2019
    On 26 December 2018, exceptionally heavy rainfall caused severe flash flooding in Idleb and Aleppo governorates in north-west Syria. This area has a high proportion of displaced people and concentration of camps and sites, making it a region with a notably large vulnerable population. Hundreds of tents were reportedly swept away and concrete houses in camps collapsed. As a result of the flooding, thousands of people have been impacted
    400+ Downloads
    This dataset updates: As needed
  • This analysis illustrates a time series analysis of the evolution of satellite-detected surface waters in Sanamxay district, Attapeu province, based on satellite data recorded on 13, 25 and 29 July 2018.
    10+ Downloads
    This dataset updates: Live
  • This map illustrates the evolution of satellite-detected surface waters in Sanamxay district, Attapeu province, as observed from the Radarsat-2 radar image acquired on 24 July 2018 and compared with a Radsarsat-2 image acquired on 10 July 2018. As of 10 July 2018, flooded areas and saturated soils were already visible, due to the heavy rains that happened previously to the collapse of the dam. As well, the reservoir controlled by the dam was full of water. As of 24 July 2018, an additional surface of 5,826 ha of inundated areas were detected, representing an increase of the surface waters of 66%, due to the collapse of the dam. At this date, the reservoir that was controlled by the dam has decreased in its size. Several villages and surrounding agricultural fields seems to be inundated. The villages of Ban Hinlat, Ban Thaseangchan, Ban Mai and Ban Samong-tai seems to be the most affected ones. It is likely that flood waters have been systematically underestimated along highly vegetated areas, along the main riverbanks and within built-up urban areas because of the special characteristics of the used satellite data. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
    This dataset updates: Live
  • This map illustrates satellite-detected flood water extent in Somali Region, Ethiopia. The analysis was conducted by analysing a Sentinel-1 image acquired on the 7 May 2018. As observed from the satellite radar image, a total of 11,329 ha of land were inundated in the area of interest. By using WorldPop data, we estimate that at least 8,800 people are potentially affected or living close to the potentially flooded area. This corresponds to about 6% of the population living in the area of interest. 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 dataset updates: Live