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  • 30+ Downloads
    Updated June 5, 2020 | Dataset date: Jan 1, 2013-Dec 31, 2013
    This dataset updates: As needed
    Flood extent in 2013 Original dataset title: Cambodia: Flood Extent in 2013
  • Updated June 3, 2020 | Dataset date: May 18, 2020
    This dataset updates: Never
    UNOSAT code: FL20200428SOM This map illustrates the flood-affected sectors of Beletweyne town in Hiraan Region, Somalia as detected from the analysis of an ICEYE satellite image acquired on 16 May 2020. Within the analysed area of about 30 km2, a total of 8 km2 of land appear to be flooded in BeletWeyne town and surroundings. This is a preliminary analysis and has not been validated in the field yet. Please send ground feedback to UNITAR-UNOSAT.
  • UNOSAT code: FL20200428SOM This map illustrates the flood-affected sectors of Beletweyne town in Hiiran Region, Somalia as detected from the analysis of a satellite Worldview-2 images acquired on the 13 May 2020. Belet Weyne is heavily affected by floods and about 50% of the town and its vicinity is largely inundated; the sectors called Kutimbo, Radar, and Lamagalay Regional Military Base appear to be the most affected by floodwaters as of 13 May 2020. More than 110 IDP sites are located inside of the town and 25% of them are located within the completely flooded areas. This is a preliminary analysis and has not been validated in the field yet. Please send ground feedback to UNITAR-UNOSAT.
  • UNOSAT code: FL20200324IRN This map illustrates satellite-detected water surface in Konarak County, Sistan and Baluchestan Province, Islamic Republic of Iran, as observed from Sentinel-2 imagery acquired on 23 March 2020. Within the analysed area of about 1,100 km2, a total of 56 km2 of land appear to be flooded in Konarak County. Based on Worldpop population data and the detected surface waters, about 3,700 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 UNITAR - UNOSAT.
  • UNOSAT code: FL20200305ZMB Status: Floods detected in Lunga district Further actions(s): monitoring over AOI completed Preliminary observations, impact and severity: AOI 1: No satellite-detected waters in Chaba city or its vicinity as of 09 March 2020 AOI 2: Mofu city appears to have no evidences of satellite-detected waters as of 09 March 2020 AOI 3: No satellite-detected waters in Samfya city as of 10 March 2020 AOI 4: Satellite-detected waters northern and eastern part of Ncheta island affecting the agricultural fields nearby as of 07 March 2020
  • UNOSAT code: FL20200305ZMB This map illustrates satellite-detected water extents in the eastern part of Ncheta Island, Lunga District, Luapula Province, Republic of Zambia as observed form Pleiades imagery acquired on 7 March 2020. Within the analyzed area several hectares of land appear to be flooded and 29 structures out of 300 are likely flooded within this area. 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 water extents in the northern part of Ncheta Island, Lunga District, Luapula Province, Republic of Zambia as observed form Pleiades imagery acquired on 7 March 2020. Within the analyzed area, a total of about 100ha of land appears to be flooded and 115 structures are completely flooded which represents about 20% of total structures in this zone. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • Updated June 3, 2020 | Dataset date: Mar 6, 2020
    This dataset updates: Never
    UNOSAT code: FL20200305ZMB This map illustrates satellite-detected water via VIIRS-NOAA over Central, Luapula, Muchinga and Northern Province in Republic of Zambia between the 1st and the 05th March 2020. Within the analysed extent not covered by clouds, a total of about 10,000 km2 appear to be flooded. Based on Worldpop population about 28,000 people were potentially exposed or living close to flooded areas in Lunga district. This is a preliminary analysis and has not yet been validated in the field. Please send ground fedback 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: FL20200128MDG This maps illustrates satellite-detected water via VIIRS-NOAA on the center and the northern part of the Republic of Madagascar between the 09 and the 13 February 2020. Within the analysed extent not covered by clouds, a total of about 9,116 km2 appear to be flooded, of which about 2,098 km2, 1,366 km2 and 834 km2 in Boeny, Melaky and Alaotra-Mangoro region respectively. Based on Worldpop population data and the detected surface waters, about 1,300,000 people are potentially exposed or living close to flooded areas. In Boeny, Melaky and Alaotra-Mangoro regions, respectively 170,000; 35,000 and 80,000 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 UNITAR - UNOSAT.
  • UNOSAT code: FL20200128MDG This maps illustrates satellite-detected water via VIIRS-NOAA on the center and the northern part of the Republic of Madagascar between the 29 January and the 02 February 2020. Within the analysed extent not covered by clouds, a total of about 9,718 km2 appear to be flooded, of which about 2,309 km2 and 851 km2 in Boeny and Alaotra-Mangoro region respectively. Based on Worldpop population data and the detected surface waters, about 1,400,000 people are potentially exposed or living close to flooded areas. In Boeny and Alaotra-Mangoro regions, respectively 144,000 and 70,000 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 UNITAR - UNOSAT.
  • UNOSAT code: FL20200128MDG Cette carte illustre les eaux de surface détectées via le capteur VIIRS-NOAA sur le centre et le nord de la république de Madagascar entre le 23 janvier et le 27 Janvier 2020. Dans la zone analysée non couverte par les nuages, environ 850,000 personnes sont exposées ou vivent à proximité des zones inondées qui couvrent 9,475 km2. Les plaines du nord-ouest situées dans les régions de Boeny, Sofia et Alaotra Mangoro semblent être particulièrement impactées par les inondations en cours. Ceci est une analyse préliminaire et n'a pas encore été validée sur le terrain. Ne pas hésiter à envoyer vos commentaires à UNITAR-UNOSAT.
  • UNOSAT code: FL20200117IRN This map illustrates satellite-detected water surface in Chabahar and Konarak County, Sistan Va Baluchestan Province, Islamic Republic of Iran as observed from Sentinel-2 imagery acquired on 18 January 2020. Within the analysed extent of about 730 km2, a total about 63 km2 of land appear to be flooded. Based on Worldpop population data and the detected surface waters, about 5,900 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 UNITAR - UNOSAT.
  • UNOSAT code: FL20200117IRN This map illustrates satellite-detected waters in Dalgan County, Sistan and Baluchestan Province, Islamic Republic of Iran, as observed from Sentinel-2 imagery acquired on 16 January 2020. Within the analysed area of 2,130 km2, a total of 647 km2 of land appear to be flooded in Dalgan County. Based on Worldpop population data and the detected surface waters, about 2,500 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 UNITAR -UNOSAT.
  • UNOSAT code: FL20200117IRN This map illustrates satellite-detected water surface in Konarak District in Sistan Va Baluchestan Province of Iran as observed from Sentinel-2 imagery acquired on 18 January 2020. Within the analysed extent of about 590 km2, a total about 55 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: FL20200101IDN This map illustrates satellite-detected surface water in Banten, Dki Jakarta and Jawa Barat Province of Indonesia as observed from Sentinel-1 imagery acquired on the 2 January 2020. Approximately 258 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 2 January 2020 may seriously underestimate presence of standing flood water in built up areas due to backscattering properties of the radar signal.
  • UNOSAT code: FL20191217MYS This map illustrates satellite-detected surface water in Kluang and Mersing District, Johor State and Rompin District, Pahang State of Malaysia as observed from Sentinel-1 imagery acquired on 15 December 2019. Within the analysed extent of about 3,500 km2, a total about 23 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 15 December 2019 may seriously underestimate the presence of standing floodwater in built-up areas due to backscattering of the radar signal
  • UNOSAT code: FL20191217MYS This map illustrates satellite-detected surface water in Kota Tinggi and Mersing district, Johor state of Malaysia as observed from Sentinel-1 imagery acquired on 15 December 2019. Within the analysed extent of about 1,300 km2, a total about 8 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 15 December 2019 may seriously underestimate the presence of standing floodwater in built-up areas due to backscattering of the radar signal
  • UNOSAT code: FL20191205COG This map illustrates satellite-detected waters in Epéna District, Likouala Department in Republic of Congo, as observed from Sentinel-1 imagery acquired on 10 December 2019. Within the analysed area of about 30,500 km2, 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 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 May 19, 2020 | Dataset date: Jun 1, 2020
    This dataset updates: As needed
    No abstract provided Original dataset title: Somalia - Flood affected roads, 01 June 2020
  • Updated April 17, 2020 | Dataset date: Jan 1, 2017-Dec 31, 2017
    This dataset updates: As needed
    This layer contains information about the combined natural shock (floods, droughts and cyclones) hazard estimated during the Integrated Context Analysis (ICA) run in Mozambique in 2017. Data source: Fewsnet 1975-2012, DRFI 2012, INGC, HQ VAM Analysis of CHIRPS Rainfall Estimates (RFE) 1981-2015, Fewsnet 1930-2000. Original dataset title: ICA Mozambique, 2017 - Natural Shocks Hazard
  • 20+ Downloads
    Updated April 17, 2020 | Dataset date: Jan 1, 1975-Dec 31, 2012
    This dataset updates: As needed
    This layer contains information about the flood hazard estimated during the Integrated Context Analysis (ICA) run in Mozambique in 2017. Data source: Fewsnet 1975-2012, Disaster Risk Financing and Insurance (DRFI), 2012. The indicators used for the analysis were the percentage of flood extent and a qualitative classification of the district at high or very high flood risk. It should be noted that the analysis did not consider information about the flood frequency and that, in the last 5 years, flood patterns are changing and affecting the northern part of the country, which is not registering extreme flood events anymore. Original dataset title: ICA Mozambique, 2017 - Flood Hazard, 1975-2012
  • Updated April 17, 2020 | Dataset date: Jan 1, 2013-Dec 31, 2013
    This dataset updates: As needed
    This layer contains information about the flood risk - by second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Niger between 2017 and 2018. The analysis is the result of a joint effort between the Regional Bureau in Dakar (RBD) and the HQ GIS Unit and Programme division. Data sources: UNEP/UNISDR GAR 2013. The main indicators used for the analysis were the percentage of district surface at flood risk and the maximum expected frequency of flood events with a 100-year return period. Cette couche contient informations regard le risque d’inondations – par unité administrative de deuxième niveau – estimé pendant l’Analyse Integrée du Contexte (AIC) executée en Niger entre 2017 et 2018. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données : UNEP/UNISDR GAR, 2013. Les indicateurs principaux utilisées pour l’analyse étaient la pourcentage de surface a risuqe d’inondation et l’attente maximale attendue des inondations. Original dataset title: ICA Niger, 2018 - Flood Risk, 2013
  • Updated April 17, 2020 | Dataset date: Jan 1, 2018-Dec 31, 2018
    This dataset updates: As needed
    This layer contains information about the final categorization resulting from the Integrated Context Analysis (ICA) performed in Niger between 2017 and 2018, showing the areas of convergence of high levels of food insecurity recurrence and major propensity to natural shocks (floods and droughts). The analysis was a joint effort between the Regional Bureau in Dakar (RBD) and HQ GIS unit and Programme division. Cette couche contient informations regard la classification finale résultant de l'Analyse Integrée de Contexte (AIC) executée en Niger entre 2017 et 2018, montrant les zones de convergence de niveaux elevés de récurrence d'insécurité alimentaire et propension aux chocs naturels (inondations et sècheresse). L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Original dataset title: ICA Niger, 2018 - ICA Categories & Areas
  • Updated April 17, 2020 | Dataset date: Jan 1, 2018-Dec 31, 2018
    This dataset updates: As needed
    This layer contains information about the natural shock risk (floods and droughts) estimated during the Integrated Context Analysis (ICA) performed in Niger between 2017 and 2018. The analysis was a joint effort between the Regional Bureau in Dakar (RBD), the HQ GIS Unit and Programme division. Data sources: UNEP/UNISDR GAR 2013, HQ VAM Analysis of CHIRPS Rainfall Estimates (RFE) 1981-2015. Cette couche contient informations regard le risque des chocs naturels (inondations et sècheresse) estimé pendant l’Analyse Integrée du Contexte (AIC) executée en Niger entre 2017 et 2018. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données : UNEP/UNISDR GAR 2013, HQ VAM Analyse des données CHIRPS d’estimation des precipitations 1981-2015. Original dataset title: ICA Niger, 2018 - Natural Shock Risk