UN Operational Satellite Applications Programme (UNOSAT)

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Data [880]
  • UNOSAT code: TC20201116NIC Este mapa ilustra las inundaciones detectadas por el satélite NOAA-VIIRS en Nicaragua entre el 13 y 17 de Noviembre. Dentro del área analizada de aproximadamente 95,000 km2, un total de aproximadamente 2,000 km2 de tierras parecen estar inundadas. Basado en los datos de población de Worldpop y la extensión de las aguas superficiales detectadas, alrededor de 100,000 personas están potencialmente expuestas o viven cerca de áreas inundadas. La población potencialmente expuesta se encuentra principalmente en el departamento de Chinandega con ~25,000 habitantes, en el departamento de Manague con ~16,000 habitantes, y em el departamento de Atlántico Norte con 10,000 habitantes. Se trata de un análisis preliminar que aún no ha sido validado en el terreno. Por favor envíe comentarios a UNITAR-UNOSAT.
    This dataset updates: Never
  • UNOSAT code: TC20201118SLV This map illustrates satellite-detected surface waters (cumulative) in El Salvador as detected by VIIRS-NOAA satellite between 13th & 17th November 2020. Within the analyzed area of about 20,000 km2, a total of about 440 km2 of lands appear to be flooded. Based on HRSL population data and the detected surface waters, about 44,000 people are potentially exposed or living close to flooded areas. The potentially exposed population is mainly located in the departments of Usulutan with ~9,000 people, La Union with ~8,500 people, and Santa Ana with ~7,500 people. 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: TC20201116HND This map illustrates satellite-detected surface waters (cumulative) aggregated using NOAA20-VIIRS in Honduras between 13 and 17 November 2020. Based on Worldpop spatial demographic data, about 140,000 people are exposed or living close to flooded areas. The potentially exposed population is mainly located in the department of Cortes with ~80,000 people, Choluteca with ~23,000 people, and Valle with ~14,000 people. 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: TC20201111PHL This map illustrates satellite-detected surface waters in Ilocos, Central Luzon and National Capital regions of Philippines as observed from a Sentinel-1 image acquired on 17 November 2020 at 05:46 local time. Within the analyzed area of about 16,500 km2, a total of about 300 km2 of lands appear to be flooded. The water extent appears to have receded of about 900 km2 since 13 November 2020. Based on Worldpop population data and the detected surface waters, about 200,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201111PHL This map illustrates satellite-detected mudslide extent in the Historical Cagsawa and surrounding in Daraga Municipality, Albay Province, Bicol Region, Philippines as observed on Pleiades image acquired on 13th of November 2020 at 10:47 Local time. About 80 buildings are identified as damaged and 30 as potentially damaged. Some roads were also identified as potentially damaged. 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: TC20201111PHL This map illustrates satellite-detected surface waters in Albay and Camarines Sur provinces of Philippines as observed from a Sentinel-1 image acquired on 13 November 2020 at 17:57 local time. Within the analyzed area of about 2,500 km2, a total of about 210 km2 of lands appear to be flooded. The water extent appears to have receded of about 20 km2 since 12 November 2020. Based on Worldpop population data and the detected surface waters, about 140,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201111PHL This map illustrates satellite-detected surface waters in CAR and Cagayan Valley regions, Philippines as observed from a Sentinel-1 image acquired on 13 November 2020 at 17:58 local time. Within the analyzed area of about 18,000 km2, a total of about 970 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 370,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201111PHL This map illustrates satellite-detected surface waters in Donsol and Pilar municipalities, Sorsogon province, Bicol region of Philippines as observed from a Sentinel-1 image acquired on 13 November 2020 at 05:30 local time. Within the analyzed area of about 180 km2, a total of about 3 km2 of lands appear to be flooded. The water extent appears to have receded of about 3 km2 since 12 November 2020. Based on Worldpop population data and the detected surface waters, about 1,200 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201111PHL This map illustrates satellite-detected surface waters in Daraga, Jovellar municipalities of Albay province & Donsol, Pilar municipalities of Sorsogon province of Philippines as observed from a Sentinel-1 image acquired on 12 November 2020 at 05:38 local time. Within the analyzed area of about 270 km2, a total of about 6 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 3,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201111PHL This map illustrates satellite-detected surface waters in Calauag and Lopez municipalities of Quezon province of Philippines as observed from a Sentinel-1 image acquired on 12 November 2020 at 05:38 local time. Within the analyzed area of about 260 km2, a total of about 20 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 8,300 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201111PHL This map illustrates satellite-detected surface waters in Camarines Norte province of Philippines as observed from a Sentinel-1 image acquired on 12 November 2020 at 05:38 local time. Within the analyzed area of about 650 km2, a total of about 60 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 32,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201111PHL This map illustrates satellite-detected surface waters in Albay and Camarines Sur provinces of Philippines as observed from a Sentinel-1 image acquired on 12 November 2020 at 05:38 local time. Within the analyzed area of about 5,000 km2, a total of about 250 km2 of lands appear to be flooded. The water extent appears to have increased of about 130 km2 since 6 November 2020. Based on Worldpop population data and the detected surface waters, about 170,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201103NIC This map illustrates satellite-detected surface waters in Puerto Cabezas, Prinzapolka and Launa de Perlas Municipality, Nicaragua as observed from Sentinel-1 image acquired on 08 November 2020. Within the analyzed area of about 12,000 km2, a total of about 1,200 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 7,500 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. Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areasand densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201028VNM This map illustrates satellite-detected surface waters in Thua Thien Hue Province of Viet Nam as observed from a Sentinel-1 image acquired on 10 November 2020 at 05:43 local time. Within the analyzed area of about 5,000 km2, a total of about 200 km2 of lands appear to be flooded. The water extent appears to have increased of about 50 km2 since 4 November 2020. Based on Worldpop population data and the detected surface waters, about 65,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201028VNM This map illustrates satellite-detected surface waters in Ha Tinh Province of Viet Nam as observed from a Sentinel-1 image acquired on 9 November 2020 at 05:51 local time. Within the analyzed area of about 6,000 km2, a total of about 40 km2 of lands appear to be flooded. The water extent appears to have receded of about 540 km2 since 3 November 2020. Based on Worldpop population data and the detected surface waters, about 17,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201028VNM This map illustrates satellite-detected surface waters in Nghe An Province of Viet Nam as observed from a Sentinel-1 image acquired on 9 November 2020 at 05:51 local time. Within the analyzed area of about 15,000 km2, a total of about 40 km2 of lands appear to be flooded. The water extent appears to have receded of about 360 km2 since 31 October 2020. Based on Worldpop population data and the detected surface waters, about 23,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201101PHL This map illustrates satellite-detected surface waters in Albay and Camarines Sur provinces of Philippines as observed from a Sentinel-1 image acquired on 6 November 2020 at 05:38 local time. Within the analyzed area of about 5,000 km2, a total of about 120 km2 of lands appear to be flooded. The water extent appears to have receded of about 120 km2 since 1 November 2020. Based on Worldpop population data and the detected surface waters, about 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. Important Note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201028VNM This map illustrates satellite-detected surface waters in Thua Thien Hue Province of Viet Nam as observed from a Sentinel-1 image acquired on 4 November 2020 at about 05:43 local time. Within the analyzed area of about 4,700 km2, a total of about 150 km2 of lands appear to be flooded. The water extent appears to have receded of about 120 km2 since 29 October 2020. Based on Worldpop population data and the detected surface waters, about 40,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201028VNM This map illustrates satellite-detected surface waters in Ha Tinh Province of Viet Nam as observed from a SAOCOM-1A image acquired on 3 November 2020 at about 16:52 local time. Within the analyzed area of about 5,800 km2, a total of about 580 km2 of lands appear to be flooded. The water extent appears to have increased of about 80 km2 since 30 October 2020. Based on Worldpop population data and the detected surface waters, about 260,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201101PHL This map illustrates floodwater depth in Nabua and Baao Municipalities, Camarines Sur Provinces & Bato and Libon, Albay Province, Bicol Region (Region V) of Philippines based on surface waters observed from a Sentinel-1 image acquired on 1st of November 2020 and digital elevation model data with the floodwater depth estimation tool (FwDET). 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201101PHL This map illustrates floodwater depth in Floodwater depth in Bula and Minalabac municipalities, Camarines Sur Provinces, Bicol Region (Region V) of Philippines based on surface waters observed from a Sentinel-1 image acquired on 1st of November 2020 and a digital elevation model data with the floodwater depth estimation tool (FwDET). 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201101PHL This map illustrates floodwater depth in Camarines Sur provinces of Philippines based on surface waters observed from a Sentinel-1 image acquired on 1st of November 2020 and a digital elevation model data with the floodwater depth estimation tool(FwDET). 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201101PHL This map illustrates satellite-detected surface waters in Albay and Camarines Sur provinces Philippines as observed from a Sentinel-1 image acquired on 1 November 2020 at about 17:57 local time. Within the analyzed area of about 5,000 km2, a total of about 240 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 160,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201028VNM This map illustrates satellite-detected surface waters in Nghe An Province of Viet Nam as observed from a Radarsat Constellation 1 image acquired on 31 October 2020 at about 17:56 local time. Within the analyzed area of about 8,000 km2, a total of about 400 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 300,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never
  • UNOSAT code: TC20201028VNM This map illustrates satellite-detected surface waters in Ha Tinh Province of Viet Nam as observed from a Sentinel-1 image acquired on 30 October 2020 at about 18:05 local time. Within the analyzed area of about 5,700 km2, a total of about 500 km2 of lands appear to be flooded. The water extent appears to have increased of about 450 km2 since 24 October 2020. Based on Worldpop population data and the detected surface waters, about 215,000 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 radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
    This dataset updates: Never