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  • 50+ Downloads
    Updated 2 September 2022 | Dataset date: August 31, 2022-August 31, 2022
    This dataset updates: Never
    UNOSAT code: FL20220808PAK This map illustrates cumulative satellite-detected water using VIIRS in Pakistan between 01 to 29 August 2022. Within the analyzed area of about 793,000 km2, a total of about 75,000 km2 of lands appear to be affected with flood waters amongst which 48,530 km2 are flooded croplands. Based on Worldpop population data and the maximum flood water coverage, at least 22 million people were potentially exposed or living close to flooded areas in August 2022. 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).
  • Updated 1 September 2022 | Dataset date: August 26, 2022-August 26, 2022
    This dataset updates: Never
    UNOSAT code: FL20220808PAK This map illustrates cumulative satellite-detected water using VIIRS in Pakistan between 03 to 23 August 2022. Within the cloud free analyzed areas of about 780,000 km2, a total of about 55,000 km2 of lands appear to be affected with flood waters. Based on Worldpop population data and the maximum flood water coverage, ~19,368,000 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 the United Nations Satellite Centre (UNOSAT).
  • Updated 1 September 2022 | Dataset date: August 24, 2022-August 24, 2022
    This dataset updates: Never
    UNOSAT code: FL20220728NER This map illustrates satellite-detected surface waters in Tillabéri Region, Niger as observed from a Sentinel-2 image acquired on 19 August 2022 at 11:37 local time. Within the analyzed area of about 26,000 km2, about 377 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, about 33,500 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 United Nations Satellite Centre (UNOSAT).
  • Updated 1 September 2022 | Dataset date: August 30, 2022-August 30, 2022
    This dataset updates: Never
    UNOSAT code: FL20220816SDN This map illustrates satellite-detected surface waters in Dongola, Algolid & Alborgag districts, Northern State as observed from a Sentinel-2 image acquired on 26 August 2022 at 10:45 local time. Within the analyzed area of about 11,900 km2, about 82 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, about 3,500 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 United Nations Satellite Centre (UNOSAT).
  • Updated 1 September 2022 | Dataset date: August 18, 2022-August 18, 2022
    This dataset updates: Never
    UNOSAT code: FL20220808PAK This map illustrates satellite-detected surface waters in Sindh province, Pakistan as observed from a Sentinel-1 image acquired on 15 August 2022 at 18:36 local time. Within the analyzed area of about 30,000 km2, about 1,550 km2 of lands appear to be flooded. Water extent appears to have decreased of about 325 km2 since the 06 August 2022. within the analyzed area. Based on Worldpop population data and the detected surface waters in the analyzed area, about 410,000 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 United Nations Satellite Centre (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.
  • Updated 1 September 2022 | Dataset date: August 16, 2022-August 16, 2022
    This dataset updates: Never
    UNOSAT code: FL20220728NER This map illustrates satellite-detected surface waters in Dosse, Niamey and Tillabéri Regions, Niger as observed from a Sentinel-2 image acquired on 11 August 2022 at 11:27 local time. Within the analyzed area of about 45,000 km2, about 330 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, about 75,000 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 United Nations Satellite Centre (UNOSAT).
  • Updated 1 September 2022 | Dataset date: August 24, 2022-August 24, 2022
    This dataset updates: Never
    UNOSAT code: FL20220816SDN This map illustrates satellite-detected surface waters in Barbar district, River Nile State as observed from a Sentinel-2 image acquired on 20 August 2022 at 10:25 local time. Within the analyzed area of about 780 km2, about 43 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, about 7,800 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 United Nations Satellite Centre (UNOSAT).
  • Updated 1 September 2022 | Dataset date: August 10, 2022-August 10, 2022
    This dataset updates: Never
    UNOSAT code: FL20220808PAK This map illustrates satellite-detected surface waters in Satellite detected water in Sindh province, Pakistan as observed from a Sentinel-1 image acquired on 06 August 2022 at 06:25 local time. Within the analyzed area of about 59,000 km2, about 2,700 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, about 750,000 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 United Nations Satellite Centre (UNOSAT).
  • Updated 1 September 2022 | Dataset date: August 12, 2022-August 12, 2022
    This dataset updates: Never
    UNOSAT code: FL20220803UGA This map illustrates satellite-detected landslides in Budwale, Lwasso, Wanale, Bungokho Mutoto sub-countries and Wanale Division and Northern Division, Mbale district, eastern region, Uganda as observed from a Sentinel-2 image aquired on 9 August 2022. Within the analyzed area, 27ha landslide scars are observed. Based on Wordlpop population data about 200,700 people live inside the analyzed area. 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).
  • Updated 1 September 2022 | Dataset date: August 11, 2022-August 11, 2022
    This dataset updates: Never
    UNOSAT code: FL20220801GMB This map illustrates satellite-detected surface waters in Satellite detected water in Banjul, Kanifing, and Brikama Regions, Gambia as observed from a Sentinel-2 image acquired on 10 Aug 2021 at 18:18 local time. Within the analyzed cloud free zones of about 960 km2, about 26 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the districts of Kanifing with ~ 7,300 people, Kombo North/St Marie with ~ 7,000 and Kombo South with ~ 4,100 people This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
  • Updated 1 September 2022 | Dataset date: August 08, 2022-August 08, 2022
    This dataset updates: Never
    UNOSAT code: FL20220424SSD This map illustrates cumulative satellite-detected water using VIIRS in South Sudan between 03 to 07 August 2022 compared with the period from 19 to 23 July 2022. Within the cloud free analyzed areas of about 605,000 km2, a total of about 22,000 km2 of lands appear to be affected with flood waters. Water extent appears to have increased of about 7,000 km2 since the period between 19 to 23 July 2022. Based on Worldpop population data and the maximal flood water coverage, ~565,000 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 the United Nations Satellite Centre (UNOSAT).
  • Updated 1 September 2022 | Dataset date: August 08, 2022-August 08, 2022
    This dataset updates: Never
    UNOSAT code: FL20220801GMB This map illustrates satellite-detected surface waters in Kombo North/St Marie District, Brikama Region, Gambia as observed from a Sentinel-2 image acquired on 5 Aug 2022 at 11:33 local time. Within the analyzed area of about 2,340 hectares, about 22 hectares of lands appear to be flooded and about 3 km of road appear to be likely affected by the flood waters. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
  • Updated 2 August 2022 | Dataset date: July 25, 2022-July 25, 2022
    This dataset updates: Never
    UNOSAT code: FL20220721NGA This map illustrates satellite-detected surface waters in Gujba LGA, Yobe state, Nigeria as observed from a Sentinel-1 image acquired on 18 Jul 2022 at 18:22 local time. Within the analyzed area of about 1,040 km2, about 22 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 1,400 people are potentially exposed or living within/close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (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.
  • Updated 2 August 2022 | Dataset date: June 28, 2022-June 28, 2022
    This dataset updates: Never
    UNOSAT code: FL20220627GEO This map illustrates satellite-detected surface waters in Samegrelo-Zemo Svaneti and Imereti Regions, Georgia as observed from a Sentinel-1 image acquired on 23 Jun 2022 at 19:11 local time. Within the analyzed area of about 2,500 km2, about 50 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 1,600 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 United Nations Satellite Centre (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.
  • 10+ Downloads
    Updated 28 June 2022 | Dataset date: June 23, 2022-June 23, 2022
    This dataset updates: Never
    UNOSAT code: FL20220525BGD This map illustrates satellite-detected surface waters in Rangpur Division, Bangladesh as observed from a Sentinel-1 images acquired on 21 Jun. 2022 at 18:05 local time and using an automated analysis with machine learning method. Within the analyzed area of about 12,400 km2, about 1,200 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Kurigram with ~537,000 people, and Gaibandha with ~355,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (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.
  • Updated 28 June 2022 | Dataset date: June 22, 2022-June 22, 2022
    This dataset updates: Never
    UNOSAT code: FL20220525BGD This map illustrates satellite-detected surface waters in Rajshahi, Rangur, Mymensingh, Dhaka and Khulna Divisions, Bangladesh as observed from a Sentinel-1 images acquired on 21 Jun. 2022 at 18:05 local time and using an automated analysis with machine learning method. Within the analyzed area of about 20,400 km2, about 2,950 km2 of lands appear to be flooded. Water extent appears to have increased of about 2,360 km2 since 9 Jun. 2022. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the division of Rajshahi with ~1,335,000 people, Dhaka with 674,000 people,and Mymensingh with ~ 640,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (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.
  • Updated 28 June 2022 | Dataset date: June 21, 2022-June 21, 2022
    This dataset updates: Never
    UNOSAT code: FL20220525BGD This map illustrates satellite-detected surface waters and impact in Sylhet and Sunamganj Districts, Sylhet Division, Bangladesh as observed from a RCM-1 image acquired on 18 Jun 2022 at 17:54 local time. Within the analyzed area of about 1,325 km2, about 840 km2 of lands appear to be flooded. In this area, about 140 km of roads and 1 km of railway appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters, about 839,000 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 United Nations Satellite Centre (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.
  • Updated 28 June 2022 | Dataset date: June 21, 2022-June 21, 2022
    This dataset updates: Never
    UNOSAT code: FL20220525BGD This map illustrates satellite-detected surface waters in Sylhet, Mymensingh, Dhaka, and Chattogram Divisions, Bangladesh observed from a RCM-1 images acquired on 19 Jun. 2022 at 18:02 local time. Within the analyzed area of about 22,300 km2, about 9,500 km2 of lands appear to be flooded. In this area, about 7,860 km2 of croplands and 1,340 km2 of herbaceous wetland appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters, about 7,334,000 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 United Nations Satellite Centre (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.
  • Updated 28 June 2022 | Dataset date: June 20, 2022-June 20, 2022
    This dataset updates: Never
    UNOSAT code: FL20220525BGD This map illustrates satellite-detected surface waters in Sylhet, Mymensingh, Dhaka, and Chattogram Divisions, Bangladesh as observed from a RCM-1 images acquired on 19 Jun. 2022 at 18:02 local time. Within the analyzed area of about 22,300 km2, about 9,500 km2 of lands appear to be flooded. Water extent appears to have increased of about 2,150 km2 since the period between 25 to 28 May 2022. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Sunamganj with ~1,822,000 people and Sylhet with ~1,550,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (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.
  • Updated 28 June 2022 | Dataset date: June 02, 2022-June 02, 2022
    This dataset updates: Never
    UNOSAT code: FL20220424SSD Dashboard showing VIIRS cumulative data. This dashboard shows statistics of the potentially exposed population and the maximum flood water extent by district over South Sudan
  • Updated 28 June 2022 | Dataset date: May 30, 2022-May 30, 2022
    This dataset updates: Never
    UNOSAT code: FL20220526GUY This map illustrates cumulative satellite-detected water using VIIRS in Guyana between 25 to 29 May 2022 compared with the period from 20 to 24 May 2022. Within the cloud free analyzed areas of about 205,000 km2, a total of about 3,900 km2 of lands appear to be affected with flood waters. Water extent appears to have increased of about 1,200 km2 since the period between 20 to 24 may 2022. Based on Worldpop population data and the maximal flood water coverage, ~22,000 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 the United Nations Satellite Centre (UNOSAT).
  • Updated 28 June 2022 | Dataset date: May 20, 2022-May 20, 2022
    This dataset updates: Never
    UNOSAT code: FL20220424SSD This map illustrates cumulative satellite-detected water using VIIRS in South Sudan between 20 to 24 April 2022 compared with the period from 14 to 18 May 2022. Within the cloud free analyzed areas of about 630,000 km2, a total of about 9,000 km2 of lands appear to be affected with flood waters. Water extent appears to have decreased of about 800 km2 since the period between 20 to 24 April 2022. Based on Worldpop population data and the maximal flood water coverage, ~220,000 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 the United Nations Satellite Centre (UNOSAT).
  • Updated 28 June 2022 | Dataset date: May 11, 2022-May 11, 2022
    This dataset updates: Never
    UNOSAT code: FL20220418ZAF Landslide impact analysis in eThekwini, Metropolitan Municipality, This map illustrates satellite-detected water and landslides/mudflow in eThekwini, Metropolitan Municipality, eThekwini District, KwaZulu-Natal Province, South Africa as observed from a WorldView-3 image acquired on 20 April 2022. Within the analyzed area, 323 ha of landslide scars were observed. Based on Worldpop population data, about 570,000 people live inside the analyzed area. Within the analysis extent, UNITAR-UNOSAT identified 164 damaged/affeted structures and 79 potentially damaged structures. 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).
  • Updated 28 June 2022 | Dataset date: May 31, 2022-May 31, 2022
    This dataset updates: Never
    UNOSAT code: FL20220525BGD This map illustrates satellite-detected surface waters in Sylhet, Mymensingh, Dhaka, and Chattogram Divisions, Bangladesh as observed from a Sentinel-1 images acquired on 28 May 2022 at 18:04 local time and using an automated analysis with machine learning method. Within the analyzed area of about 12,000 km2, about 4,500 km2 of lands appear to be flooded. In this area, about 3,400 km2 of croplands and 1,000 km2 of herbaceous wetland appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Sunamganj with ~935,000 people and Kishoreganj with ~779,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (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.
  • Updated 28 June 2022 | Dataset date: May 30, 2022-May 30, 2022
    This dataset updates: Never
    UNOSAT code: FL20220525BGD This map illustrates satellite-detected surface waters in Sylhet, Mymensingh, Dhaka, and Chattogram Divisions, Bangladesh as observed from a Sentinel-1 images acquired on 26 May 2022 at 05:47 local time and using an automated analysis with machine learning method. Within the analyzed area of about 16,000 km2, about 6,800 km2 of lands appear to be flooded. In this area, about 5,400 km2 of croplands and 1,270 km2 of herbaceous wetland appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in the district of Sunamganj with ~1,700,000 people and Sylhet with ~1,400,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (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.