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  • 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.
  • 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.
  • Updated 28 June 2022 | Dataset date: June 01, 2022-June 01, 2022
    This dataset updates: Never
    UNOSAT code: FL20220525BGD This map illustrates satellite-detected surface waters in Sylhet and Sunamganj Districts, Sylhet Division, Bangladesh as observed from a Chaohu-1 image acquired on 25 May 2022 at 22:23 local time. Within the analyzed area of about 730 km2, about 420 km2 of lands appear to be flooded. In this area, about 300 km2 of croplands and 70 km2 of herbaceous wetland appear to be likely affected by the flood waters. Based on Worldpop population data and the detected surface waters, about 307,000 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: May 30, 2022-May 30, 2022
    This dataset updates: Never
    UNOSAT code: FL20220526GUY This map illustrates satellite-detected surface waters along the Rupununi river in Upper Takutu-Upper Essequibo Region of Guyana as observed from a Sentinel-1 image acquired on 26 May 2022 at 09:45 UTC. Within the analyzed area of about 14,000 km2, a total of about 320 km2 of lands were observed as flooded. 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). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas
  • Updated 28 June 2022 | Dataset date: May 06, 2022-May 06, 2022
    This dataset updates: Never
    UNOSAT code: FL20220418ZAF This map illustrates satellite-detected landslides/mudflow in eThekwini, Metropolitan Municipality, eThekwini District, KwaZulu-Natal Province, South Africa as observed from a Kompsat-3 image acquired on 21 April 2022. Within the analyzed area, 270 ha of landslide scars were observed. Based on Worldpop population data, about 283,000 people live inside the analyzed area. Within the analysis extent, UNITAR-UNOSAT identified 506 damaged structures and 197 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 03, 2022-May 03, 2022
    This dataset updates: Never
    UNOSAT code: FL20220418ZAF This map illustrates satellite-detected landslides/mudflow-related impact in eThekwini, Metropolitan Municipality, eThekwini District, KwaZulu-Natal Province, South Africa as observed from a Kompsat-3 image acquired on 21 April 2022. Within the analyzed area, 21 ha of landslide scars were observed. Based on Worldpop population data, about 55,000 people live inside the analyzed area. Within the analysis extent, UNITAR-UNOSAT identified 121 damaged structures and 247 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 09, 2022-May 09, 2022
    This dataset updates: Never
    UNOSAT code: FL20220418ZAF Webmap of satellite based analysis related to the Floods and landslides of 13 Apr. 2022 in KwaZulu-Natal (Republic of South Africa).
  • Updated 28 June 2022 | Dataset date: April 29, 2022-April 29, 2022
    This dataset updates: Never
    UNOSAT code: FL20220418ZAF This map illustrates satellite-detected landslides/mudflow in Umzumbe & Ray Nkonyeni Local Municipalities, Ugu District, KwaZulu-Natal Province, South Africa as observed from a Kompsat-3 image acquired on 21 April 2022. Within the analyzed area, 75 ha of landslide scars were observed. Based on Worldpop population data, about 67,000 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 28 June 2022 | Dataset date: April 29, 2022-April 29, 2022
    This dataset updates: Never
    UNOSAT code: FL20220418ZAF This map illustrates satellite-detected landslides/mudflow in eThekwini, Metropolitan Municipality, eThekwini District, KwaZulu-Natal Province, South Africa as observed from a Sentinel-2 image acquired on 28 April 2022.Within the analyzed area, 11 ha of landslide scars were observed. Based on Worldpop population data, about 27,000 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 28 June 2022 | Dataset date: April 28, 2022-April 28, 2022
    This dataset updates: Never
    UNOSAT code: FL20220412PHL This map illustrates satellite detected waters, the potentially exposed population, and the related potentially affected croplands as deduced using a satellite TerraSAR-X image acquired on 26 April 2021 at 05:34 local time acquired over Leyte Province, Region VIII, Philippines. Within the analyzed area of about 30,000 hectares, a total of about 2,000 hectares of lands appear to be flooded. The water extent appears to have increased of about 900 hectares since 21 April 2021. Based on Worldpop population data and the detected surface waters, about 8,000 people are potentially exposed or living close to flooded areas. The exposed population appears to have increased with about 3,000 people since 21 April 2021. In this area, about 1,800 km2 of croplands appear to be likely affected by the flood waters. The affected croplands seems to have increased with about 900 hectares since 21 April 2021. 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: April 25, 2022-April 25, 2022
    This dataset updates: Never
    UNOSAT code: FL20220418ZAF SUMMARY OF FINDINGS: Increased water level, inundated infrastructure & damaged road observed along the Mlazi river as of 14 April 2022; Inundated SAPREF Oil Refinery as of 14 April 2022; Increased water level and damaged roadway observed along the Mhlatuzana river as of 14 April 2022; Inundated area observed along the Umbilo river as of 14 April 2022; Increased water level and landslide observed along the Palmiet river as of 14 April 2022. Status: : Increased water level and landslides observed Further action(s): Continue monitoring
  • Updated 28 June 2022 | Dataset date: April 27, 2022-April 27, 2022
    This dataset updates: Never
    UNOSAT code: FL20220424SSD This map illustrates cumulative satellite-detected water using VIIRS in South Sudan between 01 to 05 April 2022 compared with the period from 20 to 24 April 2022. Within the cloud free analyzed areas of about 16,000,000 km2, a total of about 10,000 km2 of lands appear to be affected with flood waters. Water extent appears to have decreased of about 1,700 km2 since the period between 01 to 05 April 2022. Based on Worldpop population data and the maximal flood water coverage, ~250,000 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: April 25, 2022-April 25, 2022
    This dataset updates: Never
    UNOSAT code: FL20220418ZAF This map illustrates satellite-detected landslides/mudflow West of Durban City, eThekwini Metropolitan Municipality, KwaZulu-Natal Province, South Africa as observed from a WorldView-3 imagery acquired on 14 April 2022. Within the analyzed area, at least 62 structures and 2 bridges appear to be affected by floods and/or landslides. 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: April 25, 2022-April 25, 2022
    This dataset updates: Never
    UNOSAT code: FL20220418ZAF This map illustrates satellite-detected landslides/mudflow in Umdloti village, eThekwini Metropolitan Municipality, KwaZulu-Natal Province, South Africa as observed from a NewSat image acquired on 13 April 2022. Within the analyzed area, 14 buildings appear to be affected and 13 are potentially affected. Affected roads were also identified. 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).