Data Datasets [20602] | Archived Datasets[2760] [?]
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  • 10+ Downloads
    Time Period of the Dataset [?]: February 11, 2014-February 11, 2014 ... More
    Modified [?]: 7 July 2022
    Dataset Added on HDX [?]: 28 May 2015
    This dataset updates: Never
    This map illustrates satellite-detected water bodies at the Tokwe Mukorsi Dam, Masvingo Province, Zimbabwe, as detected by TerraSAR-X on 11 February 2014. The flooded area above the dam has greatly increased due to recent heavy rains and currently encompasses about 2,300 ha. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks because of the special characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT.
  • 80+ Downloads
    Time Period of the Dataset [?]: April 23, 2015-April 23, 2015 ... More
    Modified [?]: 1 July 2022
    Dataset Added on HDX [?]: 1 July 2022
    This dataset updates: Never
    This dataset contains data on who is doing what where (3W) in response to the Cyclone Pam in Vanuatu.
  • 10+ Downloads
    Time Period of the Dataset [?]: June 27, 2022-June 27, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 2022
    This dataset updates: Never
    UNOSAT code: EQ20220622AFG This map illustrates potentially damaged structures/buildings in the northern part of Spera district, Khost province of Afghanistan as detected by Worldview-3 image acquired on 23 June 2022. Within the analyzed area, UNOSAT has identified 170 damaged buildings and 3 road obstacles, amongst the 2800 buildings identified in the analyzed zone. 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).
  • 20+ Downloads
    Time Period of the Dataset [?]: June 23, 2022-June 23, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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.
  • 20+ Downloads
    Time Period of the Dataset [?]: June 22, 2022-June 22, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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.
  • 10+ Downloads
    Time Period of the Dataset [?]: June 21, 2022-June 21, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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.
  • 10+ Downloads
    Time Period of the Dataset [?]: June 21, 2022-June 21, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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.
  • 20+ Downloads
    Time Period of the Dataset [?]: June 20, 2022-June 20, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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.
  • 60+ Downloads
    Time Period of the Dataset [?]: June 15, 2022-June 15, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 2022
    This dataset updates: Never
    UNOSAT code: CE20220223UKR This map illustrates a satellite imagery based damage analysis within an area of interest (AOI) in the residential area of Mariupol City, Ukraine. Based on imagery collected on 7, 8, 12 May 2022 and 14 March 2022, and 21 June 2021, analysts found that 5,647 structures sustained visible damage in the AOI. This represents approximately 32% of the structures. Out of these, 315 are destroyed, 2,132 severely damaged, 3,002 moderately damaged and 194 possibly damaged. Compared to the 14 March 2022 analysis, 5% of previously affected buildings sustained additional damage, and the total damage has increased by 28%, with 4,910 new damaged buildings. While no complete count of buildings for Mariupol is available, an open source dataset, which is visibly incomplete indicates at least 17,568 structures in the area. This analysis is based on structures visibly damaged as of 12, 8, 7 May 2022 and 14 March 2022 as seen in marginally degraded satellite imagery. 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).
  • 20+ Downloads
    Time Period of the Dataset [?]: June 02, 2022-June 02, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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
  • Time Period of the Dataset [?]: May 30, 2022-May 30, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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).
  • Time Period of the Dataset [?]: May 20, 2022-May 20, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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).
  • 30+ Downloads
    Time Period of the Dataset [?]: May 11, 2022-May 11, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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).
  • 10+ Downloads
    Time Period of the Dataset [?]: May 31, 2022-May 31, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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.
  • Time Period of the Dataset [?]: May 30, 2022-May 30, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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.
  • 10+ Downloads
    Time Period of the Dataset [?]: June 01, 2022-June 01, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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.
  • Time Period of the Dataset [?]: May 30, 2022-May 30, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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
  • 10+ Downloads
    Time Period of the Dataset [?]: May 06, 2022-May 06, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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).
  • Time Period of the Dataset [?]: May 03, 2022-May 03, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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).
  • 100+ Downloads
    Time Period of the Dataset [?]: May 09, 2022-May 09, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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).
  • Time Period of the Dataset [?]: April 29, 2022-April 29, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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).
  • Time Period of the Dataset [?]: April 29, 2022-April 29, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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).
  • 10+ Downloads
    Time Period of the Dataset [?]: April 28, 2022-April 28, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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.
  • 10+ Downloads
    Time Period of the Dataset [?]: April 25, 2022-April 25, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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
  • Time Period of the Dataset [?]: April 27, 2022-April 27, 2022 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 28 June 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).