United Nations Satellite Centre (UNOSAT)
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  • Updated 28 June 2022 | Dataset date: June 07, 2022-June 07, 2022
    This dataset updates: Never
    UNOSAT code: FR20220605AFG This map illustrates satellite-detected areas of wildfires in Nurgaram District, Nuristan Province, Afghanistan as observed from Sentinel-2 imagery acquired on 2 Jun. 2022 about 10:39 am. The wildfire scars cover an approximate area of 68 ha and appear to have increased of about 33 ha since 28 May 22. The fire has been spread from the top to down direction of the mountain. 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 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: July 05, 2022-July 05, 2022
    This dataset updates: Never
    UNOSAT code: EQ20220622AFG This map illustrates potentially damaged buildings and damaged buildings in Spera district, Khost province of Afghanistan as detected by a NewSat image acquired on 24 June 2022. Within the analyzed area, UNOSAT has identified 49 potentially damaged buildings, 34 damaged buildings and 145 shelters. 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 2 August 2022 | Dataset date: July 01, 2022-July 01, 2022
    This dataset updates: Never
    UNOSAT code: EQ20220622AFG This map illustrates potentially damaged buildings and damaged buildings in Spera district, Khost province of Afghanistan as detected by a NewSat image acquired on 24 June 2022. Within the analyzed area, UNOSAT has identified 81 potentially damaged buildings, 12 damaged buildings and 170 shelters. 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 2 August 2022 | Dataset date: June 30, 2022-June 30, 2022
    This dataset updates: Never
    UNOSAT code: EQ20220622AFG This map illustrates potentially damaged buildings and damaged buildings in Gyan district, Pakteka province of Afghanistan as detected by Jilin-1 satellite image acquired on 24 June 2022. Within the analyzed area, UNOSAT has identified 39 potentially damaged buildings, 22 damaged buildings and 33 shelters. 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 2 August 2022 | Dataset date: June 30, 2022-June 30, 2022
    This dataset updates: Never
    UNOSAT code: EQ20220622AFG Live web map providing geospatial information about damaged caused by the earthquake that stroke Afghanistan on 21 June 2022. This web map gives an updated overview over potentially damaged and damaged buildings based on very high-resolution satellite images. Furthermore, the application also gives an overview over identified shelters.
  • Updated 2 August 2022 | Dataset date: June 29, 2022-June 29, 2022
    This dataset updates: Never
    UNOSAT code: EQ20220622AFG This map illustrates potentially damaged buildings and damaged buildings in Tani district, Khost province of Afghanistan as detected by Worldview-3 image acquired on 23 June 2022. Within the analyzed area, UNOSAT has identified 156 potentially damaged buildings, 70 damaged buildings and 58 shelters. 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 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.
  • 30+ Downloads
    Updated Live | Dataset date: September 08, 2017-September 08, 2017
    This dataset updates: Live
    Population Exposure Analysis Based on Ground Shake Data (USGS) and Population data (WorldPop).
  • 40+ Downloads
    Updated 24 February 2017 | Dataset date: February 15, 2017-February 15, 2017
    This dataset updates: Never
    The Tropical Cyclone Dineo-17, is approaching Mozambique coasts and is expected to make landfall The 16 February 2017 in the central province of Inhambane. Potential heavy rainfall are also expected according microwave satellite sensors and might induce flooding in the affected areas. This report provides an analysis on the potentially exposed population per wind speed zones in Mozambique. According to our analysis approximately 250,000 people in Mozambique may be exposed to over 120km/h sustainable wind speeds and 59,000 people might be exposed to 90km/h wind speed. About 1,160,000 people might be exposed to moderate winds of 60km/h.
  • 100+ Downloads
    Updated Live | Dataset date: November 27, 2017-November 27, 2017
    This dataset updates: Live
    This map illustrates satellite-detected damage in Mosul, Ninawa Governorate, Iraq. Using satellite imagery acquired 4 August 2017, UNITAR - UNOSAT identified a total of 19,888 affected structures within the city. Approximately 4,773 of these were destroyed, 8,233 severely damaged and 6,882 moderately damaged. 115 of the total affected structures are greenhouses. Around 7,620 of the total affected structures are found within the Old City. The inset shows part of the second most heavily impacted area after the Old City, which appears to be the Al-Shafaa district. UNOSAT also assessed the presence of affected bridges and roads: 317 are the damaged locations and 134 of these are caused by visible impact craters. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 100+ Downloads
    Updated 5 October 2016 | Dataset date: October 05, 2016-October 05, 2016
    This dataset updates: Never
    This report illustrates the population exposure to the tropical cyclone Matthew-16 in Haiti, Cuba and Jamaica.
  • 90+ Downloads
    Updated 3 June 2020 | Dataset date: November 29, 2019-November 29, 2019
    This dataset updates: Never
    UNOSAT code: LS20191125KEN This map illustrates satellite-detected landslides in Pokot South and Sigor Sub counties located in West Pokot county (Kenya) as detected from a Pleiades-1 image acquired on 28 November 2019. Several roads in the valley have been affected and at least 5 bridges were destroyed. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • Updated Live | Dataset date: September 25, 2017-September 25, 2017
    This dataset updates: Live
    This map illustrates potentially damaged structures and buildings in Pointe Michel (Saint Luke Parish) as detected by satellite image acquired after landfall of the Tropical Cyclone Maria-17 on 19 September 2017. UNITAR-UNOSAT analysis used a Pleiades image acquired on 23 September 2017 as post imagery. UNITAR-UNOSAT identified in the analysed area Pointe Michel (St. Luke Parish) 550 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represent about 70 % of the total number of structures within the analysed area. Evidences of floods and mudflow could be also observed along the two rivers that cross the town of Pointe Michel. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • 20+ Downloads
    Updated Live | Dataset date: September 27, 2017-September 27, 2017
    This dataset updates: Live
    This map illustrates satellite-detected destroyed or otherwise damaged structures in Maungdaw and Buthindaung townships, Maungdaw District, Myanmar. The analysis found a total area of more than 400 thousand square meters of destroyed structures occurring between 16 and 25 September 2017. This represents an increase of approximately 2% since last UNOSAT analysis with imagery collected on 16 September, when more than 20 square kilometers of destroyed structures were identified. Additionally, 122 fires were detected within the area between 16 and 25 September 2017 by the MODIS and VIIRS sensors, with recent fire detections indicating destruction is likely ongoing. Most of the detected fires are located in the proximity of the affected areas as observed in the imagery collected 25 September. Finally, heavy cloud cover during the period in question, and on 16 and 25 September especially, indicates that destruction and fire detections are likely underestimated in this analysis. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 100+ Downloads
    Updated Live | Dataset date: November 27, 2017-November 27, 2017
    This dataset updates: Live
    This map illustrates satellite-detected damage density in Mosul, Ninawa Governorate, Iraq. Using satellite imagery acquired 4 August 2017, UNITAR - UNOSAT identified a total of 19,888 affected structures within the city. Approximately 4,773 of these were destroyed, 8,233 severely damaged and 6,882 moderately damaged. 115 of the total affected structures are greenhouses. Around 7,620 of the total affected structures are found within the Old City. The inset shows part of the second most heavily impacted area after the Old City, which appears to be the Al-Shafaa district. UNOSAT also assessed the presence of affected bridges and roads: 317 are the damaged locations and 134 of these are caused by visible impact craters. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 20+ Downloads
    Updated 4 May 2021 | Dataset date: November 02, 2012-November 02, 2012
    This dataset updates: Never
    This is "Flood vectors - TerraSAR-X (02 November 2012)" of the Tropical Cyclone analysis for Haiti which began on 30 October 2012. It includes 2,628 satellite detected water bodies with a spatial extent of 4.35 square kilometers derived from the TerraSAR-...
  • 20+ Downloads
    Updated 4 May 2021 | Dataset date: August 25, 2013-August 25, 2013
    This dataset updates: Never
    This is "Flood vectors - SPOT-5 (25 August 2013)" of the Flood analysis for Pakistan which began on 22 August 2013. It includes 924 satellite detected water bodies with a spatial extent of 581.47 square kilometers derived from the SPOT-5 image acquired on...
  • 10+ Downloads
    Updated 4 May 2021 | Dataset date: August 26, 2013-August 26, 2013
    This dataset updates: Never
    This is "Flood vectors - RISAT-1 (26 August 2013)" of the Flood analysis for Pakistan which began on 22 August 2013. It includes 1,076 satellite detected water bodies with a spatial extent of 3,229.89 square kilometers derived from the RISAT-1 image acqui...
  • Updated 28 June 2022 | Dataset date: June 27, 2022-June 27, 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).
  • 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.