UN Operational Satellite Applications Programme (UNOSAT)
Last updated on August 11, 2020
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  • UNOSAT code: TC20200408FJI This map illustrates potentially damaged structures and buildings in Ono-i-Lau, Lau Province, Eastern Division, Republic of Fiji as detected by satellite image acquired after landfall of the Tropical Cyclone Harold-20 on 08 April 2020. UNITAR-UNOSAT analysis used a Pleiades image acquired on 10 April 2020. Within Ono District, UNITAR-UNOSAT identified 23 potentially damages structures. Taking into account the pre-building footprints provided by OpenStreetMap, this represents about 8% of the total number of structures within the analyzed cloud free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • UNOSAT code: TC20200408FJI This map illustrates potentially damaged structures and buildings in Kadavu Province, Eastern Division, Republic of Fiji as detected by satellite image acquired after landfall of the Tropical Cyclone Harold-20 on 08 April 2020. UNITAR-UNOSAT analysis used a Pleiades image acquired on 12 April 2020. Within the Kadavu Province boundary, UNITAR-UNOSAT identified in the cloud free zones 1,003 potentially damaged structures. Taking into account the pre-building footprints provided by OpenStreetMap, this represents about 22% of the total number of structures within the analyzed cloud free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • Updated June 3, 2020 | Dataset date: Apr 10, 2020
    This dataset updates: Never
    UNOSAT code: TC20200403VUT This map illustrates potentially damaged structures and buildings in Malampa Province, Vanuatu as detected by satellite image acquired after landfall of the Tropical Cyclone Harold-20 on 6 April 2020. UNITAR-UNOSAT analysis used a Pleiades image acquired on 7, 8 and 9 April 2020 as post event images. Within the analysis extent, UNITAR-UNOSAT identified in the cloud free zones 25 potentially damaged structures. Taking into account the pre-building footprints provided by OpenStreetMap, this represents less than 1 % of the total number of structures within the analyzed cloud-free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • UNOSAT code: TC20200403VUT This map illustrates potentially damaged structures and buildings in Canal-Fanafo, Luganville and South East Santo Municipality, Sanma Province, Vanuatu as detected by satellite image acquired after landfall of the Tropical Cyclone Harold-20 on 6 April 2020. UNITAR-UNOSAT analysis used a Pleiades image acquired on 7, 8 and 9 April 2020 as post event images, Within the analysis extent, UNITAR-UNOSAT identified in the cloud free zones 3,490 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 35 % of the total number of structures within the analyzed cloud free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • Updated June 3, 2020 | Dataset date: Apr 10, 2020
    This dataset updates: Never
    UNOSAT code: TC20200403VUT This map illustrates potentially damaged structures and buildings in West Malo and East Malo Municipality, Sanma Province, Vanuatu as detected by satellite image acquired after landfall of the Tropical Cyclone Harold-20 on 6 April 2020. UNITAR-UNOSAT analysis used a Pleiades image acquired on 7 and 10 April 2020 as post event images, Within the Island extent, UNITAR-UNOSAT identified in the cloud free zones 1,345 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 45 % of the total number of structures within the analyzed cloud-free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • UNOSAT code: TC20200403VUT This map illustrates potentially damaged structures and buildings in Luganville Municipality, Sanma Province, Vanuatu as detected by satellite image acquired after landfall of the Tropical Cyclone Harold-20 on 6 April 2020. UNITAR-UNOSAT analysis used a Pleiades image acquired on 7 April 2020 as post event image. Within the Luganville Municipality boundary, UNITAR-UNOSAT identified in the cloud free zones 1,972 potentially damaged structures. Taking into account the pre-building footprints provided by OpenStreetMap, this represents about 35 % of the total number of structures within the analyzed cloud free areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • UNOSAT code: FL20200324IRN This map illustrates satellite-detected water surface in Konarak County, Sistan and Baluchestan Province, Islamic Republic of Iran, as observed from Sentinel-2 imagery acquired on 23 March 2020. Within the analysed area of about 1,100 km2, a total of 56 km2 of land appear to be flooded in Konarak County. Based on Worldpop population data and the detected surface waters, about 3,700 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.
  • UNOSAT code: FL20200305ZMB Status: Floods detected in Lunga district Further actions(s): monitoring over AOI completed Preliminary observations, impact and severity: AOI 1: No satellite-detected waters in Chaba city or its vicinity as of 09 March 2020 AOI 2: Mofu city appears to have no evidences of satellite-detected waters as of 09 March 2020 AOI 3: No satellite-detected waters in Samfya city as of 10 March 2020 AOI 4: Satellite-detected waters northern and eastern part of Ncheta island affecting the agricultural fields nearby as of 07 March 2020
  • UNOSAT code: FL20200305ZMB This map illustrates satellite-detected water extents in the eastern part of Ncheta Island, Lunga District, Luapula Province, Republic of Zambia as observed form Pleiades imagery acquired on 7 March 2020. Within the analyzed area several hectares of land appear to be flooded and 29 structures out of 300 are likely flooded within this area. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • UNOSAT code: FL20200305ZMB This map illustrates satellite-detected water extents in the northern part of Ncheta Island, Lunga District, Luapula Province, Republic of Zambia as observed form Pleiades imagery acquired on 7 March 2020. Within the analyzed area, a total of about 100ha of land appears to be flooded and 115 structures are completely flooded which represents about 20% of total structures in this zone. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • Updated June 3, 2020 | Dataset date: Mar 6, 2020
    This dataset updates: Never
    UNOSAT code: FL20200305ZMB This map illustrates satellite-detected water via VIIRS-NOAA over Central, Luapula, Muchinga and Northern Province in Republic of Zambia between the 1st and the 05th March 2020. Within the analysed extent not covered by clouds, a total of about 10,000 km2 appear to be flooded. Based on Worldpop population about 28,000 people were potentially exposed or living close to flooded areas in Lunga district. This is a preliminary analysis and has not yet been validated in the field. Please send ground fedback to UNITAR - UNOSAT.
  • UNOSAT code: FL20200305ZMB This map illustrates satellite-detected waters in Chitambo, Lunga, Samfya, Lavushimanda and Chilubi District; Central, Luapula, Muchinga and Northern Province of Zambia as observed from Sentinel-1 imagery acquired on 4 March 2020. Within the analysed area of 10,000 km2, a total of about 705 km2 of land appear to be flooded. Based on Worldpop population data and the detected surface waters, about 7,000 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 UNITARUNOSAT.
  • UNOSAT code: FL20200128MDG This maps illustrates satellite-detected water via VIIRS-NOAA on the center and the northern part of the Republic of Madagascar between the 09 and the 13 February 2020. Within the analysed extent not covered by clouds, a total of about 9,116 km2 appear to be flooded, of which about 2,098 km2, 1,366 km2 and 834 km2 in Boeny, Melaky and Alaotra-Mangoro region respectively. Based on Worldpop population data and the detected surface waters, about 1,300,000 people are potentially exposed or living close to flooded areas. In Boeny, Melaky and Alaotra-Mangoro regions, respectively 170,000; 35,000 and 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.
  • UNOSAT code: FL20200128MDG This maps illustrates satellite-detected water via VIIRS-NOAA on the center and the northern part of the Republic of Madagascar between the 29 January and the 02 February 2020. Within the analysed extent not covered by clouds, a total of about 9,718 km2 appear to be flooded, of which about 2,309 km2 and 851 km2 in Boeny and Alaotra-Mangoro region respectively. Based on Worldpop population data and the detected surface waters, about 1,400,000 people are potentially exposed or living close to flooded areas. In Boeny and Alaotra-Mangoro regions, respectively 144,000 and 70,000 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.
  • UNOSAT code: FL20200128MDG Cette carte illustre les eaux de surface détectées via le capteur VIIRS-NOAA sur le centre et le nord de la république de Madagascar entre le 23 janvier et le 27 Janvier 2020. Dans la zone analysée non couverte par les nuages, environ 850,000 personnes sont exposées ou vivent à proximité des zones inondées qui couvrent 9,475 km2. Les plaines du nord-ouest situées dans les régions de Boeny, Sofia et Alaotra Mangoro semblent être particulièrement impactées par les inondations en cours. Ceci est une analyse préliminaire et n'a pas encore été validée sur le terrain. Ne pas hésiter à envoyer vos commentaires à UNITAR-UNOSAT.
  • UNOSAT code: FL20200117IRN This map illustrates satellite-detected water surface in Chabahar and Konarak County, Sistan Va Baluchestan Province, Islamic Republic of Iran as observed from Sentinel-2 imagery acquired on 18 January 2020. Within the analysed extent of about 730 km2, a total about 63 km2 of land appear to be flooded. Based on Worldpop population data and the detected surface waters, about 5,900 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.
  • UNOSAT code: FL20200117IRN This map illustrates satellite-detected waters in Dalgan County, Sistan and Baluchestan Province, Islamic Republic of Iran, as observed from Sentinel-2 imagery acquired on 16 January 2020. Within the analysed area of 2,130 km2, a total of 647 km2 of land appear to be flooded in Dalgan County. Based on Worldpop population data and the detected surface waters, about 2,500 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.
  • UNOSAT code: FL20200117IRN This map illustrates satellite-detected water surface in Konarak District in Sistan Va Baluchestan Province of Iran as observed from Sentinel-2 imagery acquired on 18 January 2020. Within the analysed extent of about 590 km2, a total about 55 km2 of land appear to be flooded. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • UNOSAT code: FL20200101IDN This map illustrates satellite-detected surface water in Banten, Dki Jakarta and Jawa Barat Province of Indonesia as observed from Sentinel-1 imagery acquired on the 2 January 2020. Approximately 258 km2 of land appear to be flooded. 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 Sentinel-1 imagery acquired on 2 January 2020 may seriously underestimate presence of standing flood water in built up areas due to backscattering properties of the radar signal.
  • UNOSAT code: FL20191217MYS This map illustrates satellite-detected surface water in Kluang and Mersing District, Johor State and Rompin District, Pahang State of Malaysia as observed from Sentinel-1 imagery acquired on 15 December 2019. Within the analysed extent of about 3,500 km2, a total about 23 km2 of land appear to be flooded. 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 Sentinel-1 imagery acquired on 15 December 2019 may seriously underestimate the presence of standing floodwater in built-up areas due to backscattering of the radar signal
  • UNOSAT code: FL20191217MYS This map illustrates satellite-detected surface water in Kota Tinggi and Mersing district, Johor state of Malaysia as observed from Sentinel-1 imagery acquired on 15 December 2019. Within the analysed extent of about 1,300 km2, a total about 8 km2 of land appear to be flooded. 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 Sentinel-1 imagery acquired on 15 December 2019 may seriously underestimate the presence of standing floodwater in built-up areas due to backscattering of the radar signal
  • UNOSAT code: TC20191202PHL This map illustrates satellite-based structural damage assessment in San Pascual municipality in the northeastern part of Masbate region, Bicol Region province, in the Philippines. The area was affected by Typhoon Kammuri that made landfall on 3 December 2019. UNITAR-UNOSAT identified 16 potentially damaged structures around San Pascual town, in the San Pascual municipality, within the extent of this map. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • UNOSAT code: LS20191209UGA This map illustrates satellite-detected landslide at in Humya city, Bwanba County, Budibungyo District, Western Region, as seen on Pleiades-1 satellite imagery, 50 cm resolution, collected on 12 December 2019. The landslides and mudflows hit Humyai along the main streams of Bwanba County. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • UNOSAT code: FL20191205COG This map illustrates satellite-detected waters in Epéna District, Likouala Department in Republic of Congo, as observed from Sentinel-1 imagery acquired on 10 December 2019. Within the analysed area of about 30,500 km2, based on Worldpop population data and the detected surface waters, about 7,000 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 SAR Sentinel-1 images may significantly underestimate the presence of standing waters in built up and/or densely vegetated areas due to backscattering of the radar signal.
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    Updated June 3, 2020 | Dataset date: Nov 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.