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  • OCHA Niger
    Updated July 18, 2018 | Dataset date: Jan 1, 2006
    Niger administrative level 0 (country), 1 (region), 2 (department) and 3 ( 'urban commune' or FR 'commune urbaine', 'rural commune' or FR 'commune rurale', and 'administrative post' or FR 'poste administratif) boundary polygons These administrative boundary shapefiles are suitable for database or GIS linkage to the Niger administrative level 0-3 population statistics. PLEASE SEE CAVEATS / COMMENTS
  • Kenya administrative level 0 (country), 1 (county), and 2 (sub-county) boundary polygon and line shapefiles, KMZ files, geodatabase, live services, and gazeteer Updated November 2017 by Field Information and Coordination Support Section (FICSS), Division of Programme Support and Management (DPSM), UNHCR
  • OurAirports
    Updated July 17, 2018 | Dataset date: Jan 1, 2008-Dec 31, 2027
    List of airports in Zimbabwe, with latitude and longitude. Unverified community data from http://ourairports.com/countries/ZW/
    • CSV
    • 10+ Downloads
    • This dataset updates: Live
  • OurAirports
    Updated July 17, 2018 | Dataset date: Jan 1, 2008-Dec 31, 2027
    List of airports in Zambia, with latitude and longitude. Unverified community data from http://ourairports.com/countries/ZM/
    • CSV
    • This dataset updates: Live
  • OCHA ROWCA
    Updated July 17, 2018 | Dataset date: Dec 27, 2017
    LBR County : polygon dataset that shows all 15 districts (admin level 1) for LIberia, each identified by an unique P-code. The dataset was provided by UNMIL in 2011 and a new pcode structure was created using the ISO-3 System. OCHA pcodes have been also added. LBR_Disctrict.zip: polygon dataset that shows all 136 districts (admin level 2) for LIberia, each identified by an unique P-code. The dataset was provided by UNMIL in 2011 and a new pcode structure was created using the ISO-3 System. OCHA pcodes have been also added.
  • OCHA Myanmar
    Updated July 17, 2018 | Dataset date: Nov 29, 2014
    Administrative boundary, admin level 1 = state and region , admin level 2 = district and admin level 3 = township. The boundaries and names shown and the designations used on these shapefiles do not imply official endorsement or acceptance by the United Nations.
  • OCHA Myanmar
    Updated July 17, 2018 | Dataset date: Feb 1, 2012-Jul 23, 2015
    Settlements in Myanmar. Town and village
  • OurAirports
    Updated July 17, 2018 | Dataset date: Jan 1, 2008-Dec 31, 2027
    List of airports in Viet Nam, with latitude and longitude. Unverified community data from http://ourairports.com/countries/VN/
    • CSV
    • This dataset updates: Live
  • OurAirports
    Updated July 17, 2018 | Dataset date: Jan 1, 2008-Dec 31, 2027
    List of airports in South Africa, with latitude and longitude. Unverified community data from http://ourairports.com/countries/ZA/
    • CSV
    • 10+ Downloads
    • This dataset updates: Live
  • OCHA ROAP
    Updated July 17, 2018 | Dataset date: Oct 14, 2014
    Cambodia Admin Boundaries The datasets were obtained from the Department of Geography of the Ministry of Land Management, Urbanization and Construction in 2008 and unofficially updated in 2014 according to sub-decrees on administrative modifications. Data provided by WFP - VAM unit cambodia.
  • Geodata of Myanmar administrative boundaries; adm0 to adm3, including self administered zones, Wa and Kokang region.
  • OCHA ROCCA
    Updated July 16, 2018 | Dataset date: Oct 28, 2016
    Administrative boundaries (admin 0-2) and corresponding web features services. Please note that the polygons of the districts in Bishkek city (admin 2) are missing. Taxonomy on administrative boundaries (admin 0-3), including p-codes. This is the complete taxonomy and includes the administrative units of which the polygons are missing. There is also an infographic which explains the administrative division and p-coding system. ITOS is currently processing the admin3 geographic boundaries.
  • ACLED makes its dataset of disaggregated conflict and protest data publicly available. A new version of the dataset is released annually, with data from the previous year and targeted quality review being added in each new version. Files for all countries are composed of ACLED events which indicate the day, actors, type of activity, location, fatalities, sources and notes for individual politically violent events. Please see the codebook for further details on conflict categories, actors, events and sources. The user guide provides guidance on downloading and reading files. ACLED data are presented in three forms: the first is an Excel for the entire African continent; the second is a corresponding shapefile of the African continent created from those data; the third format is an Excel file called “COUNTRY X” containing data disaggregated by country which occur in the named state’s territory (including foreign groups active in a state’s territory).
    • ZIP
    • XLSX
    • 200+ Downloads
    • This dataset updates: Every year
  • This map illustrates shelters in the area of the Rukban border crossing on the Syrian-Jordanian border. Using satellite images collected by the WorldView-03 satellite on 23 June 2018 and the GaoFen-2 satellite on 24 June 2018, UNOSAT located 11,702 probable shelters along the Jordanian side of the border, 25 kilometers southwest of the Al Waleed crossing. This is a 12 percent increase in apparent shelters visible compared to the previous UNOSAT analysis done using an image collected 16 January 2018. Due to the small size and the irregularity of the shelters it is likely that some shelters may have been missed in this analysis, or some shelters were included erroneously. Due to the scale of this map and the lack of suitable border information at this scale, the border in this map has been excluded. This map is intended for field support and local authorities should be consulted for boundary information. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates satellite-detected surface water extent in the northeastern parts of Bangladesh (Sylhet distric) & India (Assam, Tipura and Mizoram states) using a Sentinel-1 satellite image acquired on the 15 June 2018. The analysis shows an increase of surface waters in Sylhet district (Bangladesh) and Assam state (India). This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates the evolution of satellite detected waters and the related wet conditions in the Cox's Bazar Myanmar nationals refugee camps located in Ukhia Upazilla, as deduced from the analysis of two Radarsat-2 Spotlight images with 0.5m resolution acquired on 16 June 2018 & 23 May 2018. The evolution of surface waters was classified into three classes of change: low, moderate and high. This analysis shows that some camps experienced a lower increase of wet conditions/surface waters, as camp 1W and camp 2E. Whereas some have moderately changed, as camp 2W, camp 6 and camp 14, others have greatly changed, as camp 17, camp 8W and camp 20 and its extension. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.
  • This map illustrates satellite-detected surface water extent in the northeastern part of Bangladesh using a Sentinel-1 satellite image acquired on the 15 June 2018. In the analysed area; about 500,000 ha of lands are likely affected. The population exposure analysis using WorldPop data shows that 3,500,000 people are potentially affected by floods in this analysed zone: ~1,500,000 are located in Sylhet Division and ~1,000,000 in Sumanganj Division and about 35% of the population is leaving within or close to inundated areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.
  • This map illustrates satellite-detected surface water extent in Teknaf Upazila, District of Cox's Bazar, Chittagong Division, located in the southeastern part of Bangladesh as detected using a Sentinel-1 satellite image acquired on the 13 June 2018 compared to a Sentinel-1 satelllite image acquired on 22 May 2018. The total analysed area is about 5,000 ha, and about 1,600 ha of surface waters could be observed on 13th of June 2018 whereas 1,050 ha were observed on 22 May 2018. The increase of observed surface waters in this area is about 50 %. Within the camps' extents, 52 ha of water were detected and the most affected seems to be camp 25. Please note that in many zones, the affected lands are mainly agricultural and open areas. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.
  • Este mapa ilustra una estimación del número de viviendas y estructuras potencialmente afectadas por el flujo piroclástico detectado por Copernicus EMS, usando una imagen satélite Sentinel-2 colectada el 4 de junio 2018. UNITAR-UNOSAT ha estimado un total de 411 viviendas / estructuras que se encuentran dentro del área afectada por el flujo piroclástico; de las cuales 260 pertenecen a la aldea de San Miguel de Los Lotes. Complejos industriales y hoteleros como el de La Reunión se encuentran también dentro de la extensión del flujo piroclástico. Este análisis es preliminar y no ha sido validado en terreno. Por favor, envíen sus comentarios a UNITAR-UNOSAT.
  • This map illustrates an estimation of the number of buildings potentially affected by pyroclastic flow detected by Copernicus EMS using a Sentinel-2 satellite image collected on 4 June 2018. UNITAR-UNOSAT estimates 411 buildings / structures within the pyroclastic flow, ~ 260 of which are located inside the community of San Miguel de Los Lotes. Industrial sites and the resort of La Reunion are also included in the extent of this pyroclastic flow. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • This map illustrates satellite-detected flood water extent and potentially damaged buildings within the town of Belet Weyne in Belet Weyne District,Hiiran Region, Somalia. The analysis was conducted analyzing GeoEye-1 & WorldView-3 images acquired on the 30 April & 1 May 2018. As observed from the satellite image, the town of Belet Weyne is completely affected by the floods. Within the extension of the town, 66% of the buildings are located inside areas totally inundated and 34% inside areas partially inundated. Building footprints were generated by Humanitarian Open Street Map using an image from 2015, so the number of buildings affected might have been underestimated. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.
  • This map illustrates potentially affected population by flooding in the eastern sub counties of Kenya. The analysis was conducted by analyzing Sentinel-1 imagery acquired on the 4 May 2018. Within the analysis extent, more than 200,000 people are potentially affected by the floods. Magarini sub county in Kilifi County, is the one with more than 40,000 people living inside flood affected areas, followed by Dadaab, Wajir South, Garsen and Malindi sub counties. Note that some sub counties have been partially analyzed depending on the area covered by satellite imagery. It is likely that flood waters have been systematically underestimated along highly vegetated areas, along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.
  • This map illustrates satellite-detected flood water extent over Dadaab & Lagdera Sub Counties, Garissa County, Kenya. The analysis was conducted analyzing Sentinel-1 image acquired on the 4 May 2018. Within the analysis extent, ~ 43,300 ha of land appear to be inundated and around 23,000 people are living inside this flood water extent. Within the analysis extent, around 23,300 ha of inundated land are located inside Dabaad Sub County, potentially affecting 18,200 people. Several refugee camps, specially the ones located inside Dadaab Sub County, seem to be affected by the floods, being Ifo 2 Refugee Camp the most affected one. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.
  • This map illustrates satellite-detected flood water extent over Wajir county, Kenya. The analysis was conducted by analyzing Sentinel-1 imagery acquired on the 4 May 2018. Within the analysis extent, around 111,800 ha of land appears to be inundated and more than 46,300 people are living inside this flood water extent.Within the analysis extent, the sub county of Wajir West presents 68,000 ha of land inundated and more than 6,100 people potentially affected while Wajir South presents ~ 26,300 ha of land inundated and ~ 19,000 people potentially affected. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.
  • This map illustrates satellite-detected flood water extent along Tana River, Galole and Garsen sub counties, Tana River county, Kenya. The analysis was conducted by analyzing Sentinel-1 imagery acquired on the 4 May 2018. The analysis extent is focused on the river bed of Tana, the surrounding land between the primary road and the limit of the Tana River boundary, specifically where the population is concentrated. Within the analysis extent, around 22,700 ha of land appears to be inundated and more than 21,600 people are living inside this flood water extent. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.