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  • OCHA Nigeria
    Updated February 23, 2017 | Dataset date: Feb 23, 2017
    The dataset represents the Common Operational Data (COD) for administrative boundaries of Nigeria. Each administrative unit contains the p-code and name. Admin COD datasets (Admin 0 – 2) for Nigeria are endorsed by the Office of the Surveyor General of the Federal Republic of Nigeria (OSGOF) and the IMWG Feb 2017. See metadata for description of methodology for admin level 3 and the cleaning and processing performed by ITOS. Levels 0 - 3 are polygonal administrative units, Level 3 only covers Borno and Yobe States.
  • This map illustrates satellite-detected flood waters over Save River in Mozambique as observed from the Radarsat-2 images acquired on 17 February 2017 and 05 February 2017. A decrease of surface waters was observed in the 17 February 2017 image compared to the 05 February 2017 image along the Save river. 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.
  • 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.
  • This map illustrates satellite-detected fires and smoke plumes at oil wells south of Mosul, and also east of Baiji, Iraq. The Mosul fires began with an initial fire at one or two wells on 8 May 2016, lasting less than one day, and intermittently burned in June. The current fire complex began on 3 July with daily fire detections occurring until about 12 July, when the fires greatly increased in number and continued to burn until gradual reductions in detected fires occurred starting in November 2016. The fires east of Baiji have been active since early January 2016. The frequency of smoke plumes (in days) is symbolized in shades of red and yellow, and was calculated using daily MODIS satellite images collected between 18 July 2016 and 24 January 2017. Note that as the plume dissipates then areas of thinner smoke are not detected in this process. The inset on the top right corner shows the infrared data from a Landsat image collected on 24 January 2017, indicating the Mosul fires in white. The inset on the top left corner, from 21 January 2017, shows the same area in real color. Additionally, precipitation data from NASA's IMERG algorithm was included to evaluate instances of rainfall intersecting the smoke plume. 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 fires and environmental damage at and around Al Qayyarah, approximately 60 Km south of Mosul, Iraq. The main frame shows fires and the oil spill as seen in imagery collected between 23 December 2016 and 24 January 2017. Marked in blue are fires that were detected in 23 December 2016 but appear inactive as of 24 January 2017. Insets on the left show the oil spill north of Al Qayyarah, detected with both radar and optical imagery from multiple dates. As seen in the imagery, the oil spill is very close to one of the streams which is incidentally a tributary to the Tigris River; therefore, it is possible that oil is spilling to the river. The spectral signature from thermal imagery also suggest that areas of the oil spill are on fire. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • This map illustrates shelters in the area of the Hadalat crossing on the Syrian-Jordanian border. Using a satellite image collected by the WorldView-1 satellite on 24 January 2017, UNOSAT located 1,535 probable shelters. This is a 13% increase in shelters since the previous UNOSAT analysis done using an image collected 12 November 2016 and the first increase since July 2016. 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.
  • OCHA ROSC
    Updated February 22, 2017 | Dataset date: Feb 17, 2017
    Administrative boundaries for levels 0 - 4, with Arabic Names, English Names, and p-codes. Geodatabase maintains Arabic names better than shapefile Note that Admin 4 is the populated places layer. Admin Level 1= Governorate = Mohafaza Admin Level 2 = District = Mantika Admin Level 3 = Sub-district= Nahya Admin Level 4 = Populated places = City or Village or Farm or Camp
  • UNHCR Turkey
    Updated February 20, 2017 | Dataset date: Jan 1, 2017
    Administrative Divisions dataset was prepared at 1:1,000,000 scale and is the property of General Command of Mapping, Turkey. This dataset was shared through http://www.hgk.msb.gov.tr/u-23-turkiye-mulki-idare-sinirlari.html for humanitarian use only. The original administrative divisions data was shared as polyline. This was converted to polygon, cleaned and PCODE were assigned jointly by UNHCR and OCHA. The PCODE reference is based on the coding system used by Turkish Statistical Institute. Refugee camps: Data collected by UNHCR. The PCODE reference is based on the coding system used by Turkish Statistical Institute.
  • OCHA DR Congo
    Updated February 17, 2017 | Dataset date: Feb 16, 2017
    Limites administratives; niveau 1 (Provinces) et Limites administratives; niveau 2 (Territoires). Les données représentent les Pays, les Provinces, les Territoires et les collectivités de la République Démocratique du Congo. Sourced from Référentiel Géographique Commun http://www.rgc.cd
  • OCHA Sudan
    Updated February 15, 2017 | Dataset date: Jan 1, 2014
    This shape file is created by IMWG, adjusted by OCHA.
    • ZIP
    • This dataset updates: Every year
  • OCHA Sudan
    Updated February 15, 2017 | Dataset date: Aug 1, 2011
    Sudan Settlements - for 18 states.
  • OCHA Sudan
    Updated February 15, 2017 | Dataset date: Nov 1, 2014
    Sudan Administrative Boundaries Level 1: State boundaries Level 2: Locality boundaries This shape file is created by IMWG and adjusted by OCHA.
  • OCHA DR Congo
    Updated February 10, 2017 | Dataset date: Oct 31, 2016
    Données Hydrologiques Les cours d'eau, les lacs, les cascades
  • OCHA DR Congo
    Updated February 10, 2017 | Dataset date: Oct 31, 2009
    Limites des zones de santé de la République Démocratique du Congo
  • OCHA DR Congo
    Updated February 10, 2017 | Dataset date: Oct 31, 2016
    Réseau de Transport : Aéroports, Axes Navigables, Bacs, Gares, Ponts, Ports, Réseau ferroviaire et Réseau routier
  • OCHA DR Congo
    Updated February 10, 2017 | Dataset date: Sep 30, 2011
    Localités Les localités de la RDC sont issues au de la comparaison de deux bases pour lesquelles les doublons ont été supprimés. Des relevés GPS ainsi que des numérisation sur images satellites ont été réalisés par différentes acteurs présent en RDC et viennent compléter le fichier initial. Des ajouts se font régulièrement (2010). Sourced from Référentiel Géographique Commun http://www.rgc.cd
  • This is the detailed version of the detailed Large Scale International Boundaries (LSIB) dataset. The boundary lines reflect all current US government policies on boundaries, boundary disputes, and sovereignty. There are no restrictions on use of this public domain data. This dataset will be updated as needed and is current as of Jan 30, 2017.
  • OCHA ROAP
    Updated February 6, 2017 | Dataset date: Jan 1, 2013
    Bangladesh Settlements and Major Towns.
  • This is the detailed version of the detailed Large Scale International Boundaries (LSIB) dataset. The boundary lines reflect all current US government policies on boundaries, boundary disputes, and sovereignty. There are no restrictions on use of this public domain data. This dataset will be updated as needed and is current as of Jan 30, 2017.
  • OCHA ROAP
    Updated February 2, 2017 | Dataset date: Jan 31, 2013
    These are boundaries for all administrative levels of Thailand.
  • OCHA ROAP
    Updated January 30, 2017 | Dataset date: Jan 1, 2000
    The original source of the data is Local Government Engineering Department (LGDE) of Bangladesh. Dataset updated by WFP, Map Action and OCHA.
  • OCHA ROAP
    Updated January 30, 2017 | Dataset date: Jan 1, 2000
    River data for Bangladesh.
  • OCHA Mali
    Updated January 26, 2017 | Dataset date: May 31, 2015
    The dataset highlights the number of IDPs in Mali by region from Sep '12 - Dec'14.
  • OCHA ROAP
    Updated January 26, 2017 | Dataset date: Dec 21, 2016
    Mongolia District Boundaries - This dataset represents the district/sum boundaries for Mongolia.
  • OCHA ROAP
    Updated January 24, 2017 | Dataset date: Oct 25, 2005
    Bangladesh: Elevation The elevation of Bangladesh depicted using polygons of equal elevation. The shapefile was downloaded from the following SWERA (Solar and Wind Energy Resource Assessment) website. The data was then reprojected into GCS_WGS_1984 by GIST.