Key Figures
Refine your search: Clear all
Featured:
Locations:
More
Formats:
More
Organisations:
More
Tags:
More
Licenses:
More
  • 30+ Downloads
    Updated July 28, 2020 | Dataset date: Jan 1, 1960-Dec 31, 2019
    This dataset updates: Every month
    Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. For the 70 percent of the world's poor who live in rural areas, agriculture is the main source of income and employment. But depletion and degradation of land and water pose serious challenges to producing enough food and other agricultural products to sustain livelihoods here and meet the needs of urban populations. Data presented here include measures of agricultural inputs, outputs, and productivity compiled by the UN's Food and Agriculture Organization.
  • 3400+ Downloads
    Updated July 27, 2020 | Dataset date: Jan 1, 2011-Dec 31, 2019
    This dataset updates: Every month
    Data used to update country toplines in HDX. Contains data from World Bank's data portal.
  • 5400+ Downloads
    Updated July 26, 2020 | Dataset date: Jan 1, 2015-Jun 30, 2020
    This dataset updates: Every month
    This dataset contains agency- and publicly-reported data for events in which an aid worker was killed, kidnapped, or arrested. Categorized by country.
  • 20+ Downloads
    Updated July 12, 2020 | Dataset date: Aug 1, 2020
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IS NOT NULL OR man_made IS NOT NULL OR shop IS NOT NULL OR tourism IS NOT NULL Features may have these attributes: opening_hours tourism beds addr:housenumber addr:street addr:full source amenity man_made name shop addr:city rooms This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 40+ Downloads
    Updated July 12, 2020 | Dataset date: Aug 1, 2020
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: waterway IS NOT NULL OR water IS NOT NULL OR natural IN ('water','wetland','bay') Features may have these attributes: covered blockage width depth tunnel source natural name layer waterway water This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 60+ Downloads
    Updated July 12, 2020 | Dataset date: Aug 1, 2020
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: highway IS NOT NULL Features may have these attributes: bridge smoothness width oneway surface source name highway layer lanes This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 60+ Downloads
    Updated July 12, 2020 | Dataset date: Aug 1, 2020
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: building IS NOT NULL Features may have these attributes: building addr:housenumber addr:street office addr:full building:materials source name building:levels addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 20+ Downloads
    Updated July 3, 2020 | Dataset date: Aug 1, 2020
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: aeroway IS NOT NULL OR building = 'aerodrome' OR emergency:helipad IS NOT NULL OR emergency = 'landing_site' Features may have these attributes: building emergency aeroway emergency:helipad operator:type addr:full source name addr:city capacity:persons This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Updated July 3, 2020 | Dataset date: Aug 1, 2020
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity = 'ferry_terminal' OR building = 'ferry_terminal' OR port IS NOT NULL Features may have these attributes: building operator:type addr:full source amenity port name addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 10+ Downloads
    Updated July 3, 2020 | Dataset date: Aug 1, 2020
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: healthcare IS NOT NULL OR amenity IN ('doctors','dentist','clinic','hospital','pharmacy') Features may have these attributes: building healthcare:speciality healthcare operator:type addr:full source amenity name addr:city capacity:persons This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Updated July 3, 2020 | Dataset date: Aug 1, 2020
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IN ('kindergarten','school','college','university') OR building IN ('kindergarten','school','college','university') Features may have these attributes: building operator:type addr:full source amenity name addr:city capacity:persons This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 800+ Downloads
    Updated July 3, 2020 | Dataset date: Jan 1, 2005-Dec 31, 2013
    This dataset updates: Every month
    Contains data from World Health Organization's data portal covering the following categories: Mortality and global health estimates, Sustainable development goals, Millennium Development Goals (MDGs), Health systems, Malaria, Tuberculosis, Child health, Infectious diseases, World Health Statistics, Health financing, Public health and environment, Substance use and mental health, Tobacco, Injuries and violence, HIV/AIDS and other STIs, Nutrition, Urban health, Noncommunicable diseases, Noncommunicable diseases CCS, Negelected tropical diseases, Health Equity Monitor, Infrastructure, Essential health technologies, Medical equipment, Demographic and socioeconomic statistics, TOBACCO, Neglected tropical diseases, International Health Regulations (2005) monitoring framework, Insecticide resistance, Oral health, Universal Health Coverage, UHC, Global Observatory for eHealth (GOe), RSUD: GOVERNANCE, POLICY AND FINANCING : PREVENTION, RSUD: GOVERNANCE, POLICY AND FINANCING: TREATMENT, RSUD: GOVERNANCE, POLICY AND FINANCING: FINANCING, RSUD: SERVICE ORGANIZATION AND DELIVERY: TREATMENT SECTORS AND PROVIDERS, RSUD: SERVICE ORGANIZATION AND DELIVERY: TREATMENT CAPACITY AND TREATMENT COVERAGE, RSUD: SERVICE ORGANIZATION AND DELIVERY: PHARMACOLOGICAL TREATMENT, RSUD: SERVICE ORGANIZATION AND DELIVERY: SCREENING AND BRIEF INTERVENTIONS, RSUD: SERVICE ORGANIZATION AND DELIVERY: PREVENTION PROGRAMS AND PROVIDERS, RSUD: SERVICE ORGANIZATION AND DELIVERY: SPECIAL PROGRAMMES AND SERVICES, RSUD: HUMAN RESOURCES, RSUD: INFORMATION SYSTEMS, RSUD: YOUTH, FINANCIAL PROTECTION, AMR GLASS, Noncommunicable diseases and mental health, Health workforce, Neglected Tropical Diseases, AMR GASP, ICD, SEXUAL AND REPRODUCTIVE HEALTH For links to individual indicator metadata, see resource descriptions.
  • 10+ Downloads
    Updated July 1, 2020 | Dataset date: Aug 1, 2020
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: railway IN ('rail','subway','station') Features may have these attributes: railway operator:type addr:full source ele name addr:city layer This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Updated July 1, 2020 | Dataset date: Aug 1, 2020
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IN ('mobile_money_agent','bureau_de_change','bank','microfinance','atm','sacco','money_transfer','post_office') Features may have these attributes: addr:full source amenity network name addr:city operator This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Updated July 1, 2020 | Dataset date: Aug 1, 2020
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: place IN ('isolated_dwelling','town','village','hamlet','city') Features may have these attributes: population place source is_in name This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Updated June 29, 2020 | Dataset date: Jan 1, 2000-Dec 31, 2020
    This dataset updates: Every year
    Age and sex structures: WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data can be found in Tatem et al, and a description of the modelling methods used found in Tatem et al and Pezzulo et al. The 'Global per country 2000-2020' datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020 structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing methods and time periods are still available for download here: Individual countries and Whole continent. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646
  • 40+ Downloads
    Updated June 29, 2020 | Dataset date: Jan 1, 2000-Dec 31, 2020
    This dataset updates: Every year
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data and methods can be found in Tatem et al, a description of the modelling methods used found in Stevens et al, and access to modelling code here. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively). Individual countries 2000-2020: Consistent 100m resolution population count datasets created using "top-down" methods for all countries of the World for each year 2000-2020. Individual countries 2000-2020 UN adjusted: Adjusted to match official United Nations population estimates (UN 2019). Global mosaics 2000-2020: Mosaiced 1km resolution versions of the "Individual countries 2000-2020" datasets. Bespoke methods for individual countries (WOPR): Bespoke 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645
  • 600+ Downloads
    Updated June 24, 2020 | Dataset date: Jun 24, 2020
    This dataset updates: Every month
    This dataset shows the list of operating health facilities. Attributes included: Name,Nature of Facility, Activities, Lat, Long
  • Updated June 3, 2020 | Dataset date: Apr 28, 2020
    This dataset updates: Never
    UNOSAT code: TC20200403VUT This map illustrates potentially damaged structures and buildings in Meawo Island, Penama 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 21 and 27 April 2020 as post event images, Within the island boundary, UNITAR-UNOSAT identified in the cloud free zones about 20 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 2% 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 West Santo and South Santo Municipality, Sanma Province, Vanuatu as detected using WorldView-2 satellite images acquired on 17 and 19 April 2020 and a Pleiades satellite image acquired on 27 April 2020. Within the analyzed zone, UNITAR-UNOSAT identified in the cloud-free zones about 3,650 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 63 % 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 27, 2020
    This dataset updates: Never
    UNOSAT code: TC20200403VUT This map illustrates potentially damaged structures and buildings in Ambae Island, Penama 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 WorldView-2 image acquired on 20 April 2020 and Pleiades image acquired on 21 April 2020 as post event images, Within the Island extent, UNITAR-UNOSAT identified in the cloud free zones about 60 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 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.
  • Updated June 3, 2020 | Dataset date: Apr 24, 2020
    This dataset updates: Never
    UNOSAT code: TC20200403VUT This map illustrates potentially damaged structures and buildings in Paama Island, 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 21 April 2020 as post event images, Within the island boundary, UNITAR-UNOSAT identified in the cloud free zones about 100 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 30% 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 south of Sanma Province, Vanuatu as detected by satellite image acquired after landfall of the Tropical Cyclone Harold-20 on 6 April 2020. UNITAR-UNOSAT analysis identified about 5,200 potentially damaged structures in the analysis extent across the south of Sanma province within the cloud free areas. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 33% of the total number of structures/buildings within the analyzed cloud free areas. Please note that some areas could not be analyzed due to the cloud cover. Total and final estimates by municipality are summarized in the table below. 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.