Key Figures
Data Grid Completeness
9/27 Core Data 16 Datasets 10 Organisations Show legend
What is Data Grid Completeness?
Data Grid Completeness defines a set of core data that are essential for preparedness and emergency response. For select countries, the HDX Team and trusted partners evaluate datasets available on HDX and add those meeting the definition of a core data category to the Data Grid Completeness board above. Please help us improve this feature by sending your feedback to hdx@un.org.
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Presence, freshness, and quality of dataset
  • Dataset fully matches criteria and is up-to-date
  • Dataset partially matches criteria and/or is not up-to-date
  • No dataset found matching the criteria
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Affected People
2 Datasets
Internally-Displaced Persons
Internal Displacement Monitoring Centre (IDMC)
Refugees & Persons of Concern
Returnees
Humanitarian Profile Locations
Humanitarian Needs
Casualties
Armed Conflict Location & Event Data Project (ACLED)
Coordination & Context
6 Datasets
3w - Who is doing what where
International Aid Transparency Initiative
Affected Areas
Conflict Events
Armed Conflict Location & Event Data Project (ACLED)
Humanitarian Access
Transportation Status
WFP - World Food Programme
Humanitarian OpenStreetMap Team (HOT)
Humanitarian OpenStreetMap Team (HOT)
Damaged & Destroyed Buildings
Food Security & Nutrition
1 Datasets
Food security
Global Acute Malnutrition Rate
Severe Acute Malnutrition Rate
Food Prices
Geography & Infrastructure
6 Datasets
Populated Places
Humanitarian OpenStreetMap Team (HOT)
Roads
WFP - World Food Programme
Humanitarian OpenStreetMap Team (HOT)
Airports
Humanitarian OpenStreetMap Team (HOT)
Health & Education
3 Datasets
Health Facilities
Global Healthsites Mapping Project
Humanitarian OpenStreetMap Team (HOT)
Education Facilities
Humanitarian OpenStreetMap Team (HOT)
Affected Schools
Population & Socio-economy
1 Datasets
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  • 50+ Downloads
    Updated July 13, 2020 | Dataset date: January 17, 2021-January 17, 2021
    This dataset updates: Every week
    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 rooms addr:full beds name tourism shop amenity addr:street source man_made addr:city addr:housenumber This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 100+ Downloads
    Updated July 13, 2020 | Dataset date: January 17, 2021-January 17, 2021
    This dataset updates: Every week
    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: highway bridge layer smoothness oneway name surface source lanes width This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 10+ Downloads
    Updated June 29, 2020 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. A description of the modelling methods used for age and sex structures can be found in Tatem et al and Pezzulo et al. The 'Unconstrained 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. These are produced using the unconstrained top-down modelling method. 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
  • Updated June 29, 2020 | Dataset date: January 01, 2018-December 31, 2018
    This dataset updates: Every year
    The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of pregnancies to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age, age-specific fertility rates, still births and abortions to map the estimated distributions of pregnancies for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al and James et al.. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Iran 1km Pregnancies. Version 1.0 2015 estimates of numbers of pregnancies per grid square, with national totals adjusted to match national estimates on numbers of pregnancies made by the Guttmacher Institute (http://www.guttmacher.org) DOI: 10.5258/SOTON/WP00607
  • Updated June 29, 2020 | Dataset date: January 01, 2018-December 31, 2018
    This dataset updates: Every year
    The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of live births to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age and age-specific fertility rates to map the estimated distributions of births for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al. and James et al.. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Iran 1km Births. Version 1.0 2015 estimates of numbers of live births per grid square, with national totals adjusted to match UN national estimates on numbers of live births (http://esa.un.org/wpp/). DOI: 10.5258/SOTON/WP00556
  • Updated June 3, 2020 | Dataset date: March 26, 2020-March 26, 2020
    This dataset updates: Never
    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.
  • Updated June 3, 2020 | Dataset date: January 22, 2020-January 22, 2020
    This dataset updates: Never
    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.
  • Updated June 3, 2020 | Dataset date: January 21, 2020-January 21, 2020
    This dataset updates: Never
    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.
  • Updated June 3, 2020 | Dataset date: January 21, 2020-January 21, 2020
    This dataset updates: Never
    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.
  • 70+ Downloads
    Updated June 1, 2020 | Dataset date: December 31, 2016-December 31, 2016
    This dataset updates: As needed
    Population results from census dis aggregated by gender and age
  • 200+ Downloads
    Updated May 30, 2020 | Dataset date: January 01, 2009-December 31, 2019
    This dataset updates: Every year
    Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. "People Displaced" refers to the number of people living in displacement as of the end of each year. "New Displacement" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once. Contains data from IDMC's Global Internal Displacement Database.
  • 50+ Downloads
    Updated April 29, 2020 | Dataset date: January 01, 1990-December 31, 2017
    This dataset updates: Every year
    The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities. The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions. The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.
  • 30+ Downloads
    Updated Live | Dataset date: January 01, 2008-December 31, 2027
    This dataset updates: Live
    List of airports in Iran (Islamic Republic of), with latitude and longitude. Unverified community data from http://ourairports.com/countries/IR/
  • 2000+ Downloads
    Updated February 22, 2020 | Dataset date: January 01, 1970-December 31, 2019
    This dataset updates: Every year
    Education: Students and Teachers indicators for Iran (Islamic Republic of). Contains data from UNESCO's data portal.
  • 30+ Downloads
    Updated January 27, 2020 | Dataset date: June 02, 2017-June 02, 2017
    This dataset updates: As needed
    This dataset is an extraction of roads from OpenStreetMap data made by WFP following UNSDI-T standards. The data is updated in near-real time from OSM servers and include all latest updates. NOTE: this dataset doesn't include streets and pathways that have been published on a separate dataset (streets and pathways). More documentation on the whole process for extracting OpenStreetMap roads can be found here: http://geonode.wfp.org/documents/6823/download
  • 10+ Downloads
    Updated January 27, 2020 | Dataset date: June 02, 2017-June 02, 2017
    This dataset updates: As needed
    This dataset is an extraction of streets and pathways from OpenStreetMap data made by WFP that follow UNSDIT standards. The data is updated in near-real time from OSM servers and include all latest updates. NOTE: this dataset doesn't include main roads that have been published on a separate dataset (main roads). More documentation on the whole process for extracting OpenStreetMap roads can be found here: http://geonode.wfp.org/documents/6823/download
  • Updated September 10, 2019 | Dataset date: May 14, 2019-May 14, 2019
    This dataset updates: Never
    UNOSAT code: FL20190321IRN This map illustrates satellite-detected surface water in western part of Golestan province, Iran as observed from Sentinel-1A imagery acquired on 10 May 2019. Within the analysed area of about 3,000 sq km, a total 76 sq km of lands appear to be flooded as of 10 May 2019. 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-1A imagery acquired on 10 May 2019 may seriously underestimate presence of standing flood water in built up areas due to backscattering of the radar signal
  • 1500+ Downloads
    Updated May 20, 2019 | Dataset date: May 20, 2019-May 20, 2019
    This dataset updates: Never
    Iran (Islamic Republic of) administrative levels 0 (country), 1 (province, ostān), and 2 (district, baxš) boundaries Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID. These layers are suitable for database or GIS link to the Iran (Islamic Republic of) administrative levels 0-2 population statistics tables.
  • 600+ Downloads
    Updated May 20, 2019 | Dataset date: April 26, 2019-April 26, 2019
    This dataset updates: Every year
    Iran (Islamic Republic of) administrative levels 0 (country), 1 (province, ostān), and 2 (district, baxš) 2016 population statistics These tables are suitable for database or GIS linkage to the Iran (Islamic Republic of) administrative levels 0-2 boundaries layers.
  • 10+ Downloads
    Updated Live | Dataset date: November 16, 2015-December 31, 2027
    This dataset updates: Live
    List of aid activities by InterAction members in Iran. Source: http://ngoaidmap.org/location/gn_130758
  • 100+ Downloads
    Updated October 30, 2018 | Dataset date: December 23, 2015-December 23, 2015
    This dataset updates: Never
    This dataset contains the daily summaries on base stations across Iran, Islamic Republic of. The four indicators included are: TPCP: Total precipitation MXSD: Maximum snow depth TSNW: Total snow fall EMXP: Extreme maximum daily precipitation Indicators are compiled by the National Centers for Environmental Information (NCEI), which is administrated by National Oceanic and Atmospheric Administration (NOAA) an organization part of the United States government. NOAA has access to data collected from thousands of base stations around the world, which collect data periodically on weather and climate conditions. This dataset contains the latest 5 years of available data.
  • 100+ Downloads
    Updated September 28, 2018 | Dataset date: January 01, 1950-December 31, 2050
    This dataset updates: Every year
    The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.
  • 10+ Downloads
    Updated April 28, 2017 | Dataset date: April 19, 2017-April 19, 2017
    This dataset updates: Never
    This map illustrates the satellite-detected waters extent south of Urmia Lake in the county of Mahabad in West Azerbaijan province of Iran as observed from the Landsat-8 image acquired on 16 April 2017. Within the area of 21,000 ha covered by this map; 2,970 ha of lands appear to be potentially affected which corresponds to 13% of the analyzed area. The flooded areas appear to be mainly agricultural zones and about 8 km of roads seem to be potentially affected. Please note that some areas were cloud covered and could not be analyzed.This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 100+ Downloads
    Updated January 29, 2016 | Dataset date: December 31, 2015-December 31, 2015
    This dataset updates: Never
    The GAR15 global exposure database is based on a top-down approach where statistical information including socio-economic, building type, and capital stock at a national level are transposed onto the grids of 5x5 or 1x1 using geographic distribution of population data and gross domestic product (GDP) as proxies.