Updated
29 June 2020
| Dataset date: January 01, 2000-December 31, 2020
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. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here.
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined
here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
Data for earlier dates is available directly from WorldPop.
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
29 June 2020
| Dataset date: January 01, 2014-December 31, 2018
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..
Data for earlier dates is available directly from WorldPop.
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Democratic Peoples Republic of Korea 1km Pregnancies. Version 2.0 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/WP00603
Updated
29 June 2020
| Dataset date: January 01, 2014-December 31, 2018
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..
Data for earlier dates is available directly from WorldPop.
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Democratic Peoples Republic of Korea 1km Births. Version 2.0 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/WP00552
Updated
16 March 2020
| Dataset date: February 10, 2020-February 10, 2020
This dataset contains the affected populations, people in need and targeted populations by sector and disaggregated by sex and age. The dataset is produced by the United Nations for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners.
Updated
7 August 2019
| Dataset date: January 01, 2018-December 31, 2018
This dataset includes any criminally motivated events in which aid agency or aid worker property was stolen, destroyed or otherwise misappropriated in 2018. Categorised by date, country, crime sub-type.
Updated
17 July 2019
| Dataset date: January 01, 2013-May 24, 2022
DPR Korea administrative level 0 (country), 1 (province, special city), and 2 (county, city, special city) boundary and line shapefiles, EMF files, geodatabase, gazetteer, and data sheet
Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.
These boundary files are suitable for database or GIS linkage to the DPR Korea administrative level 0-2 population statistics tables. Note, however the caveat below that two of the boundary features do not have corresponding COD-PS records.
Updated
14 March 2019
| Dataset date: December 31, 2018-December 31, 2018
This shape file consists of consolidated history of tropical storm paths over the past 50 years in the West Pacific, South Pacific, South Indian and North Indian basin. Attributes provides details such as storm Name, Date, Time, wind speed and GPS points for each advisory point. Wind speeds are in knots for more details on speeds conversion and storm categories please visit the original source of data: UNISYS (http://weather.unisys.com/hurricane/index.php), NOAA (http://rammb.cira.colostate.edu/products/tc_realtime/index.asp)
Updated
8 February 2019
| Dataset date: February 08, 2019-May 24, 2022
DPR Korea administrative level 0 (country), 1 (province, special city), and 2 (county, city, special city) 2008 population statistics
REFERENCE YEAR: 2008
These population statistics tables are suitable for database or GIS linkage to the DPR Korea administrative level 0-2 boundaries. Note, however the caveat below that two administrative level 2 features in the COD-AB do not have corresponding records in the COD-PS table.
Updated
16 August 2018
| Dataset date: February 10, 2015-February 10, 2015
This spatial dataset provides the delimitation of primary and secondary roads in DPR Korea. Road names in English are also included where known. Broken road segments were merged where appropriate.
Updated
16 August 2018
| Dataset date: February 10, 2015-February 10, 2015
This spatial dataset provides the delimitation of major river bodies and river banks in DPR Korea. Waterbody names in English are also included where known.
Updated
16 August 2018
| Dataset date: February 01, 2015-February 01, 2015
This spatial dataset provides the delimitation of major rivers and water courses in DPRK that are attributed with a hydrological description. Watercourse name in English are also included where known.
Updated
16 August 2018
| Dataset date: January 01, 2013-January 01, 2013
This spatial dataset of settlements is a national dataset of 729 villages, towns and cities and suburbs across DPR Korea. The attribute information includes the location name (in English) and the associated province name. This dataset can be complemented by the OSM dataset.
This dataset was provided to the UN-OCHA Regional Office for the Asia-Pacific by the World Food Programme. It is believed that the original source of the data is the Global Mapping initiative.
Updated
16 August 2018
| Dataset date: January 01, 2000-January 01, 2000
Democratic People's Republic of Korea: Elevation
This data comes from the Global Mapping initiative, a project of the International Steering Committe for Global Mapping.
Updated
16 August 2018
| Dataset date: January 01, 2000-January 01, 2000
Democratic People's Republic of Korea railroads
This data comes from the Global Mapping initiative, a project of the International Steering Committe for Global Mapping.
Updated
15 August 2018
| Dataset date: February 17, 2015-February 17, 2015
This spatial dataset of settlements is a national dataset of 643 villages, towns and cities and suburbs across DPR Korea. The attribute information includes the location name (in local Korean script concatenated with the English translation), OSM id, and the associated province and county administrative name and code. This dataset is also referred to as the village or population point dataset and can be complemented by the WFP dataset.
Updated
21 June 2016
| Dataset date: April 21, 2016-April 21, 2016
This dataset contains a list of the countries affected by the El Niño as at April 21, 2016 as reported jointly by FAO, the Global Food Security Cluster and WFP on 21 April 2016 in the 2015-2016 El Niño: WFP and FAO Overview update. According to the World Bank, El Niño is likely to have a negative impact in more isolated local food markets, and many countries are already facing increased food prices. Food Security Cluster partners have implemented preparedness activities and are responding in countries where the effects of El Niño have materialised, such as Ethiopia, Papua New Guinea, Malawi and throughout Central America. In Southern Africa, many areas have seen the driest October-December
period since at least 1981, and some 14 million people in the region are already facing hunger, which adds to fears of a spike in the numbers of the food insecure later this year through 2017.
