Data types |
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.
Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below.
These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country.
They can also be visualised and explored through the woprVision App.
The remaining datasets in the links below are produced using the "top-down" method,
with either the unconstrained or constrained top-down disaggregation method used.
Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs.
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):
- Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using
unconstrained top-down methods for all countries of the World for each year 2000-2020.
- Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using
unconstrained top-down methods for all countries of the World for each year 2000-2020.
- Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using
unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019)
-Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using
unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019).
-Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets.
-Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using
constrained top-down methods for all countries of the World for 2020.
-Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using
constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national
population estimates (UN 2019).
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.
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..
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..
East–Southeast Asia is currently one of the fastest urbanizing regions in the world, with countries such as China climbing from 20 to 50% urbanized in just a few decades. However, spatially-and temporally-detailed information on regional-scale changes in urban land or population distribution have not previously been available; previous efforts have been either sample-based, focused on one country, or drawn conclusions from datasets with substantial temporal/spatial mismatch and variability in urban definitions. In collaboration with the World Bank and University of Wisconsin-Madison, WorldPop used consistent methodology, satellite imagery and census data for >1000 agglomerations in the East–Southeast Asian region to map population changes between 2000 and 2010. The data are available here and described in detail in Schneider et al, and this report.
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.
Improved understanding of geographical variation and inequity in health status, wealth and access to resources within countries is increasingly being recognized as central to meeting development goals. Development and health indicators assessed at national or subnational scale can often conceal important inequities, with the rural poor often least well represented. WorldPop develops methods for the integration of geolocated cluster sample data from household surveys with geospatial covariates in Bayesian geostatistical modelling frameworks to map key development and health indicators at high spatial resolution. These include indicators relating to poverty, literacy, sanitation, maternal and newborn health, contraceptive use and vaccination coverage, among others. Details of methods used and outputs can be found in Utazi et al 1, Utazi et al 2, Steele et al, Bosco et al, Ruktanonchai et al and Tatem et al.
The age group composition of populations varies substantially across continents and within countries, and is linked to levels of development, health status and poverty. The subnational variability in the shape of the population pyramid as well as the respective dependency ratio are reflective of the different levels of development of a country and are drivers for a country’s economic prospects and health burdens. WorldPop’s assembly of subnational population pyramid data has here been used to produce continent-wide subnational scale dependency ratio datasets, with full details found in Pezzulo et al.
Human mobility continues to increase in terms of volumes and reach, producing growing global connectivity. Quantifying and modeling human migration can contribute towards a better understanding of the nature of migration and help develop evidence-based interventions for disease control policy, economic development, and resource allocation. WorldPop has worked to pair census microdata from multiple low and middle income countries with migrant stock data and additional geospatial datasets to develop models for internal and international migration flows, including key drivers that reflect the changing social, demographic, economic, and environmental landscapes. These have been applied to map internal and international migration at sub-national level for all low and middle income countries, with the datasets available to download here, and methods described in Sorichetta et al, Garcia et al, Ceausu et al., Modelling sex-disaggregated internal migration flows in low- and middle-income countries (in preparation), and Ceausu et al., Estimating sex-disaggregated interregional migration in the Global South (in preparation).
Knowing where people are is critical for accurate impact assessments and intervention planning, particularly those focused on population health, food security, climate change, conflicts, and natural disasters. WorldPop has demonstrated how data collected by mobile phone network operators can cost-effectively provide accurate and detailed maps of population distribution over national scales and any time period while guaranteeing phone users’ privacy. Methods are described in Deville et al and zu Erbach-Schoenberg et al, and datasets representing estimated monthly population distributions for France and Portugal are available to download here.
The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers and analysts to rely on scheduled flight seat capacity data or simple models of flow. WorldPop has collated openly available monthly statistics of air passengers across countries and years, and developed models of global air passenger flows, with annual flow methods described in Huang et al, seasonal flows described in Mao et al, and the dataset collected and output estimates available to download here.
Recent years have seen substantial growth in openly available satellite and other geospatial data layers, which represent a range of metrics relevant to global human population mapping at fine spatial scales. The specifications of such data differ widely and therefore the harmonisation of data layers is a prerequisite to constructing detailed and contemporary spatial datasets which accurately describe population distributions. Such datasets are vital to measure impacts of population growth, monitor change, and plan interventions. To this end WorldPop has produced an open access archive of 3 and 30 arc-second resolution gridded data, which are available to download here and are described further in Lloyd et al 2019 and also Lloyd et al 2017.
Changing populations are often accompanied by changing built-settlement landscapes. Here, small area population data and a limited set of environmental covariates have been combined with machine learning methods and dynamically-limited growth curves to annually interpolate (from 2000 to 2014) and annually project (from 2015 to 2020) the presence of built-settlements across the globe at 100m resolution. These annual built-settlement maps were then used to inform the WorldPop "Global per country 2000-2020" population datasets. An overview of the built-settlement growth modeling framework can be found in Nieves et al.
Grid-cell surface areas
Administrative Areas
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.
Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator)
-Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding
Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area.
These are produced using the unconstrained top-down modelling method.
-Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding
Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel,
adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area.
These are produced using the unconstrained top-down modelling method.
Holidays contribute to the seasonal variations of population movements, infectious disease transmission dynamics, socioeconomic activities, and even the climate and environmental changes. WorldPop has systematically collated the datasets of public and school holidays in 2010-2019 across the globe to support the studies for understanding the mechanism and drivers of the seasonality of population mobility, social, demographic, economic, and environmental landscapes. These have been applied to map seasonal denominator dynamics in low- and middle-income settings and assess the spread risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the COVID-19 pandemic. Further details on the methods can be found in Lai, S. et. al.
Population Weighted Density (PWD) is an alternative to conventional approaches to population density that is arguably better suited to some types of research in the fields of social science and epidemiology. In this release WorldPop publishes what we believe may be the first set of global estimates for PWD, which we offer at national and subnational levels since 2000. Please make sure you have read our Population Weighted Density overview page before choosing and downloading a dataset.