Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

In 2023, the population density in Africa was 50.1 inhabitants per square kilometer. From 2000 onwards, the density of the population on the continent has increased annually. Moreover, the average number of people living within a square kilometer was expected to increase to around 58.5 by 2030. Mauritius, Rwanda, and Burundi were the African countries with the highest population density as of 2023.

The average for 2021 based on 53 countries was 112 people per square km. The highest value was in Mauritius: 634 people per square km and the lowest value was in Namibia: 3 people per square km. The indicator is available from 1961 to 2021. Below is a chart for all countries where data are available.

These 28 tiff files represent 2015 population estimates. However, please note that many of the country-level files include 2020 population estimates including: Angola, Benin, Botswana, Burundi, Cameroon, Cabo Verde, Cote d'Ivoire, Djibouti, Eritrea, Eswatini, The Gambia, Ghana, Lesotho, Liberia, Mozambique, Namibia, Sao Tome & Principe, Sierra Leone, South Africa, Togo, Zambia, and Zimbabwe. South Sudan, Sudan, Somalia and Ethiopia are intentionally omitted from this dataset. However, a country-level dataset for Ethiopia can be found at https://data.humdata.org/dataset/ethiopia-high-resolution-population-density-maps-demographic-estimates.

Nigeria has the largest population in Africa. As of 2025, the country counted over 237.5 million individuals, whereas Ethiopia, which ranked second, has around 135.5 million inhabitants. Egypt registered the largest population in North Africa, reaching nearly 118.4 million people. In terms of inhabitants per square kilometer, Nigeria only ranked seventh, while Mauritius had the highest population density on the whole African continent in 2023. The fastest-growing world region Africa is the second most populous continent in the world, after Asia. Nevertheless, Africa records the highest growth rate worldwide, with figures rising by over two percent every year. In some countries, such as Chad, South Sudan, Somalia, and the Central African Republic, the population increase peaks at over 3.4 percent. With so many births, Africa is also the youngest continent in the world. However, this coincides with a low life expectancy. African cities on the rise The last decades have seen high urbanization rates in Asia, mainly in China and India. African cities are also growing at large rates. Indeed, the continent has three megacities and is expected to add four more by 2050. Furthermore, Africa's fastest-growing cities are forecast to be Bujumbura, in Burundi, and Zinder, Nigeria, by 2035.

Mauritius had the highest population density level in Africa as of 2023, with nearly *** inhabitants per square kilometer. The country has also one of the smallest territories on the continent, which contributes to the high density. As a matter of fact, the majority of African countries with the largest concentration of people per square kilometer have the smallest geographical area as well. The exception is Nigeria, which ranks among the largest territorial countries in Africa and is very densely populated at the same time. After all, Nigeria has also the largest population on the continent.

Historical dataset showing Africa population density by year from N/A to N/A.

The Africa Population Distribution Database provides decadal population density data for African administrative units for the period 1960-1990. The databsae was prepared for the United Nations Environment Programme / Global Resource Information Database (UNEP/GRID) project as part of an ongoing effort to improve global, spatially referenced demographic data holdings. The database is useful for a variety of applications including strategic-level agricultural research and applications in the analysis of the human dimensions of global change.

This documentation describes the third version of a database of administrative units and associated population density data for Africa. The first version was compiled for UNEP's Global Desertification Atlas (UNEP, 1997; Deichmann and Eklundh, 1991), while the second version represented an update and expansion of this first product (Deichmann, 1994; WRI, 1995). The current work is also related to National Center for Geographic Information and Analysis (NCGIA) activities to produce a global database of subnational population estimates (Tobler et al., 1995), and an improved database for the Asian continent (Deichmann, 1996). The new version for Africa provides considerably more detail: more than 4700 administrative units, compared to about 800 in the first and 2200 in the second version. In addition, for each of these units a population estimate was compiled for 1960, 70, 80 and 90 which provides an indication of past population dynamics in Africa. Forthcoming are population count data files as download options.

African population density data were compiled from a large number of heterogeneous sources, including official government censuses and estimates/projections derived from yearbooks, gazetteers, area handbooks, and other country studies. The political boundaries template (PONET) of the Digital Chart of the World (DCW) was used delineate national boundaries and coastlines for African countries.

For more information on African population density and administrative boundary data sets, see metadata files at [http://na.unep.net/datasets/datalist.php3] which provide information on file identification, format, spatial data organization, distribution, and metadata reference.

References:

Deichmann, U. 1994. A medium resolution population database for Africa, Database documentation and digital database, National Center for Geographic Information and Analysis, University of California, Santa Barbara.

Deichmann, U. and L. Eklundh. 1991. Global digital datasets for land degradation studies: A GIS approach, GRID Case Study Series No. 4, Global Resource Information Database, United Nations Environment Programme, Nairobi.

UNEP. 1997. World Atlas of Desertification, 2nd Ed., United Nations Environment Programme, Edward Arnold Publishers, London.

WRI. 1995. Africa data sampler, Digital database and documentation, World Resources Institute, Washington, D.C.

From the AfriPop website..."High resolution, contemporary data on human population distributions are a prerequisite for the accurate measurement of the impacts of population growth, for monitoring changes and for planning interventions. The AfriPop project was initiated in July 2009 with an aim of producing detailed and freely-available population distribution maps for the whole of Africa. Based on the approaches outlined in detail here and here, and summarized on the methods page, fine resolution satellite imagery-derived settlement maps are combined with land cover maps to reallocate contemporary census-based spatial population count data. Assessments have shown that the resultant maps are more accurate than existing population map products, as well as the simple gridding of census data. Moreover, the 100m spatial resolution represents a finer mapping detail than has ever before been produced at national extents. The approaches used in AfriPop dataset production are designed with operational application in mind, using simple and semi-automated methods to produce easily updatable maps. Given the speed with which population growth and urbanisation are occurring across much of Africa, and the impacts these are having on the economies, environments and health of nations, such features are a necessity for both research and operational applications."Data Source: AfriPop.org

The dataset is a zip file that contains 28 cloud optimized tiff files that cover the continent of Africa. Each of the 28 files represents a region or area - these are not divided by country. These 28 tiff files represent 2015 population estimates. However, please note that many of the country-level files include 2020 population estimates including: Angola, Benin, Botswana, Burundi, Cameroon, Cabo Verde, Cote d'Ivoire, Djibouti, Eritrea, Eswatini, The Gambia, Ghana, Lesotho, Liberia, Mozambique, Namibia, Sao Tome & Principe, Sierra Leone, South Africa, Togo, Zambia, and Zimbabwe. To create the high-resolution maps, machine learning techniques are used to identify buildings from commercially available satellite images then general population estimates are overlaid based on publicly available census data and other population statistics. The resulting maps are the most detailed and actionable tools available for aid and research organizations.

This map presents layers derived from Africapolis.org and NASA's Socioeconomic Data and Applications Center (SEDAC) hosted by Columbia University.Africapolis data consists of urban populations from 1950 through 2015 and percentage of the population that is urban (the urban level). SEDAC data represents population density at local scales for the continent of Africa.This map is featured in Urban Africa produced by Esri's StoryMaps team. In generating this map, the StoryMaps team downloaded the original data files from the Africapolis and SEDAC data portals, cleaned and processed the spreadsheets, and visualized the output feature layers in ArcGIS Online.AfricapolisTotal population, city and country (2015)Urban population, city and country (2015)Percent change in urban population, city and country (2000, 2015)SEDACPopulation density (2015)

Africa: Population density (people per sq. km of land area)

  Dataset summary

This dataset provides values for "Population density (people per sq. km of land area)" across African countries, standardized and made ML-ready. Geographic scope: 54 African countries. Temporal coverage: 1960–2024 (annual). Units: As defined by the World Bank indicator.

  Source & licensing

Source: World Bank – World Development Indicators (WDI), Indicator code: EN.POP.DNST. License:… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/Population-density-people-per-sq-km-of-land-area-africa.

The population density maps presented here for the UNDESERT study areas in Burkina Faso, Benin, Niger and Senegal for 1990, 2000 and 2010 were produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the Centro Internacional de Agricultura Tropical (CIAT). CIESIN/CIAT population density grids are available for the entire globe at a 2.5 arc-minutes resolution (http://sedac.ciesin.columbia.edu/data/collection/gpw-v3/sets/browse). The UNDESERT project (EU FP7 243906), financed by the European Commission, Directorate General for Research and Innovation, Environment Program, aims to improve the Understanding and Combating of Desertification to Mitigate its Impact on Ecosystem Services in West Africa. Humans originate and contribute significantly to desertification processes. Based on the CIESIN/CIAT population density grids we want to illustrate how population density changed in the UNDESERT study areas and countries during the last 20 years. Data for 1990 and 2000 were downloaded from the Gridded Population of the World, Version 3 (GPWv3) consisting of estimates of human population by 2.5 arc-minute grid cells and associated data sets dated circa 2000. Data for 2010 were copied from the Gridded Population of the World, Version 3 (GPWv3) consisting in a future estimate of human population by 2.5 arc-minute grid cells. The future estimate population values are extrapolated based on a combination of subnational growth rates from census dates and national growth rates from United Nations statistics.

Source: http://sedac.ciesin.columbia.edu/data/set/gpw-v3-population-density Center for International Earth Science Information Network (CIESIN)/Columbia University, and Centro Internacional de Agricultura Tropical (CIAT). 2005. Gridded Population of the World, Version 3 (GPWv3): Population Density Grid. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/gpw-v3-population-density. Accessed 28/10/2013 And http://sedac.ciesin.columbia.edu/data/set/gpw-v3-population-density-future-estimates Center for International Earth Science Information Network (CIESIN)/Columbia University, and Centro Internacional de Agricultura Tropical (CIAT). 2005. Gridded Population of the World, Version 3 (GPWv3): Population Density Grid, Future Estimates. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/gpw-v3-population-density-future-estimates. Accessed 28/10/2013

Historical dataset showing Sub-Saharan Africa population density by year from 1961 to 2022.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. Sri Lanka data available from WorldPop here.

Our Population Density Grid Dataset for Middle Africa offers detailed, grid-based insights into the distribution of population across cities, towns, and rural areas. Free to explore and visualize, this dataset provides an invaluable resource for businesses and researchers looking to understand demographic patterns and optimize their location-based strategies.

By creating an account, you gain access to advanced tools for leveraging this data in geomarketing applications. Perfect for OOH advertising, retail planning, and more, our platform allows you to integrate population insights with your business intelligence, enabling you to make data-driven decisions for your marketing and expansion strategies.

This layer shows the countries of Africa. You can click on the map to get info on each country, including its name and flag, as well as links to detailed information in The World Factbook and UN Human Development Reports.The Africa Countries layer was created by joining country population data from The World Factbook to the World Countries (Generalized) layer, using ArcGIS Online analysis tools. The popup for the map uses Arcade expressions to reference other online resources based on the country code for the selected country.The Flags of countries are provided by reference to Flagpedia, which provides flags of countries of the world and the U.S. states for display and download.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. Burkina Faso data available from WorldPop here.

The West Africa Coastal Vulnerability Mapping: GPW Version 4 Population Density, Preliminary Release 1, 2010, represents the number of persons per square kilometer, and was calculated by dividing an unreleased working version of the Gridded Population of the World (GPW), Version 4, year 2010 population count raster for the West Africa region by a land area raster and cropping the result to within 200 kilometers of the coast. GPW provides globally consistent and spatially explicit human population information and data for use in research, policy making, and communications. This is a gridded (raster) data product that renders global population data at the scale and extent required to demonstrate the spatial relationship of human populations and the environment across the globe. The gridded data set is constructed from national or subnational input Units (usually administrative Units) of varying resolutions. The native grid cell resolution of GPWv4 is 30 arc-second, or ~1 km at the equator.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.