The population density in Botswana increased by 0.1 inhabitants per square kilometer (+2.36 percent) in 2022. With 4.31 inhabitants per square kilometer, the population density thereby reached its highest value in the observed period. Notably, the population density continuously increased over the last years.Population density refers to the number of people living in a certain country or area, given as an average per square kilometer. It is calculated by dividing the total midyear population by the total land area.Find more key insights for the population density in countries like Kingdom of Eswatini and South Africa.

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. Botswana data available from WorldPop here.

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.

Botswana data available from WorldPop here.

Population density (people per sq. km of land area) in Botswana was reported at 4.3052 sq. Km in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Botswana - Population density (people per sq. km) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Botswana: Population density, people per square km: The latest value from 2021 is 5 people per square km, an increase from 4 people per square km in 2020. In comparison, the world average is 456 people per square km, based on data from 196 countries. Historically, the average for Botswana from 1961 to 2021 is 2 people per square km. The minimum value, 1 people per square km, was reached in 1961 while the maximum of 5 people per square km was recorded in 2021.

Botswana BW: Population Density: People per Square Km data was reported at 4.305 Person/sq km in 2022. This records an increase from the previous number of 4.237 Person/sq km for 2021. Botswana BW: Population Density: People per Square Km data is updated yearly, averaging 2.401 Person/sq km from Dec 1961 (Median) to 2022, with 62 observations. The data reached an all-time high of 4.305 Person/sq km in 2022 and a record low of 0.932 Person/sq km in 1961. Botswana BW: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Botswana – Table BW.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.;Food and Agriculture Organization and World Bank population estimates.;Weighted average;

Botswana population density for 2022 was 4.31, a 1.6% increase from 2021.

<ul style='margin-top:20px;'>

<li>Botswana population density for 2021 was <strong>4.24</strong>, a <strong>1.5% increase</strong> from 2020.</li>
<li>Botswana population density for 2020 was <strong>4.17</strong>, a <strong>1.45% increase</strong> from 2019.</li>
<li>Botswana population density for 2019 was <strong>4.11</strong>, a <strong>1.43% increase</strong> from 2018.</li>
</ul>Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Botswana: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49). Methodology These high-resolution maps are created using machine learning techniques to identify buildings from commercially available satellite images. This is then overlayed with general population estimates based on publicly available census data and other population statistics at Columbia University. The resulting maps are the most detailed and actionable tools available for aid and research organizations. For more information about the methodology used to create our high resolution population density maps and the demographic distributions, click here. For information about how to use HDX to access these datasets, please visit: https://dataforgood.fb.com/docs/high-resolution-population-density-maps-demographic-estimates-documentation/ Adjustments to match the census population with the UN estimates are applied at the national level. The UN estimate for a given country (or state/territory) is divided by the total census estimate of population for the given country. The resulting adjustment factor is multiplied by each administrative unit census value for the target year. This preserves the relative population totals across administrative units while matching the UN total. More information can be found here

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Botswana: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Botswana BW: Population Density: Inhabitants per sq km data was reported at 4.310 Person in 2022. This records an increase from the previous number of 4.240 Person for 2021. Botswana BW: Population Density: Inhabitants per sq km data is updated yearly, averaging 3.310 Person from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 4.310 Person in 2022 and a record low of 2.300 Person in 1990. Botswana BW: Population Density: Inhabitants per sq km data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Botswana – Table BW.OECD.GGI: Social: Demography: Non OECD Member: Annual.

Historical chart and dataset showing Botswana population growth rate by year from 1961 to 2023.

Botswana BW: Population: Growth data was reported at 1.640 % in 2023. This records an increase from the previous number of 1.588 % for 2022. Botswana BW: Population: Growth data is updated yearly, averaging 2.161 % from Dec 1961 (Median) to 2023, with 63 observations. The data reached an all-time high of 6.026 % in 1978 and a record low of 0.521 % in 1968. Botswana BW: Population: Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Botswana – Table BW.World Bank.WDI: Population and Urbanization Statistics. Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.;Derived from total population. Population source: (1) United Nations Population Division. World Population Prospects: 2024 Revision; (2) Statistical databases and publications from national statistical offices; (3) Eurostat: Demographic Statistics; (4) United Nations Statistics Division. Population and Vital Statistics Report (various years).;Weighted average;

The population density in South Africa saw no significant changes in 2022 in comparison to the previous year 2021 and remained at around 51.42 inhabitants per square kilometer. Still, the population density reached its highest value in the observed period in 2022. Population density refers to the number of people living in a certain country or area, given as an average per square kilometer. It is calculated by dividing the total midyear population by the total land area.Find more key insights for the population density in countries like Kingdom of Eswatini and Botswana.

Abstract

The purpose of the 2001 Population and Housing Census (PHC) was to provide information on the population of Botswana. The main objective of collecting data on the population was to provide basic information on the size, distribution and structure of Botswana's population. The census data would provide, among others, trends of population characteristics over the years as well as guide policy planning and implementation. The specific objectives of the 2001 PHC include:

1. To provide measures of both current and usual economic activity.
2. To obtain a measure of lifetime and current fertility.
3. To provide measures of unemployment.
4. To estimate the extent of migration.
5. To provide total population growth rate and to estimate future projections.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Housing units

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

Population and Housing Census 2001 Questionnaire

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.

Abstract

The purpose of the Population and Housing Census is to provide basic information on the size, distribution and structure of Botswana's population.

More detailed objectives were;

• To provide measures of both current and usual economic activity. • To obtain a measure of lifetime and current fertilty. • To provide measures of unemployment. • To estimate the extent of migration. • To provide total population growth rate and to estimate future projections.

Geographic coverage

National coverage

Analysis unit

The Census covered households and individuals

Universe

The universe for the census was all household members and people living in institutions

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

This zip file 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.

Notes:

• The country-by-country files that were previously hosted here have been moved into separate datasets. You can find all of them here.
• South Sudan, Sudan, Somalia and Ethiopia are intentionally omitted from this dataset. However, a country-level dataset for Ethiopia can be found here.
• 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.

Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. This dataset provides index values for small spatial units within urban areas in Botswana. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.

Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. This dataset provides index values for small spatial units within urban areas in Botswana. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.

Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. This dataset provides index values for small spatial units within urban areas in Botswana. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.