Read how data correlated with global population density helps support the rapid deployment of emergency mapping campaigns for Humanitarian OpenStreetMap Team. The tool is actively used by humanitarian mappers to take action confidently based on data correlated with world population density. The dataset was primarily designed to support visualization behind Disaster Ninja. The latest version of Kontur Population is available at. Non-integer population counts are rounded to integers. 25 km²) are spread out to neighboring cells to satisfy constraints. While the population total is accurate, extremely populated cells (i.e., 500,000 people in. Lakes, rivers, glaciers, sands, forests, and other alike land uses are marked as unpopulated. Quarries and big roads are marked as unpopulated, as they are often falsely detected as populated in GHSL. Building presence, or otherwise built-up area, implies there’s someone on the ground, which is often missed in Facebook Africa data. ![]() ![]() Known artifacts of GHSL and HRSL datasets are constrained using OpenStreetMap data. Microsoft Building Footprint, Land Information New Zealand, and Copernicus Global Land Service data are used to improve distribution accuracy. GHSL data is overlaid with Facebook population data (HRSL) where available. Population calculations are based on the Global Human Settlement Layer (GHSL) – a framework relying on a large set of sensors, including radar and optical public and commercial missions. This property greatly simplifies performing analysis and smoothing over gradients. The reason why we use H3 grid instead of the common square grid is that unlike squares, hexagons have equal distances between a hexagon centerpoint and the centers of neighboring cells. ![]() Kontur Population dataset is represented by H3 hexagons with population counts at 400m resolution. While the lowest population density is recorded by No income group available with a population density of only 24.2.The world population density map shows the distribution of people across the globe, with higher population densities typically concentrated in urban areas and lower densities in rural areas. If we devide the global population into income groups we can see that Lower-middle-income countries has the highest population density of 133.9 people per square kilometer. While the sub-region with lowest population density for the yearĪustralia/New Zealand with only 3.9 people/km². When devided into sub-subregions we can see that Southern Asia had the highest population density of 313.6 people per square kilometer.Ĭlosely followed by Caribbean with a population density of 200.4 people/km²,Īnd Western Europe with 179.6 people living per square kilometer. The geographic region with the highest population densityĪsia with a density of 150.6 people per square kilometer.Ĭlosely followed by Africa with a population density of 48.3 people/km²,Īnd Europe with 33.7 people living per square kilometer. □□ Greenland with 0.1 people per square kilometer.įollowed by □□ Falkland Islands (Malvinas) with a density of 0.3 people/km²,Īnd □□ Western Sahara with 2.2 people living per square kilometer, if said population is spread out evenly across its land mass. The country with the lowest annual population density □□ Monaco with a density of 24475.8 people per square kilometer.Ĭlosely followed by □□ China, Macao SAR with a population density of 21724.0 people/km²,Īnd □□ Singapore with 8749.2 people living per square kilometer, if spread out evenly. The country with the highest population density ![]() A population density of 61.2 (people/km²).
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