Demographic Atlas

About the data

Every number is an estimate for 2025 of the people living in the selected area. The tool combines a global population grid with statistics attached to administrative areas. Where official data is missing it is extrapolated, and each value is labelled with how it was derived.

Population

Residents are counted on the GHS-POP R2025A grid (European Commission JRC, epoch 2025, 30 arc-seconds, about 1 km). For a drawn shape, every grid cell counts in proportion to the share of the cell inside the shape. Large shapes use a coarser aggregate of the same grid (≈9 km or ≈55 km), so their edges are approximate.

City and neighbourhood populations are the grid cells inside each boundary. Many large cities have no city boundary of their own because the city is an administrative area (Tokyo, Istanbul, Berlin, Ljubljana): these use that area. Where neither exists, the city is approximated by a disc around its centre holding its reported population. Single selections also show the population reported by OpenStreetMap / Who’s On First for comparison; the grid is known to overestimate some dense high-rise cores (e.g. Shanghai).

Boundaries

Countries, provinces/states, districts/counties, cities and neighbourhoods come from the Overture Maps divisions dataset (built from OpenStreetMap and other open sources). Disputed areas follow Overture’s de-facto treatment.

GDP and GDP per capita

National values use the most recent observation from the World Bank WDI, the CIA World Factbook or the IMF WEO, grown to 2025 with recent growth rates where needed. National statistics override them for a few countries (e.g. Taiwan). Within a country, values are scaled by the region’s output relative to the national average, from the official regional accounts of national statistics offices in 78 countries (three quarters of the world’s population; England by region, Switzerland by canton, Russia by federal subject, and so on). Where a country publishes no regional GDP, the Global Data Lab subnational database is used (household surveys, which understate regional gaps); Taiwan and Lebanon use official household-income surveys. Where a region has an HDI but no income figure, income is back-calculated from the HDI (the UNDP income index inverted from HDI, health and education indices). Regional ratios are normalised so the national total is unchanged.

Wages

Average gross monthly earnings come from national statistics offices (curated for ~50 countries) or ILOSTAT, grown to 2025 with nominal GDP growth; otherwise they are modelled from GDP per capita. Net pay applies the income tax and employee contributions of a single worker without children at the average wage (OECD Taxing Wages and national tax rules). Regional wages come from official regional wage statistics where these are curated (Russia, China); elsewhere they follow regional income with an elasticity of 0.6 (0.45 where regional GDP is used), since wages vary less across regions than output. In countries with large informal sectors the average covers all employees and is lower than formal-sector headline figures.

Human development

National HDI, life expectancy and schooling are from the UNDP Human Development Report 2025; subnational values apply Global Data Lab regional deviations. Where Global Data Lab has no regional figure (e.g. Malta), the HDI's income dimension follows the area's income and the other dimensions stay national.

Ethnicity and religion

Compositions are hierarchical (e.g. White › Slavic › Slovenian, Christian › Catholic). Country profiles come from censuses where they exist, otherwise from reputable estimates (CIA World Factbook, Pew Research Center, academic and NGO sources). Many provinces and districts have their own profiles, from regional census results or, where a country does not collect such statistics (e.g. France), from cross-checked estimates of known communities (Armenians and Maghrebis in Marseille, Italians in Nice, Alsatians in Strasbourg). Regional profiles are balanced so that they add up to the national profile; the panel shows which level of profile each result rests on. US counties use American Community Survey data adjusted to 2025, with Pew Religious Landscape Study shares by state.

Towns and neighbourhoods

Where a district profile would hide sharp local contrasts, towns and neighbourhoods carry their own profile, population and income: in Israel and the West Bank every Arab, Druze and Bedouin town, the mixed and Haredi cities, the Israeli settlements and the Jewish and Arab parts of East Jerusalem (Israel CBS, Jerusalem Institute for Policy Research, PCBS). Their populations replace the grid where the grid is known to be wrong, and their income follows the official socio-economic ranking of localities. Kosovo, Lithuania, Estonia, Northern Ireland, Bosnia and Herzegovina, Jammu and Kashmir and Xinjiang have district or municipality profiles.

Comparing areas

Compare A · B · C puts up to three selections side by side: population, GDP, GDP per capita, wages, HDI, life expectancy, schooling, ethnicity and religion, as charts and as a table (downloadable as CSV).

Limits