NUTS 3 areas of Poland by population density
Miasto Warszawa had the highest population density of 73 areas in 2016, at 3,449.1 inhabitants per km². Szczecinecko-pyrzycki had the lowest, at 42.2 inhabitants per km². The median was 103.9 inhabitants per km² and the figure for Poland was 123.6 inhabitants per km². Source: Eurostat, European Commission.
Top 40 areas, 2016
Full ranking
| Rank | Areas | 2016 | Change on 2015 |
|---|---|---|---|
| 1 | Miasto Warszawa Series break | 3,449.1 | +0.5% |
| 2 | Miasto Łódź Series break | 2,378.8 | -0.7% |
| 3 | Miasto Kraków Series break | 2,369.6 | +0.3% |
| 4 | Miasto Wrocław Series break | 2,211.4 | +0.4% |
| 5 | Miasto Poznań Series break | 2,102 | -0.4% |
| 6 | Katowicki Series break | 1,960.3 | -0.5% |
| 7 | Trójmiejski Series break | 1,850.8 | +0.1% |
| 8 | Miasto Szczecin Series break | 1,732 | -0.3% |
| 9 | Gliwicki Series break | 539.5 | -0.4% |
| 10 | Rybnicki Series break | 471.6 | -0.1% |
| 11 | Tyski Series break | 435 | +0.3% |
| 12 | Sosnowiecki Series break | 384.2 | -0.6% |
| 13 | Bielski Series break | 285.5 | +0.1% |
| 14 | Bytomski Series break | 278 | -0.4% |
| 15 | Oświęcimski Series break | 275.4 | -0.1% |
| 16 | Bydgosko-toruński Series break | 270 | +0.1% |
| 17 | Warszawski zachodni Series break | 256.5 | +1% |
| 18 | Warszawski wschodni Series break | 202.4 | +0.9% |
| 19 | Krakowski Series break | 176.9 | +0.6% |
| 20 | Rzeszowski Series break | 175.7 | +0.4% |
| 20 | Tarnowski Series break | 175.7 | -0.1% |
| 22 | Łódzki Series break | 174.5 | +0.1% |
| 23 | Częstochowski Series break | 169.8 | -0.4% |
| 24 | Lubelski Series break | 169.4 | +0.1% |
| 25 | Wałbrzyski Series break | 156.5 | -0.7% |
| 26 | Kielecki Series break | 151.7 | -0.3% |
| 27 | Nowosądecki Series break | 151.6 | +0.3% |
| 28 | Tarnobrzeski Series break | 136.3 | 0% |
| 29 | Gdański Series break | 133.9 | +1.2% |
| 30 | Poznański Series break | 130.3 | +1.3% |
| 31 | Legnicko-głogowski Series break | 129.5 | -0.2% |
| 32 | Nowotarski Series break | 127.8 | +0.1% |
| 33 | Kaliski Series break | 115.6 | -0.1% |
| 34 | Opolski Series break | 110.9 | -0.3% |
| 35 | Radomski Series break | 106.9 | -0.4% |
| 36 | Starogardzki Series break | 106 | 0% |
| 37 | Koniński Series break | 103.9 | -0.1% |
| 38 | Żyrardowski Series break | 103.2 | 0% |
| 39 | Jeleniogórski Series break | 100.9 | -0.5% |
| 40 | Włocławski Series break | 100.8 | -0.4% |
| 41 | Płocki Series break | 99.9 | -0.4% |
| 42 | Piotrkowski Series break | 98.9 | -0.4% |
| 43 | Białostocki Series break | 98.3 | +0.1% |
| 44 | Grudziądzki Series break | 97 | -0.2% |
| 45 | Leszczyński Series break | 93.3 | +0.2% |
| 46 | Inowrocławski Series break | 92.3 | -0.3% |
| 47 | Przemyski Series break | 91 | -0.3% |
| 48 | Wrocławski Series break | 90.9 | +0.7% |
| 49 | Nyski Series break | 90.8 | -0.4% |
| 50 | Skierniewicki Series break | 89.2 | -0.4% |
| 51 | Krośnieński Series break | 86.2 | -0.1% |
| 51 | Puławski Series break | 86.2 | -0.6% |
| 53 | Koszaliński Series break | 81.9 | -0.2% |
| 54 | Zielonogórski Series break | 80.1 | -0.1% |
| 55 | Sieradzki Series break | 79.2 | -0.3% |
| 56 | Elbląski Series break | 73.3 | -0.4% |
| 57 | Sandomiersko-jędrzejowski Series break | 72.4 | -0.5% |
| 58 | Siedlecki Series break | 69.7 | -0.1% |
| 59 | Szczeciński Series break | 69.1 | +0.1% |
| 60 | Chełmsko-zamojski Series break | 67.6 | -0.6% |
| 61 | Ciechanowski Series break | 65.1 | -0.3% |
| 62 | Słupski Series break | 64.7 | -0.2% |
| 63 | Pilski Series break | 63.8 | 0% |
| 64 | Gorzowski Series break | 63.4 | 0% |
| 65 | Olsztyński Series break | 61 | -0.2% |
| 66 | Ostrołęcki Series break | 59.2 | -0.2% |
| 67 | Świecki Series break | 56.9 | -0.2% |
| 68 | Chojnicki Series break | 55.6 | 0% |
| 69 | Bialski Series break | 50.9 | -0.4% |
| 70 | Ełcki Series break | 48.2 | -0.2% |
| 71 | Łomżyński Series break | 44.2 | -0.7% |
| 72 | Suwalski Series break | 43.7 | -0.2% |
| 73 | Szczecinecko-pyrzycki Series break | 42.2 | -0.5% |
Other periods
About this ranking
Resident population divided by land area in km². World Bank figures use mid-year population and land area excluding inland water.
United States: Census Bureau population estimates for 1 July divided by land area (water excluded) from the latest Census Gazetteer files. US tables often give people per square mile; multiply persons per km² by 2.59 to compare.
Every value in the ranking comes from the same publisher and the same period, so the areas are compared on one definition. Equal values share a rank.
How to cite
Eurostat. Population density by NUTS 3 region (demo_r_d3dens). https://ec.europa.eu/eurostat/databrowser/view/demo_r_d3dens/default/table. Retrieved 2026-10-08.Use this data in your AI agent
Invokely serves this figure to AI assistants through MCP and to code through a REST API, with the source and citation attached. Ask your assistant:
Rank NUTS 3 areas of Poland by population density using official data, and cite the source.
rank_places {"indicator":"population_density","level":"province","within":"Poland","limit":10}
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Which area has the highest population density?
Miasto Warszawa, with 3,449.1 inhabitants per km² in 2016, according to Eurostat, European Commission.
Which area has the lowest population density?
Szczecinecko-pyrzycki, with 42.2 inhabitants per km² in 2016.
Where does this ranking come from?
Every value comes from one source and one period, so the places are comparable: Eurostat, European Commission, Population density by NUTS 3 region (demo_r_d3dens). Retrieved 2026-10-08.
Population density: other rankings
- Countries
- EU countries
- US states
- EU regions (NUTS 2)
- US counties
- Autonomous communities of Spain
- Provinces of Spain
- Municipalities of Spain
- Regions of Germany (NUTS 2)
- Regions of France (NUTS 2)
- Regions of Italy (NUTS 2)
- Regions of Poland (NUTS 2)