Saarlouis
County in Saarland
County
The population development of Saarlouis.
| Name | Status | Population Census 2011-05-09 | Population Census 2022-05-15 | |
|---|---|---|---|---|
| Saarlouis | County | 197,877 | 204,475 | → |
| Saarland | State | 999,623 | 1,006,864 |
Contents: Settlements
The population development of the settlements in Saarlouis.
icon links to further information about a selected place including its population structure (gender, age groups, citizenship, country of birth).| Name | Status | County | Population Census 2011-05-09 | Population Census 2022-05-15 | |
|---|---|---|---|---|---|
| Altforweiler | Settlement | Saarlouis | 2,280 | 2,290 | → |
| Aschbach | Settlement | Saarlouis | 1,620 | 1,470 | → |
| Beaumarais | Settlement | Saarlouis | 2,270 | 2,350 | → |
| Berus | Settlement | Saarlouis | 1,620 | 1,700 | → |
| Bisten | Settlement | Saarlouis | 850 | 870 | → |
| Bous | Settlement | Saarlouis | 7,040 | 7,100 | → |
| Campus Nobel | Settlement | Saarlouis | 200 | 630 | → |
| Derlen - Elm - Knausholz | Settlement | Saarlouis | 4,070 | 4,100 | → |
| Diefflen | Settlement | Saarlouis | 4,520 | 4,780 | → |
| Differten | Settlement | Saarlouis | 3,420 | 3,240 | → |
| Dillingen/Saar | Settlement | Saarlouis | 15,730 | 16,540 | → |
| Dörsdorf | Settlement | Saarlouis | 1,250 | 1,190 | → |
| Düren | Settlement | Saarlouis | 485 | 485 | → |
| Eidenborn | Settlement | Saarlouis | 600 | 560 | → |
| Eimersdorf | Settlement | Saarlouis | 480 | 490 | → |
| Ensdorf | Settlement | Saarlouis | 6,530 | 6,740 | → |
| Falscheid | Settlement | Saarlouis | 540 | 540 | → |
| Felsberg | Settlement | Saarlouis | 1,230 | 1,310 | → |
| Fremersdorf | Settlement | Saarlouis | 1,200 | 1,170 | → |
| Friedrichweiler | Settlement | Saarlouis | 950 | 910 | → |
| Fürweiler | Settlement | Saarlouis | 425 | 460 | → |
| Gerlfangen | Settlement | Saarlouis | 670 | 670 | → |
| Gisingen | Settlement | Saarlouis | 770 | 690 | → |
| Gresaubach | Settlement | Saarlouis | 1,820 | 1,800 | → |
| Hemmersdorf | Settlement | Saarlouis | 2,090 | 2,080 | → |
| Hülzweiler | Settlement | Saarlouis | 4,810 | 5,020 | → |
| Hüttersdorf | Settlement | Saarlouis | 4,760 | 5,040 | → |
| Ihn | Settlement | Saarlouis | 450 | 395 | → |
| Ittersdorf | Settlement | Saarlouis | 880 | 870 | → |
| Kerlingen | Settlement | Saarlouis | 580 | 540 | → |
| Körprich - Bilsdorf | Settlement | Saarlouis | 3,270 | 3,170 | → |
| Landsweiler | Settlement | Saarlouis | 1,660 | 1,600 | → |
| Lebach | Settlement | Saarlouis | 8,080 | 8,310 | → |
| Limbach | Settlement | Saarlouis | 2,360 | 2,400 | → |
| Michelbach | Settlement | Saarlouis | 840 | 820 | → |
| Nalbach | Settlement | Saarlouis | 5,880 | 5,890 | → |
| Neuforweiler | Settlement | Saarlouis | 1,460 | 1,650 | → |
| Niedaltdorf | Settlement | Saarlouis | 740 | 710 | → |
| Primsweiler | Settlement | Saarlouis | 670 | 710 | → |
| Rehlingen-Siersburg | Settlement | Saarlouis | 3,920 | 4,210 | → |
| Reisbach - Labach | Settlement | Saarlouis | 2,350 | 2,390 | → |
| Saarlouis | Settlement | Saarlouis | 30,800 | 33,610 | → |
| Saarwellingen | Settlement | Saarlouis | 7,720 | 7,620 | → |
| Sankt Barbara | Settlement | Saarlouis | 790 | 790 | → |
| Schmelz | Settlement | Saarlouis | 6,990 | 7,100 | → |
| Schwalbach | Settlement | Saarlouis | 7,480 | 7,920 | → |
| Schwarzenholz | Settlement | Saarlouis | 3,000 | 2,830 | → |
| Siersburg | Settlement | Saarlouis | 4,250 | 4,410 | → |
| Sprengen | Settlement | Saarlouis | 950 | 980 | → |
| Steinbach | Settlement | Saarlouis | 1,660 | 1,600 | → |
| Thalexweiler | Settlement | Saarlouis | 1,740 | 1,850 | → |
| Überherrn | Settlement | Saarlouis | 5,550 | 5,700 | → |
| Wadgassen | Settlement | Saarlouis | 12,320 | 12,560 | → |
| Wallerfangen | Settlement | Saarlouis | 4,560 | 4,600 | → |
| Werbeln | Settlement | Saarlouis | 1,240 | 1,240 | → |
Source: Population Grid: Statistisches Bundesamt Deutschland.
Explanation: Boundaries and population of settlements are computed by »City Population« using population figures of a 100m grid and "Ortlagen" geometries. The settlements are delimited by unsettled and not built-up areas as well as by municipal boundaries. Because of the computation method, the population figures are not exact and therefore rounded. Area figures are calculated by geospatial data.