Where to live in Klagenfurt as a student
Ranking of Klagenfurt's 25 areas with CityPulse's “Student” profile. What matters most: services on foot, protected cycle lanes, public green space and tree canopy. Preferred density: high.
What is the best area of Klagenfurt to live in as a student?
According to CityPulse: Sankt Martin (81), Villacher Vorstadt (79) and Innere Stadt (78).
Klagenfurt areas ranked
| # | Area | Score | Strength |
|---|---|---|---|
| 1 | Sankt Martin | 81 · excellent | Protected cycle lanes |
| 2 | Villacher Vorstadt | 79 · good | Protected cycle lanes |
| 3 | Innere Stadt | 78 · good | Services on foot |
| 4 | St. Veiter Vorstadt | 77 · good | Protected cycle lanes |
| 5 | Waidmannsdorf | 75 · good | Protected cycle lanes |
| 6 | Viktringer Vorstadt | 74 · good | Protected cycle lanes |
| 7 | Völkermarkter Vorstadt | 73 · good | Protected cycle lanes |
| 8 | St. Peter | 73 · good | Protected cycle lanes |
| 9 | Annabichl | 72 · good | Protected cycle lanes |
| 10 | Welzenegg | 71 · good | Protected cycle lanes |
| 11 | St. Ruprecht | 69 · good | Protected cycle lanes |
| 12 | Viktring | 57 · fair | Public green space |
| 13 | Harbach | 56 · fair | Protected cycle lanes |
| 14 | Kohldorf | 46 · fair | Tree canopy |
| 15 | St. Martin | 42 · fair | Tree canopy |
| 16 | Oberhaidach | 28 · poor | Protected cycle lanes |
| 17 | Tessendorf | 23 · poor | Tree canopy |
| 18 | Emmersdorf | 17 · poor | Tree canopy |
| 19 | Wölfnitz | 14 · poor | Tree canopy |
| 20 | Lendorf | 12 · poor | Protected cycle lanes |
| 21 | St.Georgen am Sandhof | 10 · poor | Tree canopy |
| 22 | Ponfeld | 9 · poor | Tree canopy |
| 23 | Tentschach | 4 · poor | Tree canopy |
| 24 | Hörtendorf | 4 · poor | Tree canopy |
| 25 | Gottesbichl | 4 · poor | Tree canopy |
What it does not consider
The ranking does not account for rents and house prices, noise, safety, or distance from university or work. Use it to decide where to look, then check the individual address.
Other profiles in Klagenfurt
Areas are named after OpenStreetMap neighbourhoods and have approximate boundaries: each hexagon goes to the nearest name. Values are residents' medians. Data updated on 2026-11-06. Method and sources