Where the Bicycle Network Picks Up Where Walking Stops
13 Postal Districts, 3 Amenity Categories, 1 Transit Network
Stadtwerke Münster's full GTFS feed (routes, trips, stop times, shapes) was mapped and classified by trip frequency, then QGIS's Network Analysis toolbox computed 400m walking-distance service areas from every commercial POI, school, and health facility against the city's OSM footpath network — the same network-distance technique as the companion Dortmund walkability study, applied here across three amenity types instead of two.
A Radial Network, Frequency Concentrated on a Few Corridors
Every GTFS route shape was mapped and classified into five frequency bands by trip count. Route 408 is the single busiest corridor in the network at 1,934 trips; a cluster of purely local/special routes (7, 12, 104, 105, 109, 112) run only 5 trips each. The dense core, radial spoke structure, and periphery drop-off are visible directly in the network geometry.
| Route | Trips | Route | Trips |
|---|---|---|---|
| 408 | 1,934 | 112 | 5 |
| 11 | 1,751 | 109 | 5 |
| 4 | 1,734 | 105 | 5 |
| 6 | 1,712 | 104 | 5 |
| 420 | 1,445 | 180 | 2 |
High-frequency routes create strong linear accessibility along a handful of major corridors radiating from the center, rather than uniform area coverage — the classic radial-network tradeoff. Peripheral postal codes are served by fewer, lower-frequency routes, increasing transfer dependence and wait times.
The Bicycle Network Is the Backbone Beyond Walking Distance
Overlaying the updated bicycle network, health/education points of interest, and natural land cover (water, wood, wetland, park) shows why Münster's famously dense cycling infrastructure matters here: health and education services cluster centrally, and the bicycle network is what extends practical access to them out past the 400m walking radius into the surrounding residential rings.
Large open spaces — parks, forests, wetlands, the river corridor — visibly shape where routes and services can sit: commercial and health facilities concentrate outside major green structures, and the bicycle network bends around them, consistent with the source study's own reading of the terrain.
Central Overlap, Peripheral Gaps — Consistently Across All Three Categories
QGIS's network-based Service Area analysis was run separately for every commercial POI, school, and health facility. Central postal codes show dense, overlapping 400m coverage across all three categories; outer districts — particularly south, southeast, and northeast — show visibly sparser points and correspondingly patchier coverage.
| Postal district | Commercial | Education | Health |
|---|---|---|---|
| 48143 (historic core) | 59.6% | 39.7% | 44.4% |
| 48151 | 37.3% | 8.6% | 21.9% |
| 48145 | 34.3% | 10.7% | 23.3% |
| 48147 | 22.7% | 3.1% | 14.3% |
| 48163 (outer) | 1.9% | 0.2% | 0.8% |
| 48157 (outer) | 1.2% | 0.7% | 1.1% |
Note: the source workshop's "Health access" shapefile was found to be a mislabeled duplicate of the Education layer (identical geometry, school names under a health-access filename). The health figures shown here are recomputed from the correct pharmacy/clinic point layer (201 facilities), not the duplicate.
The source study's own reading holds up under the numbers: every category shows the same shape — strong central overlap, thinning coverage moving outward, with the bicycle network doing the work of closing the gap the 400m walking buffer leaves behind in the outer postal codes.