Dortmund GWR Coefficient Monitor

Per-cell local coefficients from single-scale adaptive Geographically Weighted Regression, fit independently for 2015, 2025, and 2035 on the same 1,493-cell landscape-metrics grid used in the companion MGWR/SDM regime study. Local R² shows where each metric's model fits well; coefficient layers show how a specific covariate's local effect varies across the city and over time.

Metric
Layer
Year
Hover a cell for details.
Data & methodology ▾

Grid: 1,493 landscape-metric analysis cells across Dortmund's twelve Stadtbezirke, each assigned to one of five spatial regimes (Core, North, South, East, West City) — the same regimes used by the companion Spatial Durbin regime model.

Model: single-scale GWR (adaptive bisquare kernel), fit independently per metric and per year at that model's own optimal bandwidth — not a fixed bandwidth reused across years.

Metric201520252035
Built-up PD205205145
Veg. Cohesion608657860
Veg. PD253194209

Local R² is the model's goodness-of-fit at that specific cell. coef(X) is that cell's local regression coefficient for standardized covariate X — positive (blue) means X and the metric move together locally, negative (red) means they move oppositely.

Dashed outline flags a cell whose coefficient is more than 3 standard deviations from the layer's mean — a sign of local estimation instability (common at the edge of a bandwidth's neighbour set), not necessarily a substantive effect.

All nine models were refit live from the source shapefiles for this map, at each year's known optimal bandwidth — the values here are not copied from the static notebook figures.

Grid geometry reprojected to WGS84 and simplified for web delivery. See the full case study for the underlying coefficient-snapshot maps and cross-metric comparison.