A research presentation on how proximity to recreational areas and the availability of nearby recreational spaces may relate to housing prices in Düsseldorf.
Urban green spaces and recreational amenities are increasingly recognized as important determinants of quality of life, residential attractiveness and urban housing markets (Kolbe & Wüstemann, 2015; Ramírez-Juidías et al., 2022).
How do proximity to recreational areas and the availability of nearby recreational spaces relate to housing prices in Düsseldorf?
To examine whether recreational accessibility, measured through proximity and availability indicators, is associated with housing prices in Düsseldorf.
Understanding recreational accessibility can support evidence-based planning decisions.
Environmental amenities may influence residential attractiveness and market prices.
Parks and recreational areas contribute to health, well-being and urban livability.
The project follows the logic of research methodology: research question, objective, literature review, research gap and methodology.
The literature suggests that housing prices are influenced not only by structural characteristics but also by locational and environmental amenities.
Housing prices reflect a bundle of structural, locational and environmental characteristics.
Key Sources
Rosen (1974)
Basu & Thibodeau (1998)
Geoghegan et al. (1997)
Green spaces generate environmental, social and economic value in housing markets.
Key Sources
Kolbe & Wüstemann (2015)
Ramírez-Juidías et al. (2022)
Lee & Li (2009)
Accessibility measures influence residential attractiveness and housing market outcomes.
Key Sources
Wittowsky et al. (2020)
Helbich et al. (2014)
Apparicio et al.
GIS and geospatial analysis provide new opportunities for accessibility measurement.
Key Sources
Wei et al. (2022)
OpenStreetMap Foundation
Lovelace et al. (2024)
Existing research has examined green spaces and housing prices, but several gaps remain for this specific research project.
The study is based on Hedonic Pricing Theory, which explains housing prices as the combined value of property characteristics.
Recreational accessibility is treated as an environmental amenity within the hedonic pricing framework.
Better access to recreational areas may be reflected in higher housing prices per square meter.
Recreational accessibility is operationalized through two spatial indicators: distance to the nearest recreational area and the number of recreational areas available within a 500-meter radius.
Distance from each residential property to the nearest recreational area, measured in meters.
Number of recreational areas located within a 500-meter buffer around each residential property.
A spatial accessibility concept combining proximity and local availability of recreational spaces.
Higher recreational accessibility may be associated with higher housing prices per square meter.
The workflow translates the research question into measurable spatial indicators and statistical analysis.
| Variable | Type | Measurement |
|---|---|---|
| Housing Price | Dependent Variable | €/m² |
| Distance to Recreational Area | Independent Variable | Meters |
| Number of Recreational Areas | Independent Variable | Count within 500m |
Measured as euros per square meter.
Measured in meters from each residential property.
Measured as count of recreational areas within walking distance.
Basu, S., & Thibodeau, T. G. (1998). Analysis of spatial autocorrelation in house prices. The Journal of Real Estate Finance and Economics, 17(1), 61–85. https://doi.org/10.1023/A:1007703229507
Geoghegan, J., Wainger, L. A., & Bockstael, N. E. (1997). Spatial landscape indices in a hedonic framework: An ecological economics analysis using GIS. Ecological Economics, 23(3), 251–264. https://doi.org/10.1016/S0921-8009(97)00583-1
Helbich, M., Brunauer, W., Vaz, E., & Nijkamp, P. (2014). Spatial heterogeneity in hedonic house price models: The case of Austria. Urban Studies, 51(2), 390–411. https://doi.org/10.1177/0042098013492234
Kolbe, J., & Wüstemann, H. (2015). Estimating the value of urban green space: A hedonic pricing analysis of the housing market in Cologne, Germany. SFB 649 Discussion Papers, 2015-002. Humboldt University Berlin.
Lovelace, R., Nowosad, J., & Muenchow, J. (2024). Geocomputation with R (2nd ed.). CRC Press.
OpenStreetMap Foundation. (n.d.). OpenStreetMap. https://www.openstreetmap.org/
Ramírez-Juidías, E., Pulido-Fernández, J. I., & Cabeza-Lainez, J. M. (2022). Influence of the urban green spaces of Seville (Spain) on housing prices through the hedonic assessment methodology and geospatial analysis. Sustainability, 14(24), 16613. https://doi.org/10.3390/su142416613
Rosen, S. (1974). Hedonic prices and implicit markets: Product differentiation in pure competition. Journal of Political Economy, 82(1), 34–55. https://doi.org/10.1086/260169
Wittowsky, D., Hoekveld, J., Welsch, J., & Steier, M. (2020). Residential housing prices: Impact of housing characteristics, accessibility and neighbouring apartments: A case study of Dortmund, Germany. Urban, Planning and Transport Research, 8(1), 44–70. https://doi.org/10.1080/21650020.2019.1704429
This research project investigates whether recreational accessibility is associated with housing prices in Düsseldorf.