Abstract
Land use and transport shape our cities. The central place of integrated land use transport strategy in improving urban sustainability has been a widespread acceptance. The purpose of this research is to investigate the relationship between land use/land cover types and transport characteristics. Traffic zones, as the spatial analysis unit, are generated by partitioning parcels with single land use/land cover type. Driving accessibility, cycling accessibility and walking accessibility are proposed to quantify the transport characteristics of traffic zones. Taking Eindhoven, the Netherlands as study area, the three accessibility patterns differ but all show strong positive spatial autocorrelation. Clustering method is adopted to synthesize accessibility indicators and group traffic zones with similar transport characteristics into clusters. An contingency table analysis indicates that land use/land cover types are significantly associated with clusters, on which the validation and quantification of experience in the relationship of land use/land cover and transport are based: residential area and commercial area mainly concentrate in high accessible clusters (6 and 7); industrial area and open space tend to favor clusters (4 and 6) with adequate driving accessibility; the high percentage of natural area in medium accessible clusters (4 and 5), especially in less accessible clusters (1, 2 and 3) corroborates the low demands of natural area on mobility service. Clustering map and accessibility patterns can identify the gaps in coverage of mobility service and in efficiency of land use/land cover pattern. The applicability of these tools is demonstrated by two cases. Recommendations for urban planning are obtained from this study considering both land use and transport aspects.
Original language | English |
---|---|
Pages (from-to) | 923-940 |
Number of pages | 18 |
Journal | Applied Spatial Analysis and Policy |
Volume | 12 |
Issue number | 4 |
Early online date | 25 Oct 2018 |
DOIs | |
Publication status | Published - 1 Dec 2019 |
Keywords
- Accessibility
- Clustering analysis
- Land use/land cover type
- Transport characteristics