Urban Spatial Aggregation Issues in Transportation: A New Homogeneity-Related Zone System

Delineating urban land use patterns and the close relation to transport has long been a core research topic, in which most are analyzed at aggregate level from a macroscopic perspective. This study tended to create a new homogeneity-related zone system from the basic grid cells and examining if the improved system outperforms than traditional zone systems when conducting aggregate analysis in transportation. Within ride-hailing schemes, the selection process of drop-off locations of each trip is fully recorded by the mobile transportation platform, which offers a promising way in addressing the spatial aggregation issue. Specifically, on the basis of destination retrieval record (DRR) data, this study explored the potential relevance among them and built homogeneity pairs. Based on the improved cluster algorithm, homogeneity pairs are used to aggregate basic grid cells into the homogeneous traffic analysis zones (HTAZs) that are high in inter-zone consistency. The third ring area of Chengdu City as a case study was divided into 260 HTAZs using the proposed partition approach. Newly developed homogeneity-related zone system performs better than traditional systems in terms of geometry and internal consistency. Findings from this study also suggest that the zone partition should maintain internal consistency, namely homogeneity, as much as possible so that the aggregate-level spatial units can reflect and summarize the features of intra-zone individuals. This study demonstrates the mining potential of trip record data within transport systems, and provides a more reliable spatial structure to reveal travel patterns and conduct transportation design.