Using Tencent User Location Data to Modify Night-Time Light Data for Delineating Urban Agglomeration Boundaries - He, Xiong; Zhu, Yiting; Chang, Pengpeng; Zhou, Chunshan (Frontiers in Environmental Science, 2022)
The study of urban agglomeration boundaries is helpful to understand the internal spatial structure of urban agglomeration, evaluate the development level of urban agglomeration, and thus, assist in the formulation of regional planning and policies. However, previous studies often used only static spatial elements to delineate the boundaries of urban agglomerations, ignoring the spatial connections within urban agglomerations. In this study, night-time light and Tencent-migration data were evaluated separately and fused to delineate urban agglomeration boundaries from both static and dynamic spatial perspectives. The fusion of night-time light and Tencent-migration data had the highest accuracy in delineating urban agglomeration boundaries, which verified that the fusion of dynamic spatial elements on a single static spatial element can supplement the spatial connection of urban agglomeration. Our findings enrich the understanding of urban agglomerations, and the accurate delineation of urban agglomerations boundaries can aid urban agglomeration planning and management.