A Structure Identification Method for Urban Agglomeration Based on Nighttime Light Data and Railway Data

The urban spatial structure is a key feature of the distribution social and economic resources. an agglomeration abstract relationship expression urbanization. Urban agglomerations develop for multiple reasons, including planning natural evolution. To date, most research related to has been based on single data source, which limitation. This aims propose identification method via complex network nighttime light railway data. Firstly, we extracted built-up area using defense meteorological satellite program/operational line scanner (DMSP/OLS) data, divided it into objects obtain (NLUN) by borough. Secondly, aggregated stations at municipal level operation (RUN). Following this, established composite (CUN) consisting NLUN RUN adjacency matrix. Finally, Louvain algorithm comprehensive strength index (CSI) were used detect communities central nodes CUN core cities. results show that best accuracy, 5.72% 15.94% higher than RUN, respectively. Core cities in identified CSI are least 3.04% those single-source network. In addition, pattern Chinese study expressed as “three vertical”, development shows unbalanced trend.