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Urban connectivity information is important for regional planning of sustainable development goals. However, there are still challenges in deriving the spatial connectivity relationship among urban areas. The nighttime light data measure anthropogenic phenomenon remotely and can be seen as a unique source for monitoring urban spatial expansion and human activities. This study presents an object-based approach for investigating spatial connectivity among urban patches by incorporating Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite Day/Night Band and land use data collected in 2015. A graph-based method is used to construct connectivity networks and explore spatial patterns considering both quantity and quality of connections in three vibrant urban agglomerations in China, namely, Jing-Jin-Ji (JJJ), Yangtze River Delta (YRD), and Pearl River Delta (PRD) megaregions. Results indicate that networks follow a power law distribution according to cumulative degree distributions. A closer connectivity relationship exists among urban patches in PRD, with a relatively high-intensity connection ratio and a mean degree of 4.5, compared with YRD and JJJ. Block-like connections are observed in core areas of all urban agglomerations (UAs), and single-tree connections are found in peripheral areas. This article implies a significant inequality in the regional development and hub-spoke structures with hubs of provincial capitals and municipalities. Our proposed framework is transferrable for the analysis of connectivity relationship in other regions, and the outcome can contribute to the study of evolution of UAs and bring insights to policymakers for sustainable development at regional level.

Analyzing Urban Spatial Connectivity Using Night Light Observations: A Case Study of Three Representative Urban Agglomerations in China