27 December 2017 Monitoring evolving urban cluster systems using DMSP/OLS nighttime light data: a case study of the Yangtze River Delta region, China
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Abstract
The assessment of the dynamic urban structure has been affected by lack of timely and accurate spatial information for a long period, which has hindered the measurements of structural continuity at the macroscale. Defense meteorological satellite program’s operational linescan system (DMSP/OLS) nighttime light (NTL) data provide an ideal source for urban information detection with a long-time span, short-time interval, and wide coverage. In this study, we extracted the physical boundaries of urban clusters from corrected NTL images and quantitatively analyzed the structure of the urban cluster system based on rank-size distribution, spatial metrics, and Mann–Kendall trend test. Two levels of urban cluster systems in the Yangtze River Delta region (YRDR) were examined. We found that (1) in the entire YRDR, the urban cluster system showed a periodic process, with a significant trend of even distribution before 2007 but an unequal growth pattern after 2007, and (2) at the metropolitan level, vast disparities exist in four metropolitan areas for the fluctuations of Pareto’s exponent, the speed of cluster expansion, and the dominance of core cluster. The results suggest that the extracted urban cluster information from NTL data effectively reflect the evolving nature of regional urbanization, which in turn can aid in the planning of cities and help achieve more sustainable regional development.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Zhao Wang, Zhao Wang, Shan Yang, Shan Yang, Shuguang Wang, Shuguang Wang, Yan Shen, Yan Shen, } "Monitoring evolving urban cluster systems using DMSP/OLS nighttime light data: a case study of the Yangtze River Delta region, China," Journal of Applied Remote Sensing 11(4), 046029 (27 December 2017). https://doi.org/10.1117/1.JRS.11.046029 . Submission: Received: 23 July 2017; Accepted: 1 December 2017
Received: 23 July 2017; Accepted: 1 December 2017; Published: 27 December 2017
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