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Open AccessArticle

Characterizing the Growth Patterns of 45 Major Metropolitans in Mainland China Using DMSP/OLS Data

by Tao Jia 1,2, Kai Chen 1 and Jiye Wang 3,*
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, China
Department of Information and Communication, State Grid Corporation of China, Beijing 100031, China
Author to whom correspondence should be addressed.
Academic Editors: Bailang Yu, Yuyu Zhou, Chunyang He, Xiaofeng Li, James Campbell and Prasad S. Thenkabail
Remote Sens. 2017, 9(6), 571;
Received: 12 April 2017 / Revised: 25 May 2017 / Accepted: 4 June 2017 / Published: 7 June 2017
(This article belongs to the Special Issue Recent Advances in Remote Sensing with Nighttime Lights)
Understanding growth patterns at the metropolitan level is instructive for better planning and policy making on sustainable urban development. Using DMSP/OLS data from 1992 to 2013, this article aims to investigate growth patterns of major metropolitans in Mainland China from the aspects of intensification and expansion. We start by calibrating the DMSP/OLS data and selecting 45 major metropolitans. On intensification, results suggest that aggregately, metropolitans displayed cyclical pattern over time and large metropolitans tended to have higher levels of intensification than moderate or small ones. Individually, metropolitans with similar intensification over time could be clustered together using Dendrogram, and evolution pattern of the clusters exhibited similarity to the aggregated one. On expansion, results show that aggregately metropolitans displayed a decreasing trend over time, and moderate or small metropolitans tended to have higher levels of expansion than large ones. Particularly, moderate metropolitans were more likely to expand adjacently, and small ones were more likely to experience scatter or corridor expansion. Each metropolitan can be represented by a mixed expansion model over time, which might tell where and how much expansion occurred in the current year. Furthermore, intensification is highly correlated with expansion over time for small metropolitans, but they are poorly correlated for large or moderate ones. Lastly, the high correlation of intensification and expansion with the change of GDP in each year indicates the reliability of our work. View Full-Text
Keywords: DMSP/OLS data; metropolitan growth; intensification; expansion; sustainable urban development DMSP/OLS data; metropolitan growth; intensification; expansion; sustainable urban development
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MDPI and ACS Style

Jia, T.; Chen, K.; Wang, J. Characterizing the Growth Patterns of 45 Major Metropolitans in Mainland China Using DMSP/OLS Data. Remote Sens. 2017, 9, 571.

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