Acta Geodaetica et Cartographica Sinica ›› 2018, Vol. 47 ›› Issue (11): 1466-1473.doi: 10.11947/j.AGCS.2018.20170353

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Analysis on the Driving Factors of Urban Expansion Policy Based on DMSP/OLS Remote Sensing Image

WANG Taoyang1, ZHANG Guo2, LI Peiran3, LI Fangting2, GUO Xueyao2   

  1. 1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
    2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
    3. Chengdu Xindu District Traffic and Transportation Bureau, Chengdu 610500, China
  • Received:2017-06-26 Revised:2018-07-30 Online:2018-11-20 Published:2018-11-29
  • Supported by:
    The Key Research and Development Program of Ministry of Science and Technology of China(Nos. 2018YFB0504905;2016YFB0500801);The National Natural Science Foundation of China (Nos. 41374038;41204022;41674041)

Abstract: The speed and direction of urban expansion has become the focus of social concern, and it is a research hotspot in recent years that using night-light remote sensing for urban expansion driving force analysis of the causes. The average annual Chinese regional night-light image data is adopted that obtained by DMSP satellites. First of all, relative radiation correction is performed for 1992-2012, a total of 21 years of time-dependent night-light images. Secondly urban built area is extracted by empirical threshold method, and accuracy is verified through the Landsat images. Finally, the econometric model is introduced, the political cycle of the administrative officials of the prefecture-level city is the explanatory variable. It is analyzed the policy driving factors of the expansion of the prefecture-level cities from 1992 to 2012. Through the analysis of this article, we can see that the change of the political cycle of the administrative officials has a significant impact on the direction of urban expansion.

Key words: DMSP satellite image, night-light remote sensing, urban expansion, administrative officials, political cycle, correlation

CLC Number: