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Evaluating Urbanization and Spatial-Temporal Pattern Using the DMSP/OLS Nighttime Light Data: A Case Study in Zhejiang Province

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  • Pengfei Xu
  • Pingbin Jin
  • Yangfan Yang
  • Quan Wang

Abstract

The application of DMSP/OLS nighttime light data provides an effective measure for characterizing urbanization and its spatial-temporal changes. Combined with the social economic statistics and calibrated nighttime data, the nighttime light imagery of Zhejiang province was fully intercalibrated during the period 1992–2013. The backgrounds were explained and the model of region light index (RLI) was built to make further research. The methods of mutation detection, regression analysis, and spatial analysis were adopted in this study. The results show that the urbanization progress of Zhejiang experienced a transformation from rapid development to steady improvement and was accompanied by a changing direction of urban expansion from coastal to inland areas from 2000. Further research indicated that Zhejiang province possessed a relative high level of urbanization, where a spatial pattern of urbanization with one center and four axes was initially formed. It is a novel attempt to investigate the urbanization of Zhejiang province on the basis of the DMSP/OLS night-lighting data, which may provide a significant guideline for the urban planning and development.

Suggested Citation

  • Pengfei Xu & Pingbin Jin & Yangfan Yang & Quan Wang, 2016. "Evaluating Urbanization and Spatial-Temporal Pattern Using the DMSP/OLS Nighttime Light Data: A Case Study in Zhejiang Province," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-8, November.
    • Handle: RePEc:hin:jnlmpe:9850890
    DOI: 10.1155/2016/9850890
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    Cited by:

    1. Tingting Xu & Yunting Zong & Heng Su & Aohua Tian & Jay Gao & Yurui Wang & Ruiqi Su, 2023. "Prediction of Multi-Scale Socioeconomic Parameters from Long-Term Nighttime Lights Satellite Data Using Decision Tree Regression: A Case Study of Chongqing, China," Land, MDPI, vol. 12(1), pages 1-22, January.

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