4.7 Article

Environmental degradation in the urban areas of China: Evidence from multi-source remote sensing data

期刊

REMOTE SENSING OF ENVIRONMENT
卷 193, 期 -, 页码 65-75

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2017.02.027

关键词

Environmental conditions; Multi-source remote sensing; Multi-scale analysis; Urban expansion; China

资金

  1. National Natural Science Foundation of China [41621061, 41501092]
  2. National Basic Research Program of China [2014CB954302, 2014CB954303]
  3. project of New Century Excellent Teacher from Ministry of Education of China [NCET-13-0053]

向作者/读者索取更多资源

The rapid and timely evaluation of urban environmental change is highly important for understanding urban sustainability in China. However, the comprehensive understanding of urban environmental change in China based on multi-source remote sensing data remains inadequate because current studies have mainly focused on a single aspect of the urban environment using a specific source of remote sensing data. In this study, we developed a comprehensive evaluation index (CEI) combining the remote sensing data of the fine particulate matter (PM2.5) concentration, land surface temperature (1ST) and vegetation cover (VC) to assess the urban environmental change in China at the national scale, among urban agglomerations and across the rapidly urbanized regions. We found a trend of environmental degradation in the urban areas of China between 2000 and 2012. Environmentally degraded and moderately degraded urban areas accounted for 48.14% of the total urban area in China. In particular, the expanded urban areas exhibited the most extensive environmental degradation, with 52.33% of the total expanded urban areas from 1992 to 2012 exhibiting environmental degradation or moderately environmental degradation. The increase in the PM2.5 concentration was one of the main manifestations of the environmental degradation in the expanded urban areas. We suggest that more attention should be paid to urban environmental issues during future urban development in China. (C) 2017 Elsevier Inc. All rights reserved.

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