1. School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China 2. Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
Urban expansion caused by urbanization brings many problems to the social and ecological environment. Monitoring urban change is an entry point to solve these problems. As an important indicator of urban expansion, the impervious surface has become a hotspot of research. The acquisition of impervious surface data and its time series variation analysis are the core of the current study. Compared with early planar map-based impervious surface extraction, remote sensing has been widely used in impervious surface research due to its continuous, rapid and extensive observation of the ground. Multi-source data fusion and multiple retrieval method make constant progress in remote sensing-based retrieval of ground impervious surface percentage, and the focus of the study is gradually shifted from the classification map of impervious surface to the quantitative retrieval of impervious surface percentage. In this paper, the authors summarized the methods of remote sensing retrieval of sub-pixel impervious surface percentage from the perspectives of single period and time series, analyzed the advantages and disadvantages of the retrieval methods in detail, and briefly described and compared the common precision validation method. Finally, the authors summarized the problems existing in the current remote sensing retrieval methods, proposed the corresponding solutions, and pointed out the trend of development in the future.
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2019, Vol. 31 
), 李爱农2, 雷光斌2, 张正健2
