The sub-pixel impervious surface percentage（SPIS） is the fraction of impervious surface area in one pixel,and it is an important indicator of urbanization.Using remote sensing data,the spatial distribution of SPIS values over large areas can be extracted,and these data are significant for studies of urban climate,environment and hydrology.To develop a stabilized,multi-temporal SPIS estimation method suitable for typical temperate semi-arid climate zones with distinct seasons,an optimal model for... 

【文章來(lái)源】：Chinese Geographical Science. 2017,27(04)

【文章頁(yè)數(shù)】：12 頁(yè)

【文章目錄】：
1 Introduction
2 Materials and Methods
    2.1 Study area
    2.2 Data and processing
    2.3 Methods
        2.3.1 CART algorithm
        2.3.2 Training-test data collection
        2.3.3 CART modeling and validation
3 Results and Analyses
    3.1 CART modeling and accuracy assessment
    3.2 Regional extension of model and input vari-able selection
        3.2.1 Overall assessment of regional modeling
        3.2.2 Analysis of modeling with NLT data
        3.2.3 Analysis of modeling using multi-seasonal im-ages
    3.3 Final CART model and SPIS results
    3.4 Multi-temporal SPIS mapping
4 Discussion
    4.1 Effect of bands selection on the SPIS estimates
    4.2 Accuracy assessment in different categories of SPIS
5 Conclusions


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