Impervious surface mapping is essential for urban environmental studies. Spectral Mixture Analysis (SMA) and its extensions are widely employed in impervious surface estimation from medium-resolution images. For SMA, inappropriate endmember combinations and inadequate endmember classes have been recognized as the primary reasons for estimation errors. Meanwhile, the spectral-only SMA, without considering urban spatial distribution, fails to consider spectral variability in an adequate manner. The lack of endmember class diversity and their spatial variations lead to over/underestimation. To mitigate these issues, this study integrates a hierarchical strategy and spatially varied endmember spectra to map impervious surface abundance, taking Wuhan and Wuzhou as two study areas. Specifically, the piecewise convex multiple-model endmember detection algorithm is applied to automatically hierarch-ize images into three regions, and distinct endmember combinations are independently developed in each region. Then, spatially varied endmember spectra are synthesized through neighboring spectra using the distance-based weight. Comparative analysis indicates that the proposed method achieves better performance than Hierarchical SMA and Fixed Four- endmembers SMA in terms of MAE, SE, and RMSE. Further analysis suggests that the hierarch-ical strategy can expand endmember class types and considerably improve the performance for the study areas in general, specifically in less developed areas. Moreover, we find that spatially varied endmember spectra facilitate the reduction of heterogeneous surface material variations and achieve the improved performance in developed areas.

Zhenfeng Shao;Yuan Zhang;Cheng Zhang;Xiao Huang;Tao Cheng

State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan,China;Department of Geosciences,University of Arkansas,Fayetteville,AR,USA

地球空间信息科学学报（英文版）

[1]Zhenfeng Shao;Yuan Zhang;Cheng Zhang;Xiao Huang;Tao Cheng-.Mapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution)[J].地球空间信息科学学报（英文版）,2022(04):550-567

Impervious,Wuzhou,hierarch

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