Mapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution
ABSTRACTImpervious 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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-10-01
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| Series: | Geo-spatial Information Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2022.2028535 |
| _version_ | 1811205481414262784 |
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| author | Zhenfeng Shao Yuan Zhang Cheng Zhang Xiao Huang Tao Cheng |
| author_facet | Zhenfeng Shao Yuan Zhang Cheng Zhang Xiao Huang Tao Cheng |
| author_sort | Zhenfeng Shao |
| collection | DOAJ |
| description | ABSTRACTImpervious 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 hierarchize 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 hierarchical 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. |
| first_indexed | 2024-04-12T03:33:30Z |
| format | Article |
| id | doaj.art-a49a4905d24b4f64bbce144cf73c09eb |
| institution | Directory Open Access Journal |
| issn | 1009-5020 1993-5153 |
| language | English |
| last_indexed | 2024-04-12T03:33:30Z |
| publishDate | 2022-10-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geo-spatial Information Science |
| spelling | doaj.art-a49a4905d24b4f64bbce144cf73c09eb2022-12-22T03:49:30ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532022-10-0125455056710.1080/10095020.2022.2028535Mapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distributionZhenfeng Shao0Yuan Zhang1Cheng Zhang2Xiao Huang3Tao Cheng4State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan, ChinaDepartment of Geosciences, University of Arkansas, Fayetteville, AR, USAState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan, ChinaABSTRACTImpervious 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 hierarchize 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 hierarchical 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.https://www.tandfonline.com/doi/10.1080/10095020.2022.2028535Impervious surfaceSpectral Mixture Analysis(SMA)hierarchical strategyendmember classspatially varied endmember spectra |
| spellingShingle | Zhenfeng Shao Yuan Zhang Cheng Zhang Xiao Huang Tao Cheng Mapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution Geo-spatial Information Science Impervious surface Spectral Mixture Analysis(SMA) hierarchical strategy endmember class spatially varied endmember spectra |
| title | Mapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution |
| title_full | Mapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution |
| title_fullStr | Mapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution |
| title_full_unstemmed | Mapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution |
| title_short | Mapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution |
| title_sort | mapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution |
| topic | Impervious surface Spectral Mixture Analysis(SMA) hierarchical strategy endmember class spatially varied endmember spectra |
| url | https://www.tandfonline.com/doi/10.1080/10095020.2022.2028535 |
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