Impervious surface extraction based on different methods from multiple spatial resolution images: a comprehensive comparison
Many efforts have been devoted to extracting impervious surfaces based on different methods from multiple spatial resolution images. Differences in extraction methods and spatial resolutions are significant and have led to discrepant performances in terms of the impervious surface extraction accurac...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-09-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/17538947.2021.1936227 |
| _version_ | 1797678515464699904 |
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| author | Shanshan Feng Fenglei Fan |
| author_facet | Shanshan Feng Fenglei Fan |
| author_sort | Shanshan Feng |
| collection | DOAJ |
| description | Many efforts have been devoted to extracting impervious surfaces based on different methods from multiple spatial resolution images. Differences in extraction methods and spatial resolutions are significant and have led to discrepant performances in terms of the impervious surface extraction accuracy. However, which extraction method is more suitable for which kind of spatial resolution image in practice is poorly understood. This study systematically compared the performances of 12 methods of impervious surface extraction for four spatial resolution images (i.e. Landsat 8 [30 m], Sentinel-2A [20 m], Sentinel-2A [10 m], and Gaofen-2 [4 m]) in three testing areas. The results indicated that for the medium-spatial resolutions of 30 and 20 m, the support vector machine (SVM) method was considered as the optimal classification method with the highest accuracy of impervious surface extraction. For the high-spatial resolutions of 10 and 4 m, the object based image analysis (OBIA) method obtained the highest accuracy of the impervious surface distribution. Furthermore, the perpendicular impervious surface index (PISI) outperformed the other indices in obtaining the impervious surface distribution, with the highest accuracy for four spatial resolution images. These comprehensive assessments can provide a valuable guidance for future impervious surface extraction from different spatial resolutions. |
| first_indexed | 2024-03-11T23:00:55Z |
| format | Article |
| id | doaj.art-cf5e15426d514e9393edfc2a7453d429 |
| institution | Directory Open Access Journal |
| issn | 1753-8947 1753-8955 |
| language | English |
| last_indexed | 2024-03-11T23:00:55Z |
| publishDate | 2021-09-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj.art-cf5e15426d514e9393edfc2a7453d4292023-09-21T14:57:10ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552021-09-011491148117410.1080/17538947.2021.19362271936227Impervious surface extraction based on different methods from multiple spatial resolution images: a comprehensive comparisonShanshan Feng0Fenglei Fan1South China Normal UniversitySouth China Normal UniversityMany efforts have been devoted to extracting impervious surfaces based on different methods from multiple spatial resolution images. Differences in extraction methods and spatial resolutions are significant and have led to discrepant performances in terms of the impervious surface extraction accuracy. However, which extraction method is more suitable for which kind of spatial resolution image in practice is poorly understood. This study systematically compared the performances of 12 methods of impervious surface extraction for four spatial resolution images (i.e. Landsat 8 [30 m], Sentinel-2A [20 m], Sentinel-2A [10 m], and Gaofen-2 [4 m]) in three testing areas. The results indicated that for the medium-spatial resolutions of 30 and 20 m, the support vector machine (SVM) method was considered as the optimal classification method with the highest accuracy of impervious surface extraction. For the high-spatial resolutions of 10 and 4 m, the object based image analysis (OBIA) method obtained the highest accuracy of the impervious surface distribution. Furthermore, the perpendicular impervious surface index (PISI) outperformed the other indices in obtaining the impervious surface distribution, with the highest accuracy for four spatial resolution images. These comprehensive assessments can provide a valuable guidance for future impervious surface extraction from different spatial resolutions.http://dx.doi.org/10.1080/17538947.2021.1936227impervious surfacemethod comparisonspatial scalelandsatsentinelgf-2 |
| spellingShingle | Shanshan Feng Fenglei Fan Impervious surface extraction based on different methods from multiple spatial resolution images: a comprehensive comparison International Journal of Digital Earth impervious surface method comparison spatial scale landsat sentinel gf-2 |
| title | Impervious surface extraction based on different methods from multiple spatial resolution images: a comprehensive comparison |
| title_full | Impervious surface extraction based on different methods from multiple spatial resolution images: a comprehensive comparison |
| title_fullStr | Impervious surface extraction based on different methods from multiple spatial resolution images: a comprehensive comparison |
| title_full_unstemmed | Impervious surface extraction based on different methods from multiple spatial resolution images: a comprehensive comparison |
| title_short | Impervious surface extraction based on different methods from multiple spatial resolution images: a comprehensive comparison |
| title_sort | impervious surface extraction based on different methods from multiple spatial resolution images a comprehensive comparison |
| topic | impervious surface method comparison spatial scale landsat sentinel gf-2 |
| url | http://dx.doi.org/10.1080/17538947.2021.1936227 |
| work_keys_str_mv | AT shanshanfeng impervioussurfaceextractionbasedondifferentmethodsfrommultiplespatialresolutionimagesacomprehensivecomparison AT fengleifan impervioussurfaceextractionbasedondifferentmethodsfrommultiplespatialresolutionimagesacomprehensivecomparison |