Evaluation of the Impact of Morphological Differences on Scale Effects in Green Tide Area Estimation
Green tide area is a crucial indicator for monitoring green tide dynamics. However, scale effects arising from differences in image resolution can lead to estimation errors. Current pixel-level and sub-pixel-level methods often overlook the impact of morphological differences across varying resoluti...
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MDPI AG
2025-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/2/326 |
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| author | Ke Wu Tao Xie Jian Li Chao Wang Xuehong Zhang Hui Liu Shuying Bai |
| author_facet | Ke Wu Tao Xie Jian Li Chao Wang Xuehong Zhang Hui Liu Shuying Bai |
| author_sort | Ke Wu |
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| description | Green tide area is a crucial indicator for monitoring green tide dynamics. However, scale effects arising from differences in image resolution can lead to estimation errors. Current pixel-level and sub-pixel-level methods often overlook the impact of morphological differences across varying resolutions. To address this, our study examines the influence of morphological diversity on green tide area estimation using GF-1 WFV data and the Virtual-Baseline Floating macroAlgae Height (VB-FAH) index at a 16 m resolution. Green tide patches were categorized into small, medium, and large sizes, and morphological features such as elongation, compactness, convexity, fractal dimension, and morphological complexity were designed and analyzed. Machine learning models, including Extra Trees, LightGBM, and Random Forest, among others, classified medium and large patches into striped and non-striped types, with Extra Trees achieving outstanding performance (accuracy: 0.9844, kappa: 0.9629, F1-score: 0.9844, MIoU: 0.9637). The results highlighted that large patches maintained stable morphological characteristics across resolutions, while small and medium patches were more sensitive to scale, with increased estimation errors at lower resolutions. Striped patches, particularly among medium patches, were more sensitive to scale effects compared to non-striped ones. The study suggests that incorporating morphological features of patches, especially in monitoring striped and small patches, could be a key direction for improving the accuracy of green tide monitoring and dynamic change analysis. |
| format | Article |
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| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-b54f1542376c4a87946eb305d57922b32025-01-24T13:48:08ZengMDPI AGRemote Sensing2072-42922025-01-0117232610.3390/rs17020326Evaluation of the Impact of Morphological Differences on Scale Effects in Green Tide Area EstimationKe Wu0Tao Xie1Jian Li2Chao Wang3Xuehong Zhang4Hui Liu5Shuying Bai6School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Electronics and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaGreen tide area is a crucial indicator for monitoring green tide dynamics. However, scale effects arising from differences in image resolution can lead to estimation errors. Current pixel-level and sub-pixel-level methods often overlook the impact of morphological differences across varying resolutions. To address this, our study examines the influence of morphological diversity on green tide area estimation using GF-1 WFV data and the Virtual-Baseline Floating macroAlgae Height (VB-FAH) index at a 16 m resolution. Green tide patches were categorized into small, medium, and large sizes, and morphological features such as elongation, compactness, convexity, fractal dimension, and morphological complexity were designed and analyzed. Machine learning models, including Extra Trees, LightGBM, and Random Forest, among others, classified medium and large patches into striped and non-striped types, with Extra Trees achieving outstanding performance (accuracy: 0.9844, kappa: 0.9629, F1-score: 0.9844, MIoU: 0.9637). The results highlighted that large patches maintained stable morphological characteristics across resolutions, while small and medium patches were more sensitive to scale, with increased estimation errors at lower resolutions. Striped patches, particularly among medium patches, were more sensitive to scale effects compared to non-striped ones. The study suggests that incorporating morphological features of patches, especially in monitoring striped and small patches, could be a key direction for improving the accuracy of green tide monitoring and dynamic change analysis.https://www.mdpi.com/2072-4292/17/2/326green tide areascale effectsmorphological featurefractal dimensionstriped patchesresolution sensitivity |
| spellingShingle | Ke Wu Tao Xie Jian Li Chao Wang Xuehong Zhang Hui Liu Shuying Bai Evaluation of the Impact of Morphological Differences on Scale Effects in Green Tide Area Estimation Remote Sensing green tide area scale effects morphological feature fractal dimension striped patches resolution sensitivity |
| title | Evaluation of the Impact of Morphological Differences on Scale Effects in Green Tide Area Estimation |
| title_full | Evaluation of the Impact of Morphological Differences on Scale Effects in Green Tide Area Estimation |
| title_fullStr | Evaluation of the Impact of Morphological Differences on Scale Effects in Green Tide Area Estimation |
| title_full_unstemmed | Evaluation of the Impact of Morphological Differences on Scale Effects in Green Tide Area Estimation |
| title_short | Evaluation of the Impact of Morphological Differences on Scale Effects in Green Tide Area Estimation |
| title_sort | evaluation of the impact of morphological differences on scale effects in green tide area estimation |
| topic | green tide area scale effects morphological feature fractal dimension striped patches resolution sensitivity |
| url | https://www.mdpi.com/2072-4292/17/2/326 |
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