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Fine-Resolution Wetland Mapping in the Yellow River Basin Using Sentinel-1/2 Data via Zoning-Based Random Forest with Remote Sensing Feature Preferences

Accurate wetland classification in the Yellow River Basin (YRB) is crucial for China’s ecological security, sustainable development, and wetland resource management. This calls for more sustained research on regional variations and studies on remote sensing features, especially with temporal conside...

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Bibliographic Details
Published in:Water (Basel) 2024-09, Vol.16 (17), p.2415
Main Authors: Huo, Xuanlin, Niu, Zhenguo
Format: Article
Language:English
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Summary:Accurate wetland classification in the Yellow River Basin (YRB) is crucial for China’s ecological security, sustainable development, and wetland resource management. This calls for more sustained research on regional variations and studies on remote sensing features, especially with temporal considerations. To address this and the optimization of feature extraction as well as ranking, Sentinel-1 and Sentinel-2 images were used. Additionally, to achieve more precise wetland classification, the YRB was subdivided into four regions for random forest classification. The results show that different remote sensing indices effectively distinguish various wetland types and that key percentiles play a significant role in distinguishing wetland types. The 10 m refined wetland classification map for 2020, with an overall accuracy of 85%, demonstrates that this framework can meet the needs of conventional large-scale wetland analysis and management. The total area of wetlands in the YRB in 2020 was 33,554.67 km2, mainly distributed in the upper reaches of the YRB (71%), with seasonal marshes being predominant. The total water area reached 8538.64 km2, primarily distributed in the upper reaches of the YRB (57.40%). This high-resolution wetland map offers crucial insights and tools for monitoring, protecting wetland resources, and shaping policies, advancing regional sustainable development goals.
ISSN:2073-4441
2073-4441
DOI:10.3390/w16172415