Detailed Classification of River Ice Types Using Sentinel-2 Imagery: A Case Study of the Inner Mongolia Reach of Yellow River

作者：Yupeng Leng, Chunjiang Li, Pai Lu, Xiaohua Hao, Xiangqian Li, Shamshodbek Akmalov, Xiang Fu, Shengbo Hu, Yu Zheng · 发表于：Remote Sensing · 年份：2026 · DOI：10.3390/rs18050672 · 被引用次数：1 · 研究领域：Arctic and Antarctic ice dynamics、Cryospheric studies and observations、Climate change and permafrost

Due to the complexity inherent in river ice dynamics, the utilization of remote sensing imagery represents the most crucial and effective method currently available for monitoring changes in river ice. In the Inner Mongolia segment of the Yellow River during winter, two distinct types of ice surfaces are observed: juxtaposed ice and consolidated ice. Additionally, certain areas of open water remain unfrozen. Rapid identification and classification of extensive ice formations and open water zones along this lengthy river section constitute critical information for informed decision-making in ice prevention and management strategies within the Yellow River basin. This paper takes the formation and characteristic analysis of different types of ice in the Yellow River channels in Inner Mongolia as the starting point. It employs a support vector machine (SVM) as the classifier and introduces an optimized model for classifying river ice types using high-resolution Sentinel-2 optical imagery. The model utilizes multi-band spectral features, along with multi-spectral fusion indices such as the normalized difference snow index (NDSI) and the normalized difference frozen surface index (NDFSI), as feature vectors. This approach attains an overall accuracy of 94.91% in classifying different types of ice and can significantly contribute to river ice monitoring by offering robust theoretical support. In the winter of 2023–2024, the proportion of juxtaposed ice on the Yellow River section i...