Snow Depth Retrieval Using Sentinel-1 Radar Data: A Comparative Analysis of Random Forest and Support Vector Machine Models with Simulated Annealing Optimization

Snow plays a crucial role in global climate regulation, hydrological processes, and environmental change, making the accurate acquisition of snow depth data highly significant. In this study, we used Sentinel-1 radar data and employed a simulated annealing algorithm to select the optimal influencing...

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Autors principals:	Yurong Cui, Sixuan Chen, Guiquan Mo, Dabin Ji, Lansong Lv, Juan Fu
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2025-07-01
Col·lecció:	Remote Sensing
Matèries:	snow depth retrieval active microwave remote sensing machine learning feature selection comparative analysis
Accés en línia:	https://www.mdpi.com/2072-4292/17/15/2584
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