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What is Snow Depth Retrieval with Sentinel-1 Data about?

This study investigates snow depth retrieval using Sentinel-1 radar data, comparing Random Forest (RF) and Support Vector Machine (SVM) models optimized with simulated annealing. The RF model outperforms the SVM model, achieving a high correlation with in situ measurements in the Xinjiang region, while the SVM model shows lower predictive accuracy. The findings highlight the potential of machine learning techniques in enhancing snow depth estimation through active microwave remote sensing methods.

Author

chpunlan

Language

EN