High wind speed retrieval from SAR images using random forest algorithm

Wenjin Yang; Peng Yu; Xiaoying Cai; Xiaojing Zhong; Yuanrong He

doi:10.1117/12.3010314

15 November 2023 High wind speed retrieval from SAR images using random forest algorithm

Wenjin Yang, Peng Yu, Xiaoying Cai, Xiaojing Zhong, Yuanrong He

Proceedings Volume 12815, International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023); 128150M (2023) https://doi.org/10.1117/12.3010314
Event: International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023), 2023, Kaifeng, China

Abstract

This study provides a random forest (RF) based method to retrieve high wind speeds, which takes advantage of RF's powerful nonlinear fitting ability and prevents overfitting. The high wind speed data from the Stepping Frequency Microwave Radiometer (SFMR) are used as the reference data. Compared with two traditional GMF models, the C-band cross-polarized ocean model (C-2PO) and the C-band cross-polarized coupled parameter ocean model (C-3PO), the wind speed inversion results using the RF method have been greatly improved.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wenjin Yang, Peng Yu, Xiaoying Cai, Xiaojing Zhong, and Yuanrong He "High wind speed retrieval from SAR images using random forest algorithm", Proc. SPIE 12815, International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023), 128150M (15 November 2023); https://doi.org/10.1117/12.3010314

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