FY4A cloud detection based on EfficientNetV2

Chao Wan; Cuifang Zhao Sr.; Yongle Tian; Haibin Chen; Lei Jin

doi:10.1117/12.3033725

13 June 2024 FY4A cloud detection based on EfficientNetV2

Chao Wan, Cuifang Zhao Sr., Yongle Tian, Haibin Chen, Lei Jin

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 131801Z (2024) https://doi.org/10.1117/12.3033725
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

Optical remote sensing cloud detection is the basis of quantitative remote sensing and remote sensing application, Aiming at the problems of single cloud detection method and cumbersome label making, The multi-channel data of the geostationary orbit radiation Imager (AGRI) on the domestic FY4A satellite was selected as the research object, Cross-polarized cloud-aerosol Lidar (CALIOP) was used as the reference object, Achieve all-weather, all-terrain and efficient cloud detection, Through spatio-temporal matching, the overall accuracy of FY4A official cloud detection product is about 85.1%. Through regional similarity, image processing and other methods, Improved EfficientNetV2 model. The overall accuracy of the model is more than 89.9%, It is higher than the accuracy rate of FY4A official cloud detection products, providing a new reference for the research of cloud detection related products.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chao Wan, Cuifang Zhao Sr., Yongle Tian, Haibin Chen, and Lei Jin "FY4A cloud detection based on EfficientNetV2", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 131801Z (13 June 2024); https://doi.org/10.1117/12.3033725

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