FY4A cloud detection based on EfficientNetV2

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.