Research on Land Cloud Detection Algorithm Based on AGRI of Fengyun-4B Satellite - Zhang, Chen (International Journal of Computer Science and Information Technology, 2025)
Clouds are an important component of weather and climate change and have a significant impact on ecology, weather forecasting and aviation safety. Cloud detection is a preprocessing step in many satellite image processing and remote sensing inversion. Clouds not only cover the subsurface, but also absorb and scatter solar radiation, which affects the remote sensing analysis and study of the surface and reduces the utilization of data. Accurate detection of cloud-covered areas in satellite images can effectively reduce the interference of cloud cover on remote sensing data application. The Fengyun-4B Satellite is the latest generation of geostationary meteorological satellites in China, with significant performance advantages. In this paper, a land cloud detection algorithm for AGRI sensors is constructed based on the existing cloud detection algorithm using the AGRI full disk data of Fengyun 4B Satellite. Through the analysis of cloud detection product quality, the algorithm threshold is optimized to significantly improve the accuracy of cloud detection. The experimental results show that the algorithm has good overall cloud detection performance in full disk imagery, especially in the thick cloud region, but there are some misclassifications in the high brightness surface region such as the Tibetan Plateau. This study expands the application scenarios of domestic geostationary meteorological satellites, and provides new technical support for meteorological monitoring and remote sensing applications.