Chun-Xiang Shi

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The crowning objective of this research was to identify a better cloud classification method to upgrade the current window-based clustering algorithm used operationally for China's first operational geostationary meteorological satellite FengYun-2C (FY-2C) data. First, the capabilities of six widely-used Artificial Neural Network (ANN) methods are analyzed,(More)
Although cumulonimbus (Cb) clouds are the main source of precipitation in south China, the relationship between Cb cloud characteristics and precipitation remains unclear. Accordingly, the primary objective of this study was to thoroughly analyze the relationship between Cb cloud features and precipitation both at the pixel and cloud patch scale, and then(More)
Based on the satellite data such as precipitation estimation, incident radiation, brightness temperature etc. and the assimilation data of CLSMDAS, combined with B-P neural network to develop a new model of soil moisture monitoring. The model mining the relationship between the soil moisture and the satellite products, then calculate the weight and build(More)
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