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)
OBJECTIVE Rapid nondestructive determination of salvianolic acid B and tanshinone IIA in Radix Salviae Miltiorrhizae with near-infrared reflectance spectroscopy. METHOD A quantitive model was built up with near-infrared diffuse reflectance spectroscopy. RESULTS The RMSEP in quantitative calibration model for salvianolic acid B and tanshinone IIA were(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)
Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data.Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by(More)
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