Runzhe Tao1, *, Yonghong Zhang1, Lihua Wang1, Pengyan Cai1, Haowen Tan2
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2455-2474, 2020, DOI:10.32604/cmc.2020.011526
Abstract Aiming at the problem of radar base and ground observation stations on the
Tibet is sparsely distributed and cannot achieve large-scale precipitation monitoring. UNet, an advanced machine learning (ML) method, is used to develop a robust and rapid
algorithm for precipitating cloud detection based on the new-generation geostationary
satellite of FengYun-4A (FY-4A). First, in this algorithm, the real-time multi-band
infrared brightness temperature from FY-4A combined with the data of Digital Elevation
Model (DEM) has been used as predictor variables for our model. Second, the efficiency
of the feature was improved by changing the traditional convolution layer serial
connection method of… More >
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