首页|New Machine Learning Study Findings Reported from Chinese Academy of Sciences (S urface Soil Moisture From Combined Active and Passive Microwave Observations: In tegrating Ascat and Smap Observations Based On Machine Learning Approaches)
New Machine Learning Study Findings Reported from Chinese Academy of Sciences (S urface Soil Moisture From Combined Active and Passive Microwave Observations: In tegrating Ascat and Smap Observations Based On Machine Learning Approaches)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news reporting originating in Beijing, People’s Republic of China, by NewsRx journalists, research stated, “The fusion of active and pas sive microwave measurements is expected to provide more robust surface soil mois ture (SSM) mapping across various environmental conditions compared to the use o f a single sensor. Thus, the integration of the newest L-band passive (i.e., Soi l Moisture Active Passive, SMAP) and the active (i.e., the Advanced Scatteromete r, ASCAT) observations provides an opportunity for SSM mapping with improved acc uracy.”
BeijingPeople's Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningChinese Academy of Sciences
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