首页|Martin Luther-University Halle-Wittenberg Reports Findings in Machine Learning ( Estimation of 100 m root zone soil moisture by downscaling 1 km soil water index with machine learning and multiple geodata)
Martin Luther-University Halle-Wittenberg Reports Findings in Machine Learning ( Estimation of 100 m root zone soil moisture by downscaling 1 km soil water index with machine learning and multiple geodata)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting from Halle Saale, Germany, by NewsRx journalists, research stated, “Root zone soil moisture(RZSM) is crucial for agricultural water management and land surface processes. The 1 km soil wat erindex (SWI) dataset from Copernicus Global Land services, with eight fixed ch aracteristic time lengths(T), requires root zone depth optimization (T) and is limited in use due to its low spatial resolution.”
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