首页|Tsinghua University Reports Findings in Machine Learning (Improved remote sensin g reference evapotranspiration estimation using@@simple satellite data and machin e learning)
Tsinghua University Reports Findings in Machine Learning (Improved remote sensin g reference evapotranspiration estimation using@@simple satellite data and machin e learning)
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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 out of Beijing, People’s Repu blic of China, by NewsRx editors, research stated, “Reference evapotranspiration (ET) estimation is crucial for efficient irrigation planning, optimized water m anagementand ecosystem modeling, yet it presents significant challenges, partic ularly when meteorological dataavailability is limited. This study utilized rem ote sensing data of land surface temperature (LST), day ofyear, and latitude, a nd employed a machine learning approach (i.e., random forest) to develop an improved remote sensing ET model.”
BeijingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningRemote Sensing
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