首页|Tsinghua University Reports Findings in Machine Learning (An improved remote sen sing reference evapotranspiration estimation by simple satellite data and machin e learning)
Tsinghua University Reports Findings in Machine Learning (An improved remote sen sing reference evapotranspiration estimation by 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 news originatingfrom Beijing, People’s Repu blic of China, by NewsRx correspondents, research stated, “Referenceevapotransp iration (ET) estimation is crucial for efficient irrigation planning, optimized water managementand ecosystem modeling, yet it presents significant challenges, particularly when meteorological dataavailability is limited. This study utili zed remote sensing data of land surface temperature (LST), dayof year, and lati tude, and employed a machine learning approach (e.g., random forest) to develop animproved remote sensing ET model.”
BeijingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningRemote Sensing
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