首页|Reports Summarize Machine Learning Research from Institute of Applied Physics (G lobal soil moisture mapping at 5 km by combining GNSS reflectometry and machine learning in view of HydroGNSS)
Reports Summarize Machine Learning Research from Institute of Applied Physics (G lobal soil moisture mapping at 5 km by combining GNSS reflectometry and machine learning in view of HydroGNSS)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on artificial intelligence is now available. According to news reportingoriginating from Firenze, Italy, by NewsRx correspondents, research stated, “The potential of GNSS re-flectometry (GNSS-R) for the monitoring of soil and vegetation parameters as soil moisture ( SM) andforest aboveground biomass (AGB) has been largely investigated in recent years. In view of the ESA’sHydroGNSS mission, planned to be launched in 2024, this study has explored the possibility to map SMat global scale and relatively high resolution of about 0.05° (corresponding approximately to 5 Km) usingGNSS -R observations, by implementing and comparing two retrieval algorithms based on machine learningtechniques, namely Artificial Neural Networks (ANN) and Random Forest Regressors (RF).”
Institute of Applied PhysicsFirenzeI talyEuropeCyborgsEmerging TechnologiesMachine Learning
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