Assessing the performance of the Gaussian Process Regression algorithm to fill gaps in the time-series of daily actual evapotranspiration of different crops in temperate and continental zones using ground and remotely sensed data
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DOI: 10.1016/j.agwat.2023.108596
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Keywords
Daily actual evapotranspiration; Gap-filling; Gaussian Process Regression (GPR); Agro-meteorological and remote sensed data; Sentinel-2; MODIS;All these keywords.
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