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Improving Retrievals Of Crop Vegetation Parameters From Remote Sensing Data, Nathaniel Levitan
Improving Retrievals Of Crop Vegetation Parameters From Remote Sensing Data, Nathaniel Levitan
Dissertations and Theses
Agricultural systems are difficult to model because crop growth is driven by the strongly nonlinear interaction of Genotype x Environment x Management (G x E x M) factors. Due to the nonlinearity in the interaction of these factors, the amount of data necessary to develop and utilize models to accurately predict the performance of agricultural systems at an operational scale is large. Satellite remote sensing provides the potential to vastly increase the amount of data available for modelling agricultural systems as a result of its high revisit time and spatial coverage. Unfortunately, there have been significant difficulties in deploying remote …