Prediction of Large Spatio-Temporal Data Using Machine Learning Methods
Abstract
This project was a step forward in statistical methodology for predicting green vegetation land cover in homogeneous grazing land. A supervised machine learning method, namely Boosted Regression Tree, was applied to satellite imagery. The predictive capabilities of the method was established using different data sets and approaches. Four research aims were achieved, including improved land-use prediction in a semi-arid region sensitive to climate variability.
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