Automatic Classification of Agricultural Summer Crops in Uruguay. [Conference paper]

ABSTRACT - In this work, we present a study for the classification of summer crops on a nationwide perspective. Using both optical and radar satellite images, we implement a time-series classification algorithm using XGBoost. Two datasets with farm-level information were used:one with ground truth obtained directly from farmers' production and the other with declared crops obtained at the government level. The crops analyzed were corn, soybean, sorghum, and pastures.