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Advanced possibilities have emerged in the recent years for semi-automatic crop type mapping at national level due to the availability of Sentinel-1 and -2 satellite data. In this study, 14 crop type classes were mapped over Bulgaria using three bi-monthly composite image mosaics for 2019 generated in the Google Earth Engine (GEE) cloud computing platform. The overall accuracy, when both Sentinel-1 and -2 mosaics were used, was 78%, while the accuracy was slightly less when only Sentinel-2 datadoi:10.3897/arb.v33.e04 fatcat:mrov47ro5vbt3cpvo4zedd2udm