The role of spatial context and multitask learning in the detection of organic and conventional farming systems based on Sentinel-2 time series

ArXi:2603.24552v1 Announce Type: new Organic farming is a key element in achieving sustainable agriculture. For a better understanding of the development and impact of organic farming, comprehensive, spatially explicit information is needed. This study presents an approach for the discrimination of organic and conventional farming systems using intra-annual Sentinel-2 time series. In addition, it examines two factors influencing this discrimination: the joint learning of crop type information in a concurrent task and the role of spatial context.