High-precision mapping of smallholder rapeseed combining UAV imagery and deep learning

Rapeseed is a valuable crop used for its oil-rich seeds and bright yellow flowers. Accurately mapping rapeseed planting areas can not only help optimize crop management and improve yields, but is also essential for various studies in agriculture, including sustainable agriculture and global food security. Remote sensing technology and image analysis methods have been widely used for rapeseed mapping. However, most of these remote-sensing-based methods producing rapeseed maps with medium-resolution multi-spectral images which cannot support high-precision rapeseed mapping of smallholders. Thus, with the help of the unmanned aerial vehicles (UAVs) and deep learning (DL), a high-precision approach was developed to mapping rapeseed at Smallholder parcel-level. The overall accuracy reaches 97. 12%, and the intersection over union reaches 81.37% on study area.