Remote sensing applied to precision agriculture and malherbology

We develop innovative and efficient strategies to improve agricultural management, making it more effective and sustainable through a rationalized use of phytosanitary products (herbicides and foliar applications), maintaining an optimal level of control, avoiding the appearance of resistance and respecting the balance between productive agriculture and environmental requirements. As an example, we have demonstrated that herbicide applications can be reduced by up to 70% in crops such as corn, wheat, sunflower and vineyards. In our research, we seek to provide knowledge for a localized management of phytosanitary products according to real crop needs by integrating technological tools (remote images from unmanned aerial vehicles), agronomic tools (e.g. agro-ecology of weeds, pruning types, phenotyping of varieties) and computational tools (object-based image analysis-OBIA, Data Mining and Geostatistics).