3 papers
q-bio.QM2024
From parcels to people: development of a spatially explicit risk indicator to monitor residential pesticide exposure in agricultural areas
Francesco Galimberti, Stephanie Bopp, Alessandro Carletti +12
The increase in global pesticide use has mirrored the rising demand for food over the last decades, resulting in a boost in crop yields. However, concerns about the impact of pesti…
cs.CE2023
Earth Observation based multi-scale analysis of crop diversity in the European Union: first insights for agro-environmental policies
Melissande Machefer, Matteo Zampieri, Marijn van der Velde +3
To understand the resilience of farms and the agricultural sector, as well as the provision of ecosystem services, we need to characterize and quantify crop diversity. Using a 10m…
cs.CV2023
Crop identification using deep learning on LUCAS crop cover photos
Momchil Yordanov, Raphael d'Andrimont, Laura Martinez-Sanchez +3
Crop classification via deep learning on ground imagery can deliver timely and accurate crop-specific information to various stakeholders. Dedicated ground-based image acquisition…