Description du projet
Un suivi avancé pour la modernisation de la PAC
Dans le cadre de sa démarche de simplification et de modernisation de la politique agricole commune (PAC), la Commission européenne a adopté de nouvelles règles permettant l’utilisation d’une série de technologies modernes lors du contrôle des subventions versées en fonction de la superficie. Par exemple, la nouvelle technologie satellitaire réduira le nombre d’inspections sur le terrain et les coûts de gestion des contrôles et des vérifications. Sur la base de ces avancées, le projet DIONE, financé par l’UE, met au point un instrument de contrôle des paiements directs pour orienter la règle modernisée de la PAC attendue sur l’utilisation de technologies avancées. Un système reposant sur l’apprentissage automatique, développé à l’échelle régionale ou nationale, évaluera les niveaux actuels de qualité des sols afin de formuler des conclusions fondées sur des preuves concernant d’éventuelles incidences environnementales sur une région entière.
Objectif
DIONE proposes a close-to-market (TRL7) area-based direct payments monitoring toolbox that will address the forthcoming Modernised CAP regulation of using automated technologies to ensure more frequent, accurate and inexpensive compliance checks. In particular, DIONE will:
(i) Capitalise on recent results of ESA’s SEN4CAP project that showcased the capability of Sentinel data to monitor the crop diversification rules. DIONE shall further integrate generated crop-type maps in a way directly exploitable by the paying agencies;
(ii) Include in the analysis the so far neglected EFA types (fallow land of all sizes, buffer strips, hedges, trees), by making use of super-resolution technology that improves the 10-20m Sentinel resolution to an improved resolution range (5-10m). This is enabled through Machine-Learning (ML) based post-processing and data fusion of Copernicus DIAS-sourced data with targeted drone-obtained data. This aims to motivate the use of such EFAs over the –of ambiguous environmental impact- use of productive areas (nitrogen-fixing crops and catch crops).
(iii) Complement the use of EO data with a system of reliable, ground-based geo-tagged photos, captured by the farmers that exploits (a) advances that allow for improved positional accuracy, (ii) low-footprint encryption techniques for improved data security and reliability and (iii) image detecting manipulation techniques (image forensics). The system will allow for an improved LC/LU annotation and ensure the process is untampered.
(iv) Implement a Green Compliance toolbox, integrated with the paying agencies’ aforementioned tools. This will benefit from (a) low-cost spectral sensors measuring soil quality and assessing the status of land-degradation in the land parcels and (b) an ML-based inferencing system deployed on a larger scale (regional, national) to quantify the levels of some of the monitored parameters and consequently extract tangible environmental performance metrics for an entire region
Champ scientifique
- natural sciencescomputer and information sciencescomputer securitydata protection
- natural sciencesphysical sciencesopticsmicroscopysuper resolution microscopy
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- agricultural sciencesagriculture, forestry, and fisheriesagriculture
Mots‑clés
Programme(s)
Régime de financement
IA - Innovation actionCoordinateur
106 82 ATHINA
Grèce