06-13, 17:00–17:15 (Europe/London), Sala Biblioteca @ PoliBa
Starting from 1962 the Common Agricultural Policy (CAP) has supported through contributions the agricultural sector aiming at preserving the environment and improving crops production. The local Paying Agencies (PA) verify the correctness, completeness and compliance of farmers applications by administrative checks (ACs) and on-the-spot checks (OTSCs). ACs are performed on 100% of applications to automatically detect formal faults through informatics tools. OTSCs are performed on about the 5% of applications testing the compliance with envisaged commitments and obligations, verify eligibility criteria and checking the truthfulness of declared area size. Recently, the article 10 of the recent EU regulation (N. 1173/2022), defined new controls based on remote sensing, specifically by adopting Copernicus Sentinel-2 (S2) imagery, or “other data” at least equivalent value. The adoption of S2 imagery allows to monitor all areas declared by farmers’ applications longing for irregularities detection. Consequently, this type of control can be applied to all CAPs (no longer 5%) applications in each member state. In this framework, the new CAP 2023-2027, requires a gradual implementation of such remote-sensing based tools within member states control systems, becoming compulsory in 2024. Furthermore, the 2023-2027 CAP will introduce some new types of contributions called 'eco-schemes' related to the climate, environment and animal welfare. Nevertheless, a proper review of how remote sensing-based tools can be applied to these new contributions is missing. Therefore, in this work we preliminary explore which marker can be detected by Copernicus S2 data in terms of field surface, agronomic practices and monitor period, possibly related to a specific CAP contribution requirement. Focuses will concern: (a) basic payment; (b) eco-schemes; (c) enhanced conditionality.
- Double Crop Mapping using Sentinel-2 Data in Support to Implementation and Monitoring of the 2023-2027 Common Agricultural Policy within Rural Development Interventions
- A Possible Role of NDVI Time Series from Landsat Mission to Characterize Lemurs’ Habitats Degradation in Madagascar
- Monitoring Erbaluce and Nebbiolo vineyards by means of Sentinel-2 NDVI index maps
- Pixel Mixture Issue in Mapping Vineyard Phenology. A Possible Solution Based on Sentinel-2 Imagery and Local Least Squares
- Opening Session AIT Congress
Dott. Alessandro Farbo
PhD Student - SUSTNET (Unito)
Department of Agricultural, Forest and Food Sciences - DISAFA - University of Torino (Italy)
GEO4Agri Lab - Laboratorio di Geomatica e Telerilevamento Agro-Forestale del DISAFA
Dr. Filippo Sarvia graduated with full marks from the University of Torino with a Master's degree in Agricultural Science. He won the annual award for best thesis in optical remote sensing (2019). Immediately after graduation, he won a scholarship and successfully competed for a Ph.D. position with DISAFA. Presently, his research objectives concern remote sensing technology for agroforestry. In particular, he is dealing with climate change-related topics, such as evaluation of the reaction of natural and agricultural systems to ongoing changes (drought, floods and hail); EU CAP controls by multi-temporal satellite imagery; and damage estimates to crops by extreme weather events (supporting insurance policies).