Mapping the "Green-on-Green" trade-off: tracking new solar photovoltaic plants in Italy through the CLC2024 change detection framework.

The CORINE Land Cover (CLC) project, part of the Copernicus program, provides harmonized European data for detecting and monitoring land cover and land use dynamics, with particular attention to environmental protection.

ISPRA (Italian Institute for Environmental Protection and Research), as the National Focal Point of the Europea Environment Agency (EEA) network Eionet, is responsible for producing national CLC datasets for Italy.

The first CLC database was created in 1990 and is updated every six years since 2000. CORINE Land Cover 2024 (CLC2024) introduces an important innovation: the voluntary mapping of newly established ground-mounted photovoltaic (PV) power stations (solar parks, solar power plants) built between 2018 and 2024 on previously non-built-up land.

The mapping is voluntary, however recommended as results will give information not only on the increase of renewable energy production, but also on the extent and type of land occupied by these structures. Given that PV power stations occupy at least one hectare per megawatt of installed capacity, their rapid growth raises increasing concerns about competition for land with agriculture and natural ecosystems.

In this context, Italy, with over 37 MW of PV capacity installed at the end of 2024, represents a critical case study, where 80% of the 1,702 ha of land consumed in 2024 by new ground-mounted plants was previously agricultural.In line with the updated technical guidelines, CLC2024 classification system has been improved by introducing a fourth hierarchical level within class 121. This innovation allows, for the first time, the systematic identification of new bigger ground-mounted PV installation from other industrial or commercial units.

This study presents a nationwide assessment of new PV plants constructed in Italy between 2018 and 2024. Using the CLC change detection framework (MMU 5 ha), we quantify the conversion of agricultural (class 2) and natural (class 3) land into energy infrastructure, comparing results with other national and more detailed data (MMU in order to derive the accuracy. The aim is to provide objective data on the so-called ‘Green-on-Green’ trade-off: balancing the urgent need for renewable energy expansion with the preservation of existing land cover.

The paper describes the national mapping methodology and the statistical analysis carried out on the complete dataset. The results will provide a comprehensive overview of the land cover classes most affected by PV expansion, contributing to the broader debate on agrivoltaics and soil protection. The final results will support land use planners and policymakers in harmonizing energy transition goals with the protection of the national ecological heritage.