Open-Source GIS and Remote Sensing Analysis of Rooftop Photovoltaic Potential in Padova's Industrial Zone: Implications for Sustainable Urban Energy Planning
The rapid expansion of solar photovoltaic (PV) deployment across the European Union (EU) underscores renewables' growing role in decarbonization, energy security, and land-efficient urban transitions. In Italy, one of Europe's leading solar markets, this shift benefits from high solar irradiation (1,400–1,800 kWh/kWp annually in northern regions like Veneto), progressive policies (e.g., Conto Energia legacy, updated NECP targets, and REPowerEU-aligned incentives), and abundant rooftop surfaces, particularly in industrial zones. Such areas are particularly strategic: large, flat, already-sealed surfaces enable substantial PV deployment with minimal additional land take, reduced pressure on agricultural or natural systems, and proximity to high industrial energy demand. For example, in 2024, 80% of the land used for photovoltaic installations was previously agricultural land, thus available rooftops would potentially avoid or reduce future land take as existing rooftops show a potential of 84-110 GW PV energy production (ISPRA, 2026). This amount is sufficient to cover the increase in overall renewable energy foreseen by the PNIEC by 2030 (ISPRA, 2026). Despite rising interest in distributed rooftop PV, high-resolution data on existing installations and further potential remain fragmented, aggregated at coarse scales, not updated frequently, or inaccessible for local scale planning. This limits accurate potential assessment, grid integration planning, and evidence-based prioritization, challenges especially acute in industrial districts where untapped roof stock is significant but site-specific evidence is scarce.
This study evaluates the technical potential for additional rooftop PV in Padova's industrial zone (ZIP, Zona Industriale di Padova), a major northern Italian logistics and manufacturing hub of 8 km² comprising approximately 1000 buildings. The objectives of this research include: (1) characterizing rooftop suitability based on geometry, orientation, and slope, adopting the methodology from Ahmadi (et al., 2026); (2) mapping existing PV installations and distinguishing occupied from available roofs; (3) estimating annual electricity generation under technical constraints; and (4) quantifying avoided CO₂ emissions from displaced grid electricity.
The analysis employs an open-source, reproducible GIS- and remote sensing-based workflow implemented in QGIS and utilizing the PVGIS solar yield modeling formula developed by Joint Research Center- European Commission. Input datasets include municipal building footprints, LiDAR-derived DSM and DTM at 50 cm spatial resolution, and orthophotos at 20 cm spatial resolution, made openly available by the Veneto Region and the Municipality of Padova, and multispectral satellite imagery from PlanetScope at 3 m resolution, freely available for academic non-commercial purposes. Existing rooftop PV systems are detected via manual photo-interpretation of the orthophoto of the study area. Results of this step are also used as a ground-truth layer for comparison with the resulting semi-automatic satellite classification for installed PV identification, thus allowing an assessment of the potential of semiautomatic classification for local-scale existing PV analysis.
Results reveal substantial untapped potential in the ZIP area. The estimated total area of flat rooftops is approximately 1.5 km² on about 500 buildings. Under the assessed technical scenario, additional rooftop PV could generate up to 415 GWh annually, confirming industrial roofs as a high-value, low-impact resource for expanding distributed solar generation without new land consumption. The photo-interpretation demonstrates reliable identification of existing systems, while the comparison with semi-automatic classification highlights the capability and limitations of the PlanetScope satellite image. The results also indicate substantial CO₂ emission avoidance through substitution of fossil-based grid electricity.
This research provides transferable, open-source methods for GIS-RS rooftop PV cadastres, supporting local authorities in translating EU/national decarbonization targets into actionable urban strategies. By prioritizing industrial zones, the framework advances spatially explicit renewable planning and strengthens the evidence base for integrating distributed PV into regional and local energy systems.
