Rooftop photovoltaic potential in data-scarce regions using open-source geospatial information: Scenario-based approach for a Mediterranean coastal city
Energy for Sustainable Development, cilt.96, 2027 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 96
- Basım Tarihi: 2027
- Doi Numarası: 10.1016/j.esd.2026.102162
- Dergi Adı: Energy for Sustainable Development
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, Geobase, INSPEC
- Anahtar Kelimeler: Collective self-consumption, Geographic Information Systems, Open-source big data, Rooftop photovoltaics, Scenario-based modeling, Urban solar potential
- Akdeniz Üniversitesi Adresli: Evet
Özet
Rooftop photovoltaic (PV) systems can support urban decarbonization, yet data scarcity limits city-scale assessments in developing regions. This study develops an open-source 2D GIS workflow for five central districts of Antalya, Turkiye, using Overture Maps building footprints. A three-stage procedure combined spatial and size filters, geometry and land-use screening, and targeted image inspection to retain the continuous urban building stock while excluding rural settlements, greenhouses, and structures smaller than 60 m2. Planimetric agreement was evaluated against 60 manually delineated reference structures totaling 93,070 m2. Structure-level mean absolute percentage error was 8.48%, whereas total-area relative error was 0.13%; leave-one-out values ranged from −0.43% to +0.96%, demonstrating sensitivity to sample composition. After screening, 130,458 structures with 38.97 million m2 of gross rooftop footprint remained. Because verified building-use labels and citywide 3D height data were unavailable, rooftop availability was represented by literature-supported utilization factors of 0.20 and 0.50, incorporating obstructions, access, setbacks, layout constraints, and inter-row spacing. With annual plane-of-array irradiation of 2084.62 kWh m−2, module efficiency of 21%, and a performance ratio of 0.75, technical generation was estimated at 2.56 to 6.40 TWh yr−1. Under an average-grid displacement factor of 0.430 tCO₂ MWh−1, this corresponds to 1.10 to 2.75 MtCO₂ yr−1. These estimates represent screening-level technical potential, not building-specific deployment forecasts, because source-data omissions, inter-building shading, structural suitability, permitting, and grid constraints remain unresolved. The workflow separates footprint error, preprocessing decisions, and rooftop-utilization uncertainty, providing a transparent screening framework for data-scarce cities.