An integrated framework for rooftop solar viability assessment: Enhancing building reuse and urban sustainability through UAV-Derived 3D modeling and performance simulation

• Integrated UAV-based workflow combines centimeter-accurate photogrammetry, dynamic solar simulation, and economic analysis. • Case study on a historic building demonstrates 96 MWh annual generation, 17.9 % effective efficiency, and 5.8-year payback. • Workflow reduces geometry preparation time by 77 % and simulation duration by 71 % compared with manual methods. • Direct benchmarking against PVsyst demonstrates improved accuracy and reliability of UAV-derived models. • Future climate scenarios confirm resilience of rooftop PV performance under projected irradiance and temperature changes. Rooftop solar photovoltaic (PV) systems play a key role in reducing reliance on grid-supplied electricity, therefore contributing to lower net energy demand and greater urban energy resilience. However, current assessment methods relying on satellite imagery, GIS datasets, or manual 3D modeling often lack geometric precision, leading to large uncertainties in estimating rooftop solar potential. To address this gap, this study proposes an integrated UAV-based framework that combines high-resolution photogrammetry, 3D modeling, solar-radiation simulation, and economic analysis to evaluate rooftop PV feasibility with improved reproducibility. The workflow was demonstrated through a case study of a historic multi-story structure in Binghamton, New York. UAV-derived models captured detailed roof morphology and surrounding obstructions, informing simulations of solar irradiance, PV performance, and financial return. Results indicate that the UAV-based workflow reduced geometry preparation time by 77 % and simulation duration by 71 % compared with manual methods, while improving roof-area accuracy by 1.5 %. The system achieved an annual generation potential of 96 MWh, an effective efficiency of 17.9 %, and a payback time of 5.8 years. By integrating geometric fidelity, performance simulation, and economic evaluation, this framework bridges the gap between traditional satellite-based assessments and dynamic building-scale analyses, providing a scalable decision-support tool for adaptive reuse and climate-responsive urban energy planning.