Integration of photovoltaics (PV) into the urban environment will play a major role in the energy transition. However, installing PV systems on building roofs can be challenging, particularly for monumental buildings with strict architectural and social value restrictions. Assessing roof surface visibility is, therefore, key to finding as much permitted roof surface area as possible that may be used for PV installation. In this study, a GIS-based large-scale visibility assessment tool is developed that can assist in evaluating roof visibility, using LiDAR, road networks, and cadastral data as inputs. The tool delivers multi-level outputs, including maps of roof binary visibility, roof visual amplitude, roof PV system layout, roof PV system AC yield, and roof PV module visibility. After optimization, an average speed of 0.12 s/m² is achieved. For each roof surface, an additional sensitivity analysis has been conducted. This step determines the optimal values for two visibility analysis parameters: assessment range and observer spacing, balancing the computational demand and result accuracy. Application of this workflow to the monumental buildings on the TU Delft campus revealed that approximately 2.68 GWh/year of electricity could be harvested from imperceptible PV modules, while an additional 0.42 GWh/year of energy is attributed to PV modules with medium visibility, and 0.37 GWh/year of energy is associated with PV modules with high visibility. This modeling workflow supports the multi-criteria decision-making process for urban roof PV planning.