A point-cloud-driven framework for risk and sustainability assessment of historic stone bridges

Abstract Historic stone bridges represent a critical intersection between infrastructure performance, cultural heritage value, and sustainability concerns. While terrestrial laser scanning (TLS) is widely used for geometric documentation of such structures, the resulting point clouds are rarely exploited directly for risk and sustainability assessment. This paper proposes a non-modeling framework based exclusively on TLS point cloud analysis, using CloudCompare for geometric analysis and Excel for numerical processing. Five point-cloud-derived indicators are extracted, related to surface roughness, geometric completeness, irregularity, and occlusion, and evaluated using a simplified probability–severity risk logic. A risk index is mapped to environmental, economic, and social sustainability pillars. The framework is demonstrated through a case study of the Stone Bridge in Băile Herculane, confirming that meaningful risk-aware and sustainability-oriented insights can be obtained without BIM or HBIM modeling, supporting early-stage assessment in heritage contexts where modeling effort or data availability may be limited.