• Introduces a predictive feasibility framework for TLS-based HBIM planning. • Formalizes scan feasibility as a computable pre-acquisition decision layer. • Integrates geometric visibility and environmental constraints within a unified model. • Refines field-of-view behavior using sine-based angular correction. • Enables automation-ready feasibility assessment prior to station optimization. This paper presents an enhanced predictive framework, denoted as the Predictive Scan Feasibility Estimation Model (PSFEM), developed to support reliable data acquisition planning for Historic Building Information Modeling (HBIM) applications. The proposed formulation addresses limitations of Terrestrial Laser Scanning (TLS) in heritage documentation, particularly those associated with restricted access, vegetation-induced occlusions, and unfavorable scanner–structure geometries. An Adjusted Scan Feasibility Index ( SF I a d j ) is introduced to quantify expected scan feasibility under environmental and geometric constraints. The formulation incorporates a structured uncertainty factor together with two environment-dependent modifiers, namely the Vegetation Density Index (VDI) and the Access Factor (AF), enabling representation of macro-occlusions and accessibility constraints through deterministic environmental adjustment. In addition, the geometric model incorporates distance, height, and Field-of-View (FOV) parameters, with improved representation of vertical visibility based on a sinusoidal function. The accuracy and effectiveness of the proposed model are validated through two heritage chapel case studies representing distinct scanning challenges. The first case involves a densely vegetated environment characterized by significant occlusions, while the second examines controlled variations in scanner-to-object distance to evaluate the influence of incidence angles on roof visibility. Multiple TLS surveys are conducted to obtain empirical coverage data for comparison. The results demonstrate that the PSFEM accurately reproduces global and element-level visibility, achieving improved agreement with measured coverage compared to geometric deterministic formulations, while reducing overestimation of feasible coverage under occlusion- and access-constrained conditions and providing a quantitative basis for identifying coverage deficiencies during the planning stage.
Salah et al. (Fri,) studied this question.