Multimetric Performance Evaluation of Smartphone-Based Close-Range Photogrammetry on a Reinforced Concrete Structure

The ubiquity of smartphones presents a significant opportunity for accessible reality capture in digital construction; however, the operational limits for its reliable, metric use remain lacking in realistic construction scenarios. This paper quantifies a multimetric performance evaluation for smartphone-based close-range photogrammetry (SCP) by benchmarking it against unmanned aerial vehicle (UAV) photogrammetry and terrestrial laser scanning (TLS) for as-built modeling. Using a reinforced concrete structure as a validation case study, we assessed geometric accuracy and the intrinsic point cloud quality metrics critical for digital construction workflows. Results demonstrated that with surveyed ground control, SCP produces point clouds with higher local density and lower surface noise compared with the TLS reference, while maintaining low surface deviation. The key contributions include establishing a detailed performance baseline for SCP across accuracy and intrinsic data quality, quantifying the role of surveyed ground control for achieving metric accuracy with SCP, highlighting how acquisition geometry governs the trade-off between local fidelity and areal coverage, analyzing the benefits of coprocessing SCP+UAV data sets for improved areal coverage and surface conformity, and providing a practical time-resource investment profile for each modality. These findings provide a quantitative basis for integrating SCP as a viable, low-cost method for detailed, ground-level inspections and establish a framework for its use in demanding as-built verification and digital construction workflows.