Digital Site Progress Monitoring and Crack Detection Using UAV Photogrammetry: A Critical Review

The demand for objective, rapid, and automated construction-site inspection has generated significant interest in the application of unmanned aerial vehicles (UAVs) for construction management and structural assessment. UAV photogrammetry facilitates the capture of high-resolution images and three-dimensional reconstruction at construction sites and civil infrastructure, allowing for a more economical alternative to frequently repeated manual surveys, and for certain applications also terrestrial laser scanning. This review highlights UAV photogrammetry as the critical technology that ties together digital construction progress monitoring and crack detection. The paper reviews recent advances in Structure-from-Motion photogrammetry, point-cloud generation and workflows for Building Information Modeling (BIM) integration, deep learning and digital twin construction. Point clouds derived from UAV can be utilized for comparison of As-built vs. as-planned, quantities estimation, component recognition and progress verification while high-resolution UAV imagery offers automated crack detection, segmentation, measurement and spatial localization. Yet the accuracy of photogrammetry still depends on image overlap, ground sampling distance, camera calibration, surface texture, illumination, occlusion flight geometry and georeferencing quality. In the case of crack measurement, problems compound further since very small defects can become close to the spatial resolution limit of the images captured. The review concludes with the recommendation to utilize UAV photogrammetry for efficient integrated progress and condition monitoring but warns against treating it as an infallible substitute for conventional surveying or engineering inspection. Reliable digital site-monitoring are likely to be future systems based on UAV photogrammetry, BIM/digital twins-belued by AI-based defect analysis and uncertainty estimation requiring adaptive flight planning.