Validation of UAV-Derived Discontinuity Data Against Field-Based Measurements for Kinematic Analysis in an Open-Pit Mine

Comparative Accuracy Assessment of UAV-Derived Orthophoto, DSM, and DTM Generated with and without Ground Control Points: A Case Study of the LMTC Premises, Nepal

Unmanned Aerial Vehicle (UAV) photogrammetry is increasingly used for local-scale mapping because it enables rapid generation of high-resolution orthophotos and elevation products. However, the positional and vertical quality of these products depends strongly on the georeferencing strategy, particularly the use of Ground Control Points (GCPs). This study evaluates the effect of GCPs on the accuracy of UAV-derived orthophoto, Digital Surface Model (DSM), and Digital Terrain Model (DTM) at the premises of the Land Management Training Center (LMTC), Dhulikhel, Nepal. The same UAV image block of 334 images was processed under two workflows: one using only onboard image geolocation and another using five surveyed GCPs. Eight independent checkpoints were used for accuracy assessment. Orthophoto planimetric accuracy was evaluated using checkpoint coordinates, while vertical agreement of DSM and DTM was assessed using surveyed ground elevations. In addition, pairwise checkpoint-distance analysis and supplementary object-based comparison were used to examine relative geometric differences in the orthophotos. The with-GCP orthophoto achieved a horizontal RMSEH of 0.063 m, whereas the without-GCP orthophoto showed an RMSEH of 3.507 m. Similarly, the with-GCP DSM and DTM achieved RMSEZ values of 0.131 m and 0.143 m, respectively, compared with 15.385 m and 15.347 m in the without-GCP workflow. The without-GCP orthophoto also exhibited systematic westward and northward displacement and minor scale-related geometric differences. The results demonstrate that GCP-based processing remains essential for reliable campus-scale UAV photogrammetry when the outputs are intended for measurement, terrain representation, planning, and other applications requiring dependable absolute accuracy.

A UAV-Based Engineering-Detectability Framework for Slope-Road Crack Propagation Assessment

Repeated non-equidistant unmanned aerial vehicle (UAV) inspections of slope-road cracks require measurements from different distances, poses, and image scales to remain comparable and sufficiently precise for engineering-state decisions. Existing studies rarely integrate cross-view physical conversion, measurement uncertainty, and a project-defined minimum detectable change. We develop an engineering-detectability framework that defines cross-period criteria for crack width and displacement and derives equivalent widths for ideal, representative non-standard, and arbitrary viewpoints. First-order error propagation and reliability allocation convert the minimum detectable change into accuracy requirements for range, field of view, and normalized image coordinates. Crack-boundary coordinates and localization uncertainties provide a common interface for interchangeable detection and photogrammetric modules. Validation combines a controlled fixed-camera sequence with a close-range field-camera multiview test of seven physical openings under local coplanarity. All six determinate stages in the controlled sequence agreed with the digital image correlation (DIC) comparison, while one borderline stage required review. Across the seven openings, the four-view means gave a mean absolute error (MAE) of 0.196 mm and a root mean square error (RMSE) of 0.270 mm, with cross-view coefficients of variation (CVs) of 0.33–4.93%. An illustrative error budget demonstrates reverse screening of system configurations from project thresholds. The framework therefore connects viewpoint-equivalent measurements, uncertainty constraints, and engineering-state decisions in an auditable chain.

Monitoring Coastal Geomorphic Change and Sediment Transport Using Kite Aerial Photography (KAP) and Structure-from-Motion (SfM) Photogrammetry

Coastal areas are particularly suitable study sites for kite aerial photography (KAP) surveys because of consistent wind and open space. This study uses KAP surveys conducted in January, March, June, August, and October 2025, combined with Structure from Motion photogrammetry and spatially variable error modeling for DEM of Difference (DoD) thresholding to monitor a dune revegetation project at Ocean Beach in San Francisco. Two independent ground surveys were conducted in June and October to compare measured elevation data with KAP-derived elevation. A fuzzy inference system was used to model spatially variable error for uncertainty thresholding with a 95% confidence interval based on point cloud density and surface roughness. The elevation models (raw and thresholded) were then analyzed through geomorphic change detection to assess volumetric change over time. DoD estimates from the four sampling periods between flights were used to derive mass transport rates (120.09, 415.04, 270.86, and 102.22 kg m−1 d−1, respectively) from cross-sections aligned with estimated wind directions, with results similar to wind model estimates from the same time periods, ranging from 50 to 80% (R2 = 0.98) of the latter. This method holds promise for better connecting geomorphic to atmospheric research methods, especially important when pursuing process-based restoration.

Application of satellite for geotechnical monitoring of high-speed railway subgrade settlement: a comparative study of PS-InSAR and ComSAR

UAV photogrammetry for riverine analysis: A systematic review of methodologies, accuracy, and challenges

High-resolution spatial data is crucial for riverine modeling and flood mitigation. Traditional data often lacks necessary resolution or flexibility, making Unmanned Aerial Vehicles (UAVs) a transformative solution for generating precise Digital Elevation Models (DEMs). This systematic review analyzes 65 peer-reviewed studies published between 2014 and 2025. Following PRISMA guidelines, studies were selected based on specific inclusion and exclusion criteria focusing on riverine hydraulic applications to evaluate data acquisition methods, spatial accuracy, and operational challenges. The synthesis reveals a standard workflow using multirotor platforms, Structure from Motion (SfM) photogrammetry, and Ground Control Points (GCPs) to feed hydrodynamic models like HEC-RAS. While the literature consistently reports centimeter-level vertical accuracy—ideal for mapping flood inundation—critical challenges persist regarding the optical penetration of dense vegetation and submerged bathymetry. Ultimately, while UAV photogrammetry is a robust spatial analysis tool, advancing high-fidelity riverine analytics requires hybrid approaches integrating technologies like UAV-borne LiDAR and sonar. Creating these seamless topobathymetric models is essential for improving reliable flood risk management and informing effective environmental policy.

UAV-mounted single-beam sonar for rapid bathymetric monitoring of coastal infrastructure: implications for structural health assessment

Accurate bathymetric data are essential for the design and monitoring of coastal structures, but conventional multibeam surveys are costly and often impractical in shallow or confined areas. We evaluate a single-beam echosounder (SBES, ECT400) suspended beneath an unmanned aerial vehicle (UAV) as a rapid method with low logistical requirements for bathymetric monitoring of coastal infrastructure. Fieldwork was performed in an operational dry dock that was alternately drained and filled, enabling direct geometric validation against an ultra-high-resolution photogrammetric DEM (0.55 cm GSD). The co-registered dataset comprises N = 16,137 sonar returns to depths of ≈ 8 m. The UAV-mounted SBES produced a mean depth difference of 0.15 m (SD = 0.58 m) relative to the photogrammetric reference. From these residuals we estimate a 95% Minimum Detectable Change (MDC95) of ≈ 0.5 m when changes are assessed by aggregating repeated co-located passes. These results indicate that the UAV-SBES workflow is suitable as a Tier-1 screening tool for structural-health monitoring, effective for detecting metre- to decimetre-scale changes and triaging sites for targeted high-precision follow-up, but not for micrometre/mm-scale deformation monitoring. The method’s portability and vessel-free operation make it especially useful for frequent inspections in shallow, confined coastal settings.