High-Accuracy Corridor Mapping Without GCPs: Assessing Precisions of DSMs Generated from UAS Photogrammetry with On-Site Pre-Calibration
Keywords: Digital Elevation Model (DEM), In-situ camera calibration, On-the-job camera calibration, Unmanned Aerial Vehicle (UAV), GNSS-Assisted Aerial Triangulation
Abstract. High-resolution Digital Surface Models (DSMs) are crucial for diverse geospatial analyses and UAS photogrammetry offers a cost-effective option for DSM acquisition. However, corridor mapping, due to its linear geometry, challenges the extraction of 3D information without relying on Ground Control Points (GCPs). While onboard GNSS-RTK can improve accuracy, robust camera calibration is critical to mitigate systematic vertical errors propagating in derived DSM. Existing research lacks sufficient investigation into feasible pre-calibration strategies for corridor mapping without GCPs. Therefore, this study addresses this gap by evaluating the precision of DSMs obtained from five photogrammetric experiments without GCPs: one on-the-job calibration and four GNSS-Assisted Aerial Triangulation using on-site pre-calibrations with different sub-blocks of images. For precision assessment of DSMs, a reference experiment with 17 GCPs and all available images was also carried out. Our results show that including oblique images in on-site pre-calibration with sub-blocks significantly reduced the critical correlation between focal length and Z object-space coordinates (from 99% to less than 20%). That outcome directly influenced focal length estimation and allowed mitigation of vertical bias in generated DSMs. The results demonstrate that on-site pre-calibration notably improved the accuracy and precision of vertical spatial data acquisition. These findings highlight on-site oblique pre-calibration with a sub-block of images as a feasible and robust strategy for producing high-resolution 3D models in UAS corridor mapping, significantly reducing reliance on GCPs.
