Evaluation of the Influence of Processing Parameters in Structure-from-Motion Software on the Quality of Digital Elevation Models and Orthomosaics in the Context of Studies on Earth Surface Dynamics

Abstract

The fully automated Structure-from-Motion approach for developing digital elevation models and orthomosaics has been known and used in photogrammetry for at least 15 years. Years of practice and experience have allowed researchers to provide a solid description of the applicability and limitations of this method. That being said, the impact of input processing parameters in software on the quality of photogrammetric products has yet to be fully ascertained empirically. This study is aimed at identifying the most advantageous processing workflow to fill this research gap by testing 375 different setup variations in the Agisoft Metashape software for the same set of images acquired using an unmanned aerial vehicle in a proglacial area. The purpose of the experiment was to determine three workflows: (1) the fastest, which has the shortest calculation time; (2) the best quality, which is as accurate as possible, regardless of the time taken for the calculations; and (3) the optimal, which is a compromise between accuracy and calculation time. Each of the 375 processing setup variations was assessed based on final product accuracy, i.e., orthomosaics and digital elevation models. The three workflows were selected based on calculating the height differences between the digital elevation models and the control points that did not participate in their georeferencing. The analyses of the root mean square errors (RMSE) and standard deviations indicate that excluding some of the optimization parameters during the camera optimization stage results in high RMSE and an increase in the values of standard deviation errors. Furthermore, it was shown that increasing the detail of individual processing steps in software does not always positively affect the accuracy of the resulting models. The experiment resulted in the development of three different workflows in the form of Python scripts for Agisoft Metashape software, which will help users to process image sets efficiently in the context of earth surface dynamics studies.

Post‐wildfire coastal dunefield response using photogrammetry and satellite indices

“…Camera calibration coefficients in this study show errors that are significantly lower than their coefficient values, with errors representing a miniscule fraction of the corrections applied. Although there is not consensus regarding the optimal parameters available in SfM software ( Śledź & Ewertowski, 2022), flight design and acceptable error bounds need to be fit for purpose to answer the research objectives considering the scale, resolution, precision and accuracy of the methods (Anderson, 2019).…”

Active temperate glacial landsystem evolution in association with outwash head/depositional overdeepenings

“…We adopted the general approach as proposed by Evans et al (2016) and generated dense point clouds, DEMs and orthomosaics. In addition, individual processing parameters were set up as indicated in the ‘optimal’ workflow for processing UAV data in Metashape (Śledź & Ewertowski, 2022). Following the approach proposed by Cook & Dietze (2019) and de Haas et al (2021), we selected 2022 as a master model (because it was surveyed with RTK UAV) and co‐registered each of the models with it.…”

Landscape degradation and development as a result of touristic activity in the fragile, high‐mountain environment of Vinicunca (Rainbow Mountain), Andes, Peru

“…Geomorphological mapping involved a field‐based approach combined with the interpretation of orthomosaics (0.02 m ground sampling distance [GSD]) generated from unmanned aerial vehicles (UAV) imagery and high‐resolution (0.5 m GSD) satellite data (WorldView‐2, 2020). UAV images were processed using standard structure‐from‐motion workflow (Evans et al, 2016; Ewertowski et al, 2019; Śledź & Ewertowski, 2022). The characterisation of dominant processes responsible for land surface transformation (i.e., geomorphological processes) was based on ground‐based observations, photographic documentation and remote sensing data.…”