ALBERT

Description: We demonstrate the efficacy of using close-range photogrammetry from a consumer grade camera as a tool in generating high-resolution, three-dimensional coloured point clouds for detailed analysis or monitoring of wheel ruts. Ground-based timber harvesting results in vehicle traffic on 12–70 per cent of the site, depending on the system used, with a variable probability of causing detrimental soil disturbance depending on climatic, hydrological and soil conditions at the time of harvest. Applying the technique described in this article can reduce the workload associated with the conventional manual measurement of wheel ruts, while providing a greatly enhanced source of information that can be used in analysing both physical and biological impact, or stored in a repository for later operation management or monitoring. Approaches for deriving and quantifying properties such as rut depths and soil displacement volumes are also presented. In evaluating the potential for widespread adoption of the method among forest or environmental managers, the study also presents the workflow and provides a comparison of the ease of use and quality of the results obtained from one commercial and two open source image processing software packages. Results from a case study showed no significant difference between packages on point cloud quality in terms of model distortion. Comparison of photogrammetric profiles against profiles measured manually resulted in root mean square errors of between 2.07 and 3.84 cm for five selected road profiles. Maximal wheel rut depth for three different models were 1.15, 0.99 and 1.01 m, and estimated rut volumes were 9.84, 9.10 and 9.09 m 3 , respectively, for 22.5 m long sections.