Exploring the potential to minimize forest road cost in Ontario with LiDAR and RoadENG

Abstract

The objective of this study was to determine if light detection and ranging (LiDAR) and RoadENG could produce a more cost-effective road design than a field-based road design. A Triangulated irregular network (TIN) was created from raw LiDAR files (LAS). Roads were created within the TIN and had attributes for soil layer, road class, road templates, culverts, soil swell and shrinkage factors for excavation, and hauling. Three iterations were done, each with different excavation costs applied to compare road cost by iteration. Each iteration was run through Softree Opitmal to determine the lowest optimized road cost for each road section. Compared to Eacom’s field-based road designs, the blind design had a decrease in total cost by 1.5% and the second attempt had an increase in cost by 23.4%. Future research in this area type of study should include the added cost and time spent doing field-based layout compared to office-based reconnaissance with ground truthing. There should be no existing roads within the generated TIN model when comparing road alignment cost. As well, a more detailed soil layers, and more detailed cost for excavation and hauling cost. Making these changes would increase the accuracy and usefulness of the RoadENG Forest Engineer program and achieve a more ideal analysis tool for road building in Ontario forestry.