Estimating Sediment Reduction Cost for Low-Volume Forest Roads Using a Lidar-Derived High-Resolution DEM
DOI:
https://doi.org/10.3846/bjrbe.2014.07Keywords:
forest roads, optimal alignment, sediment prediction, Light Detection and Ranging, Digital Elevation ModelAbstract
Traditional methods of designing forest roads using topographic maps and aerial photos are not always capable of leading to an optimal road alignment solution that minimizes the environmental effects of road construction. Forest road construction activities have the potential to cause more environmental impacts, especially excessive amount of sediment production, than perhaps any other forest management activity. In order to select an optimum road alignment that considers environmental constraints, mathematical optimization techniques are applied to a digital landscape in order to identify and evaluate a potentially large number of alignment solutions. A 3D forest road alignment optimization model TRACER was developed to assist road managers in designing a preliminary forest road alignment while minimizing total road cost and considering design specifications, environmental requirements, and driver safety. A 3D forest road alignment optimization model TRACER relies on a high resolution Digital Elevation Model for accurate representation of the terrain, while sediment production estimates are derived from a GIS-based SEDiment MODeL (SEDMODL). In this study, the 3D forest road alignment optimization model was used to generate two road alignments: 1) an optimum alignment with minimum total cost and, 2) a road alignment with minimum sediment delivery to streams. Both road alignment options were then analysed to better investigate the cost of sediment reduction associated with forest road construction.
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