In this study we developed a forest road design program based on a high-resolution digital elevation model (DEM) from a light detection and ranging (LIDAR) system. After a designer has located the intersection points on a horizontal plane, the model first generates the horizontal alignment and the ground profile. The model precisely generates cross-sections and accurately calculates earthwork volumes using a high-resolution DEM. The model then optimizes the vertical alignment based on construction and maintenance costs using a heuristic technique known as tabu search. As the distance between cross-sections affects the accuracy of earthwork volume calculations, the results were examined by comparing them with the exact earthwork volume calculated by the probabilistic Monte Carlo simulation method. The earthwork volumes calculated by the Pappus-based method were similar to those calculated by the Monte Carlo simulation when the distance between cross-sections was within 10 m. The model was applied to a high-resolution DEM from the LIDAR of Capitol Forest in Washington State, USA. The model generated a horizontal alignment, length 827 m, composed of five horizontal curves. We examined the number of grade change points. The results indicated that tabu search found the best solution ($61.42/m) with five grade change points. This was composed of two vertical curves that almost followed the ground profile. As the accuracy of a high-resolution DEM from LIDAR increases, the model would become a useful tool for a forest road designer because it eliminates or at least reduces the time-consuming process of road surveys.
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