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Terrain Trafficability Prediction with GIS Analysis

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The aim of this article is to test a GIS-based model for predicting terrain trafficability. The resistance forces restricting the movement of a forest tractor are estimated using a digital soil map, a 25 × 25-m digital elevation model (DEM) and an improved elevation model. Virtual total resistances along the 1,150-m test track were measured using the controller area network (CAN) bus-based technique. Rolling resistance prediction based on the soil type map was quite successful on frictional soils, but the predictions were clear underestimations on cohesive soils because the characteristics of Finnish soil types as substrates for vehicle motion are not well known. The 25 × 25-m DEM seems to be too inaccurate to predict the slope resistance and total resistance, whereas the results obtained with the improved DEM support the null hypothesis that the prediction is adequate enough from a terramechanical point of view and that the method could be used as a tool for predicting terrain trafficability.

Keywords: controller area network; digital elevation model; forwarder; mobility; soil type

Document Type: Research Article

Publication date: 2009-10-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 in forestry

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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