A Timber Extraction Method Based On Pavement Serviceability and Forest Inventory Data
Abstract:A methodology for integrating pavement classification and forest inventory data to determine the capability of forest access roads with weak subgrades to support timber extraction is described. GPS location data recorded in stand-alone mode was superimposed on forest and Ordnance Survey maps. Within a GIS, the acquired spatial data was manipulated and integrated with pavement attribute information and the current and projected forest inventory data. Potential pavement damage by a typical timber haulage truck with payloads of 22, 27, 30, and 35 tonnes (t) was then assessed. It was found that by overloading the truck by 3 and 8 t (GVW of 43 t and 48 t, respectively), the total volume of timber that could be conveyed without damaging the serviceable pavements reduced by an average of 16 and 44%, respectively. Rerouting of timber to avoid critical and failed sections could significantly increase the transportation costs. Rerouting was found to be impractical where forest compartments were accessible by single routes; hence, necessary repairs to facilitate the extraction are recommended in such cases. The final database could be extended to include specific costing of repair and maintenance requirements, and so determine the economic implications of respective routing strategies. For. Sci. 46(1):76-85.
Document Type: Journal Article
Publication date: February 1, 2000
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- 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
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