Preharvest Measurement of Marked Stands Using Airborne Laser Scanning
Abstract:The customer-oriented wood procurement chain from forest to raw material user starts with a knowledge of stands available for harvesting and information on these marked stands. Despite several studies, no adequate method has been developed for obtaining preharvest measurement information to meet existing requirements. The aim here was to develop a method for the preharvest measurement of a marked stand based on single tree detection and airborne laser scanning. The trees were detected from high-density laser scanning data using automatic detection procedures, and their dbh was estimated using either local or regional models. The method was compared with actual harvester measurement of the stand and alternative methods for obtaining preharvest measurement information (systematic plot sampling, subjective inventory by compartments, and the laser canopy height distribution method). The comparisons of the methods were based on goodness-of-fit tests of diameter distributions and bucking simulations. The results indicated that the laser scanning-based single tree detection procedure has considerable advantages over other methods. The crucial point in applying the method seemed to be the choice of diameter prediction model.
Document Type: Research Article
Publication date: December 1, 2007
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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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