Object-Based Classification of Abandoned Logging Roads under Heavy Canopy Using LiDARReportar como inadecuado




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Department of Geography and Environment, San Francisco State University, 1600 Holloway Avenue, San Francisco, CA 94132, USA





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Abstract LiDAR-derived slope models may be used to detect abandoned logging roads in steep forested terrain. An object-based classification approach of abandoned logging road detection was employed in this study. First, a slope model of the study site in Marin County, California was created from a LiDAR derived DEM. Multiresolution segmentation was applied to the slope model and road seed objects were iteratively grown into candidate objects. A road classification accuracy of 86% was achieved using this fully automated procedure and post processing increased this accuracy to 90%. In order to assess the sensitivity of the road classification to LiDAR ground point spacing, the LiDAR ground point cloud was repeatedly thinned by a fraction of 0.5 and the classification procedure was reapplied. The producer’s accuracy of the road classification declined from 79% with a ground point spacing of 0.91 to below 50% with a ground point spacing of 2, indicating the importance of high point density for accurate classification of abandoned logging roads. View Full-Text

Keywords: LiDAR; object-based classification; logging roads; forest roads LiDAR; object-based classification; logging roads; forest roads





Autor: Jason Sherba * , Leonhard Blesius and Jerry Davis

Fuente: http://mdpi.com/



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