We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Object-Based Classification of Abandoned Logging Roads under Heavy Canopy Using LiDAR.
- Authors
Sherba, Jason; Blesius, Leonhard; Davis, Jerry
- 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.
- Subjects
MARIN County (Calif.); CALIFORNIA; FOREST canopies; LIDAR; LASER based sensors; LOGGING
- Publication
Remote Sensing, 2014, Vol 6, Issue 5, p4043
- ISSN
2072-4292
- Publication type
Article
- DOI
10.3390/rs6054043