Skip to Main Content
Object-oriented classification of forest structure from light detection and ranging data for stand mappingAuthor(s): Alicia A. Sullivan; Robert J. McGaughey; Hans-Erik Andersen; Peter Schiess
Source: Western Journal of Applied Forestry. 24(4): 198-204
Publication Series: Scientific Journal (JRNL)
Station: Pacific Northwest Research Station
PDF: Download Publication (3.15 MB)
DescriptionStand delineation is an important step in the process of establishing a forest inventory and provides the spatial framework for many forest management decisions. Many methods for extracting forest structure characteristics for stand delineation and other purposes have been researched in the past, primarily focusing on high-resolution imagery and satellite data. High-resolution airborne laser scanning offers new opportunities for evaluating forests and conducting forest inventory. This study investigates the use of information derived from light detection and ranging (LIDAR) data as a potential tool for delineation of forest structure to create stand maps. Delineation methods are developed and tested using data sets collected over the Blue Ridge study site near Olympia, Washington. The methodology developed delineates forest areas using LIDAR data and object-oriented image segmentation and supervised classification. Error matrices indicate classification accuracies with a kappa hat values of 78 and 84% for 1999 and 2003 data sets, respectively.
- Visit PNW's Publication Request Page to request a hard copy of this publication.
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationSullivan, Alicia A.; McGaughey, Robert J.; Andersen, Hans-Erik; Schiess, Peter. 2009. Object-oriented classification of forest structure from light detection and ranging data for stand mapping. Western Journal of Applied Forestry. 24(4): 198-204.
KeywordsLIDAR, light detection and ranging, forest classification, object-oriented image segmentation, supervised classification, stand mapping
- Development of FVSOntario: A Forest Vegetation Simulator Variant and application software for Ontario
- Imputing forest inventory data to stands formed by image segmentation in Maryland's Green Ridge State Forest
- Computer-based synthetic data to assess the tree delineation algorithm from airborne LiDAR survey
XML: View XML