Skip to Main Content
Tree species differentiation using intensity data derived from leaf-on and leaf-off airborne laser scanner dataAuthor(s): Sooyoung Kim; Robert J. McGaughey; Hans-Erik Andersen; Gerard Schreuder
Source: Remote Sensing of Environment. 113: 1575-1586
Publication Series: Scientific Journal (JRNL)
Station: Pacific Northwest Research Station
PDF: Download Publication (4.85 MB)
DescriptionTree species identification is important for a variety of natural resource management and monitoring activities including riparian buffer characterization, wildfire risk assessment, biodiversity monitoring, and wildlife habitat assessment. Intensity data recorded for each laser point in a LIDAR system is related to the spectral reflectance of the target material and thus may be useful for differentiating materials and ultimately tree species. The aim of this study is to test if LIDAR intensity data can be used to differentiate tree species. Leaf-off and leaf-on LIDAR data were obtained in the Washington Park Arboretum, Seattle, Washington, USA. Field work was conducted to measure tree locations, tree species and heights, crown base heights, and crown diameters of individual trees for eight broad leaved species and seven coniferous species. LIDAR points from individual trees were identified using the field-measured tree location. Points from adjacent trees within a crown were excluded using a procedure to separate crown overlap, Mean intensity values of laser returns within individual tree crowns were compared between species. We found that the intensity values for different species were related not only to reflective properties of the vegetation, but also to a presence or absence of foliage and the arrangement of foliage and branches within individual tree crowns. The classification results for broad leaved and coniferous species using linear discriminant function with a cross validation suggests that the classification rate was higher using leaf-off data (83.4%) than using leaf-on data (73.1%), with highest (90.6%) when combining these two LIDAR data sets. The result also indicates that different ranges of intensity values between two LIDAR datasets didn't affect the result of discriminant functions. Overall results indicate that some species and species groups can be differentiated using LIDAR intensity data and implies the potential of combining two LIDAR datasets for one study.
- 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.
CitationKim, Sooyoung; McGaughey, Robert J.; Andersen, Hans-Erik; Schreuder, Gerard. 2009. Tree species differentiation using intensity data derived from leaf-on and leaf-off airborne laser scanner data. Remote Sensing of Environment. 113: 1575-1586.
KeywordsLIDAR intensity, tree crown separation, species differentation
- A density-based approach for leaf area index assessment in a complex forest environment using a terrestrial laser scanner
- Estimating individual tree leaf area in loblolly pine plantations using LiDAR-derived measurments of height and crown dimensions
- Layer stacking: A novel algorithm for individual forest tree segmentation from LiDAR point clouds
XML: View XML