Research article - Peer-reviewed, 2020
Individual tree detection using template matching of multiple rasters derived from multispectral airborne laser scanning data
Huo, Langning; Lindberg, EvaAbstract
Multispectral airborne laser scanning (MS-ALS) provides information about 3D structure as well as the intensity of the reflected light and is a promising technique for acquiring forest information. Data from MS-ALS have been used for tree species classification and tree health evaluation. This paper investigates its potential for individual tree detection (ITD) when using intensity as an additional metric. To this end, rasters of height, point density, vegetation ratio, and intensity at three wavelengths were used for template matching to detect individual trees. Optimal combinations of metrics were identified for ITD in plots with different levels of canopy complexity. The F-scores for detection by template matching ranged from 0.94 to 0.73, depending on the choice of template derivation and raster generalization methods. Using intensity and point density as metrics instead of height increased the F-scores by up to 14% for the plots with the most understorey trees.Published in
International Journal of Remote Sensing2020, volume: 41, number: 24, pages: 9525-9544
Publisher: TAYLOR & FRANCIS LTD
Authors' information
Swedish University of Agricultural Sciences, Department of Forest Resource Management
Swedish University of Agricultural Sciences, Department of Forest Resource Management
Associated SLU-program
Remningstorp
UKÄ Subject classification
Forest Science
Remote Sensing
Publication Identifiers
DOI: https://doi.org/10.1080/01431161.2020.1800127
URI (permanent link to this page)
https://res.slu.se/id/publ/108705