Abstract
This study analyses the underestimation of tree and shrub heights for different airborne laser scanner systems and point cloud distribution within the vegetation column. Reference data was produced by a novel UAV-borne laser scanning (ULS) with a high point density in the complete vegetation column. With its physical parameters (e.g. footprint) and its relative accuracy within the block as stated in Section 2.2 the reference data is supposed to be highly suitable to detect the highest point of the vegetation. An airborne topographic (ALS) and topo-bathymetric (ALB) system were investigated. All data was collected in a period of one month in leaf-off condition, while the dominant tree species in the study area are deciduous trees. By robustly estimating the highest 3d vegetation point of each laser system the underestimation of the vegetation height was examined in respect to the ULS reference data. This resulted in a higher under-estimation of the airborne topographic system with 0.60 m (trees) and 0.55 m (shrubs) than for the topo-bathymetric system 0.30 m (trees) and 0.40 m (shrubs). The degree of the underestimation depends on structural characteristics of the vegetation itself and physical specification of the laser system.
Highlights
Airborne laser scanning (ALS) has established itself as the stateof-the-art method for high precision topographic data acquisition over the last two decades
The results of this study clearly present an underestimation of vegetation heights derived from airborne laser scanner systems
While the most prominent factor for underestimation is the footprint size of airborne systems, other characteristics of the different airborne systems can lead to different scales of underestimation of vegetation heights
Summary
Airborne laser scanning (ALS) has established itself as the stateof-the-art method for high precision topographic data acquisition over the last two decades. With forestry related applications, the strength of ALS lies in the ability to capture both the terrain and the canopy height. This capability allows the direct tree height measurement (Holmgren, 2004; Hyyppä and Inkinen, 1999; Kwak et al, 2007; Lim et al, 2001; Næsset, 1997), which constitutes one of the most important forest parameters. Several studies have analysed the possibility of tree detection and tree height estimation based on the 3d point cloud or based on the derived canopy height models (CHM). The studies of Gaveau und Hill (2003) and Hopkinson (2007) examined the canopy height underestimation due to laser beam penetration. These studies show the influence of flying altitude, beam divergence and pulse repetition frequency on the canopy point distribution but are limited to ALS scanners operating at a wavelength of ~1064 nm. Gaveau and Hill (2003) stated an underestimation for the raw point cloud of 1.27 m and 0.91 m for trees and shrub respectively, while Hopkins (2007)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
