Detection of individual trees and estimation of tree height using LiDAR data

Abstract

For estimation of tree parameters at the singletree level using light detection and ranging (LiDAR), detection and delineation of individual trees is an important starting point. This paper presents an approach for delineating individual trees and estimating tree heights using LiDAR in coniferous (Pinus koraiensis, Larix leptolepis) and deciduous (Quercus spp.) forests in South Korea. To detect tree tops, the extended maxima transformation of morphological image-analysis methods was applied to the digital canopy model (DCM). In order to monitor spurious local maxima in the DCM, which cause false tree tops, different h values in the extended maxima transformation were explored. For delineation of individual trees, watershed segmentation was applied to the distance-transformed image from the detected tree tops. The tree heights were extracted using the maximum value within the segmented crown boundary. Thereafter, individual tree data estimated by LiDAR were compared to the field measurement data under five categories (correct delineation, satisfied delineation, merged tree, split tree, and not found). In our study, P. koraiensis, L. leptolepis, and Quercus spp. had the best detection accuracies of 68.1% at h = 0.18, 86.7% at h = 0.12, and 67.4% at h = 0.02, respectively. The coefficients of determination for tree height estimation were 0.77, 0.80, and 0.74 for P. koraiensis, L. leptolepis, and Quercus spp., respectively.

Estimating Crown Variables of Individual Trees Using Airborne and Terrestrial Laser Scanners

“…The application of optical remote sensing techniques enables the measurement of forest growth factors, and ecological and environmental information over wide areas [4]. However, remote sensing using optical sensors, except stereo-image analysis of the forest, suffers from the limitation of restricted time and cost when stand information for three-dimensional vertical structures is extracted [5].…”

Detecting Individual Tree Position and Height Using Airborne LiDAR Data in Chollipo Arboretum, South Korea

“…Pure forest tends to have easier conditions permitting individual tree identification because it is much easier to extract inflection points in mixed forest with various species than in mixed forest. In contrast, Kwak et al (2007) conducted their study under higher forest density conditions than our study. As previously emphasized in this study, tree detection algorithms are essential in finding the lowest inflection point, which is the treetop.…”

“…In other words, the crown shape in Yoon's study area can unpredictably change with the stand age, i.e., each tree has various inflection points interrupting the analysis, which might have resulted in lower accuracy than that in our study because our study area is mono-storied with relatively low forest density. Kwak et al (2007) detected P. koraiensis (Korean Pine), L. leptolepis (Japanese Larch), and Quercus spp. (Oaks) in a pure forest, with R 2 values of 0.68, 0.87, and 0.67, respectively.…”

“…Leckie et al (2003) mentioned that LiDAR could reduce large amounts of commission errors in falsely identified trees in open stands compared to optical imagery (Chen et al 2006). LiDAR has the ability to acquire vertical tree information such as tree height using geo-registered 3D points (Kwak et al 2007). With improved high point density (pts m -2 ), many studies have recently performed individual tree level analysis using program based algorithms and image segmentation methods as well as plot-level analysis (St-Onge et al 1999;Persson et al 2002;Clark et al 2004Clark et al , 2011Chave et al 2005).…”

“…Most recent studies on tree detection can be categorized to five main methods: local maxima (LM) filtering (Popescu et al 2002), region-growing , valley-following (Gougeon 1995), watershed segmentation (Kwak et al 2007), and the integrated methods relying on LM (Eysn et al 2015). LM filtering has been widely used to detect trees in remotely sensed images (Pouliot et al 2002;Park et al 2011).…”