Published works

Published works

Deriving comprehensive forest structure information from mobile laser scanning observations using automated point cloud classification

TitleDeriving comprehensive forest structure information from mobile laser scanning observations using automated point cloud classification
Publication TypeJournal Article
Year of Publication2016
AuthorsMarselis, S, Yebra, M, Jovanovic, T, van Dijk, A
JournalEnvironmental Modelling & Software
Volume82
Start Page142
Pagination142-151
Date Published08/2016
Abstract

The advent of mobile laser scanning has enabled time efficient and cost effective collection of forest structure information. To make use of this technology in calibrating or evaluating models of forest and landscape dynamics, there is a need to systematically and reproducibly automate the processing of LiDAR point clouds into quantities of forest structural components. Here we propose a method to classify vegetation structural components of an open-understorey eucalyptus forest, scanned with a ‘Zebedee’ mobile laser scanner. It detected 98% of the tree stems (N = 50) and 80% of the elevated understorey components (N = 15). Automatically derived DBH values agreed with manual field measurements with r2 = 0.72, RMSE = 3.8 cm, (N = 27), and total basal area agreed within 1.5%. Though this methodological study was restricted to one ecosystem, the results are promising for use in applications such as fuel load, habitat structure, and biomass estimations.

URLhttp://www.sciencedirect.com/science/article/pii/S1364815216301207
DOI10.1016/j.envsoft.2016.04.025
Refereed DesignationRefereed
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