Research Papers

Site quality assessment of a Pinus radiata plantation in Victoria, Australia, using LiDAR technology

Published in: Southern Forests: a Journal of Forest Science
Volume 74, issue 4, 2012 , pages: 217–227
DOI: 10.2989/20702620.2012.741767
Author(s): Y ChenSchool of Geography and Environmental Science, Australia, X ZhuSchool of Geography and Environmental Science, Australia


The aim of site quality assessment of Pinus radiata plantations is to determine the quality and productivity of the growing stock at different sites. It provides a useful indication of the site productivity to assist in the allocation of optimum thinning and fertiliser regimes and the scheduling of silvicultural operations. The predominant stand height (PDH) at a specific reference age, also known as site index (SI), is often used for site quality assessment of Pinus radiata plantations in Australia, as it is closely correlated with site productivity. However, measuring PDH in the field can be a time- and resource-consuming task. This paper proposes the use of light detection and ranging (LiDAR) data to estimate PDH for assessing the site quality of Pinus radiata. LiDAR provides highly accurate digital elevation and surface data that can be used to build a canopy height model (CHM). In this study, the state-of-the-art image segmentation technique, marker-controlled watershed segmentation, was employed for identifying locations of individual trees and estimating their heights from a CHM. Using an empirically derived SI equation, PDHs with reference age 11 years (SI11) were estimated from the tallest trees identified in each forest stand, and were then used to determine the site quality class for each stand. The comparison of LiDAR-derived tree heights with field measurements produced an RMSE value of 0.42 m. The maximum horizontal distance between the field-measured locations of individual trees and the LiDAR-detected locations of their treetops was 1.87 m. Site quality classification was conducted in terms of 0.05 ha gridded plots, which revealed more detailed spatial variations of site quality across the study area than classification based on management plots. The study demonstrated that LiDAR provides an effective and accurate method for site quality classification of Pinus radiata.

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