Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/16816
Title: Use of LiDAR data to quantify the influence of topography on radiata pine ('Pinus radiata' D. Don) at the sub-compartment level
Contributor(s): Saremi, Hanieh  (author); Kumar, Lalit  (supervisor)orcid ; Turner, Russell (supervisor)
Conferred Date: 2015
Copyright Date: 2014
Open Access: Yes
Handle Link: https://hdl.handle.net/1959.11/16816
Abstract: Accurate estimation of inventory estimates, such as aboveground tree biomass, is a fundamental aspect of studies on carbon stocks of forest ecosystems since it reflects the accumulation of organic carbon and ecosystem productivity. Diameter at Breast Height (DBH) and tree height are the two main variables used for numerous forest inventory parameters, including stand stem volume and biomass. The significant variability within these factors, however, can challenge the acceptable levels of precision and bias required for inventory estimates at the operational Planning Unit. In Hanging Rock State Forest, New South Wales, Australia, despite the similar genetic sources, edaphic (geology and soil type) and climatic (temperature and rainfall) variables as well as similar initial stocking rate, the radiata pine ('Pinus radiata' D. Don) trees displayed significant height and DBH variation within even-aged compartments. The aim of this research was to determine the significant factors causing these variations and identify the relationships between height and DBH variables with these factors. The knowledge of intra-compartment variability in tree height and DBH is important as these small area inventories are used for operational yield predictions and facilitate local silvicultural and harvesting decisions.
Publication Type: Thesis Doctoral
Field of Research Codes: 050205 Environmental Management
050209 Natural Resource Management
Rights Statement: Copyright 2014 - Hanieh Saremi
HERDC Category Description: T2 Thesis - Doctorate by Research
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Appears in Collections:School of Environmental and Rural Science
Thesis Doctoral

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