Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/18402
Title: Estimating trunk diameter at breast height for scattered Eucalyptus trees: a comparison of remote sensing systems and analysis techniques
Contributor(s): Verma, Niva Kiran (author); Lamb, David (supervisor); Reid, Nick (supervisor); Wilson, Brian (supervisor)orcid 
Conferred Date: 2015
Copyright Date: 2014
Open Access: Yes
Handle Link: https://hdl.handle.net/1959.11/18402
Abstract: 'Farmscapes' are farming landscapes that comprise combinations of forests and scattered remnant vegetation (trees), natural and improved grasslands and pastures and crops. Scattered eucalypt trees are a particular feature of Australian farmscapes. There is a growing need to assess carbon and biomass stocks in these farmscapes in order to fully quantify the carbon storage change in response to management practices and provide evidence-based support for carbon inventory. Since tree trunk diameter, more formally known as diameter at breast height (DBH), is correlated with tree biomass and associated carbon stocks, DBH is accepted as a means inferring the biomass–carbon stocks of trees. On ground measurement of DBH is straightforward but often time consuming and difficult in inaccessible terrain and certainly inefficient when seeking to infer stocks over large tracts of land. The aim of this research was to investigate various avenues of estimating DBH using synoptic remote sensing techniques. Tree parameters like crown projected area, tree height and crown diameter are all potentially related to DBH. This thesis first uses on–ground measurements to establish the fundamental allometric relationships between such parameters and DBH for scattered and clustered Eucalyptus trees on a large, ~3000-ha farm in north eastern part of New South Wales, Australia. The thesis then goes on to investigate a range of remote sensing techniques including very high spatial resolution (decicentimetre) airborne multispectral imagery and satellite imagery and LiDAR to estimate the related parameters. Overall, the research demonstrated the usefulness of remote sensing of tree parameters such as crown projection area and canopy volume as a means of inferring DBH on a large scale.
Publication Type: Thesis Doctoral
Field of Research Codes: 070104 Agricultural Spatial Analysis and Modelling
050206 Environmental Monitoring
Rights Statement: Copyright 2014 - Niva Kiran Verma
HERDC Category Description: T2 Thesis - Doctorate by Research
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