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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) | 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 | Fields of Research (FoR) 2008: | 070104 Agricultural Spatial Analysis and Modelling 050206 Environmental Monitoring |
Fields of Research (FoR) 2020: | 300206 Agricultural spatial analysis and modelling 410599 Pollution and contamination not elsewhere classified |
Socio-Economic Objective (SEO) 2008: | 960302 Climate Change Mitigation Strategies | Socio-Economic Objective (SEO) 2020: | 190301 Climate change mitigation strategies | Rights Statement: | Copyright 2014 - Niva Kiran Verma | HERDC Category Description: | T2 Thesis - Doctorate by Research |
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Appears in Collections: | Thesis Doctoral |
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