The potential of airborne LiDAR technology to quantify forest structure within eucalypt forests has been evaluated with a focus on the understorey stratum. To achieve this, three studies have been undertaken using multiple (4) LiDAR datasets acquired over three test areas located in Wedding Bells State Forest, Coffs Harbour, Australia. Initially, the effects of sensor configuration were evaluated using field measurements collected from three structurally and topographically differing field plots (40 x 90 m areas). Results indicated that canopy height profiles derived from LiDAR data at the plot scale were largely unaffected by a change in platform altitude from 1000 to 3000 m (p > 0.05). In addition, the derivation of individual tree attributes was found to be highly sensitive to the density of LiDAR observations whilst higher platform altitudes showed an increased proportion of single returns over forested areas. In the second study, an innovative field based approach was developed to sample the structure of the understorey (horizontally and vertically) for LiDAR validation purposes. Using two separate LiDAR datasets, this research confirmed that mean understorey height and understorey cover can be effectively mapped in areas of low to medium canopy cover whilst no significant relationship (p > 0.05) was identified between field and LiDAR estimates of maximum understorey height. In the third study, an optimised LiDAR beam interception model was developed and validated, and then applied to assess the interaction of extrinsic and intrinsic factors of the LiDAR survey. This demonstrated that the probability of beam interception through the forest canopy can be affected by factors both intrinsic (e.g. crown cover) and extrinsic (e.g. scan angle) to the structure of the canopy. Overall, the results of this research indicate that optimising the sensor configuration is important to the derivation of particular forest structural attributes and significantly, there is potential for LiDAR technology to provide quantitative and spatially detailed estimates of key understorey attributes such as mean height and cover.
| Identifer | oai:union.ndltd.org:ADTP/215513 |
| Date | January 2006 |
| Creators | Goodwin, Nicholas R., School of Biological, Earth & Environmental Sciences, UNSW |
| Publisher | Awarded by:University of New South Wales. School of Biological, Earth and Environmental Sciences |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | Copyright Nicholas R. Goodwin, http://unsworks.unsw.edu.au/copyright |
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