Statistical analysis of airborne LiDAR data for forest classification in the Strzelecki Ranges, Victoria, Australia
Paper
Paper/Presentation Title | Statistical analysis of airborne LiDAR data for forest classification in the Strzelecki Ranges, Victoria, Australia |
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Presentation Type | Paper |
Authors | Zhang, Z. (Author), Liu, X. (Author), Peterson, J. (Author) and Wright, W. (Author) |
Editors | Chan, F., Marinova, D. and Anderssen, R. S. |
Journal or Proceedings Title | Proceedings of the 19th International Congress on Modelling and Simulation (MODSIM2011) |
ERA Conference ID | 44996 |
Number of Pages | 7 |
Year | 2011 |
Publisher | Modelling and Simulation Society of Australia and New Zealand |
Place of Publication | Australia |
ISBN | 9780987214317 |
Web Address (URL) of Paper | http://www.mssanz.org.au/modsim2011/index.htm |
Conference/Event | 19th International Congress on Modelling and Simulation (MODSIM2011) |
International Congress on Modelling and Simulation | |
Event Details | International Congress on Modelling and Simulation MODSIM Rank C C C C C C C C C C C C C C |
Event Details | 19th International Congress on Modelling and Simulation (MODSIM2011) Parent International Congress on Modelling and Simulation Delivery In person Event Date 12 to end of 16 Dec 2011 Event Location Perth, Australia |
Abstract | Although remotely sensed data have been widely explored for forest applications, passive remote sensing techniques are limited in their ability to capture forest structural complexity, particularly in uneven-aged, mixed species forests with multiple canopy layers. Generally, these techniques are only able to provide information on horizontal (two-dimensional) forest extent. The vertical forest structure (or the interior of the canopy and understorey vegetation) cannot be mapped using these passive remote sensing techniques. Fortunately, it has been shown that active remote sensing techniques via airborne LiDAR (light detection and ranging) with capability of canopy penetration yields such high density sampling that detailed description of the forest structure in three-dimensions can be obtained. Accordingly, much interest is attached to exploring the application of this approach for identifying the distribution of designated vegetation |
Keywords | LiDAR; cool temperate rainforest; forest classification; statistical analysis; Strzelecki Ranges |
ANZSRC Field of Research 2020 | 300707. Forestry management and environment |
401304. Photogrammetry and remote sensing | |
401302. Geospatial information systems and geospatial data modelling | |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | Australian Centre for Sustainable Catchments |
Monash University | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q114w/statistical-analysis-of-airborne-lidar-data-for-forest-classification-in-the-strzelecki-ranges-victoria-australia
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