Discrimination of remnant tree species and regeneration stages in Queensland, Australia using hyperspectral imagery
Paper
Paper/Presentation Title | Discrimination of remnant tree species and regeneration stages in Queensland, Australia using hyperspectral imagery |
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Presentation Type | Paper |
Authors | Apan, Armando (Author), Phinn, Stuart (Author) and Maraseni, Tek (Author) |
Editors | Luo, Bin |
Journal or Proceedings Title | Proceedings of the 1st Workshop on Hyperspectral Image and Signal Processing (WHISPERS 2009) |
Number of Pages | 4 |
Year | 2009 |
Place of Publication | Piscataway, NJ. United States |
ISBN | 9781424446872 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/WHISPERS.2009.5288981 |
Web Address (URL) of Paper | http://www.ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5288981&isnumber=5288971 |
Conference/Event | WHISPERS 2009: Evolution in Remote Sensing |
Event Details | WHISPERS 2009: Evolution in Remote Sensing Event Date 26 to end of 28 Aug 2009 Event Location Grenoble, France |
Abstract | This study assessed the utility of hyperspectral imagery in discriminating remnant tree species and stand regeneration stages in Southeast Queensland, Australia. Reflectance data of three species of woody vegetation (i.e. Eucalyptus populnea, Acacia pendula and Eucalyptus orgadophila), acquired using a HyMap™ airborne system, were analysed using partial least squares (PLS) regression. Three groups of E. orgadophila species, representing stand regeneration status, were also evaluated. For discriminating such tree species, the PLS results showed high prediction accuracy ranging from 83-88%. The most significant spectral bands span from the visible region (peak at 558nm and 689nm), near-infrared region (peak at 987nm), and shortwave infrared region (peak at 1788nm). Hyperspectral data was able to discriminate the old stand of E. orgadophila from the young stand, with a moderate accuracy of 72%. Results such as these confirmed the potential utility of hyperspectral data in vegetation mapping and stand characterisation. |
Keywords | vegetation; species; regeneration; Australia; HyMap airborne system; Southeast Queensland; hyperspectral imagery; partial least squares regression; remnant tree species discrimination; vegetation mapping |
ANZSRC Field of Research 2020 | 300707. Forestry management and environment |
410304. Environmental biotechnology diagnostics (incl. biosensors) | |
401304. Photogrammetry and remote sensing | |
Public Notes | © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Byline Affiliations | Australian Centre for Sustainable Catchments |
University of Queensland |
https://research.usq.edu.au/item/9z93y/discrimination-of-remnant-tree-species-and-regeneration-stages-in-queensland-australia-using-hyperspectral-imagery
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