Mapping olive varieties and within-field spatial variability using high resolution QuickBird imagery
Paper
Paper/Presentation Title | Mapping olive varieties and within-field spatial variability using high resolution QuickBird imagery |
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Presentation Type | Paper |
Authors | Apan, Armando (Author), Young, Frank R. (Author), Phinn, Stuart (Author), Held, Alex (Author) and Favier, Jason (Author) |
Journal or Proceedings Title | Proceedings of the 12th Australasian Remote Sensing and Photogrammetry Conference |
Year | 2004 |
Place of Publication | Australia |
ISBN | 0958136610 |
Web Address (URL) of Paper | http://www.rss.dola.wa.gov.au/12arspc/ |
Conference/Event | 12th Australasian Remote Sensing and Photogrammetry Conference (ARSPC 2004): To Measure is to Manage |
Event Details | 12th Australasian Remote Sensing and Photogrammetry Conference (ARSPC 2004): To Measure is to Manage Event Date 18 to end of 22 Oct 2004 Event Location Fremantle, Australia |
Abstract | [Abstract]: The growth of the Australian olive (Olea europaea L.) industry requires support from research to ensure its profitability and sustainability. To contribute to this goal, our project tested the ability of remote sensing imagery to map olive groves and their attributes. Specifically, this study aimed to: (a) discriminate olives varieties; and to (b) detect and interpret within-field spatial variability. Using high spatial resolution (2.8m) QuickBird multispectral imagery acquired over Yallamundi (southeast Queensland) on 24 December 2003, both visual interpretation and statistical (divergence) measures were employed to discriminate olive varieties. Similarly, the detection and interpretation of within-field spatial variability was conducted on enhanced false colour composite imagery, and confirmed by the use of statistical methods. establishment in 1998 was identified. More work is being done to develop image classification techniques for mapping within-field spatial variability in olive varieties, biomass and condition using hyperspectral image data, as well as interpreting the cause of observed variability. |
Keywords | QuickBird, olive mapping |
ANZSRC Field of Research 2020 | 401304. Photogrammetry and remote sensing |
Public Notes | No evidence of copyright restrictions. |
Byline Affiliations | Faculty of Engineering and Surveying |
Department of Surveying and Land Information | |
University of Queensland | |
Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia | |
O'Reilly Nunn Favier Consulting Surveyors, Australia |
https://research.usq.edu.au/item/9xw96/mapping-olive-varieties-and-within-field-spatial-variability-using-high-resolution-quickbird-imagery
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