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Identification of patterns over regional scales using self-organising maps on images from marine modelling outputs


de Souza Jr, PA and Williams, RN and Jones, EM, Identification of patterns over regional scales using self-organising maps on images from marine modelling outputs, Proceedings of the 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA), 3-5 December 2012, Perth, Australia, pp. 1-6. ISBN 978-1-4673-2179-2 (2012) [Refereed Conference Paper]

Copyright Statement

Copyright 2012 IEEE

DOI: doi:10.1109/DICTA.2012.6411677


The Self-Organizing Feature Map (or SOM) has been used to analyse a dataset consisting of oceanographic modelling output images, in order to identify patterns in the hydrodynamic behaviour of the south-east Tasmanian (SETas) coastal region over a 360-day period between August 2009 and August 2010. The SOM provided a visualization of the dataset, distributed across a 5x7 two-dimensional grid, which enabled an oceanographer to identify significant hydrodynamic patterns being exhibited by the SETas region over that period. Four prototype (typical) states were identified by the oceanographer, who then interpreted each of these states in terms of the major ocean currents which impact on the region; the East Australian Current and the Zeehan Current. These results indicate that SOM analysis can be a useful technique for identifying patterns in large oceanographic datasets, such as those now being provided by remote sensing, ocean modelling and marine sensor network technologies.

Item Details

Item Type:Refereed Conference Paper
Keywords:self-organizing maps, ocean modelling, pattern recognition, model output images
Research Division:Information and Computing Sciences
Research Group:Computer vision and multimedia computation
Research Field:Pattern recognition
Objective Division:Environmental Management
Objective Group:Marine systems and management
Objective Field:Oceanic processes (excl. in the Antarctic and Southern Ocean)
UTAS Author:de Souza Jr, PA (Professor Paulo de Souza Junior)
UTAS Author:Williams, RN (Dr Ray Williams)
ID Code:82202
Year Published:2012
Deposited By:Information and Communication Technology
Deposited On:2013-01-21
Last Modified:2017-11-06

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