The particle swarm optimisation for spectral matching applied to inland water quality remote sensing

Campbell, G. and Phinn, S. and Dekker, A. and Brando, V. (2011) The particle swarm optimisation for spectral matching applied to inland water quality remote sensing. In: 34th International Symposium on Remote Sensing of Environment, 10-15 April 2011, Sydney, Australia.

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Abstract

Spectrum matching is one approach to estimating water quality parameter concentrations (chlorophyll a, tripton and coloured dissolved organic matter (CDOM)) from remotely sensed images of inland waters. The Particle Swarm Optimisation (PSO) is a stochastic search technique that can be used to search the solution space for the closest match and deliver the best estimate of the water quality parameter concentrations. For Burdekin Falls Dam, a tropical freshwater impoundment, the PSO and four different matching criteria were applied to MERIS images to retrieve the water quality parameters. The mean retrieval error of the best performed similarity measure was 2.0 μgl-1, 2.45 mgl-1 and 0.3 m-1 for chlorophyll a, tripton and CDOM respectively. The paper found that the PSO, as implemented in this case, did not offer improvements in accuracy and precision sufficient enough to justify the increased computational overhead in the inversion.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: No
Item Status: Live Archive
Additional Information: No evidence of copyright restrictions preventing deposit.
Depositing User: Mr Glenn Campbell
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - No Department
Date Deposited: 08 Mar 2012 06:15
Last Modified: 03 Jul 2013 00:37
Uncontrolled Keywords: inland water, Particle Swarm Optimisation, phytoplankton, tripton, CDOM
Fields of Research (FOR2008): 09 Engineering > 0909 Geomatic Engineering > 090905 Photogrammetry and Remote Sensing
05 Environmental Sciences > 0502 Environmental Science and Management > 050206 Environmental Monitoring
Socio-Economic Objective (SEO2008): D Environment > 96 Environment > 9606 Environmental and Natural Resource Evaluation > 960608 Rural Water Evaluation (incl. Water Quality)
URI: http://eprints.usq.edu.au/id/eprint/18949

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