Campbell, Glenn and Phinn, Stuart (2008) The efficacy of band weighting schemes for improving the accuracy and precision of water quality parameters estimated from MERIS and MODIS image data. In: 14th Australasian Remote Sensing and Photogrammetry Conference incorporating the North Australian Remote Sensing and GIS Conference, 29 Sept - 03 Oct 2008, Darwin, Australia.
[Abstract]: Optical remote sensing has been used to map and monitor water quality parameters such as the concentrations of hydrosols (chlorophyll and other pigments, total suspended material, and coloured dissolved organic matter). One approach to estimate hydrosol concentrations is to apply a Matrix Inversion Method (MIM) to the reflectance in each band, creating a system of linear equations, and then apply a least squares method to solve for the hydrosol concentrations.
The accuracy and precision of this method depends on the width, position and inherent noise in the spectral bands of the sensor being employed, as well as the radiometric corrections applied to images to calculate the subsurface
reflectance. It has been suggested that by differentially weighting the band equations in over-determined systems the reliance of the solution on any one band can adjusted. The aim of this work was to establish if this is true and if so,determine the optimal weighting regime for each sensor.
The Hydrolight® radiative transfer model and typical hydrosol concentrations from Wivenhoe Dam, a large freshwater storage in South East Queensland, were used to simulate 1089 reflectance spectra for MERIS and MODIS images acquired at two sun positions. The accuracy and precision of hydrosol concentrations derived from each weighting regime were evaluated after errors associated with the air-water interface correction, atmospheric correction and the IOP measurement were modelled and applied to the simulated reflectance spectra. The technique showed the ability of a weighting regime to alleviate the effect of these errors and was used as a measure of a regime’s efficacy.
The results of this study will be used to improve an algorithm for the remote sensing of water quality for freshwater impoundments.
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|Item Type:||Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)|
|Publisher:||Spatial Sciences Institute|
|Item Status:||Live Archive|
|Additional Information (displayed to public):||No evidence of copyright restrictions.|
|Depositing User:||Mr Glenn Campbell|
|Faculty / Department / School:||Historic - Faculty of Engineering and Surveying - No Department|
|Date Deposited:||15 Jan 2009 05:26|
|Last Modified:||02 Jul 2013 23:12|
|Uncontrolled Keywords:||reamote sensing, water, least squares, algal blooms, sediment|
|Fields of Research (FoR):||09 Engineering > 0909 Geomatic Engineering > 090905 Photogrammetry and Remote Sensing|
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