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Towards airborne remote sensing of water quality in The Netherlands - validation and error analysis

Hakvoort, H. and De Haan, J. and Jordans, R.W.J. and Vos, R. and Peters, S.W.M. and Rijkeboer, M. (2002) Towards airborne remote sensing of water quality in The Netherlands - validation and error analysis. ISPRS Journal of Photogrammetry and Remote Sensing, 57, 171-183. ISSN 0924-2716.

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Water managers request maps of water quality parameters such as concentrations of dissolved organic matter (CDOM), chlorophyll or total suspended matter (TSM). Rijkswaterstaat sets up a production chain for such maps using a hyperspectral imaging scanner installed in the Dutch coast guard aircraft. Water quality parameters are retrieved from remote-sensed images using successively: (1) a module calculating the subsurface reflectance spectra and (2) a module calculating the concentrations using specific inherent optical properties (SIOP) of the water constituents and the Gordon reflectance model implemented in a matrix inversion technique. The accuracy of several numerical methods for retrieval of concentrations from reflectance spectra was assessed. Effects of instrumental noise, errors in the atmospheric correction and errors in the specific inherent optical properties on the derived concentrations were also estimated. A benchmark data set was collected for Lake Veluwe in the Netherlands. For ideal circumstances, two of the tested numerical methods were able to retrieve both total suspended matter as well as chlorophyll concentration. For less favourable circumstances, total suspended matter could still be retrieved, but chlorophyll became less accurate. Dissolved organic matter concentrations could not be retrieved for any case. Application of the matrix inversion technique tested on an airborne image from Lake Veluwe showed promising results. [KEYWORDS: algorithms; coastal zones; hyperspectral; inland water; sensors; simulation]

Item Type:Article
Institutes:Nederlands Instituut voor Ecologie (NIOO)
ID Code:11157
Deposited On:24 Nov 2011 01:00
Last Modified:31 Mar 2014 10:28

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