Paper
25 November 1986 Shallow Water Bathymetry And Bottom Classification By Means Of The Landsat And SPOT Optical Scanners
D Spitzer, R.W . J Dirks
Author Affiliations +
Abstract
Optical remote sensing of coastal and estuarine areas concerns observations of the bottom and watercolumn features. Though the spectral characteristics of the Landsat and. SPOT sensors do not allow detailed determination of concentrations of specific components suspended and dissolved in the seawater, it can provide the data on the depth and bottom type. Modelling of the radiative transfer in the watermass gives evaluation of the upwelled radiance signals detected by the remote sensors in the specific bands. Typical watercolumn and bottom spectral signatures are used as input parameters in a two-flow model. Algorithms are developed relating the optical signals tot the features to be remotely mapped. An optimal bottom depth algorithm should be linear, highly sensitve to the depth variations and insensitive to the watercolumn and bottom composition variations. Analogously, an optimal bottom classification algorithm should be sensitive only to the bottom type variations. Generally, algorithms employing ratios and/or differences between the outputs of the sensor's spectral channels are most favourable due to their capability of canceling out some unwanted surface and atmospheric effects. From the modelling several algorithms are proposed and their (in)sensitivity to the features of interest tested. The results demonstrate the applicability of the Landsat and SPOT sensors for mapping of the bottom depth and type down to 3-20 m, dependently on the watercolumn and bottom composition.
© (1986) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
D Spitzer and R.W . J Dirks "Shallow Water Bathymetry And Bottom Classification By Means Of The Landsat And SPOT Optical Scanners", Proc. SPIE 0660, Earth Remote Sensing Using the Landsat Thermatic Mapper and SPOT Sensor Systems, (25 November 1986); https://doi.org/10.1117/12.938578
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Cited by 5 scholarly publications.
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KEYWORDS
Reflectivity

Sensors

Earth observing sensors

Landsat

Absorption

Algorithm development

Remote sensing

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