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Characterisation of surface roughness and sediment texture of intertidal flats using ERS SAR imagery
van der Wal, D.; Herman, P.M.J.; Wielemaker-Van den Dool, A. (2005). Characterisation of surface roughness and sediment texture of intertidal flats using ERS SAR imagery. Remote Sens. Environ. 98(1): 96-109
In: Remote Sensing of Environment. Elsevier: New York,. ISSN 0034-4257; e-ISSN 1879-0704, meer
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| Trefwoorden |
Mapping
Sedimentary structures > Bedding structures > Ripple marks
Surface roughness
Marien/Kust |
| Auteurs | | Top |
- van der Wal, D.
- Herman, P.M.J.
- Wielemaker-Van den Dool, A.
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| Abstract |
High resolution, synoptic information on sediment characteristics of intertidal flats is required for coastal management, e.g., for habitat mapping and dredging studies. This study aims to derive such information from space-borne Synthetic Aperture Radar (SAR). Estimates of the backscattering coefficient were extracted from ERS-1 SAR and ERS-2 SAR PRI imagery of four intertidal flats in the Westerschelde (southwest Netherlands). They were related to field measurements of surface roughness, moisture conditions and sediment texture. The field data were also used as input to the backscattering model IEM. The data and model predictions show that on the intertidal flats, backscattering depends mainly on vertical surface roughness, with rougher surfaces associated with more backscattering. Surface roughness, mainly determined by the ripple structure of the bed, decreased with the amount of mud in the sediment. This resulted in a significant negative correlation between backscattering and mud content, and a significant positive correlation between backscattering and median grain-size of the sediment. Sediment texture was also correlated with the volumetric moisture content of the sediment, with finer sediments being associated with higher moisture contents. However, moisture contents were generally high, and therefore the backscatter signal was not sensitive to differences in moisture content. The relationships allowed the development of regression models for the prediction of surface characteristics from SAR imagery, from which maps of, for example, mud content, have been derived. |
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