Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/7734
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Detection of estuarine and tidal river hydromorphology using hyper-spectral and LiDAR data: Forth estuary, Scotland
Authors: Gilvear, David
Tyler, Andrew
Davids, Corine
Contact Email: a.n.tyler@stir.ac.uk
Keywords: airborne remote sensing
geomorphology
estuaries
satellites
rivers
river and coastal engineering
Issue Date: Nov-2004
Publisher: Elsevier
Citation: Gilvear D, Tyler A & Davids C (2004) Detection of estuarine and tidal river hydromorphology using hyper-spectral and LiDAR data: Forth estuary, Scotland, Estuarine, Coastal and Shelf Science, 61 (3), pp. 379-392.
Abstract: High spatial resolution hyper-spectral imagery (CASI) and light detection and ranging (LiDAR) imagery acquired for the tidal River Carron and Forth estuary, Scotland, were used in conjunction with field surveys to assess the feasibility of monitoring hydromorphology and human alterations with satellite and airborne remote sensing data. The study was undertaken in the context of the European Union Water Framework Directive (WFD) that requires member states to monitor hydromorphological elements as a component of the ecological status of rivers, estuaries and shorelines. Visual assessment and automated classifications of the imagery were compared with field survey data for an estuarine reach comprising saline waters, mudflats, a tidal reach of a tributary river and an urban/ industrialised shoreline. The morphology of the estuary and inflowing tidal waters together with most artificial features of interest could be clearly seen in the CASI imagery at 1 m spatial resolution. Supervised classification of the imagery produced an overall accuracy value of 72%. Downgrading the imagery to simulate the spatial resolution of 4 m IKONOS satellite data surprisingly improved the accuracy to 74%. Simulation of 10 m SPOT imagery resulted in an image where many artificial features of interest such as roads, pipelines and jetties were rendered invisible. Adding LiDAR data as an additional data set aided manual and automated identification of features and visualisation of the hydromorphology of the rivers and estuaries in the study area. Shadows cast from tall objects were a feature of the winter imagery and reduced automated classification accuracy. Overall, the study demonstrates that high spatial resolution remotely sensed digital imagery has the potential to be a useful tool for panoptic mapping of the geomorphology and human impact on tidal rivers and estuaries. In the context of the WFD, remote sensing provides a potential way forward for monitoring the physical status of rivers and estuaries at the national scale. The possibilities and constraints, in light of the findings of this study, are discussed.
Type: Journal Article
URI: http://hdl.handle.net/1893/7734
URL: http://www.sciencedirect.com/science/article/pii/S0272771404001362
DOI Link: http://dx.doi.org/10.1016/j.ecss.2004.06.007
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
Affiliation: Biological and Environmental Sciences
Biological and Environmental Sciences
University of Stirling

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