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LiDAR mapping of tidal marshes for ecogeomorphological modelling in the TIDE project

Mason, D. C. ORCID: https://orcid.org/0000-0001-6092-6081, Marani, M., Belluco, E., Feola, A., Ferrari, S., Katzenbeisser, R., Lohani, B., Menenti, M., Paterson, D.M., Scott, T.R., Vardy, S., Wang, C. and Wang, H.-J. (2005) LiDAR mapping of tidal marshes for ecogeomorphological modelling in the TIDE project. In: Eighth International Conference on Remote Sensing for Marine and Coastal Environments, 17-19 May 2005, Halifax, Nova Scotia. (Unpublished)

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Abstract/Summary

The European research project TIDE (Tidal Inlets Dynamics and Environment) is developing and validating coupled models describing the morphological, biological and ecological evolution of tidal environments. The interactions between the physical and biological processes occurring in these regions requires that the system be studied as a whole rather than as separate parts. Extensive use of remote sensing including LiDAR is being made to provide validation data for the modelling. This paper describes the different uses of LiDAR within the project and their relevance to the TIDE science objectives. LiDAR data have been acquired from three different environments, the Venice Lagoon in Italy, Morecambe Bay in England, and the Eden estuary in Scotland. LiDAR accuracy at each site has been evaluated using ground reference data acquired with differential GPS. A semi-automatic technique has been developed to extract tidal channel networks from LiDAR data either used alone or fused with aerial photography. While the resulting networks may require some correction, the procedure does allow network extraction over large areas using objective criteria and reduces fieldwork requirements. The networks extracted may subsequently be used in geomorphological analyses, for example to describe the drainage patterns induced by networks and to examine the rate of change of networks. Estimation of the heights of the low and sparse vegetation on marshes is being investigated by analysis of the statistical distribution of the measured LiDAR heights. Species having different mean heights may be separated using the first-order moments of the height distribution.

Item Type:Conference or Workshop Item (Paper)
Refereed:No
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Environmental Systems Science Centre
ID Code:5887

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