Abstract

Quantification of tidal flat morphological changes at varying timescales is critical from a management point of view. High-resolution tidal flat morphology data, including those for mudflats and salt-marshes, are rare due to monitoring difficulty by traditional methods. Recent advances in Terrestrial Laser Scanner (TLS) technology allow rapid acquisition of high-resolution and large-scale morphological data, but it remains problematic for its application on salt-marshes due to the presence of dense vegetation. In this study, we applied a TLS system to retrieve high-accuracy digital elevation models in a tidal flat of the Yangtze Estuary by using a robust and accurate Progressive Morphological filter (PM) to separate ground and non-ground points. Validations against GPS-supported RTK measurements suggested remarkable performance. In this case the average estimation error was about 0.3cm, while the Root Mean Square Error (RMSE) was 2.0cm. We conducted three TLS surveys on the same field including salt-marshes and mudflats at the time points 5days before, 3days after, and 45days after a typhoon event. The retrieved data showed that the mudflats suffered from profound erosion while the salt-marshes slightly accreted during the typhoon period. The average elevation change of the total area was about −4cm (−0.28cm per day). However, both the mudflats and salt-marshes deposited in the post-typhoon period and the accretion over salt-marshes occurred at a higher rate than that during the typhoon. The elevation of the total area increased by 15.9cm (0.37cm per day), suggesting fast recovery under calm conditions. Quantification of the erosion and deposition rates was aided by the high quality TLS data. This study shows the effectiveness of TLS in quantifying morphological changes of tidal flats at an event (and post-event) timescale. The data and analysis also provide sound evidence on vegetation impact in stimulating salt-marsh development and restoration, shedding lights on bio-morphological interactions.

Full Text
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