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1 September 2009 Time-Frequency Methods for Characterizing Cuspate Landforms in Lidar Data
Joseph F. van Gaalen, Sarah E. Kruse, Stephen M. Burroughs, Giovanni Coco
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Time-frequency techniques to characterize cuspate patterns in light detection and ranging (lidar) data are introduced using examples from the Atlantic coast of Florida, United States. These techniques permit the efficient study of beach face landforms over many kilometers of coastline at multiple spatial scales. From a lidar image, a beach-parallel spatial series is generated. Here, this series is the shore-normal position of a specific elevation (contour line). Well-established time-frequency analysis techniques, wavelet transforms, and S-Transforms, are then applied to the spatial series. These methods yield results entirely compatible with the traditional method of estimating the spacing of cuspate features. In addition, confidence intervals are readily established for the spatial extent and wavelengths of cuspate landforms simultaneously at multiple scales. Examples show this method is useful for capturing transitions in cuspate shapes. With the advent of land-based time-lapse lidar, such techniques should be particularly useful for characterizing the evolution of cuspate landforms and testing models for beach face dynamics.

Joseph F. van Gaalen, Sarah E. Kruse, Stephen M. Burroughs, and Giovanni Coco "Time-Frequency Methods for Characterizing Cuspate Landforms in Lidar Data," Journal of Coastal Research 2009(255), 1143-1148, (1 September 2009).
Received: 2 February 2008; Accepted: 1 October 2008; Published: 1 September 2009
Cuspate patterns
time-frequency analysis
Wavelet transform
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