Automated Detection of Rip Currents in ARGUS Imagery using Direction of Minimum Variance Parameter

Authors: Sarah Trimble*, US Naval Research Laboratory
Topics: Coastal and Marine, Geographic Information Science and Systems, Remote Sensing
Keywords: coastal, rip current, radar, remote sensing, GIS
Session Type: Guided Poster
Day: 4/4/2019
Start / End Time: 3:05 PM / 4:45 PM
Room: Roosevelt 3.5, Marriott, Exhibition Level
Presentation File: No File Uploaded


Rip currents play an important role in nearshore geomorphologic evolution, sediment transport, and surfzone safety. With the increase of remotely sensed observations over the last decade, new methods to study and detect rip current generation and evolution have become more available. Here, we use a well-known parameter, the direction of minimum variance, to automatically detect bathymetric rip currents from remotely sensed ARGUS Imagery. The direction of minimum variance was previously used to automate the identification of anisotropic, shore-normal features in high resolution bathymetric data. We have developed a method utilizing this parameter to analyze the variance in the dark and light pixels of time lapse ARGUS imagery that allows for the detection of bathymetric rip currents. Rip currents detected with this method are compared to those detected by X-band radar with good agreement. This method can therefore successfully discriminate between bathymetric rip currents and other surfzone features, such as sandbars, and is computationally efficient. Results have implications for surfzone safety, as well as optimizing nearshore research. It is also suggested that the direction of minimum variance parameter could be further adapted to automate detection of additional geomorphological features of interest in other types of grid data.

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