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We present a numerical method to identify regions of phase space that areapproximately retained in a mobile compact neighbourhood over a finite timeduration. Our approach is based on spatio-temporal clustering of trajectorydata. The main advantages of the approach are the ability to produce usefulresults (i) when there are relatively few trajectories and (ii) when there aregaps in observation of the trajectories as can occur with real data. The methodis easy to implement, works in any dimension, and is fast to run.

A rough-and-ready cluster-based approach for extracting finite-time coherent sets from sparse and incomplete trajectory data