Machine Learning‐Based Clustering of Oceanic Lagrangian Particles: Identification of the Main Pathways of the Labrador Current
M. Jutras,
N. Planat,
C. O. Dufour
et al.
Abstract:Modeled geospatial Lagrangian trajectories are widely used in Earth Science, including in oceanography, atmospheric science and marine biology. The typically large size of these data sets makes them arduous to analyze, and their underlying pathways challenging to identify. Here, we show that we can use a machine learning unsupervised k‐means++ clustering method combined with expert aggregation of clusters to identify the pathways of the Labrador Current from a large set of modeled Lagrangian trajectories. The … Show more
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