1. A method for discriminating and tracking a coherently structured flow feature dynamically evolving in structure over time within a migratory medium, comprising: establishing a data set captured for a medium undergoing migratory flow at a plurality of physical points defined within a multi-dimensional physical space, each said data set including data content captured for each physical point in terms of a plurality of scalar parameter values; establishing at least one pre-selected target feature type; establishing a scalar field predefined by at least one of said scalar parameters; selectively generating a sparse set of key points within said scalar field, said key points corresponding to at least one coherently structured feature of said target feature type occurring within said physical space, each said key point coinciding with one of said physical points, wherein said coherently structured feature re-shapes over time with respect to other portions of the migratory medium; eliminating a portion of the data set according to said key points to form a partial data set, said partial data set containing the data content of said key points within said sparse set; adaptively determining descriptive information for each said key point according to said target feature type from said data content within a neighborhood of said physical point coinciding therewith, said neighborhood being defined responsive to said target feature type, said descriptive information being determined according to a proximity-based weighting of said data content relative to said key point; and, executing over a time period at least one predetermined feature-based operation responsive to said descriptive information on said partial data set as a surrogate for execution of said predetermined feature-based operation on said data set over the time period, whereby the execution predictively generates evolving flow feature data substantially representative of said data set.