Analysing spatially extended high-dimensional dynamics by recurrence plots

TL;DR

This paper demonstrates how recurrence plot measures can effectively analyze high-dimensional spatially extended dynamics, including complex chaos and real-world satellite data, revealing key dynamical properties.

Contribution

It introduces the application of recurrence plot measures to high-dimensional spatially extended systems, including real-world satellite imagery, highlighting their effectiveness.

Findings

Recurrence plot measures can distinguish chaotic from periodic dynamics.

The method successfully analyzes high-dimensional chaos from the Lorenz96 model.

Satellite image time series exhibit identifiable dynamical properties using recurrence plots.

Abstract

Recurrence plot based measures of complexity are capable tools for characterizing complex dynamics. In this letter we show the potential of selected recurrence plot measures for the investigation of even high-dimensional dynamics. We apply this method on spatially extended chaos, such as derived from the Lorenz96 model and show that the recurrence plot based measures can qualitatively characterize typical dynamical properties such as chaotic or periodic dynamics. Moreover, we demonstrate its power by analyzing satellite image time series of vegetation cover with contrasting dynamics as a spatially extended and potentially high-dimensional example from the real world.