Mining Evolution Patterns from Complex Trajectory Structures—A Case Study of Mesoscale Eddies in the South China Sea

Abstract

Real-word phenomena, such as ocean eddies and clouds, tend to split and merge while they are moving around within a space. Their trajectories usually bear one or more branches and are accordingly defined as complex trajectories in this study. The trajectories may show significant spatiotemporal variations in terms of their structures and some of them may be more prominent than the others. The identification of prominent structures in the complex trajectories of such real-world phenomena could better reveal their evolution processes and even shed new light on the driving factors behind them. Methods have been proposed for the extraction of periodic patterns from simple trajectories (i.e., those with linear structure and without any branches) with a focus on mining the related temporal, spatial or semantic information. Unfortunately, it is not appropriate to directly use such methods to examine complex trajectories. This study proposes a novel method to study the periodic patterns of complex trajectories by considering the inherent spatial, temporal and topological information. First, we use a sequence of symbols to represent the various structures of a complex trajectory over its lifespan. We then, on the basis of the PrefixSpan algorithm, propose a periodic pattern mining of structural evolution (PPSE) algorithm and use it to identify the largest and most frequent patterns (LFPs) from the symbol sequence. We also identify potential periodic behaviors. The PPSE method is then used to examine the complex trajectories of the mesoscale eddy in the South China Sea (SCS) from 1993 to 2016. The complex trajectories of ocean eddies in the southeast of Vietnam show are different from other regions in the SCS in terms of their structural evolution processes, as indicated by the LFPs with the longest lifespan, the widest active range, the highest complexity, and the most active behaviors. The LFP in the southeast of Vietnam has the longest lifespan, the widest active range, the highest complexity, and the most active behaviors. Across the SCS, we found seven migration channels. The LFPs of the eddies that migrate through these channels have a temporal cycle of 17–24 years. These channels are also the regions where eddies frequently emerge, as revealed by flow field data.

PoSDMS: A Mining System for Oceanic Dynamics with Time Series of Raster-Formatted Datasets

“…The world is geographically dynamic [1,2], and this dynamism has drawn increasing attention in recent years. This attention has focused on dynamic object extraction and analysis, dynamic mining methods, mining frameworks and tools [3][4][5][6] and especially on oceanic dynamics [3,[7][8][9][10]. Series of images taken by advanced Earth-observing technologies over long periods of time, combined with historical climate records, constitute the main source of continuous and consistent information about the marine environment [11,12] and offer new opportunities for monitoring oceanic dynamics and understanding their evolutionary patterns [10].…”

“…Generally, a scale of geographical dynamic evolution is out of step with the scale of data observation; some evolutionary relationships among geographical dynamics will be lost. To obtain true evolutionary relationships, a process-oriented idea was proposed to obtain marine anomalies [13,19,26]; to represent and analyze such dynamic changes, the graph-based model was used for urban hot islands [30], rainstorms [17,31], land use and cover changes [12] and oceanic eddies [3,9].…”

Multi-Objective Design of Profit Volumes and Closeness Ratings Using MBHS Optimizing Based on the PrefixSpan Mining Approach (PSMA) for Product Layout in Supermarkets

“…Product layout can not only catch the eyes and draw the attention of consumers but also increase customer purchases and satisfaction. Previous studies [10][11][12][13] have also implemented sequential pattern mining to explore frequent sequential patterns, which are considered necessary for determining the frequency of product purchases [14].…”