Research On Spatio-temporal Analysis Of Stay Characteristics Of Vessel’s Trajectory Based On AIS Data

With the gradual increase in the focus of maritime trade,the number of vessels invested in marine transportation is increasing,and the commerce,logistics,and shipping industries in coastal areas have developed rapidly.In this context,on the one hand,a large number of AIS(Automatic Identification System)has generated largescale vessel navigation data;on the other hand,the huge consumer market and huge profits at home and abroad have promoted illegal crimes at sea(smuggling,smuggling,piracy,etc.)to become increasingly rampant.AIS data contains various behavioral characteristics of the vessel’s activity trajectory.Among them,the occurrence of staying behavior is an important representation of the change of the vessel’s activity state.Usually,the place where the staying behavior occurs is at the anchorage or berth,but the complexity of the purpose of the marine activity behaviors makes the staying space not limited to the anchorage or berth in space.Therefore,extracting the vessel’s stay characteristics based on AIS data and exploring its spatio-temporal aggregation characteristics and spatio-temporal correlation characteristics are of great significance for the maritime department to monitor the vessel’s stay activities and discover the stay rules.This study is based on vessel trajectory AIS data to realize the AIS spatial with time series database building.Combining the vessel’s stay characteristics and trajectory data’s time series characteristics,this paper analyzes the trajectory expression method that takes into account the vessel’s stay characteristics,and on this basis,analyzes the vessel’s stay trajectory spatio-temporal aggregation.combined with the feature of vessel characteristics and trajectory data sequence,trajectory expression method of analyzing the characteristic of the stay of vessel,and on this basis,the analysis of vessel trajectorytemporal aggregation characteristics,and explore the spatio-temporal correlation characteristics of unconventional anchoring and staying behavior.The study contents and results of this paper are as follows:(1)Building of AIS Database Based on Time Series Features.Aiming at the basic characteristics of time series data,explore the data characteristics to be dealt with when building AIS database.By analyzing the organization structure of the time series database,the benefits of AIS data expressed in a wide-table model are determined,and the building of the AIS time series database based on Timescale DB is realized.Timescale DB provides data organization and query methods that take into account time partition and spatial property and is used in data storage and query processing.Experimental analysis on both sides further shows that the time series database building scheme can support the AIS data storage and query processing of the vessel in the dynamically changing navigatetional status.(2)Trajectory expression method considering vessel’s stay characteristics.According to the expression characteristics of vessel’s staying activity,the analysis of speed,time and distance shows that the stay-trajectory is a set of time series points with low speed and aggregation.Intuitively expressed the characteristics of the flat sequence of the stay trajectory,and compared the extraction effect of the stay trajectory with the ST-DBSCAN method and validation stay-points dataset,and the results show that the method based on geometric curve is more accurate and efficient.(3)Analysis of the spatio-temporal characteristics of vessel’s staying point in Zhoushan sea waters.Aiming at the aggregation of vessel’s staying points,the semantic information of staying points is extracted.On the one hand,it analyzes the spatial and temporal aggregation characteristics of the vessel’s staying behavior.Information,construct a spatio-temporal correlation feature model of ship staying behavior,and combine association rule mining methods to achieve spatio-temporal correlation analysis of ship staying behavior in unconventional anchoring areas away from the island coast scene.In this study,taking the vessel AIS data in Zhoushan sea water as an example,the spatio-temporal features of the vessel’s stay-points are excavated.The main features are:(1)spatio-temporal aggregation features.The spatial distribution of vessel’s staypoints is not random or evenly distributed,but mainly concentrated on the near-shore anchorages and berths(island and shore),and randomly distributed on the offshore anchorages and other sea waters;in addition,there are obvious anchoring factors for stay-points hot spots There are still hot spots for staying in other seas;Vessel stays are mainly cargo vessels,tankers,passenger vessels,fishing,and tugboats,and there are obvious differences in distribution;The staying rules of different anchorage areas have spatial stratified heterogeneity;on the other hand,the duration of stay-points is mainly within 24 hours,and the beginning of the stay In terms of time and end time,the number of stays per hour changes in a period of 24 hours;(2)spatio-temporal correlation features.For the vessel’s staying scene away from the coast of the island,the typical spatio-temporal association rules of the staying behavior are extracted,and the front and back of each rule have positive correlation,which reflects the effectiveness of the mining results.