期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2010
卷号：XXXVIII - Part 2
页码：86-91
出版社：Copernicus Publications
摘要：More and more mobile objects are now equipped with sensors allowing real time monitoring of their movements. Nowadays, the data produced by these sensors can be stored in spatio-temporal databases. The main goal of this article is to perform a data mining on a huge quantity of mobile object's positions moving in an open space in order to deduce its behaviour. New tools must be defined to ease the detection of outliers. First of all, a zone graph is set up in order to define itineraries. Then, trajectories of mobile objects following the same itinerary are extracted from the spatio-temporal database and clustered. A statistical analysis on this set of trajectories lead to spatio-temporal patterns such as the main route and spatio-temporal channel followed by most of trajectories of the set. Using these patterns, unusual situations can be detected. Furthermore, a mobile object's behaviour can be defined by comparing its positions with these spatio-temporal patterns. In this article, this technique is applied to ships' movements in an open maritime area. Unusual behaviours such as being ahead of schedule or delayed or veering to the left or to the right of the main route are detected. A case study illustrates these processes based on ships' positions recorded during two years around the Brest area. This method can be extended to almost all kinds of mobile objects (pedestrians, aircrafts, hurricanes, ...) moving in an open area
关键词：spatio-temporal patterns; data mining; mobile object; outlier detection; maritime GIS
