Title
Spatio-temporal polygonal clustering with space and time as first-class citizens
Abstract
Detecting spatio-temporal clusters, i.e. clusters of objects similar to each other occurring together across space and time, has important real-world applications such as climate change, drought analysis, detection of outbreak of epidemics (e.g. bird flu), bioterrorist attacks (e.g. anthrax release), and detection of increased military activity. Research in spatio-temporal clustering has focused on grouping individual objects with similar trajectories, detecting moving clusters, or discovering convoys of objects. However, most of these solutions are based on using a piece-meal approach where snapshot clusters are formed at each time stamp and then the series of snapshot clusters are analyzed to discover moving clusters. This approach has two fundamental limitations. First, it is point-based and is not readily applicable to polygonal datasets. Second, its static analysis approach at each time slice is susceptible to inaccurate tracking of dynamic cluster especially when clusters change over both time and space. In this paper we present a spatio-temporal polygonal clustering algorithm known as the Spatio-Temporal Polygonal Clustering (STPC) algorithm. STPC clusters spatial polygons taking into account their spatial and topological properties, treating time as a first-class citizen, and integrating density-based clustering with moving cluster analysis. Our experiments on the drought analysis application, flu spread analysis and crime cluster detection show the validity and robustness of our algorithm in an important geospatial application.
Year
DOI
Venue
2013
10.1007/s10707-012-0157-8
GeoInformatica
Keywords
Field
DocType
Spatio-temporal data mining,Temporal data analysis,Polygonal clustering,Drought analysis,Trend analysis
Geospatial analysis,Cluster (physics),Fuzzy clustering,Data mining,Correlation clustering,Static analysis,Robustness (computer science),FLAME clustering,Cluster analysis,Geography
Journal
Volume
Issue
ISSN
17
2
1384-6175
Citations 
PageRank 
References 
6
0.48
11
Authors
3
Name
Order
Citations
PageRank
Deepti Joshi1625.55
A Samal21033213.54
Leen-kiat Soh359281.43