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  4. Scalable analysis of movement data for extracting and exploring significant places
 
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2013
Journal Article
Title

Scalable analysis of movement data for extracting and exploring significant places

Abstract
Place-oriented analysis of movement data, i.e., recorded tracks of moving objects, includes finding places of interest in which certain types of movement events occur repeatedly and investigating the temporal distribution of event occurrences in these places and, possibly, other characteristics of the places and links between them. For this class of problems, we propose a visual analytics procedure consisting of four major steps: 1) event extraction from trajectories; 2) extraction of relevant places based on event clustering; 3) spatiotemporal aggregation of events or trajectories; 4) analysis of the aggregated data. All steps can be fulfilled in a scalable way with respect to the amount of the data under analysis; therefore, the procedure is not limited by the size of the computer's RAM and can be applied to very large data sets. We demonstrate the use of the procedure by example of two real-world problems requiring analysis at different spatial scales.
Author(s)
Andrienko, Gennady
Andrienko, Natalia
Hurter, C.
Rinzivillo, Salvatore
Wrobel, Stefan  
Journal
IEEE transactions on visualization and computer graphics  
Open Access
DOI
10.1109/TVCG.2012.311
Language
English
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
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