McArdle, Gavin and Demšar, Urška and van der Spek, Stefan and Sean, McLoone (2013) Interpreting Pedestrian Behaviour by Visualising and Clustering Movement Data. Web and Wireless Geographical Information Systems: Lecture Notes in Computer Science, 7820. pp. 61-81. ISSN 0302-9743

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Abstract

Recent technological advances have increased the quantity of movement data being recorded. While valuable knowledge can be gained by analysing such data, its sheer volume creates challenges. Geovisual analytics, which helps the human cognition process by using tools to reason about data, offers powerful techniques to resolve these challenges. This paper introduces such a geovisual analytics environment for exploring movement trajectories, which provides visualisation interfaces, based on the classic space-time cube. Additionally, a new approach, using the mathematical description of motion within a space-time cube, is used to determine the similarity of trajectories and forms the basis for clustering them. These techniques were used to analyse pedestrian movement. The results reveal interesting and useful spatiotemporal patterns and clusters of pedestrians exhibiting similar behaviour.

Item Type:	Article
Keywords:	Geovisual Analysis; Clustering; Space-time Cube; Movement Data Analysis;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
Item ID:	5515
Depositing User:	Dr. Gavin McArdle
Date Deposited:	28 Oct 2014 11:01
Journal or Publication Title:	Web and Wireless Geographical Information Systems: Lecture Notes in Computer Science
Publisher:	Springer
Refereed:	Yes
Funders:	Science Foundation Ireland
URI:
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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