Interpreting Pedestrian Behaviour by Visualising and Clustering Movement Data

Interpreting Pedestrian Behaviour by Visualising and Clustering Movement Data

McArdle, G.
Demsar, U.
Van der Spek, S.C.
McLoone, S.

Architecture and The Built Environment

Urbanism

2013-01-01

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.

geovisual analysis
clustering
space-time cube
movement data analysis

http://resolver.tudelft.nl/uuid:251ef5b0-c839-4544-b574-4cdbe20e17b2

Springer

978-3-642-37086-1

https://doi.org/10.1007/978-3-642-37087-8_6

Lecture Notes in Computer Science, 7820, 2013: Proceedings of the 12th International Symposium W2GIS, Banff, Canada, 4-5 April 2013; Authors version

Institutional Repository

conference paper

(c) 2013 Springer