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Mov Ecol. 2015 Mar 10;3(1):5. doi: 10.1186/s40462-015-0032-y. eCollection 2015.

Analysis and visualisation of movement: an interdisciplinary review.

Author information

1
School of Geography & Geosciences, University of St Andrews, Irvine Building, North Street, St Andrews, Fife, Scotland KY16 9AL UK.
2
Department of Mathematics and Computer Science, Technical University Eindhoven, Eindhoven, The Netherlands.
3
Biodiversity and Molecular Ecology Department, IASMA Research and Innovation Centre, Fondazione Edmund Mach, Trento, Italy.
4
Department of Migration and Immuno-ecology, Max Planck Institute for Ornithology, Munich, Germany ; Department of Biology, University of Konstanz, Konstanz, Germany.
5
Department of Geography, Ghent University, Ghent, Belgium.
6
Visualization Research Center, University of Stuttgart, Stuttgart, Germany.
7
Department of Geography, University of Zurich, Zurich, Switzerland.

Abstract

The processes that cause and influence movement are one of the main points of enquiry in movement ecology. However, ecology is not the only discipline interested in movement: a number of information sciences are specialising in analysis and visualisation of movement data. The recent explosion in availability and complexity of movement data has resulted in a call in ecology for new appropriate methods that would be able to take full advantage of the increasingly complex and growing data volume. One way in which this could be done is to form interdisciplinary collaborations between ecologists and experts from information sciences that analyse movement. In this paper we present an overview of new movement analysis and visualisation methodologies resulting from such an interdisciplinary research network: the European COST Action "MOVE - Knowledge Discovery from Moving Objects" (http://www.move-cost.info). This international network evolved over four years and brought together some 140 researchers from different disciplines: those that collect movement data (out of which the movement ecology was the largest represented group) and those that specialise in developing methods for analysis and visualisation of such data (represented in MOVE by computational geometry, geographic information science, visualisation and visual analytics). We present MOVE achievements and at the same time put them in ecological context by exploring relevant ecological themes to which MOVE studies do or potentially could contribute.

KEYWORDS:

Animal movement; Computational geometry; Geographic information science; Interdisciplinary developments; Movement ecology; Spatio-temporal analysis; Spatio-temporal visualisation; Trajectories; Visual analytics; Visualisation

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