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dc.contributor.authorBrum-Bastos, Vanessa
dc.contributor.authorŁoś, Marcelina
dc.contributor.authorLong, Jed
dc.contributor.authorNelson, Trisalyn
dc.contributor.authorDemsar, Urska
dc.date.accessioned2021-08-11T16:30:15Z
dc.date.available2021-08-11T16:30:15Z
dc.date.issued2021-08-09
dc.identifier.citationBrum-Bastos , V , Łoś , M , Long , J , Nelson , T & Demsar , U 2021 , ' Context-aware movement analysis in ecology : a systematic review ' , International Journal of Geographical Information Science , vol. Latest Articles . https://doi.org/10.1080/13658816.2021.1962528en
dc.identifier.issn1365-8816
dc.identifier.otherPURE: 275239586
dc.identifier.otherPURE UUID: a4d6132e-5dc7-4e60-9b41-36996c975d07
dc.identifier.otherWOS: 000683215700001
dc.identifier.otherScopus: 85112045824
dc.identifier.urihttp://hdl.handle.net/10023/23763
dc.descriptionThis work was supported by the Coordination for the Improvement of Higher Education Personnel (BEX:13438/13-1), the Leverhulme Trust Research Project Grant (RPG-2018-258); the Discovery grant from the Natural Sciences and Engineering Research Council of Canada the Polish National Science Centre (UMO-2019/35/O/ST6/04127).en
dc.description.abstractResearch on movement has increased over the past two decades, particularly in movement ecology, which studies animal movement. Taking context into consideration when analysing movement can contribute towards the understanding and prediction of behaviour. The only way for studying animal movement decision-making and their responses to environmental conditions is through analysis of ancillary data that represent conditions where the animal moves. In GIScience this is called Context-Aware Movement Analysis (CAMA). As ecology becomes more data-oriented, we believe that there is a need to both review what CAMA means for ecology in methodological terms and to provide reliable definitions that will bridge the divide between the content-centric and data-centric analytical frameworks. We reviewed the literature and proposed a definition for context, develop a taxonomy for contextual variables in movement ecology and discuss research gaps and open challenges in the science of movement more broadly. We found that the main research for CAMA in the coming years should focus on: 1) integration of contextual data and movement data in space and time, 2) tools that account for the temporal dynamics of contextual data, 3) ways to represent contextualized movement data, and 4) approaches to extract meaningful information from contextualized data.
dc.format.extent23
dc.language.isoeng
dc.relation.ispartofInternational Journal of Geographical Information Scienceen
dc.rightsCopyright © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.en
dc.subjectMovement analysisen
dc.subjectTracking dataen
dc.subjectEnvironmental dataen
dc.subjectContexten
dc.subjectMovement ecologyen
dc.subjectG Geography (General)en
dc.subjectZ665 Library Science. Information Scienceen
dc.subject.lccG1en
dc.subject.lccZ665en
dc.titleContext-aware movement analysis in ecology : a systematic reviewen
dc.typeJournal itemen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.School of Geography & Sustainable Developmenten
dc.contributor.institutionUniversity of St Andrews.Bell-Edwards Geographic Data Instituteen
dc.contributor.institutionUniversity of St Andrews.Environmental Change Research Groupen
dc.identifier.doihttps://doi.org/10.1080/13658816.2021.1962528
dc.description.statusPeer revieweden


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