A framework for models of movement in geographic space
Wang, Jia ORCID: 0000-0003-4379-9724, Duckham, Matt and Worboys, Michael (2016) A framework for models of movement in geographic space. International Journal of Geographical Information Science (Special Issue: Analysis of Movement Data), 30 (5). pp. 970-992. ISSN 1365-8816 (Print), 1365-8824 (Online) (doi:https://doi.org/10.1080/13658816.2015.1078466)
|
PDF (Author's Accepted Manuscript)
15536_Wang_A framework for models of movement (AAM) 2016.pdf - Accepted Version Download (1MB) | Preview |
Abstract
This article concerns the theoretical foundations of movement informatics. We discuss general frameworks in which models of spatial movement may be developed. In particular, the article considers the object–field and Lagrangian–Eulerian dichotomies, and the SNAP/SPAN ontologies of the dynamic world, and classifies the variety of informatic structures according to these frameworks. A major challenge is transitioning between paradigms. Usually data is captured with respect to one paradigm but can usefully be represented in another. We discuss this process in formal terms and then describe experiments that we performed to show feasibility. It emerges that observational granularity plays a crucial role in these transitions.
Item Type: | Article |
---|---|
Additional Information: | This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Geographical Information Science in 20/8/2015, available online: http://www.tandfonline.com/doi/full/10.1080/13658816.2015.1078466 |
Uncontrolled Keywords: | movement, field, object, Eulerian, Lagrangian, granularity |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Faculty / School / Research Centre / Research Group: | Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science |
Last Modified: | 04 Mar 2022 13:07 |
URI: | http://gala.gre.ac.uk/id/eprint/15536 |
Actions (login required)
View Item |
Downloads
Downloads per month over past year