A Route Map to Calibrate Spatial Interaction Models from GPS Movement Data

Sila-Nowicka, K. and Fotheringham, A. S. (2016) A Route Map to Calibrate Spatial Interaction Models from GPS Movement Data. In: GIScience 2016 Workshop on Analysis of Movement Data (AMD'16), Monteral, Canada, 27-30 Sep 2016,

Abstract

The development of sensors such as GPS trackers that capture movement data in realtime and at detailed spatial and temporal scales has transformed our ability to collect mobility data (Kwan and Neutens, 2014). Currently, however, these developments in movement data collection technologies are much further ahead than current methods for extracting meaningful patterns from such data (Laube et al., 2007; Long and Nelson, 2012). Furthermore, there have been very few studies that have tried to explore decision-making processes related with movements using GPS data and similar sources. There is a need therefore to discover if new forms of mobility data can be translated into new insights into movement behaviour. Here we do this through an examination of the calibration of spatial interaction with GPS data. As part of this experiment, we discover what needs to be done to transform raw GPS data into origin-destination matrices of aggregated flows.

• Item Type: Conference Proceedings
• Additional Information: The research leading to these results has received funding from the European Union Seventh Framework Programme - Marie Curie Actions, Initial Training Network GEOCROWD under grant agreement n° FP7-PEOPLE- 2010-ITN-.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Sila-Nowicka, Ms Katarzyna
• Authors: Sila-Nowicka, K., and Fotheringham, A. S.
• Subjects: G Geography. Anthropology. Recreation > G Geography (General); G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography
• College/School: College of Social Sciences > School of Social and Political Sciences > Urban Studies
• Published Online: 20 August 2016
• Copyright Holders: Copyright © 2016 The Authors
• First Published: First published in GIScience 2016 Workshop on Analysis of Movement Data (AMD'16)
• Publisher Policy: Reproduced with the permission of the Editor

Related URLs

• Organisation