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Dynamic and Mobile GIS: Investigating Changes in Space and Time - Chapter 14

Chapter 14 Analysing Point Motion with Geographic Knowledge Discovery Techniques Patrick Laube 1, Ross S. Purves 2, Stephan Imfeld 2 and Robert Weibel 2 1 School of Geography and Environmental Science, University of Auckland, New Zealand 2 Department of Geography, University of Zurich, Switzerland 14.1 Introduction Mobility is key to contemporary life. In a globalised world, people, goods, data and ideas move in increasing volumes at increasing speeds over increasing distances, and more and more leave a digital trail behind them. More and more such tracking data is automatically collected in large databases. Exploring the dynamic processes afforded by the study of such digital trails—in. | Chapter 14 Analysing Point Motion with Geographic Knowledge Discovery Techniques Patrick Laube 1 Ross S. Purves 2 Stephan Imfeld 2 and Robert Weibel 2 1 School of Geography and Environmental Science University of Auckland New Zealand 2 Department of Geography University of Zurich Switzerland 14.1 Introduction Mobility is key to contemporary life. In a globalised world people goods data and ideas move in increasing volumes at increasing speeds over increasing distances and more and more leave a digital trail behind them. More and more such tracking data is automatically collected in large databases. Exploring the dynamic processes afforded by the study of such digital trails in other words motion is an emerging research area in Geographical Information Science. This chapter argues that Geographical Information Science can centrally contribute to discovering knowledge about the patterns made in space-time by individuals and groups within large volumes of tracking data. Whereas the representation and visualisation of motion is quite widespread within the discipline approaches to actually quantitatively analysing motion are rare. Hence this chapter introduces an approach to analysing the tracks of moving point objects which are considered as the most basic and commonly used conceptualisation in representing motion in geography. The methodological approach adopted is Geographic Knowledge Discovery GKD an interactive and iterative process integrating a collection of methods from geography computer science statistics and scientific visualisation Miller and Han 2001 . Its goal is the extraction of high-level information from low-level data in the context of large geographic datasets Fayyad et al. 1996 . This chapter sets out to illustrate that the integration of knowledge discovery methods within Geographical Information Science provides a powerful means to investigate motion processes captured in tracking data. The chapter is structured as follows. Section 14.2 provides a