Analysing Long Term Spatial Mobility Patterns of Individuals and Large Groups Using 3D‐GIS: A Sport Geographic Approach. (14th March 2022)

• Record Type: Journal Article
• Authors: Rauch, Sebastian
• Is Part Of: Tijdschrift voor economische en sociale geografie. Volume 113:Number 3(2022)
• Page Start: 257
• Page End: 272
• Publication Date: 2022-03-14
• Subjects: geovisualization -- sport geography -- time geography -- 3D GIS analysis -- individual mobility -- path analysis; Economic geography -- Periodicals; Human geography -- Periodicals; 330.9005
• DOI: 10.1111/tesg.12513
• Languages: English
• ISSNs: 0040-747X

Abstract

Abstract: Individual mobility and human patterns analyses is receiving increasing attention in numerous interdisciplinary studies and publications using the concept of time‐geography but is largely unknown to the subdiscipline of sports geography. Meanwhile the visualization and evaluation of large data of individual patterns are still a major challenge. While a qualitative, microscale view on spatial‐temporal topics is more common in today's pattern research using mostly 24h time intervals, this work examines a quantitative approach focusing on an extended period of life. This paper presents a combination of time‐geographic approaches with 3D‐geoinformation systems and demonstrates their value for analysing individual mobility by implementing a path‐homogeneity factor (HPA). Using the example of professional athletes, it is shown which groups display greater similarities in their career paths. While a high homogeneity suggests that groups make similar decisions through socially influenced processes, low values allow the assumption that external processes provide stronger, independent individual structures.