@article{Rauch2022,
  author    = {Rauch, Sebastian},
  title     = {Analysing Long Term Spatial Mobility Patterns of Individuals and Large Groups Using 3D-GIS: A Sport Geographic Approach},
  series = {Tijdschrift voor Economische en Sociale Geografie},
  volume    = {113},
  journal   = {Tijdschrift voor Economische en Sociale Geografie},
  number    = {3},
  issn      = {0040-747X},
  doi       = {10.1111/tesg.12513},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-318551},
  pages     = {257 -- 272},
  year      = {2022},
  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.},
  language  = {en}
}