The endpoint hypothesis: A topological-cognitive assessment of geographic scale movement patterns

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Scopus citations


Movement patterns of individual entities at the geographic scale are becoming a prominent research focus in spatial sciences. One pertinent question is how cognitive and formal characterizations of movement patterns relate. In other words, are (mostly qualitative) formal characterizations cognitively adequate? This article experimentally evaluates movement patterns that can be characterized as paths through a conceptual neighborhood graph, that is, two extended spatial entities changing their topological relationship gradually. The central questions addressed are: (a) Do humans naturally use topology to create cognitive equivalent classes, that is, is topology the basis for categorizing movement patterns spatially? (b) Are 'all' topological relations equally salient, and (c) does language influence categorization. The first two questions are addressed using a modification of the endpoint hypothesis stating that: movement patterns are distinguished by the topological relation they end in. The third question addresses whether language has an influence on the classification of movement patterns, that is, whether there is a difference between linguistic and non-linguistic category construction. In contrast to our previous findings we were able to document the importance of topology for conceptualizing movement patterns but also reveal differences in the cognitive saliency of topological relations. The latter aspect calls for a weighted conceptual neighborhood graph to cognitively adequately model human conceptualization processes.

Original languageEnglish (US)
Title of host publicationSpatial Information Theory - 9th International Conference, COSIT 2009, Proceedings
Number of pages18
StatePublished - 2009
Event9th International Conference on Spatial Information Theory, COSIT 2009 - Aber Wrac'h, France
Duration: Sep 21 2009Sep 25 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5756 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other9th International Conference on Spatial Information Theory, COSIT 2009
CityAber Wrac'h

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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