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Towards the Statistical Analysis and Visualization of Places (Short Paper)

Authors René Westerholt, Mathias Gröbe, Alexander Zipf, Dirk Burghardt

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ACM Subject Classification
  • Information systems → Geographic information systems
  • Theory of computation → Probabilistic computation
  • Applied computing → Cartography
Keywords
  • Platial Analysis
  • Visualization
  • Statistics
  • Geosocial Media

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Abstract

The concept of place recently gains momentum in GIScience. In some fields like human geography, spatial cognition or information theory, this topic already has a longer scholarly tradition. This is however not yet completely the case with statistical spatial analysis and cartography. Despite that, taking full advantage of the plethora of user-generated information that we have available these days requires mature place-based statistical and visualization concepts. This paper contributes to these developments: We integrate existing place definitions into an understanding of places as a system of interlinked, constituent characteristics. Based on this, challenges and first promising conceptual ideas are discussed from statistical and visualization viewpoints.

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René Westerholt, Mathias Gröbe, Alexander Zipf, and Dirk Burghardt. Towards the Statistical Analysis and Visualization of Places (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 63:1-63:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018) https://doi.org/10.4230/LIPIcs.GISCIENCE.2018.63

Author Details

René Westerholt
  • Heidelberg University, Institute of Geography, Heidelberg, Germany
Mathias Gröbe
  • TU Dresden, Institute for Cartography, Dresden, Germany
Alexander Zipf
  • Heidelberg University, Institute of Geography, Heidelberg, Germany
Dirk Burghardt
  • TU Dresden, Institute for Cartography, Dresden, Germany

Funding

This work was generously supported by the German Research Foundation (DFG) through the priority programme ‘Volunteered Geographic Information: Interpretation, Visualisation and Social Computing’ (SPP 1894).

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