License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GIScience.2023.71
URN: urn:nbn:de:0030-drops-189662
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/18966/
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Takahashi, Takuya ; Hannes, Geneviève ; Neureiter, Nico ; Ranacher, Peter

Inferring the History of Spatial Diffusion Processes (Short Paper)

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LIPIcs-GIScience-2023-71.pdf (2 MB)

Abstract

When studying the spatial diffusion of a phenomenon, we often know its geographic distribution at one or more snapshots in time, while the complete history of the diffusion process is unknown. For example, we know when and where the first Indo-European languages arrived in South America and their current distribution. However, we do not know the history of how these languages spread, displacing the indigenous languages from their original habitat. We present a Bayesian model to interpolate the history of a diffusion process between two points in time with known geographical distributions. We apply the model to recover the spread of the Indo-European languages in South America and infer a posterior distribution of possible evolutionary histories of how they expanded their areas since the time of the first invasion by Europeans. Our model is more generally applicable to infer the evolutionary history of geographic diffusion phenomena from incomplete data.

BibTeX - Entry

@InProceedings{takahashi_et_al:LIPIcs.GIScience.2023.71,
  author =	{Takahashi, Takuya and Hannes, Genevi\`{e}ve and Neureiter, Nico and Ranacher, Peter},
  title =	{{Inferring the History of Spatial Diffusion Processes}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{71:1--71:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2023/18966},
  URN =		{urn:nbn:de:0030-drops-189662},
  doi =		{10.4230/LIPIcs.GIScience.2023.71},
  annote =	{Keywords: Bayesian inference, geographic diffusion, language evolution, Indo-European, colonisation of the Americas}
}

Keywords: Bayesian inference, geographic diffusion, language evolution, Indo-European, colonisation of the Americas
Collection: 12th International Conference on Geographic Information Science (GIScience 2023)
Issue Date: 2023
Date of publication: 07.09.2023

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