Inferring the History of Spatial Diffusion Processes (Short Paper)

Authors Takuya Takahashi , Geneviève Hannes , Nico Neureiter , Peter Ranacher

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Author Details

Takuya Takahashi
  • Department of Geography, University of Zurich, Switzerland
Geneviève Hannes
  • Department of Geography, University of Zurich, Switzerland
Nico Neureiter
  • Department of Geography, University of Zurich, Switzerland
  • NCCR Evolving Language, University of Zurich, Switzerland
Peter Ranacher
  • URPP Language and Space, University of Zurich, Switzerland
  • Department of Geography, University of Zurich, Switzerland
  • NCCR Evolving Language, University of Zurich, Switzerland


We thank Gereon Kaiping for valuable discussion and ideas in the early phase of the project.

Cite AsGet BibTex

Takuya Takahashi, Geneviève Hannes, Nico Neureiter, and Peter Ranacher. Inferring the History of Spatial Diffusion Processes (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 71:1-71:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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.

Subject Classification

ACM Subject Classification
  • Computing methodologies
  • Bayesian inference
  • geographic diffusion
  • language evolution
  • Indo-European
  • colonisation of the Americas


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