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Kernel-based formulation of intervening opportunities for spatial interaction modelling.

Masaki Kotsubo1, Tomoki Nakaya2

  • 1Graduate School of Environmental Studies, Tohoku University, 468-1, Aoba, Aramaki, Aoba-ku, Sendai-city, Miyagi, 980-0845, Japan. masaki.kotsubo.s3@dc.tohoku.ac.jp.

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Area of Science:

  • Spatial analysis
  • Geography
  • Traffic engineering

Background:

  • Human mobility and spatial interactions are key research areas.
  • Classical intervening opportunities models, including the radiation model, explain distance-based decision-making.
  • Existing models struggle to accurately predict short-distance flows.

Purpose of the Study:

  • To propose a novel formulation of intervening opportunities using a kernel function.
  • To develop an improved variant of the radiation model.
  • To enhance the prediction accuracy of spatial interaction models.

Main Methods:

  • Introduced a kernel function to model fuzzy spatial search behaviors for destinations.
  • Developed a modified radiation model incorporating kernel-based intervening opportunities.
  • Validated the model against four datasets of inter-regional mobility flows.

Main Results:

  • The modified radiation model demonstrated superior performance compared to the original model.
  • Kernel-based intervening opportunities significantly improved the prediction of mobility patterns.
  • The enhanced model showed better accuracy in fitting real-world inter-regional flow data.

Conclusions:

  • The proposed kernel-based intervening opportunities offer a more realistic approach to modeling spatial interactions.
  • This modification enhances the predictive power of the radiation model, especially for short-distance movements.
  • The findings have implications for urban planning, transportation, and spatial economics.