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An Integrated Uncertainty and Sensitivity Analysis for Spatial Multicriteria Models (Short Paper)

Authors Piotr Jankowski , Arika Ligmann-Zielińska , Zbigniew Zwoliński , Alicja Najwer



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Author Details

Piotr Jankowski
  • San Diego State University, CA, USA
  • Adam Mickiewicz University, Poznan, Poland
Arika Ligmann-Zielińska
  • Michigan State University, East Lansing, MI, USA
  • Adam Mickiewicz University, Poznan, Poland
Zbigniew Zwoliński
  • Adam Mickiewicz University, Poznan, Poland
Alicja Najwer
  • Adam Mickiewicz University, Poznan, Poland

Cite AsGet BibTex

Piotr Jankowski, Arika Ligmann-Zielińska, Zbigniew Zwoliński, and Alicja Najwer. An Integrated Uncertainty and Sensitivity Analysis for Spatial Multicriteria Models (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 42:1-42:6, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.GIScience.2023.42

Abstract

This paper introduces an integrated Uncertainty and Sensitivity Analysis (US-A) approach for Spatial Multicriteria Models (SMM). The US-A approach evaluates uncertainty and sensitivity by considering both criteria values and weights, providing spatially distributed measures. A geodiversity assessment case study demonstrates the application of US-A, identifying influential inputs driving uncertainty in specific areas. The results highlight the importance of considering both criteria values and weights in analyzing model uncertainty. The paper contributes to the literature on spatially-explicit uncertainty and sensitivity analysis by providing a method for analyzing both categories of SMM inputs: evaluation criteria values and weights, and by presenting a novel form of visualizing their sensitivity measures with bivariate maps.

Subject Classification

ACM Subject Classification
  • Information systems → Geographic information systems
Keywords
  • model uncertainty
  • input factor sensitivity
  • geodiversity
  • spatial multicriteria models

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References

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