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.2023.42
URN: urn:nbn:de:0030-drops-189375
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/18937/
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Jankowski, Piotr ; Ligmann-Zielińska, Arika ; Zwoliński, Zbigniew ; Najwer, Alicja

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

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LIPIcs-GIScience-2023-42.pdf (5 MB)

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.

BibTeX - Entry

@InProceedings{jankowski_et_al:LIPIcs.GIScience.2023.42,
  author =	{Jankowski, Piotr and Ligmann-Zieli\'{n}ska, Arika and Zwoli\'{n}ski, Zbigniew and Najwer, Alicja},
  title =	{{An Integrated Uncertainty and Sensitivity Analysis for Spatial Multicriteria Models}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{42:1--42:6},
  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/2023/18937},
  URN =		{urn:nbn:de:0030-drops-189375},
  doi =		{10.4230/LIPIcs.GIScience.2023.42},
  annote =	{Keywords: model uncertainty, input factor sensitivity, geodiversity, spatial multicriteria models}
}

Keywords: model uncertainty, input factor sensitivity, geodiversity, spatial multicriteria models
Collection: 12th International Conference on Geographic Information Science (GIScience 2023)
Issue Date: 2023
Date of publication: 07.09.2023

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