Decision making under uncertainty: increasing the impact of public Participatory GIS

Despite decades of research and celebration of Public Participatory GIS (PPGIS) as a powerful means to democratise decision making, there is little evidence that it has any influence on decisions whatsoever. There are likely to be a range of interconnected reasons for this, one of which is the inability to rigorously quantify the findings of PPGIS surveys. This is challenging because participants’ views cannot be assumed to be independent, are characterised by very high levels of uncertainty, and frequently contain conflicting and contradictory information. These challenges are addressed in this manuscript by a novel extension of Dempster Shafer theory, which is a generalisation of Bayes’ theorem that permits uncertainty to be modelled explicitly in the determination of belief. The approach presented here provides a mathematically rigorous assessment of the level of belief in a statement based on evidence (in the form of spatial data) collected from participants. A further extension allows the results to be transformed back to probability values, facilitating engagement with decision makers through this familiar and easily interpretable representation of uncertainty. The approach is demonstrated using a case study of perceptions of tree planting in the English Lake District, UK.

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.29382499.v1
Primary Topic
Geographic Information Systems Studies
Type
article
Field-Weighted Citation Impact
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article

Decision making under uncertainty: increasing the impact of public Participatory GIS

Figshare
Geographic Information Systems Studies
article

Decision making under uncertainty: increasing the impact of public Participatory GIS

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Abstract

Despite decades of research and celebration of Public Participatory GIS (PPGIS) as a powerful means to democratise decision making, there is little evidence that it has any influence on decisions whatsoever. There are likely to be a range of interconnected reasons for this, one of which is the inability to rigorously quantify the findings of PPGIS surveys. This is challenging because participants’ views cannot be assumed to be independent, are characterised by very high levels of uncertainty, and frequently contain conflicting and contradictory information. These challenges are addressed in this manuscript by a novel extension of Dempster Shafer theory, which is a generalisation of Bayes’ theorem that permits uncertainty to be modelled explicitly in the determination of belief. The approach presented here provides a mathematically rigorous assessment of the level of belief in a statement based on evidence (in the form of spatial data) collected from participants. A further extension allows the results to be transformed back to probability values, facilitating engagement with decision makers through this familiar and easily interpretable representation of uncertainty. The approach is demonstrated using a case study of perceptions of tree planting in the English Lake District, UK.

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Decision making under uncertainty: increasing the impact of public Participatory GIS · Figshare (2025) | TGRS Research Map | TGRS