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.

Focal analyses (also known as ‘buffer’ or ‘neighbourhood’ analyses) seek to characterise a location based on its surroundings and are commonplace in GIS applications across many fields and disciplines. However, the implicit assumptions made by researchers in these analyses result in an unintended bias towards the periphery of the focal window, which we term Focal Area Bias (FAB). FAB can have a substantial impact upon the resulting values, and in the most extreme cases can result in paradoxical outcomes. Where geographical weighting functions are used, the interaction between the weighting function and FAB means that it will not have the expected effect, leading to the misinterpretation of results. This research characterises the issue of FAB, before presenting a corrective function to remove it. The efficacy of the proposed corrective function and the spatial characteristics of FAB are then evaluated to demonstrate the importance of this issue. We recommend that researchers and practitioners should consider the impact of FAB when undertaking focal analysis and make use of the corrective functions presented here to remove this issue, particularly where geographical weighting is desired.

The problem of mapping regions with socially-derived boundaries has been a topic of discussion in the GIS literature for many years. Fuzzy approaches have frequently been suggested as solutions, but none have been adopted. This is likely due to difficulties associated with determining suitable membership functions, which are often as arbitrary as the crisp boundaries that they seek to replace. This paper presents a novel approach to fuzzy geographical modelling that replaces the membership function with a possibility distribution that is estimated using Bayesian inference. In this method, data from multiple sources are combined to estimate the degree to which a given location is a member of a given set and the level of uncertainty associated with that estimate. The Fuzzy Bayesian Inference approach is demonstrated through a case study in which census data are combined with perceptual and behavioural evidence to model the territory of two segregated groups (Catholics and Protestants) in Belfast, Northern Ireland, UK. This novel method provides a robust empirical basis for the use of fuzzy models in GIS, and therefore has applications for mapping a range of socially-derived and otherwise vague boundaries.

Whilst empathy is considered an essential component of what it means to be human, it is frequently absent as a design objective when creating modern communication systems. This paper presents an approach to designing for, as opposed to with, empathy using the example of two design interventions to create embodied rituals reflecting prayers and worries of individuals within a church community. The aim of these interventions is to facilitate conversation and support within the community, thus generating empathy between community members, and inciting prosocial behaviour through embodied cognition.