Combining visual and noise characteristics of a neighborhood environment to model residential satisfaction: An application using GIS-based metrics

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This paper focuses on the combined impact of sound and visibility features on residential satisfaction in a suburban context. Based on a modeling approach, the study presents an integrated analysis where a set of spatial metrics, describing visibility of landscape features and road-traffic noise, are associated with data from a survey of neighborhood satisfaction. This survey was conducted on a sample of 845 inhabitants living in a medium-size French city. Using a PLS path model, the main objective of this paper is to assess how visual and sound metrics combine to provide complementary explanations of neighborhood satisfaction. Moreover, the analysis focuses on assessing the extent to which a part of the heterogeneity of the residents’ neighborhood perception is due to their socio-economic position or to their neighborhood’s characteristics. The results show that visual and sound criteria influence residential satisfaction cumulatively, and that sensitivity to these criteria varies according to the socio-economic position of individuals, opposing specifically homeowners and tenants. By using digital spatial data and GIS methods, an integrated indicator is produced to map the spatial distribution of neighborhood satisfaction for all residential locations of the study area. In an urban planning context, such a spatially oriented approach can be considered as a decision-making tool for planning and development to identify high-stakes zones in order to improve the inhabitants’ quality of life.