Researchers from many disciplines have examined neighborhood satisfaction. The research has focused more on the personal, social, and psychological dimensions than on the physical environment in relation to neighborhood satisfaction. When studies include physical characteristics, they tend to look at the perceived physical characteristics, possibly overlooking the impact of the physical environmental features on neighborhood satisfaction. Furthermore, while studies have identified physical attributes of environments related to “aesthetic” response, research has not examined the link between physical and judgmental ratings of those attributes, nor has it looked at the link between those measures and neighborhood satisfaction.
This dissertation builds a conceptual model that focuses on the multi-level connections among the physical, perceptual, and evaluative measures of the neighborhood environment as determinants of overall neighborhood satisfaction.
It uses on-line survey, on-site observations, and the combined satellite image processing and GIS spatial analysis. The survey asks residents to rate their perceptions and evaluations of the neighborhood environment, and then to rate their overall neighborhood satisfaction. 382 survey responses were collected in Franklin County, Ohio. Observations assess the conditions of the fixed and semi-fixed physical environmental elements on 2021 blocks. For observations, this study designed, used, and tested the neighborhood physical environment inventory (NPEI) instrument on a handheld Personal Digital Assistant (PDA). The Normalized Differential Vegetation Index (NDVI) method was combined with GIS spatial analysis.
To assess both structural and measurement relations in a single model, this study uses a Structural Regression Model based on the two-step modeling process. The findings reveal the significant direct and indirect effects of physical, perceptual, and evaluative measures on neighborhood satisfaction. The results extend the understanding of the neighborhood environment and residents´ quality of life. Methodologically, the study demonstrates advances in data collection through its on-line survey, on-site observation via a personal digital assistant (PDA), and GIS.