Parks, playgrounds, trails, lakes and other public green and blue spaces are locally desirable land uses that provide recreation and open space opportunities in addition to various other environmental, social, health, and economic benefits. Access to recreation opportunities has been shown to have a substantial impact on individual and community health and well-being, especially in urban areas. Disparities in levels of access to recreation opportunities, whether in terms of age, race/ethnicity, income or other demographic or socioeconomic factors, represent an environmental justice concern. Level of access to recreation opportunities is based partially on the distribution of recreation opportunities. Assessing the level of environmental justice inherent in the distribution of recreation opportunities is, therefore, a valuable prerequisite for effective recreation planning and management. Assessment of results provides information for public leisure agencies that can help them allocate limited resources more equitably. Such assessments have, in the past, focused on measuring the degree of equity associated with the distribution of access to recreation opportunities. Multivariate linear regression analyses using the ordinary least squares (OLS) method typically have employed; however, these approaches fail to explore important local variations in the relationships among variables caused by spatial effects such as spatial dependence (spatial autocorrelation) and spatial heterogeneity (spatial non-stationarity) that can lead to biased estimation results. Thus, the equity of recreation opportunities ideally should be examined using specialized research methods that incorporate spatial data. The purpose of this study was to demonstrate the utility of spatial statistical techniques for assessing the distribution of recreation opportunities within the framework of environmental justice. To achieve this, the level of access to and the degree of equity inherent in the distribution of public beaches in the Detroit Metropolitan Area (DMA) were assessed. Results indicated that spatial statistical techniques have the potential to serve as a useful tool not only to assess the distribution of recreation opportunities, but also to deal with spatial effects when measuring the degree of equity inherent in the distribution of access to public beaches in the DMA. Specifically, results indicated substantial regional disparities in access to public beaches resulting from spatial clustering of public beaches in the DMA. Furthermore, the two local regression models based on a geographically weighted regression (GWR) approach explored spatially varying relationships between variables, with great improvements in model performance (as measured by R2, AICc, and Moran’s I statistics of standardized residuals) over their corresponding global regression models based on the OLS approach. In addition to development of an improved approach to the measurement of equity, the findings of this study can help parks and recreation agencies better understand local patterns of equity by identifying the areas with inequitable access to public beaches, which corresponds with their residents’ racial/ethnic and socioeconomic statuses and, thus, facilitate the formulation of appropriate policy solutions as and where needed.
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