ABSTRACT
Recreation resource planners and managers have for many years recognized the importance of aesthetic dimensions in the provision of recreation opportunites. This chapter argues that the ability of canonical correlation analysis to examine the relationship between two sets of variables provides several advantages over more traditional statistical techniques. Traditional regression techniques, for example, regress each criterion variable on a set of predictor variables. Engineers, chemists, and atmospheric scientists have developed increasingly sophisticated technology to measure, monitor, and identify factors impairing visual quality. Other social researchers have studied recreation and visual values from the perspective of the influence that visual impairment has on the outdoor recreation experience. The chapter suggests that there is a need for a "macro" approach to visual value research. This "macro" approach examines the complex interaction of human and environmental variables that influence visibility values. At a very generalized level, canonical correlation analysis can be viewed as a type of regression analysis.
