Modeling and Predicting Human Response to the Visual Recreation Environment

Abstract

A strategy is proposed for measuring and analyzing human preferences for the visual recreation environment. The aim is to develop quantitative preference functions which are sensitive both to individual differences and to visual characteristics of the environment. The strategy employs available measurement tools and statistical methods. The approach is applied to Lake Michigan beaches in the Chicago area. Black and white photographs were used to elicit perceptions of and preferences for gross visual characteristics of a variety of beaches. Data acquisition proceeded in two stages, beginning with free responses to identify variables and culminating in the use of semantic differentials to measure selected attributes. Results show that two groups having distinctly different preferences are identifiable. One of the two groups prefers scenic natural beaches, is attracted by trees and natural growth, and finds crowding distasteful. The other group prefers city swimming beaches, is sensitive to the quality of the sand and attractiveness of surrounding buildings. It was determined, tentatively, that the two groups were using beaches for different purposes and that the group which preferred scenic natural beaches tended to be older and more educated.