Linking People's Perceptions and Physical Components of Sidewalk Environments—An Application of Rough Sets Theory

Abstract

This paper aims to develop a new approach to investigating the relationships between people's perceptions and physical components of sidewalk environments. A psychological survey composed of semantic differential items was administered to 112 participants in order to assess their perceptions of 20 sidewalk environments in Iksan city, South Korea. A field survey of the selected sidewalks was conducted to survey the physical components of the sidewalk environments. Because conventional statistical methods are not appropriate owing to the qualitative data, small sample size, and uncertainty, a new approach based on an artificial intelligence technique—rough sets theory—is applied to deal with the collected data. The application of the rough sets theory outputs the most important attributes of people's perceptions, minimal attribute sets without redundancy, and a series of decision rules that represent the relationships between perceptions and physical components of sidewalk environments. The analytical approach helps to understand better people's perceptions to sidewalk environments in a small city and then to establish a useful and constructive ground of discussion for walking environment design and management.