Visual Preference Analysis and Planning Responses Based on Street View Images: A Case Study of Gulangyu Island, China

Abstract

The features of a street environment play an essential role in human behavior, but predicting the preferred environment becomes challenging for city planning. This paper takes Gulangyu Island as an example and examines tourists’ visual preferences through street view images and a stated preference survey. Based on the findings, planning responses were proposed to provide references for improving tourists’ visual perception of the street’s environment. The results show that tourists’ preferences for the street environment are significantly affected by visual features. From highest to lowest are variety, the green view index, crowdedness, sky openness, and enclosure. The green view index, sky openness, and variety positively affect the visual utility, while crowdedness and enclosure have a negative effect. Among them, variety has the most potent positive effect on visual preference, while crowdedness has the most substantial negative effect. Moreover, there is a balance between green view and enclosure that is affected by green plants, and when the enclosure value is too high, the marginal effect of the green view index will be less effective. Last, the streets with high visual utility have an ideal natural environment, spacious roads, an open sky, and limited architecture.

Keywords

• street environment
• visual preference
• fully convolutional network
• stated preference
• street view images
• Gulangyu