The Relationships between Perceived Design Intensity, Preference, Restorativeness and Eye Movements in Designed Urban Green Space

Abstract

Recent research has demonstrated that landscape design intensity impacts individuals’ landscape preferences, which may influence their eye movement. Due to the close relationship between restorativeness and landscape preference, we further explore the relationships between design intensity, preference, restorativeness and eye movements. Specifically, using manipulated images as stimuli for 200 students as participants, the effect of urban green space (UGS) design intensity on landscapes’ preference, restorativeness, and eye movement was examined. The results demonstrate that landscape design intensity could contribute to preference and restorativeness and that there is a significant positive relationship between design intensity and eye-tracking metrics, including dwell time percent, fixation percent, fixation count, and visited ranking. Additionally, preference was positively related to restorativeness, dwell time percent, fixation percent, and fixation count, and there is a significant positive relationship between restorativeness and fixation percent. We obtained the most feasible regression equations between design intensity and preference, restorativeness, and eye movement. These results provide a set of guidelines for improving UGS design to achieve its greatest restorative potential and shed new light on the use of eye-tracking technology in landscape perception studies.

Gender Differences and Optimizing Women’s Experiences: An Exploratory Study of Visual Behavior While Viewing Urban Park Landscapes in Tokyo, Japan

“…Therefore, this study attempted to explore objective gender differences from a visual perspective, assuming that different visual behaviors result in different experiences between men and women. Wu et al (2021) [27] pointed out that eye-movement indicators are likely to be predictors of landscape preference. A study by Li et al (2020) [28] revealed the importance of landscape elements decomposition for visual perception and evaluation.…”

“…Eye-tracking technology provided effective data to test this hypothesis. Eye trackers can accurately record respondents' eye-movement trajectories when observing a scene and generate large amounts of data to analyze observation patterns and focus [27,29]. Multiple studies have used eye tracking to investigate group differences in landscape perception, often examining variables such as expertise, gender, and cultural background [30][31][32][33].…”

Back to the Village: Assessing the Effects of Naturalness, Landscape Types, and Landscape Elements on the Restorative Potential of Rural Landscapes

“…Most studies investigating the relationship between landscapes and perceived restorativeness have used psychological questionnaires [36,37]. However, some scholars have employed physiological measurement techniques such as heart rate variability (HRV) [38], blood pressure (BP) [39], skin conductance response (SCR) [3], electroencephalography (EEG) [40], and eye-tracking [41] to more scientifically and objectively verify the relationship between landscapes and perceived restorativeness. Among these measures, EEG most effectively reflects the degree of stimulation experienced by individuals, thus indicating their emotional changes in different landscape settings [42].…”

“…In this study, photographs were used to represent each rural landscape type. Multiple studies have confirmed that photographs can effectively substitute for on-site environmental surveys [3,41,60]. The selection of images for the experiment was completed through focus group interviews and expert evaluations [61].…”

Analysis and Optimization of Landscape Preference Characteristics of Rural Public Space Based on Eye-Tracking Technology: The Case of Huangshandian Village, China

“…Meanwhile, Wu et al examined the effects of urban green space (UGS) design intensity on landscape preference, restorativeness, and eye movement, using treatment images with 200 students as participants. The most feasible regression equations between design intensity and preference, restorativeness, and eye movement were obtained [46]. In addition, Ding et al used eyetracking technology to study the extent of people's preference for native greenery plants from the perspective of visual preference using pictures of plant organs such as leaves, flowers, and fruits as stimulating materials to improve rural greening techniques, with a study conducted by students from the Central South University of Forestry Technology and villagers in Changkou Village, Fujian Province [47].…”