The vegetation landscape in urban green space has been shown to provide great psychological benefits to people. Flower border is a well-designed small-scale vegetation landscape with the advantages of color and vegetation richness. This study focused on the effects of the visual attributes of flower borders on the aesthetic preference and emotional perception. The face recognition measurement method was used to obtain the emotional perception and the questionnaire survey method was used to measure the aesthetic preference. The results indicated the following: (1) regarding the ‘color features’ factor, high proportions of cool color and green vegetation significantly increased aesthetic preference and emotional valence, while the proportion of warm color had a negative effect on valence; (2) the ‘visual attractiveness’ (color brightness, and visual richness) and ‘color configuration’ (number of plant patches and number of color hues) factor was positively associated with aesthetic preference and emotional valence; (3) aesthetic preference was significantly related to emotional valence; (4) males expressed higher aesthetic preference and valence for flower border images than females. The results are expected to improve the aesthetic quality of flower borders and to promote public emotional health through the effective design of urban vegetation landscapes.

The up-close experience of perennial landscapes has been shown to enhance residents’ perception of naturalness in the context of increasing small-scale vegetation landscapes. This study explored how formal aesthetic characteristics were related to landscape perception and whether landscape preference correlated with eye movements. We created a series of photomontages showing perennial combinations that contained different plant forms, degrees of species richness, and plant arrangements and recorded 73 participants’ eye movements during 10 s of free viewing in Experiment A and task-oriented viewing in Experiment B and ratings of landscape preference collected through rating scales. We found that the effects of plant form and species richness were significant for gaze behavior, while arrangement showed no significant effect. We also found that landscape preference was positively correlated with fixation count but negatively correlated with mean fixation duration and total fixation duration. Additionally, women had more but shorter fixations than men while viewing these photomontages, and the difference in aesthetic preferences between men and women was not significant. Concerning the different professional background groups, no significant gaze behavior difference between professionals and nonprofessionals was detected, but compared with professionals, nonprofessionals tended to give strongly higher preference ratings. The outcomes shed light on the influence of formal aesthetic characteristics on gaze behavior and advanced the application of eye-tracking technology in perennial landscape studies. Our findings also confirmed the efficiency of vegetation landscapes designed based on public preferences for providing restoration from stress or fatigue.

Emotional responses are significant for understanding public perceptions of urban green space (UGS) and can be used to inform proposals for optimal urban design strategies to enhance public emotional health in the times of COVID-19. However, most empirical studies fail to consider emotion-oriented landscape assessments under dynamic perspectives despite the fact that individually observed sceneries alter with angle. To close this gap, a real-time sentimental-based landscape assessment framework is developed, integrating facial expression recognition with semantic segmentation of changing landscapes. Furthermore, a case study using panoramic videos converted from Google Street View images to simulate changing scenes was used to test the viability of this framework, resulting in five million big data points. The result of this study shows that through the collaboration of deep learning algorithms, finer visual variables were classified, subtle emotional responses were tracked, and better regression results for valence and arousal were obtained. Among all the predictors, the proportion of grass was the most significant predictor for emotional perception. The proposed framework is adaptable and human-centric, and it enables the instantaneous emotional perception of the built environment by the general public as a feedback survey tool to aid urban planners in creating UGS that promote emotional well-being.

Although creating a high-quality urban green space (UGS) is of considerable importance in public health, few studies have used individuals’ emotions to evaluate the UGS quality. This study aims to conduct a multidimensional emotional assessment method of UGS from the perspective of spatial quality. Panoramic videos of 15 scenes in the West Lake Scenic Area were displayed to 34 participants. For each scene, 12 attributes regarding spatial quality were quantified, including perceived plant attributes, spatial structure attributes, and experiences of UGS. Then, the Self-Assessment-Manikin (SAM) scale and face recognition model were used to measure people’s valence-arousal emotion values. Among all the predictors, the percentages of water and plants were the most predictive indicators of emotional responses measured by SAM scale, while the interpretation rate of the model measured by face recognition was insufficiently high. Concerning gender differences, women experienced a significantly higher valence than men. Higher percentages of water and plants, larger sizes, approximate shape index, and lower canopy densities were often related to positive emotions. Hence, designers must consider all structural attributes of green spaces, as well as enrich visual perception and provide various activities while creating a UGS. In addition, we suggest combining both physiological and psychological methods to assess emotional responses in future studies. Because the face recognition model can provide objective measurement of emotional responses, and the self-report questionnaire is much easier to administer and can be used as a supplement.

The emotional health benefits of urban green space have been widely recognized. Flower borders, as a perennial plant landscape, have gradually become a current form of plant application in urban green spaces due to their rich color configurations. However, the related research primarily focuses on the impact of urban green spaces on public health, with relatively little attention given to how the colors of flower borders affect public emotional health. This study explored the relationship between the flower borders color characteristics and the public emotional health. In this study, 24 sample images were used as experimental materials, which selected based on their color richness and harmony. Additionally, face recognition technology and online random questionnaires were utilized to measure the public basic emotions and pleasure, respectively. The result shows that, based on the HSV color model and expert recommendations, 19 color characteristics were identified. The correlation analysis of the results from the public emotion with these color characteristics revealed that 13 color characteristics correlated with public emotional pleasure. Among them, blue, neutral purple, and low saturation were positively correlated. Through factor analysis, these thirteen color characteristics were summarized and categorized into four common factors (F1–F4), three of which are related to color. They are “low saturation of blue-violet percentage” (F1), “color configuration diversity” (F2), “bright red percentage” (F3), and “base green percentage” (F4), with F1 having the largest variance explained (27.88%). Finally, an evaluation model of color characteristics was constructed based on the variance explained by these four factors, which was demonstrated to effectively predict the level of public emotional pleasure when viewing flower borders. The results shed light on the effects of color characteristics on public emotions and provide new perspectives for subsequent flower border evaluations. Our results provide a valuable reference for future flower border color design, aiming to better improve public emotional health.