Effects of Spatial Type and Scale of Small Urban Open Spaces on Perceived Restoration: An Online Survey-Based Experiment

Abstract

Small urban open spaces are critical components of high-density urban environments, and could bring multiple health benefits. However, the factors related to the restorative effect of these small urban open spaces are not well studied. This study explored how site type (lawn, water, and plaza) and spatial scales (10 × 10 m, 20 × 20 m, 30 × 30 m, and 40 × 40 m) might be associated with small urban open space’s restorative effects. We created the virtual scene images of the 12 sites and used PRS-11 to measure 1130 participants’ perceived restoration when viewing those images. The results indicated that lawn has the highest restorative effects, and are the most preferred. No significant differences in the restorative effects of sites with different spatial scales were detected, even a 10 × 10 m site has considerable restorative effects. We found high preference contributes to larger differences in the restorative effects of lawns and plazas. Those who prefer the sites may gain more restoration increases when viewing lawn scenes compared to plaza scenes. Moreover, adults over 50 years old have higher perceived restorations, and young adults aged 18–25 have a greater increase in restoration between plaza scenes and natural scenes, indicating young adults could benefit more from the building of small green spaces. These findings have direct implications for design practice. More small urban open spaces of lawn and water should be built to provide more restoration benefits, especially for young people.

1. Introduction

Urban green spaces (UGS) are important for citizens’ mental health [1,2,3,4]. High-density urban environments may contribute to citizens’ perceived oppression and bring mental health problems [5,6,7,8]. With 70% of the world’s population living in urban areas by 2050 (United Nations, 2014), more efforts are needed to address this problem. UGS’s role in promoting mental health has been widely acknowledged, including contributing to positive moods [9,10,11], restoring attention [12,13], recovering from stresses [1,14,15,16], and reducing depression [17,18]. For example, a study involving 9186 nursing homes found elderly residents who lived in nursing homes with more surrounding green coverage had fewer depression symptoms [17]. High school classrooms with green views are also shown to be related to better restoration and stress recovery of students, compared to classrooms with no windows or barren views [2]. A study involving 439 employees in Sweden indicated that green accessibility in the workplace had a stress-reducing effect on male participants [19]. Winter forest bathing is also beneficial to improve the mood, vitality, and restoration of college students in Poland [20]. A study conducted in Arizona found homebuyers are willing to pay almost USD 18,000 more to buy the greenest residential spaces compared to the residential spaces with average greenery [21]. Built environments containing water were found to have similar positive effects on emotion as natural green spaces [22]. Existing studies indicated that even viewing natural photos or experiencing virtual spaces, rather than being in real UGS, has tremendous mental health benefits [23,24].

Perceived restoration is one of the most important components of mental health [25,26]. Several factors have been shown related to UGS’s perceived restoration effects, including environmental components [27], enclosure [28], and users’ characteristics [29]. First, in terms of environmental components, natural components such as mountains, forests, lawns, and water have a greater restorative effect than urban environment components and hardscape components [24,27,30,31,32,33,34,35]. High forest vegetation density had a greater restorative effect on attention than low vegetation density [36]. The restorative potential was significantly higher in lawns compared with small lakes and plazas [35]. A study utilizing conjoint methodology also found the amount of grass was one of the most important factors when people choose which park to visit [37]. Second, studies have suggested that environments with more open views are regarded as being optimal for restoration [38,39], and were significantly preferred more [40,41,42]. A proper enclosure can enhance the sense of security [43], and make people feel more calm and more peaceful [42]. One explanation for this effect is that a specific region in the brain (the parahippocampal region, PPA) has a strong response to environmental enclosure [44]. From an evolutionary perspective, a too-closed enclosure will increase the risk of being attacked [45,46]. In addition, perceived restoration is also related to citizens’ demographic characteristics, such as gender [29], whether or not experts [41], whether they have an agricultural background or not [47], and income level [48]. Existing studies have suggested that middle-aged and elderly adults obtain more restoration from natural environments compared to other age groups [13,49,50,51,52].

Extent research indicates that perceived restoration is also related to beauty [53,54,55] as well as preference [34,53,55], although the strength of that association has varied. A face-to-face on-site survey involving 233 participants showed that the perceived pleasantness and aesthetic quality of parks and cemeteries are significant predictors of perceived restoration [54]. Another study in China also demonstrates a strong positive correlation between aesthetic preference and the restorative potential of natural scenes [34]. Preference is shown to be an important mediator between beauty and restoration [38,56]. A study in England assessed human aesthetic reaction and the restorative effect of planting structures, indicating that there was a correlation between perceived attractiveness and restorative effect [57]. Another study in Malaysia has found a positive relationship between perceived restorative potential and three out of four predictors of visual landscape preference (Complexity, Coherence, Mystery) [58]. A survey involving 120 participants showed that people with a nature preference perceived far more restoration potential in nature environments, while those with an urban preference perceived both nature and urban environments as equal in restoration potential [56].

Small open spaces are essentially important for urban areas with a high population density and limited lands for green spaces [59] and are also related to residential choices and land rent [60]. These small-scale UGS are important parts of UGS with significant physical health, mental health, and social benefits [61,62]. Small urban green spaces can provide recreation opportunities, nature experience, a sense of belonging, and restoration to people [63]. For instance, during COVID-19, nearby small parks significantly helped meet human needs of contacting nature [64] and socialization [61,65]. Even very small-scale greening, including indoor green walls and potted plants, can be effective in reducing depression [66] and stress [67,68]. However, UGS in most cities are insufficient [58,69] and are unevenly distributed [70]. In Los Angeles, there are 4 acres of parks per 1000 residents, which is much less than the national norm (6.25–10.5 acres per 1000 residents), and the availability of parks varies by race [59]. One study mentioned that the inner districts of Santa Cruz, Bolivia, have one-third of the total land area of the city, but two-thirds of the most desirable green space [69]. Under such a circumstance, small open spaces are important to provide accessible places and facilities for various activities [69,71]. Research shows that unofficial green areas embedded in the built environment, such as tree-lined streets, landscaped streetscapes, and pedestrian corridors are tremendously important for local people [59]. For example, pocket parks always have large numbers, wide distribution, and accessibility in the city [72]. Research shows that studies on the usage of pocket parks in recent years are increasing and many studies have reported the mental well-being and social benefits of pocket parks [62]. They can enhance the quality of spaces in confined fragments of an urban structure [73]. Above all, small-scale UGS have a high potential value that is often underestimated [74]. Currently, there is no consensus on the definition of small urban open spaces, especially what spatial scale defines a “small” space. One research, which studied the associations between park characteristics and perceived restoration of small public urban green spaces, defined “small” as smaller than 5000 m² [75]. Pocket parks, as a classic example of small urban open spaces, are defined as 400–10,000 m² by the Ministry of Housing and Urban-Rural Development of China. Other researchers also defined pocket parks as smaller than 3000 m² [28] or 400–8000 m² [72]. Based on this existing research, in this study, we defined small urban open space as open land within an urban environment with areas ranging from 100 m² (10 m × 10 m) to 2500 m² (50 m × 50 m), including green spaces, blue spaces, and plazas.

In conclusion, small urban open spaces have high restorative potential. However, there are still some research gaps: (1) Few studies investigated the restorative effect of small urban open spaces, especially addressing their characteristics of scale and type. (2) Few studies have explored the impact of the interaction between scale and type on the restoration of different demographic groups.

To address the above gaps, this study focuses on small urban open spaces with lengths less than 40 m and tries to explore how landscape type and spatial scale may impact the perceived restorative effects of these small-scale spaces. We would like to explore: (1) What are the effects of different scales/types on the restoration of space? (2) Whether the restoration of different spatial scales is heterogeneous in different types. (3) Whether the restoration of different scales/types of space is heterogeneous in different people groups.

Particularly, we emphasized three types of small urban open space, including lawn, water, and plaza, and four types of spatial characters, including 10 × 10 m, 20 × 20 m, 30 × 30 m, and 40 × 40 m. Gender [29,76], age [77], job status [78], whether have a background in design [53,79], spending childhood in rural or city [80], and monthly household income [11] have been proven to relate to the perceived restoration and mental health. Following the existing studies, we also included demographic characteristics such as age and gender. These variables could work as confounding variables as well as moderating variables to explore perceived restoration between different demographic groups. This study focuses on the role of single visual perception in psychological effects. The research findings could provide direct implications for healthy urban environment design and planning.

2. Methods

2.1. Creation of Virtual Landscape Site Images

In the present study, we addressed the associations among the type and spatial scale of small urban open spaces and their restorative effects. Currently, there is no consensus on the definition of small urban open spaces, and specifically what spatial scale defines a “small” space. In highly dense urban areas, spatial resources for constructing open spaces are extremely limited, and small plots affiliated with buildings are usually used to build open spaces. In this study, we defined the small urban open spaces as those with a length of less than 50 m, or with an area of less than 2500 m². We selected three common types of landscape sites, including lawn, water, and paved plazas. Twelve landscape site images with three types (lawn, water, and plaza) and four types of spatial scales (10 × 10 m, 20 × 20 m, 30 × 30 m, and 40 × 40 m) were involved in the study.

We created virtual landscape site models and generated images from the same viewing angle, to control the influences of other environmental variables, such as surrounding plants and buildings. Previous studies have used virtual modeling to generate two-dimensional images in the study of enclosure perception [81,82], flooded bank design preference [83], and oppressiveness perception related to building permeability [5]. First, we created 3D landscape site scenes using the Mars (https://www.sheencity.com/mars, accessed on 15 August 2022) and Lumion (https://www.lumion.net.cn, accessed on 27 August 2022) programming and kept other factors consistent across the sites, including the light, shape of the site, buildings, trees, and shrubs. The sites are all square-shaped, with three sides enclosed by trees and one side open. The viewpoint is set at the midpoint of the open-side edge, retreating 1 m from the side to ensure that the whole site is included in the field of view. The viewing point was set at a height of 1.6 m. These measures aim to make the images as close as possible to the actual human perspective. Other environmental factors of the sites were all kept consistent (Table 1). Second, we captured the sight of the view from the viewpoint to create the study images for each landscape site (Figure 1). The resolution of the images is 300 dpi.

2.2. Restorative Effects Measure and Questionnaire Design

We applied the Perceived Restorative Scale-11 (PRS-11) to measure participants’ perceived restoration when viewing the study sites. PRS-11 is a short version of the original PRS-26 proposed by Hartig [84] and with high reliability [85]. PRS-11 focused on four dimensions of restorations, including fascination, being away, coherence, and scope (Table 2), which have been widely used in previous studies [86,87].

In the questionnaire, we also inquired about participants’ preferences, perceived beauty, and perceived openness of the study sites. The “preference” here means the degree of liking to a particular scene. The questions take the form of “Do you like this scene (preference)”, “Do you think the scene is open (openness)”, “Do you think it’s a beautiful scene (beauty)”, and “Do you agree with the following descriptions of this scene (Perceived Restoration Scale)”. All these questions were measured using an 11-point Likert scale ranging from 0 to 10 (0 = not at all, 10 = very much). Participants’ demographic information was also collected, including gender, age, employment status, whether they have a background in design, spending childhood in rural or city, and monthly household income.

2.3. Procedures

We created the online questionnaire using the Star Questionnaires program (https://www.wjx.cn/, accessed on 12 September 2022), and then distributed the questionnaire program hyperlink in the WeChat program (https://weixin.qq.com/, accessed on 13 September 2022). Star Questionnaire is a widely used platform for surveys, and WeChat is the most popular communication App in China with a total number of users of 1.327 billion (until 30 June 2023). The questionnaires were collected in October and November in 2022, and April and May in 2023. We used a between-subject design for this study, where each participant only viewed one scene randomly selected from the 12 landscape sites. Participants were asked to view the landscape site image and answer the questions based on their immediate feelings. The site was shown on each page of the questionnaire to ensure the participants could see the site all the time during the survey.

We set up two filter questions to identify invalid samples due to the “brain-dead” choice. We asked the participants to answer in which month did they participate in the survey. If a participant chose the wrong time, the sample would be considered invalid. Moreover, participants who finished the survey in less than 60 s would also be excluded, since our preliminary examinations showed that finishing the 22 questions carefully needs at least one minute. We acquired permission for this study from the Research Ethics Committee of Tongji University.

2.4. Statistical Analyses

We conducted three steps of analysis to explore how landscape type and spatial scales affect landscape sites’ restorative effects. First, to investigate the separate effects of site scale/type on restoration, we performed a multiple linear regression analysis, with variables including landscape type, spatial scale, and participants’ demographic characteristics.

Y = β₀ + β₁type + β₂scale + β₃gender + β₄age + β₅occupation + β₆design major + β₇the place grown-up + β₈income(1)

where

• Y = continuous variable: restorative effect reported by participant (measured with PRS-11).

• type = categorical variable: plaza (reference), lawn, water.

• scale = categorical variable: 10 × 10 m (reference), 20 × 20 m, 30 × 30 m, 40 × 40 m.

• gender = binary variable: female (reference), male.

• age = categorical variable: 18–25 years old (reference), 26–50 years old, over 50 years old.

• occupation = categorical variable: student (reference), employed, retired, or unemployed.

• design major = binary variable: no (reference), yes.

• the place grown-up = binary variable: countryside (reference), town/city.

• income = categorical variable: under RMB 10,000 (reference), RMB 10,000–30,000, over RMB 30,000.

• β₁ = the restorative effect of lawn/water compared to the plaza, after adjusting for scale and demographic variables.

• β₂ = the restorative effect of differences in larger scales compared to 10 × 10 m, after adjusting for landscape type and demographic variables.

Second, to investigate whether the restoration of different site scales is heterogeneous in different types, we set the interaction term between landscape type and spatial scale in the model.

Y = β₀ + β₁type + β₂scale + β₃gender + β₄age +β₅occupation + β₆design major + β₇the place grown-up + β₈income + β₉ type × scale(2)

where

• β₉ = the effect differences of larger scales in lawn/water versus plaza.

Finally, we modeled the interaction term between site scale/type and demographic attributes, as well as the interaction term between site scale/type and preference, to investigate the restorative effects of different scales/types of landscape sites among participants with different demographic attributes and with different levels of preferences.

Y = β₀ + β₁type + β₂scale + β₃gender + β₄age + β₅occupation + β₆design major + β₇the place grown-up + β₈income + β₉₁ scale/type × demographic characteristics(3)

Y = β₀ + β₁type + β₂scale + β₃gender + β₄age + β₅occupation + β₆design major + β₇the place grown-up + β₈income + β₉₂ scale/type × preference + β₁₀ preference(4)

where

• β₉₁ = the effect differences in viewing lawn/water vs. plaza among different age groups.

• demographic characteristics = Plugin in turn: gender, age, occupation, design major, the place grown-up, income.

• β₉₂ = the effect differences in viewing lawn/water vs. plaza among different preference-level groups.

• preference = binary variable: low-level preference (reference), high-level preference.

3. Results

3.1. Descriptive Statistics

A total of 1575 people participated in the survey, and we obtained 1130 valid samples in total (71.7%). The number of questionnaires for each scene ranges from 81 to 116, due to the random allocation system of the Star Questionnaire (Table 3). The Cronbach’s alpha of all 12 sites is larger than 0.93, and the mean Cronbach’s alpha is 0.940, indicating that the questionnaire has a high reliability. We divided the participants into three age groups, including those aged between 18 and 25, 26 and 50, and those aged over 50. These three groups of people constituted 57.96%, 30.53%, and 11.51% of all the participants. More participants were female (67.96%), without a design background (62.65%), were students (59.47%), grew up in cities (60.88%), with monthly household income under RMB 10,000 (around USD 1367) per month (49.56%). Moreover, 67.52% (763/1130) of the participants were located in southern China, and 85.85% (655/763) of them were located in the Yangtze River Delta (Table 4).

We calculated the average score of the restorative effect and preference of all 12 sites (Figure 2). For each restorative dimension, the average score of the related questions was computed to represent the dimension score. The overall restorative effect of the site is represented by the mean of all the 11 questions addressed in PRS-11. For the overall restoration, water sites and lawn sites have higher perceived restorations compared to plazas. Specifically, the 30 m lawn site had the highest mean score of 6.57, and the 30 m plaza had the lowest score of 5.53. For the four dimensions of restoration, the 20 m water site had the highest score in fascination (5.64), the 30 m water had the highest score in being away (6.67), the 30 m lawn had the highest score in coherence (7.38), and the 40 m plaza had the highest score in scope (8.08). The 30 m plaza was most preferred (7.03), and participants thought the 30 m lawn site was thought as the most beautiful one (6.88).

3.2. Factors Related to Restorative Effects of Land Sites

For the overall restoration, we found that compared with plaza sites, lawn sites (β = 0.532, p < 0.001) and water sites (β = 0.342, p < 0.05) have significantly stronger restorative effects (Table 5, Figure 3). That means for small urban open spaces, lawn, and water sites have higher restorative effects compared to plazas, especially in lawn sites. However, no significant associations between site scale and the overall restorative effects were detected. Those aged over 50 (β = 1.417, p < 0.001) or retired/unemployed (β = 1.253, p < 0.001) experienced more restoration from the sites, indicating that older adults perceived more restorative effects than younger people. And participants with a design background (β = −0.408, p < 0.05), grew up in the city/town (β = −0.258, p < 0.05), with monthly household between RMB 10,000 and 30,000 (β = −0.338, p < 0.05) obtained less restoration from the sites.

For the four dimensions of restoration, compared with general restoration, the above factors had similar impacts on “fascination” and “being away”. But “coherence” was only significantly positively related to age (β = 1.098, p < 0.001), indicating that older people were more likely to regard the scene as coherent. There is a strong positive correlation between scale and “scope” (β = 0.800/0.879/1.396, p < 0.001), indicating that the larger the scale, the more open people’s perception of the site. In addition, water decreases the perception of “scope” (β = −1.594, p < 0.001) compared to that of the plaza. It indicated that with the same spatial scale, participants felt narrower when viewing the water site than the plaza site.

For other indicators, compared to the plaza, lawn (β = 0.871, p < 0.001) and water (β = 0.813, p < 0.001) sites were more preferred by participants. Those with an age older than 26 years old (β = 0.622 and 1.405, p < 0.05) or retired/unemployed (β = 1.152, p < 0.001) had more preference for sites, while people with a design background (β = −0.719, p < 0.001) or grew up in city/town (β = −0.431, p < 0.05) had less preference towards the same sites. Compared with people with monthly household incomes under 10,000, those with incomes between RMB 10,000 and 30,000 (β = −0.316, p < 0.001) also had less preference towards these sites. The factors that influence “beauty” are similar to “preference”, and factors affecting “openness” are similar to “scope”.

3.3. Restorative Effects of Landscape Sites among Different Scales, Age Groups, and Preference Levels

Through analyzing interaction terms between type and scale, age, and preference, we found that compared with 10 × 10 m sites, the perceived restoration of 30 × 30 m sites had a higher increment between the sites of plaza and lawn (β = 1.01, p = 0.009). This result indicated that people had a higher perceived restoration increase in 30 × 30 m sites compared with 10 × 10 m sites, when viewing lawn vs. plaza (Figure 4a, Table 6). In addition, we found that the age group (25–50 years old, over 50 years old) alone and landscape type (water, lawn) alone are significantly associated with higher restorative effects. As shown in Figure 4b, elderly people have higher restoration means (symbol “×”) than young people. For example, for the lawn, the perceived restorations are 8.09 (age 50+) > 6.61 (age 26–50) > 5.87 (age 18–25). These results indicated that elderly people generally receive higher restoration from small urban open spaces, which is consistent with current studies. Young people receive greater restoration change between the plaza and the water. Specifically, compared with participants aged between 18 and 25 years old, the perceived restoration of participants over 50 years old had a lesser increase between the sites of plaza and water (β = −1.23, p = 0.006). As shown in Figure 4b, the score change from water to the plaza (the horizontal connecting line slope) was greater in the younger group than in the older group, the perceived restoration differences are 0.55 (age 18–25) > 0.09 (age 26–50) > −0.58 (age 50+). These results indicated that young people have a higher perceived restoration increase compared with those with age over 50 years old when viewing water vs. plaza (Figure 4b, Table 6).

We did not observe significant associations between restorative effects and site type (p = 0.921/0.416) or preference (p = 0.197) alone. However, we found participants with high preference have larger increments in restorative effects with a borderline significance when viewing lawn sites (β = 0.61, p = 0.09) vs. plaza (Figure 4c, Table 6). This indicates the more the participant preferred the sites, the more restorative benefit increase he/she could obtain from the lawn than that from the plaza.

4. Discussion

4.1. Lawn Site Has the Highest Restorative Effects and Is the Most Preferred

Our results suggested that lawn site has the highest restorative effects and is the most preferred. Such results are consistent with previous findings regarding general open spaces. For instance, a study found that the restorative potential was significantly higher in lawns compared with small lakes and plazas [35]. Another study also found the amount of grass was one of the most important factors when people choose which park to visit [37]. That corroborates our finding that lawn is the most preferred.

Generally, natural elements contribute to environmental preference. We found water is more preferred than plaza. This finding is consistent with the existing studies, which found that the presence of water contributes to environmental preference and positive emotion [22,34]. But we found that water is less preferred than lawns. This is different from existing research findings that blue spaces are more preferred compared to green spaces [88]. One possible explanation for such a difference is that the water sites in the present study are with a small scale which could not provide an open view. Permeability theory assumes locomotive permeability could affect perceived openness, and water will reduce perceived locomotive permeability [81], which results in lower perceived openness. The insecurity caused by low openness is associated with low preference. This could explain why we found water sites are less preferred than lawn ones. So, in practice, designers should build more lawns to maximize the restorative benefits of limited space. As for water sites, designers should change the shape of the water bank to improve the contact between people and water, which would improve their preference for water.

4.2. Spatial Scale Is an Effect Modifier for the Association between Site Type and Restoration

We did not observe significant differences in restorative effects among landscape sites with various spatial scales. This finding conflicts with the existing studies that related to small urban parks, which found the most predictive of the likelihood of restoration was the park size [27], and openness contributed to restorative effects [39,40]. Such an incongruence might be due to the following reasons. In the present study, the landscape sites with lengths less than 40 m and areas less than 1600 m² are much smaller than the sites in previous studies. Our study found for spaces less than 1600 m² that spatial scale might not be a critical factor in influencing restorative effects. In other words, the lawn with a side length of 10 m may have similar restorative effects as the lawn with a side length of 40 m. But we also found that compared with plazas, the increase in the scale of the lawn (from 10 m × 10 m to 30 m × 30 m) has a more significant improvement in the perceptive restoration. Such results indicate that with limited lands, we should provide multiple small urban open spaces rather than an integrated one to provide more restorative effects. Moreover, we should provide more lawns rather than plazas when the spaces are around 30 m × 30 m in size to promote mental wellness.

4.3. Older Adults Have Higher Perceived Restorations, Young Adults Obtain a Greater Increase in Restoration from Lawn and Plaza

Our results suggested that older adults perceived more restorative effects than younger people, which is consistent with the existing studies [13,49,50,51,52]. The possible explanation is that the elderly pay more attention to the healthy function of the environment, so they can receive higher restoration in lawns and water sites than young people [89,90]. For example, a study addressing the perceived functions of green roofs found senior people cared more about the well-being functions of green roofs, such as having social interaction and recreational activities, while for the younger population, environmental functions, such as increasing biodiversity, are more valued [89]. However, compared to the elderly, the perceptive restoration of the young people increased more when the site changed from plazas to lawns. This means that the elderly restore more easily in small urban open spaces, while the young are more suitable for restoring on grass.

We also found that compared with participants who lived in rural areas, those who grew up in towns/cities had lower restorative effects and a lower preference. A possible explanation is that sites congruent with people’s environmental preferences have higher restoration potential [91]. We found participants who spent their childhood in the countryside perceived higher restorative effects. People who grew up in environments with more natural surroundings may prefer nature more, thus have higher perceived restorations. These findings suggest that in urban areas with a large number of senior citizens, designers should consider building enough small open spaces to provide sufficient restorative spaces for them. While in urban areas with more young people, more lawns could be built to maximize their restoration benefits. In addition, in urban areas with more local people, designers should pay more attention to their preferences to maximize the restorative effects of small open spaces.

4.4. High Preference Contributes to Larger Differences in the Restorative Effects of Lawn and Plaza

We found that a high preference is associated with a larger increase in restorative effects of lawn sites compared to plazas. Existing research indicates that preference is correlated with restoration likelihood [27,30,34,53] and mediated scenic beauty and restoration [38]. This is consistent with what we found, whereby high preference can promote the restorative effects of lawns. However, the relations between environmental preference and restoration are complex, some studies also assume restoration is a mediator between environment and preference [26], which calls for further exploration in future studies.

4.5. Limitations and Strengths

The study has three main limitations that need cautious interpretation. Firstly, we used two-dimensional images generated by virtual modeling instead of real ones, which might be different from the actual environment experience. Specifically, the water sites need improvements. Secondly, we provided one image for each landscape site from the observation point, and the participants had no chance to view the scenes from other visual angles. Thirdly, the baseline mental health condition of the participants was not controlled.

The strength of the study lies in the fact we kept other confounding variables consistent across the 12 sites in virtual environment creation, which eliminates the influences of other variables. In addition, in the survey, each participant only views one scene, which avoids the bias brought by show orders and repeats answers from multiple sites.

5. Conclusions

In addressing small urban open spaces with side lengths of less than 40 m, we investigated the effects of landscape type and spatial scale on these sites’ restorative effects. The results indicated that the lawn has the highest restorative effects and is most preferred by participants. No associations between restorative effects and spatial scales alone were detected. However, the spatial scale plays an important role as an effect modifier for the association between site type and restoration. We found high preference contributes to larger differences in the restorative effects of lawns and plazas. In other words, those who prefer the sites may gain more restoration increases when viewing lawns compared to plazas. Moreover, although older adults have higher perceived restorations, young adults have a greater increase in restoration between lawn scenes and plaza scenes, indicating that young adults could benefit more from the building of small natural open spaces. The findings of the present study have direct implications for design practice. First, small natural urban open spaces of lawn and water should be developed, even as small as 100 m², to provide more restorative benefits. Second, if the space scale reaches about 900 m², more lawns should be built instead of plazas to promote restoration, especially for young people. In addition, the findings of this study could help to supplement the research gap in the field of small urban open spaces and improve people’s attention to small open spaces. This study also adds to the research field on the relationship between urban open space and restoration. To further address the limitations of this study, we plan to initiate a within-subject experiment with real scenes to let each participant view all scenes with different types and scales to investigate the restorative effects of small open spaces.

Author Contributions

Conceptualization, Y.Z. and J.Y. (Jie Yin); formal analysis, Y.Z., B.F., J.Y. (Jingyao Yu), R.G. and J.Y. (Jie Yin); investigation, B.F. and J.Y. (Jingyao Yu); writing—original draft preparation, Y.Z. and B.F.; writing—review and editing, J.Y. (Jie Yin); funding acquisition, Y.Z. and J.Y. (Jie Yin). All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The raw data in this article will be available on request.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

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Figures and Tables

Figure 1. Images of the 12 landscape sites.

Figure 2. Average scores of 12 sites.

Figure 3. Scores of three landscape-type groups by four scale groups.

Figure 4. Restoration of sites with different scales (a), age groups (b), and preference levels (c).

Table 1

Elements in the virtual landscape scene.

Element	Characteristics
Surrounding buildings	Height in the range of 6–15 m (2–5 floors).
	Be placed in the same position across different scenes.
	Without decorations or bright colors on the facades.
Plants	Trees are oak (8.5 m high) and fir (9 m or 5.5 m high), and shrubs are American boxwood (2.3 m) and holly (1.3 m).
	Plants are placed in a single row.
	The proportions among the broadleaf, tall conifer, and short conifer are around 3:1:2.
Other factors	1 m × 1 m blocks are paved on the plaza
	The water is with ripples and close to the ground.
	The lawn has a yellow-green grass texture.

Table 2

The Perceived Restorative Scale-11.

Dimension	Items
Fascination	Places like that are fascinating.
	In places like this, my attention is drawn to many interesting things.
	In places like this, it is hard to be bored.
Being Away	Places like that are a refuge from nuisances.
	To get away from things that usually demand my attention I like to go to places like this.
	To stop thinking about the things that I must get done I like to go to places like this.
Coherence	There is a clear order in the physical arrangement of places like this.
	In places like this, it is easy to see how things are organized.
	In places like this, everything seems to have its proper place.
Scope	That place is large enough to allow exploration in many directions.
	In places like that, there are few boundaries to limit my possibility of moving about.

Table 3

The number of questionnaires for each scene.

		Scale				Total
		10 m × 10 m	20 m × 20 m	30 m × 30 m	40 m × 40 m
Type	Lawn	91	92	94	92	369
	Water	81	92	99	95	367
	Plaza	116	82	99	97	394
Total		288	266	292	284	1130

Table 4

Descriptive statistics of the participants’ demographic information.

Participants’ Demographic Information		n	%
Gender	Male	362	32.04
	Female	768	67.96
Age	18–25	655	57.96
	26–50	345	30.53
	Over 50	130	11.51
Whether have a design background	Yes	422	37.35
	No	708	62.65
Occupation	Student	672	59.47
	Employed	291	25.75
	Retired/unemployed	167	14.78
Place grown up	City/town	688	60.88
	Countryside	442	39.12
Monthly household income (RMB)	Under 10,000	560	49.56
	10,000–30,000	416	36.81
	Over 30,000	154	13.63
Regional distribution	South	763	67.52
	North	367	32.48
Total		1130	100

Table 5

Results of the multiple linear regression analysis.

		Restoration	Fascination	Being Away	Coherence	Scope	Preference	Beauty	Openness
Independent variables
Site type	Plaza (reference)
	Lawn	0.532 **	0.690 **	1.061 **	0.220	−0.031	0.871 **	0.739 **	0.049
	Water	0.342 *	0.991 **	1.287 **	0.037	−1.594 **	0.813 **	0.816 **	−0.516 *
Site scale	10 × 10 m (reference)
	20 × 20 m	0.146	0.140	−0.082	−0.057	0.800 **	0.100	0.107	1.259 **
	30 × 30 m	0.052	−0.081	−0.390	0.076	0.879 **	0.035	0.060	1.497 **
	40 × 40 m	0.197	0.023	−0.400	0.169	1.396 **	0.047	−0.034	e
Control variables
Gender	Female (reference)
	Male	−0.056	−0.053	0.017	−0.127	−0.064	0.070	0.034	0.160
Age	18–25 (reference)
	26–50	0.385	0.502	0.281	0.416	0.320	0.622 *	0.719 *	0.128
	Over 50	1.417 **	1.804 **	1.377 *	1.098 **	1.374 **	1.405 **	1.718 **	1.223 *
Design major	No (reference)
	Yes	−0.408 *	−0.602 **	−0.583 *	−0.078	−0.352 *	−0.719 **	−0.591 **	−0.164
Occupation	Student (reference)
	Employed	0.259	0.442	0.303	0.061	0.214	0.108	0.083	0.254
	Retired/unemployed	1.253 **	1.675 **	1.409 **	0.798 *	1.072 *	1.152 **	1.119 *	1.176 *
The place grown-up	Countryside (reference)
	Town/city	−0.258 *	−0.252	−0.330 *	−0.113	−0.378 *	−0.431 *	−0.318 *	−0.302 *
Monthly household income (RMB)	Under 10,000 (reference)
	10,000–30,000	−0.338 *	−0.447 *	−0.319	−0.192	−0.377 *	−0.361 *	−0.151	−0.069
	Over 30,000	−0.239	−0.296	−0.241	−0.172	−0.252	−0.295	−0.225	−0.078
R2		0.203	0.239	0.173	0.099	0.215	0.217	0.204	0.196
F		20.277	25.061	16.676	8.713	21.856	22.078	20.453	19.398
p		p < 0.001

Note. p Pearson correlation coefficients. * p < 0.05 (2-tailed). ** p < 0.001 (2-tailed).

Table 6

Results of the multiple linear regression models with interaction terms.

		Scale × Type			Age × Type			Preference × Type
		β	SE	p	β	SE	p	β	SE	p
Variable
Site type	Plaza (reference)	-	-	-	-	-	-	-	-	-
	Lawn	0.23	0.27	0.389	0.71	0.18	<0.001 **	0.03	0.32	0.921
	Water	0.27	0.28	0.33	0.62	0.18	0.001 **	0.27	0.33	0.416
Site scale	10 × 10 m (reference)	-	-	-	-	-	-	-	-	-
	20 × 20 m	0.29	0.25	0.255	0.15	0.16	0.374	0.15	0.16	0.345
	30 × 30 m	−0.34	0.24	0.155	0.07	0.16	0.671	0.07	0.16	0.67
	40 × 40 m	0.06	0.24	0.795	0.19	0.16	0.234	0.21	0.16	0.185
Gender	Female (ref)	-	-	-	-	-	-	-	-	-
	Male	0.06	0.12	0.627	0.07	0.12	0.567	0.05	0.12	0.697
Age	18–25 (ref)	-	-	-	-	-	-	-	-	-
	26–50	0.42	0.24	0.077	0.61	0.28	0.031 *	0.41	0.24	0.079
	Over 50	1.42	0.31	<0.001 **	1.96	0.37	<0.001 **	1.44	0.31	<0.001 **
Design Major	No (ref)	-	-	-	-	-	-	-	-	-
	Yes	−0.41	0.13	0.002 *	−0.43	0.13	0.001 **	−0.41	0.13	0.002 *
occupation	Student (ref)	-	-	-	-	-	-	-	-	-
	Employed	−0.22	0.25	0.368	−0.25	0.24	0.304	−0.24	0.25	0.323
	Retired/unemployed	1.03	0.21	<0.001 **	0.97	0.21	<0.001 **	0.98	0.21	<0.001 **
The place grown-up	Countryside (ref)	-	-	-	-	-	-	-	-	-
	Town/city	−0.26	0.13	0.037 *	−0.24	0.13	0.054	−0.26	0.13	0.04 *
Monthly household income	Under 10,000 (ref)	-	-	-	-	-	-	-	-	-
	10,000–30,000	−0.35	0.13	0.006 *	−0.35	0.13	0.006 *	−0.33	0.13	0.009 *
	Over 30,000	−0.25	0.18	0.168	−0.26	0.18	0.149	−0.24	0.18	0.178
Preference	Low (ref)	-	-	-	-	-	-	-	-	-
	High	-	-	-	-	-	-	−0.31	0.24	0.197
Interaction terms
Site scale × Site type	scale (10 × 10 m) × type (plaza) (ref)	-	-	-	-	-	-	-	-	-
	scale (20 × 20 m) × type (lawn)	−0.15	0.39	0.707	-	-	-	-	-	-
	scale (30 × 30 m) × type (lawn)	1.01	0.39	0.009 *	-	-	-	-	-	-
	scale (40 × 40 m) × type (lawn)	0.31	0.39	0.423	-	-	-	-	-	-
	scale (20 × 20 m) × type (water)	−0.27	0.4	0.495	-	-	-	-	-	-
	scale (30 × 30 m) × type (water)	0.37	0.39	0.346	-	-	-	-	-	-
	scale (40 × 40 m) × type (water)	0.17	0.39	0.671	-	-	-	-	-	-
Age × Site type	age (18–25) × type (plaza) (ref)	-	-	-	-	-	-	-	-	-
	age (26–50) × type (lawn)	-	-	-	−0.3	0.31	0.333	-	-	-
	age (over 50) × type (lawn)	-	-	-	−0.71	0.46	0.12	-	-	-
	age (26–50) × type (water)	-	-	-	−0.42	0.31	0.178	-	-	-
	age (over 50) × type (water)	-	-	-	−1.23	0.45	0.006 *	-	-	-
Preference × Site type	preference (low) × type (plaza) (ref)	-	-	-	-	-	-	-	-	-
	preference (high) × type (lawn)	-	-	-	-	-	-	0.61	0.36	0.09
	preference (high) × type (water)	-	-	-	-	-	-	0.08	0.36	0.827
R2		0.196			0.196			0.193
F		14.8			16.31			16.92
p		<0.001			<0.001			<0.001

Note. p Pearson correlation coefficients. * p < 0.05 (2-tailed) ** p < 0.001 (2-tailed).

References

1. Grahn, P.; Stigsdotter, U.K. The relation between perceived sensory dimensions of urban green space and stress restoration. Landsc. Urban Plan.; 2010; 94, pp. 264-275. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2009.10.012]

2. Li, D.; Sullivan, W.C. Impact of views to school landscapes on recovery from stress and mental fatigue. Landsc. Urban Plan.; 2016; 148, pp. 149-158. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2015.12.015]

3. Schipperijn, J.; Stigsdotter, U.K.; Randrup, T.B.; Troelsen, J. Influences on the use of urban green space—A case study in Odense, Denmark. Urban For. Urban Green.; 2010; 9, pp. 25-32. [DOI: https://dx.doi.org/10.1016/j.ufug.2009.09.002]

4. Van den Berg, M.; Wendel-Vos, W.; van Poppel, M.; Kemper, H.; van Mechelen, W.; Maas, J. Health benefits of green spaces in the living environment: A systematic review of epidemiological studies. Urban For. Urban Green.; 2015; 14, pp. 806-816. [DOI: https://dx.doi.org/10.1016/j.ufug.2015.07.008]

5. Asgarzadeh, M.; Lusk, A.; Koga, T.; Hirate, K. Measuring oppressiveness of streetscapes. Landsc. Urban Plan.; 2012; 107, pp. 1-11. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2012.04.001]

6. Fung, H.H.; Jiang, D. Cross-cultural psychology of aging. Handbook of the Psychology of Aging; Academic Press: Cambridge, MA, USA, 2016; pp. 323-337.

7. Jiang, D.; Fung, H.H. Social and emotional theories of aging. Work Across the Lifespan; Academic Press: Cambridge, MA, USA, 2019; pp. 135-153.

8. Luo, L.; Jiang, B. From oppressiveness to stress: A development of Stress Reduction Theory in the context of contemporary high-density city. J. Environ. Psychol.; 2022; 84, 101883. [DOI: https://dx.doi.org/10.1016/j.jenvp.2022.101883]

9. Elsadek, M.; Liu, B.; Lian, Z. Green façades: Their contribution to stress recovery and well-being in high-density cities. Urban For. Urban Green.; 2019; 46, 126446. [DOI: https://dx.doi.org/10.1016/j.ufug.2019.126446]

10. Elsadek, M.; Liu, B.; Xie, J. Window view and relaxation: Viewing green space from a high-rise estate improves urban dwellers’ wellbeing. Urban For. Urban Green.; 2020; 55, 126846. [DOI: https://dx.doi.org/10.1016/j.ufug.2020.126846]

11. Scopelliti, M.; Carrus, G.; Adinolfi, C.; Suarez, G.; Colangelo, G.; Lafortezza, R.; Panno, A.; Sanesi, G. Staying in touch with nature and well-being in different income groups: The experience of urban parks in Bogotá. Landsc. Urban Plan.; 2016; 148, pp. 139-148. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2015.11.002]

12. Bratman, G.N.; Daily, G.C.; Levy, B.J.; Gross, J.J. The benefits of nature experience: Improved affect and cognition. Landsc. Urban Plan.; 2015; 138, pp. 41-50. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2015.02.005]

13. Kabisch, N.; Püffel, C.; Masztalerz, O.; Hemmerling, J.; Kraemer, R. Physiological and psychological effects of visits to different urban green and street environments in older people: A field experiment in a dense inner-city area. Landsc. Urban Plan.; 2021; 207, 103998. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2020.103998]

14. Lin, W.; Chen, Q.; Jiang, M.; Zhang, X.; Liu, Z.; Tao, J.; Wu, L.; Xu, S.; Kang, Y.; Zeng, Q. The effect of green space behaviour and per capita area in small urban green spaces on psychophysiological responses. Landsc. Urban Plan.; 2019; 192, 103637. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2019.103637]

15. Van Den Berg, A.E.; Maas, J.; Verheij, R.A.; Groenewegen, P.P. Green space as a buffer between stressful life events and health. Soc. Sci. Med.; 2010; 70, pp. 1203-1210. [DOI: https://dx.doi.org/10.1016/j.socscimed.2010.01.002] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20163905]

16. Thompson, C.W.; Roe, J.; Aspinall, P.; Mitchell, R.; Clow, A.; Miller, D. More green space is linked to less stress in deprived communities: Evidence from salivary cortisol patterns. Landsc. Urban Plan.; 2012; 105, pp. 221-229. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2011.12.015]

17. Browning, M.H.; Lee, K.; Wolf, K.L. Tree cover shows an inverse relationship with depressive symptoms in elderly residents living in U.S. nursing homes. Urban For. Urban Green.; 2019; 41, pp. 23-32. [DOI: https://dx.doi.org/10.1016/j.ufug.2019.03.002]

18. Taylor, M.S.; Wheeler, B.W.; White, M.P.; Economou, T.; Osborne, N.J. Research note: Urban street tree density and antidepressant prescription rates—A cross-sectional study in London, UK. Landsc. Urban Plan.; 2015; 136, pp. 174-179. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2014.12.005]

19. Lottrup, L.; Grahn, P.; Stigsdotter, U.K. Workplace greenery and perceived level of stress: Benefits of access to a green outdoor environment at the workplace. Landsc. Urban Plan.; 2013; 110, pp. 5-11. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2012.09.002]

20. Bielinis, E.; Takayama, N.; Boiko, S.; Omelan, A.; Bielinis, L. The effect of winter forest bathing on psychological relaxation of young Polish adults. Urban For. Urban Green.; 2018; 29, pp. 276-283. [DOI: https://dx.doi.org/10.1016/j.ufug.2017.12.006]

21. Bark, R.H.; Osgood, D.E.; Colby, B.G.; Halper, E.B. How do homebuyers value different types of green space?. J. Agric. Resour. Econ.; 2011; 36, pp. 395-415.

22. White, M.; Smith, A.; Humphryes, K.; Pahl, S.; Snelling, D.; Depledge, M. Blue space: The importance of water for preference, affect, and restorativeness ratings of natural and built scenes. J. Environ. Psychol.; 2010; 30, pp. 482-493. [DOI: https://dx.doi.org/10.1016/j.jenvp.2010.04.004]

23. Van den Berg, A.E.; Jorgensen, A.; Wilson, E.R. Evaluating restoration in urban green spaces: Does setting type make a difference?. Landsc. Urban Plan.; 2014; 127, pp. 173-181. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2014.04.012]

24. Yu, C.-P.; Lee, H.-Y.; Luo, X.-Y. The effect of virtual reality forest and urban environments on physiological and psychological responses. Urban For. Urban Green.; 2018; 35, pp. 106-114. [DOI: https://dx.doi.org/10.1016/j.ufug.2018.08.013]

25. Kaplan, S. The restorative benefits of nature: Toward an integrative framework. J. Environ. Psychol.; 1995; 15, pp. 169-182. [DOI: https://dx.doi.org/10.1016/0272-4944(95)90001-2]

26. Kaplan, R.; Kaplan, S. The Experience of Nature: A Psychological Perspective; Cambridge University Press: New York, NY, USA, 1989.

27. Nordh, H.; Hartig, T.; Hagerhall, C.; Fry, G. Components of small urban parks that predict the possibility for restoration. Urban For. Urban Green.; 2009; 8, pp. 225-235. [DOI: https://dx.doi.org/10.1016/j.ufug.2009.06.003]

28. Nordh, H.; Hagerhall, C.M.; Holmqvist, K. Tracking Restorative Components: Patterns in Eye Movements as a Consequence of a Restorative Rating Task. Landsc. Res.; 2013; 38, pp. 101-116. [DOI: https://dx.doi.org/10.1080/01426397.2012.691468]

29. Jiang, B.; Chang, C.-Y.; Sullivan, W.C. A dose of nature: Tree cover, stress reduction, and gender differences. Landsc. Urban Plan.; 2014; 132, pp. 26-36. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2014.08.005]

30. Herzog, T.R.; Maguire, C.P.; Nebel, M.B. Assessing the restorative components of environments. J. Environ. Psychol.; 2003; 23, pp. 159-170. [DOI: https://dx.doi.org/10.1016/S0272-4944(02)00113-5]

31. Huang, Q.; Yang, M.; Jane, H.-A.; Li, S.; Bauer, N. Trees, grass, or concrete? The effects of different types of environments on stress reduction. Landsc. Urban Plan.; 2020; 193, 103654. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2019.103654]

32. Sonntag-Öström, E.; Nordin, M.; Lundell, Y.; Dolling, A.; Wiklund, U.; Karlsson, M.; Carlberg, B.; Järvholm, L.S. Restorative effects of visits to urban and forest environments in patients with exhaustion disorder. Urban For. Urban Green.; 2014; 13, pp. 344-354. [DOI: https://dx.doi.org/10.1016/j.ufug.2013.12.007]

33. Tang, I.-C.; Tsai, Y.-P.; Lin, Y.-J.; Chen, J.-H.; Hsieh, C.-H.; Hung, S.-H.; Sullivan, W.C.; Tang, H.-F.; Chang, C.-Y. Using functional Magnetic Resonance Imaging (fMRI) to analyze brain region activity when viewing landscapes. Landsc. Urban Plan.; 2017; 162, pp. 137-144. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2017.02.007]

34. Wang, R.; Zhao, J.; Meitner, M.J.; Hu, Y.; Xu, X. Characteristics of urban green spaces in relation to aesthetic preference and stress recovery. Urban For. Urban Green.; 2019; 41, pp. 6-13. [DOI: https://dx.doi.org/10.1016/j.ufug.2019.03.005]

35. Wang, X.; Rodiek, S.; Wu, C.; Chen, Y.; Li, Y. Stress recovery and restorative effects of viewing different urban park scenes in Shanghai, China. Urban For. Urban Green.; 2016; 15, pp. 112-122. [DOI: https://dx.doi.org/10.1016/j.ufug.2015.12.003]

36. Chiang, Y.-C.; Li, D.; Jane, H.-A. Wild or tended nature? The effects of landscape location and vegetation density on physiological and psychological responses. Landsc. Urban Plan.; 2017; 167, pp. 72-83. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2017.06.001]

37. Nordh, H.; Alalouch, C.; Hartig, T. Assessing restorative components of small urban parks using conjoint methodology. Urban For. Urban Green.; 2011; 10, pp. 95-103. [DOI: https://dx.doi.org/10.1016/j.ufug.2010.12.003]

38. Han, K.-T. An exploration of relationships among the responses to natural scenes—Scenic Beauty, Preference, and Restoration. Environment and Behavior. Environ. Behav.; 2010; 42, pp. 243-270. [DOI: https://dx.doi.org/10.1177/0013916509333875]

39. Stigsdotter, U.K.; Corazon, S.S.; Sidenius, U.; Refshauge, A.D.; Grahn, P. Forest design for mental health promotion—Using perceived sensory dimensions to elicit restorative responses. Landsc. Urban Plan.; 2017; 160, pp. 1-15. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2016.11.012]

40. Franěk, M. Landscape Preference: The Role of Attractiveness and Spatial Openness of the Environment. Behav. Sci.; 2023; 13, 666. [DOI: https://dx.doi.org/10.3390/bs13080666]

41. Rogge, E.; Nevens, F.; Gulinck, H. Perception of rural landscapes in Flanders: Looking beyond aesthetics. Landsc. Urban Plan.; 2007; 82, pp. 159-174. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2007.02.006]

42. Shi, S.; Gou, Z.; Chen, L.H. How does enclosure influence environmental preferences? A cognitive study on urban public open spaces in Hong Kong. Sustain. Cities Soc.; 2014; 13, pp. 148-156. [DOI: https://dx.doi.org/10.1016/j.scs.2014.04.011]

43. Norberg-Schulz, C. Intentions in Architecture; No. 74 MIT Press: Cambridge, MA, USA, 1968.

44. Epstein, R.; Kanwisher, N. A cortical representation of the local visual environment. Nature; 1998; 392, pp. 598-601. [DOI: https://dx.doi.org/10.1038/33402]

45. Schiebel, T.; Gallinat, J.; Kühn, S. Testing the Biophilia theory: Automatic approach tendencies towards nature. J. Environ. Psychol.; 2022; 79, 101725. [DOI: https://dx.doi.org/10.1016/j.jenvp.2021.101725]

46. Strumse, E. Environmental attributes and the prediction of visual preferences for agrarian landscapes in western Norway. J. Environ. Psychol.; 1994; 14, pp. 293-303. [DOI: https://dx.doi.org/10.1016/S0272-4944(05)80220-8]

47. Van den Berg, A.E.; Koole, S.L. New wilderness in the Netherlands: An investigation of visual preferences for nature development landscapes. Landsc. Urban Plan.; 2006; 78, pp. 362-372. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2005.11.006]

48. Carrus, G.; Scopelliti, M.; Lafortezza, R.; Colangelo, G.; Ferrini, F.; Salbitano, F.; Agrimi, M.; Portoghesi, L.; Semenzato, P.; Sanesi, G. Go greener, feel better? The positive effects of biodiversity on the well-being of individuals visiting urban and peri-urban green areas. Landsc. Urban Plan.; 2015; 134, pp. 221-228. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2014.10.022]

49. Berto, R. Assessing the restorative value of the environment: A study on the elderly in comparison with young adults and adolescents. Int. J. Psychol.; 2007; 42, pp. 331-341. [DOI: https://dx.doi.org/10.1080/00207590601000590]

50. Fornara, F.; Troffa, R. Restorative experiences and perceived affective qualities in different built and natural urban places. Proceedings of the Revitalising Built Environments: Requalifying Old Places for New Uses; Istanbul, Turkey, 12–16 October 2009; pp. 1-10.

51. Qiu, L.; Chen, Q.; Gao, T. The Effects of Urban Natural Environments on Preference and Self-Reported Psychological Restoration of the Elderly. Int. J. Environ. Res. Public Health; 2021; 18, 509. [DOI: https://dx.doi.org/10.3390/ijerph18020509]

52. Yu, C.-P.; Lee, H.-Y.; Lu, W.-H.; Huang, Y.-C.; Browning, M.H. Restorative effects of virtual natural settings on middle-aged and elderly adults. Urban For. Urban Green.; 2020; 56, 126863. [DOI: https://dx.doi.org/10.1016/j.ufug.2020.126863]

53. Deng, L.; Luo, H.; Ma, J.; Huang, Z.; Sun, L.-X.; Jiang, M.-Y.; Zhu, C.-Y.; Li, X. Effects of integration between visual stimuli and auditory stimuli on restorative potential and aesthetic preference in urban green spaces. Urban For. Urban Green.; 2020; 53, 126702. [DOI: https://dx.doi.org/10.1016/j.ufug.2020.126702]

54. Lai, K.Y.; Sarkar, C.; Sun, Z.; Scott, I. Are greenspace attributes associated with perceived restorativeness? A comparative study of urban cemeteries and parks in Edinburgh, Scotland. Urban For. Urban Green.; 2020; 53, 126720. [DOI: https://dx.doi.org/10.1016/j.ufug.2020.126720]

55. Van Den Berg, A.E.; Koole, S.L.; van der Wulp, N.Y. Environmental preference and restoration: (How) are they related?. J. Environ. Psychol.; 2003; 23, pp. 135-146. [DOI: https://dx.doi.org/10.1016/S0272-4944(02)00111-1]

56. Wilkie, S.; Stavridou, A. Influence of environmental preference and environment type congruence on judgments of restoration potential. Urban For. Urban Green.; 2013; 12, pp. 163-170. [DOI: https://dx.doi.org/10.1016/j.ufug.2013.01.004]

57. Hoyle, H.; Hitchmough, J.; Jorgensen, A. All about the ‘wow factor’? The relationships between aesthetics, re-storative effect and perceived biodiversity in designed urban planting. Landsc. Urban Plan.; 2017; 164, pp. 109-123. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2017.03.011]

58. Pazhouhanfar, M.; Mustafa Kamal, M.S. Effect of predictors of visual preference as characteristics of urban natural landscapes in increasing perceived restorative potential. Urban For. Urban Green.; 2014; 13, pp. 145-151. [DOI: https://dx.doi.org/10.1016/j.ufug.2013.08.005]

59. Pincetl, S.; Gearin, E. The Reinvention of Public Green Space. Urban Geogr.; 2013; 26, pp. 365-384. [DOI: https://dx.doi.org/10.2747/0272-3638.26.5.365]

60. Picard, P.; Tran, T. Small urban green areas. J. Environ. Econ. Manag.; 2021; 106, 102418. [DOI: https://dx.doi.org/10.1016/j.jeem.2021.102418]

61. Liu, S.; Wang, X. Reexamine the value of urban pocket parks under the impact of the COVID-19. Urban For. Urban Green.; 2021; 64, 127294. [DOI: https://dx.doi.org/10.1016/j.ufug.2021.127294]

62. Kerishnan, P.B.; Maruthaveeran, S. Factors contributing to the usage of pocket parks―A review of the evidence. Urban For. Urban Green.; 2021; 58, 126985. [DOI: https://dx.doi.org/10.1016/j.ufug.2021.126985]

63. Egerer, M.; Annighöfer, P.; Arzberger, S.; Burger, S.; Hecher, Y.; Knill, V.; Probst, B.; Suda, M. Urban oases: The social-ecological importance of small urban green spaces. Ecosyst. People; 2024; 20, 2315991. [DOI: https://dx.doi.org/10.1080/26395916.2024.2315991]

64. Ugolini, F.; Massetti, L.; Calaza-Martínez, P.; Cariñanos, P.; Dobbs, C.; Ostoić, S.K.; Marin, A.M.; Pearlmutter, D.; Saaroni, H.; Šaulienė, I. et al. Effects of the COVID-19 pandemic on the use and perceptions of urban green space: An international exploratory study. Urban For. Urban Green.; 2020; 56, 126888. [DOI: https://dx.doi.org/10.1016/j.ufug.2020.126888]

65. Soga, M.; Evans, M.J.; Tsuchiya, K.; Fukano, Y. A room with a green view the importance of nearby nature for mental health during the COVID-19 pandemic. Ecol. Appl.; 2021; 31, e2248. [DOI: https://dx.doi.org/10.1002/eap.2248] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33205530]

66. Dzhambov, A.M.; Lercher, P.; Browning, M.H.E.M.; Stoyanov, D.; Petrova, N.; Novakov, S.; Dimitrova, D.D. Does greenery experienced indoors and outdoors provide an escape and support mental health during the COVID-19 quarantine?. Environ. Res.; 2021; 196, 110420. [DOI: https://dx.doi.org/10.1016/j.envres.2020.110420]

67. Gu, J.; Liu, H.; Lu, H. Can Even a Small Amount of Greenery Be Helpful in Reducing Stress? A Systematic Review. Int. J. Environ. Res. Public Health; 2022; 19, 9778. [DOI: https://dx.doi.org/10.3390/ijerph19169778] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36011414]

68. Gunn, C.; Vahdati, M.; Shahrestani, M. Green walls in schools—The potential well-being benefits. J. Affect. Disord.; 2022; 224, 109560. [DOI: https://dx.doi.org/10.1016/j.buildenv.2022.109560]

69. Wendel, H.E.W.; Zarger, R.K.; Mihelcic, J.R. Accessibility and usability: Green space preferences, perceptions, and barriers in a rapidly urbanizing city in Latin America. Landsc. Urban Plan.; 2012; 107, pp. 272-282. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2012.06.003]

70. Gibson, S.; Loukaitou-Sideris, A.; Mukhija, V. Ensuring park equity: A California case study. J. Urban Des.; 2018; 24, pp. 385-405. [DOI: https://dx.doi.org/10.1080/13574809.2018.1497927]

71. Xiao, Y.; Miao, S.; Zhang, Y.; Chen, H.; Wu, W. Exploring the health effects of neighborhood greenness on Lilong residents in Shanghai. Urban For. Urban Green.; 2021; 66, 127383. [DOI: https://dx.doi.org/10.1016/j.ufug.2021.127383]

72. Huang, Y.; Lin, X.; Lin, S.; Chen, Z.; Fu, W.; Wang, M.; Dong, J. Pocket Parks: A New Approach to Improving the Psychological and Physical Health of Recreationists. Forests; 2023; 14, 1983. [DOI: https://dx.doi.org/10.3390/f14101983]

73. Bajwoluk, T.; Langer, P. The pocket park and its impact on the quality of urban space on the local and supralocal scale—Case study of Krakow, Poland. Sustainability; 2023; 15, 5153. [DOI: https://dx.doi.org/10.3390/su15065153]

74. Forsyth, A.; Musacchio, L. Designing Small Parks: A Manual for Addressing Social and Ecological Concerns; John Wiley & Sons: Hoboken, NJ, USA, 2005.

75. Peschardt, K.K.; Stigsdotter, U.K. Associations between park characteristics and perceived restorativeness of small public urban green spaces. Landsc. Urban Plan.; 2013; 112, pp. 26-39. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2012.12.013]

76. Taylor, A.F.; Kuo, F.E.; Sullivan, W.C. Views of nature and self-discipline: Evidence from inner city children. J. Environ. Psychol.; 2002; 22, pp. 49-63. [DOI: https://dx.doi.org/10.1006/jevp.2001.0241]

77. Bu, J.; Yin, J.; Yu, Y.; Zhan, Y. Identifying the daily activity spaces of older adults living in a high-density urban area: A study using the smartphone-based global positioning system trajectory in Shanghai. Sustainability; 2021; 13, 5003. [DOI: https://dx.doi.org/10.3390/su13095003]

78. Tomasso, L.P.; Yin, J.; Laurent, J.G.C.; Chen, J.T.; Catalano, P.J.; Spengler, J.D. The Relationship between Nature Deprivation and Individual Wellbeing across Urban Gradients under COVID-19. Int. J. Environ. Res. Public Health; 2021; 18, 1511. [DOI: https://dx.doi.org/10.3390/ijerph18041511]

79. Xu, L.; Zhang, Y.; Li, F.; Yin, J. Perceptual difference of urban public spaces between design professionals and ‘laypersons’: Evidence, health implications and ready-made urban design templates. Indoor Built Environ.; 2023; 32, pp. 494-520. [DOI: https://dx.doi.org/10.1177/1420326X221116318]

80. Chen, D.; Yin, J.; Yu, C.P.; Sun, S.; Gabel, C.; Spengler, J.D. Physiological and psychological responses to transitions between urban built and natural environments using the cave automated virtual environment. Landsc. Urban Plan.; 2024; 241, 104919. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2023.104919]

81. Stamps, A.E. Atmospheric Permeability and Perceived Enclosure. Environ. Behav.; 2012; 44, pp. 427-446. [DOI: https://dx.doi.org/10.1177/0013916510393277]

82. Stamps, A.E. Permeability theory and palace Athena. Percept. Mot. Ski.; 2013; 116, pp. 806-815. [DOI: https://dx.doi.org/10.2466/24.27.PMS.116.3.806-815]

83. Chen, C.; Wang, Y.; Jia, J. Public perceptions of ecosystem services and preferences for design scenarios of the flooded bank along the Three Gorges Reservoir: Implications for sustainable management of novel ecosystems. Urban For. Urban Green.; 2018; 34, pp. 196-204. [DOI: https://dx.doi.org/10.1016/j.ufug.2018.06.009]

84. Hartig, T.; Korpela, K.; Evans, G.W.; Gärling, T. A measure of restorative quality in environments. Scand. Hous. Plan. Res.; 1997; 14, pp. 175-194.

85. Pasini, M.; Berto, R.; Brondino, M.; Hall, R.; Ortner, C. How to Measure the Restorative Quality of Environments: The PRS-11. Procedia Soc. Behav. Sci.; 2014; 159, pp. 293-297. [DOI: https://dx.doi.org/10.1016/j.sbspro.2014.12.375]

86. Berto, R. The Role of Nature in Coping with Psycho-Physiological Stress: A Literature Review on Restorativeness. Behav. Sci.; 2014; 4, pp. 394-409. [DOI: https://dx.doi.org/10.3390/bs4040394] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25431444]

87. Senese, V.P.; Pascale, A.; Maffei, L.; Cioffi, F.; Sergi, I.; Gnisci, A.; Masullo, M. The influence of personality traits on the measure of restorativeness in an urban park: A multisensory immersive virtual reality study. Neural Approaches Dyn. Signal Exch.; 2020; 151, pp. 347-357.

88. Luo, H.; Deng, L.; Song, C.; Jiang, S.; Huang, Y.; Wang, W.; Liu, X.; Li, S.; Guo, B.; Peng, L. et al. Which characteristics and integrations between characteristics in blue–green spaces influence the nature experience?. J. Environ. Plan. Manag.; 2023; 66, pp. 1253-1279. [DOI: https://dx.doi.org/10.1080/09640568.2022.2026307]

89. Rezaei, M.; Emmanuel, N.; Kim, J.; Kim, D.H. Analyzing the impact of green roof functions on the citizens’ mental health in metropolitan cities. Iran. J. Public Health; 2021; 50, pp. 900-907. [DOI: https://dx.doi.org/10.18502/ijph.v50i5.6107]

90. Rosenbaum, M.S. Restorative servicescapes: Restoring directed attention in third places. J. Serv. Manag.; 2009; 20, pp. 173-191. [DOI: https://dx.doi.org/10.1108/09564230910952762]

91. Wilkie, S.; Clements, H. Further exploration of environment preference and environment type congruence on restoration and perceived restoration potential. Landsc. Urban Plan.; 2017; 170, pp. 314-319. [DOI: https://dx.doi.org/10.1016/j.landurbplan.2017.04.013]