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Article

What Is the Perceived Environmental Restorative Potential of Informal Green Spaces? An Empirical Study Based on Visitor-Employed Photography

by
Jiayi Jiang
1,2,3,
Hong Xu
2,4,
Ruochen Ma
5,*,
Shi Chen
1,
Huixin Wang
5,* and
Ziang Zheng
6
1
School of Architecture, Soochow University, No. 199 Ren-ai Road, Suzhou Industrial Park, Suzhou 215123, China
2
Soochow University—Suzhou Yuanke (SU-SY) Collaborative Innovation Center of Architecture and Urban Environment, School of Architecture, Soochow University, No. 199 Ren-ai Road, Suzhou Industrial Park, Suzhou 215123, China
3
China-Portugal Joint Laboratory of Cultural Heritage Conservations Science Supported by the Belt and Road Initative, Soochow University, Suzhou 215123, China
4
Suzhou Yuanke Ecological Construction Group, No. 268 Dongping Street, Suzhou 215123, China
5
Graduate School of Horticulture, Chiba University, Chiba 271-8510, Japan
6
The Liverpool School of Architecture, University of Liverpool, 25 Abercromby Square, Liverpool L69 7ZN, UK
*
Authors to whom correspondence should be addressed.
Land 2024, 13(11), 1768; https://doi.org/10.3390/land13111768
Submission received: 17 September 2024 / Revised: 23 October 2024 / Accepted: 24 October 2024 / Published: 28 October 2024
(This article belongs to the Special Issue Urban Regeneration: Challenges and Opportunities for the Landscape)
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Abstract

:
Informal green spaces (IGSs) play an essential role in enhancing urban well-being by offering restorative environments, yet the impact of visitor behaviors on perceived restorativeness (PR) remains underexplored. This study investigates how different spatio-temporal behaviors influence PR in IGS, providing urban planners with actionable insights to optimize these spaces for better user experiences. Using a visitor-employed photography (VEP) survey and post-visit PR assessments, K-means clustering was applied to identify distinct visitor behavior patterns. Correlation analysis further explored the relationships between these patterns and PR; the results reveal three unique clusters of visitor behaviors—fast, extensive exploration; moderate, focused exploration; and slow, thorough exploration—each showing distinct impacts on PR. Visitors who engage in rapid, broad exploration perceive larger, navigable spaces as more restorative, while those focusing on specific or in-depth exploration emphasize psychological aspects like escape and fascination. These behavioral patterns demonstrate varying strengths in their association with restorative experiences; This study underscores the importance of integrating spatio-temporal behavior data with PR assessments, highlighting how the physical and psychological features of IGS influence visitor experiences. These findings offer critical insights for designing and managing IGS to accommodate diverse user needs and promote urban well-being.

1. Introduction

High-density urban areas are facing numerous challenges due to urbanization, such as environmental pollution [1,2], the urban heat island effect [3,4], and a growing disconnection between people and nature [5]. A substantial body of research highlights that exposure to natural environments provides significant physical and mental health benefits for urban residents, including stress reduction, attention restoration, positive emotional states, and disease prevention [6,7,8]. However, as urban density rises, per capita green space is decreasing, reducing access to nature in cities [9,10]. In this context, informal green spaces (IGSs) have garnered increased attention as potential solutions.
IGS refers to urban green spaces that are not formally planned and are characterized by spontaneous vegetation and irregular maintenance [11]. Introduced by Rupprecht and Byrne, examples of IGSs include vacant lots, brownfields, and the edges of streets or railroads [12]. Unlike formal green spaces, which are intentionally planned and maintained, IGSs tend to emerge in neglected urban areas, exhibiting a disorganized and heterogeneous appearance [11,13]. This natural disorganization, however, is exactly what grants IGSs unique ecological and social functions, supporting biodiversity and offering unstructured recreational opportunities [14,15,16]. Furthermore, IGSs enhance ecological resilience in urban development by providing essential green infrastructure services, such as regulating temperature, pollution control, and disaster mitigation [17,18]
Research on IGS varies in focus across different regions globally. In Europe, especially in Poland, several studies have shown that IGSs contribute significantly to the well-being of urban residents and ecosystem services [18,19]. In addition, Sikorska et al. state that IGS has the potential to reduce inequitable distribution of urban green space availability [15]. In Asian countries, particularly Japan and China, research on IGS has focused more on residents’ perceptions. In Japan, studies often use questionnaires to investigate residents’ views, usage patterns, and management preferences regarding IGS [20,21]. In contrast, Chinese researchers, such as Chen et al., have employed machine learning techniques to accurately measure and analyze residents’ complaints about IGS on social media platforms [13]. Rupprecht et al. conducted two cross-cultural studies exploring residents’ perceptions of IGS in Australia and Japan, finding that the functional role of IGS in the lives of respondents from both countries was quite similar [14,22]. However, how the respondents used and evaluated IGS was closely tied to their personal environmental preferences.
Urban residents hold mixed attitudes toward IGS. Some residents prefer the less manicured, more natural appearance of IGSs compared to formal green spaces and already use IGSs for activities such as children’s play, dog walking, and barbecuing [23]. Meanwhile, the unofficial and unmanaged nature of IGS raises safety concerns for others, limiting the full realization of its potential [23,24]. The lack of formal protection for IGS further limits its potential as a valuable urban resource [25].
In densely populated urban environments where formal green spaces are limited, IGS can provide substantial social and environmental benefits, but its potential has not yet been fully realized [20]. To unlock the potential of IGS in high-density urban areas, it is crucial to better understand the specific contributions that IGS can make to human well-being [21]. Although most existing studies have focused on the spatial distribution [25,26], resident attitudes [13,14,27], and ecological functions like biodiversity and climate regulation [11,19,28], limited attention has been paid to its potential restorative effects on mental health. Herman et al., for instance, examined the emotional well-being of 20 participants using a portable electroencephalography device during their visits to IGS but found no significant difference in emotional states compared to visits to formal green space [17].
To further investigate the mental health benefits of IGS, this study introduces Perceived Restorativeness as a key indicator for measuring the psychological benefits provided by urban green spaces [29,30]. According to Kaplan et al.’s Attention Restoration Theory (ART), perceived restorativeness refers to the extent of psychological recovery that an individual experiences in a given environment, typically linked to reduced mental fatigue, restored attention, and improved mood states [31,32]. Numerous studies have demonstrated that individuals perceive higher levels of restorativeness in natural environments compared to urban settings [33,34,35,36,37]. Despite the potential for IGS to provide higher levels of perceived restorativeness due to its natural features, there is still a lack of empirical evidence to support this assumption [38]. Most existing studies on restorative effects have focused on traditional green spaces (e.g., parks and gardens), often employing methods such as on-site questionnaires, photographs, or video assessments [39,40]. However, these methods have limitations when applied to IGS, as they are typically not designated by management authorities or owners for public use, and their disorganized and uncertain nature makes them less visible to the public [25,41]. Many people have little direct experience with IGSs, and relying solely on these methods may fail to accurately capture their restorative potential or could underestimate their contribution to psychological well-being [21]. Considering this, this study aims to fill this research gap by validating the perceived restorative function of IGS through surveys of participants’ experiences following their on-site visits, while considering the specific characteristics of IGS environments.
One distinctive feature of IGS is the absence of designated pathways, meaning that individuals’ choices regarding route selection and the duration of their visit can significantly influence their green space experience, potentially leading to varying levels of psychological restoration [42,43]. Spatio-temporal behavioral patterns—referring to the trajectories and time-related dynamics of individuals’ movements across space—capture how people navigate environments and interact with different areas [44]. GPS-based tracking systems provide an effective tool to capture such movement patterns, shedding light on how individuals explore and experience IGS over time [45,46]. This study introduces GPS-based spatio-temporal data to link movement patterns with perceived restorativeness, providing a dynamic approach to understanding the utilization of IGS.
Spatio-temporal analysis has been widely used in various fields to better understand movement patterns, space exploration behaviors, and visitor flows [46], to analyze public space use [47], and to monitor urban mobility [48,49]. In particular, spatio-temporal clustering techniques have been proven effective in identifying tourist characteristics and understanding how visitors use different spaces. For example, Liu et al. [50] utilized open GPS trajectory data in mountainous scenic areas to identify microscopic movement patterns, revealing key insights for managing tourist flows and resource allocation. Brian et al. [51] applied spatio-temporal analysis of GPS trajectory data to cluster and compare travel groups in a national park, helping optimize resource allocation and management strategies by identifying the time visitors spent in different areas. Research methods that employ GPS trajectory data to analyze visitor behavior within destinations have become relatively advanced [52]. By treating IGSs, which are less restricted spaces, as small-scale destinations and combining spatio-temporal behavioral data with perceived restorativeness assessments, it is possible to provide a more precise and dynamic analytical perspective. This approach allows for a more nuanced understanding of how different route selection in IGS environments influence visitors’ restorative experiences, providing valuable insights into how these informal spaces can be better integrated into urban planning to enhance human well-being. Ultimately, this study will propose specific planning and management strategies for IGS based on the analysis results, aiming to better realize their potential as a valuable resource for enhancing the well-being of urban residents.
Although previous research has examined IGS across various urban contexts, there remains limited understanding of how visitor behaviors specifically influence their perception of restorativeness. This study seeks to bridge that gap by employing GPS-based spatio-temporal analysis in conjunction with psychological assessments of restorativeness, offering new insights into how different routes and behaviors within IGS impact mental well-being. The study aims to address the following key research questions:
(1)
What are the spatio-temporal behavioral patterns of visitors within IGS?
(2)
How do these behavioral patterns influence visitors’ perceived restorative effects?
(3)
How can the findings from these patterns inform the planning and management of IGS to optimize their use and enhance restorative experiences?
Through this research, we aim to provide a scientific basis for the integration of IGS into urban planning, offering new insights and practical recommendations for the allocation of limited natural resources in high-density urban areas.

2. Materials and Methods

2.1. Study Sites

Suzhou, located in the Yangtze River Delta region, is a significant central city known for its rapid economic growth and urbanization. By the end of 2023, the city had a permanent resident population of approximately 12.96 million, ranking first in Jiangsu Province in both population size and Gross Domestic Product (GDP). Suzhou Industrial Park (SIP), a leading industrial development zone within the city, is characterized by its significant industrial agglomeration and robust economic growth (Figure 1a). The informal green spaces (IGSs) within SIP have developed in response to rapid urban expansion, offering unique opportunities to examine the dynamics of urban green space formation and utilization due to their distinct locations and flexible usage patterns.
In identifying potential study sites, we applied specific criteria based on the work of Sikorski et al. [15], the Code for the Design of Public Parks [53], and the findings of Jiang et al. [54]. The criteria included a substantial area size, a green space ratio of at least 65%, vegetation coverage exceeding 30% [11], and unrestricted public access. Based on these parameters, four potential IGS sites were identified (Figure 1b). Following a comprehensive evaluation involving on-site surveys, assessments of site longevity, and preliminary experimental data, a site adjacent to Dushu Lake was selected as the sample site. The site covers approximately 11.4 hectares, with 85.18% consisting of a mix of trees, shrubs, and grasses. It features multiple access points and open areas conducive to visitor exploration (Figure 1c).
Data collection was conducted on clear, windless days, including visitor behavior observation through hired photographers and a structured questionnaire survey. According to historical imagery, the site has existed for approximately 15 years and is classified as a Type I residential area [55].

2.2. Research Protocol

A total of 89 students majoring in landscape architecture and related fields participated in this study, including 75 undergraduates and 14 Master’s students, with a gender ratio of approximately 1:1.5 (male to female). Participants were instructed to explore an informal green space (IGS) site and record their paths using a mobile app, followed by completing a questionnaire. The trajectory data were collected using the “Six Feet (version 4.202.23)” app, which recorded participants’ GPS coordinates and timestamps in real time, as well as their routes and travel distances. The questionnaire gathered information on spatio-temporal behaviors, socio-demographic characteristics, usage of park and informal green spaces, and perceived environmental restorative qualities of the site. Given their academic background in environmental studies, participants were expected to provide informed and reliable feedback. Each participant was compensated with RMB 60 for their involvement.

2.2.1. Visitor-Employed Photography (VEP)

The visitor-employed photography (VEP) survey was conducted on two clear, windless mornings, 13 and 14 April 2024, from 9:00 to 12:00, with average temperatures of 20 °C and 21 °C, respectively, to avoid weather-related variability and ensure consistent conditions. Based on the methodology and guidelines suggested by Liang et al. [56] and Fefer et al. [57], we ultimately recruited 89 volunteers to participate in the VEP survey, ensuring a diverse sample size to capture a range of visitor behaviors.
Since the IGS lacked designated entry points, two fixed entrances along a secondary road were established to ensure participant safety and manage participant flow (Figure 2). To minimize entry bias, considering the positive correlation between physical fatigue and travel distance, and to ensure sufficient data collection while avoiding redundancy [58], multiple entrances at different locations were used as starting points for the VEP survey. Specifically, on 13 April, groups 1, 2, and 3 entered from Entrance 1, while on April 14, groups 4, 5, and 6 entered from Entrance 2, following the methodology of Jurisic et al. [59].
Participants used the “Six Feet” app, which they were required to download before the survey. After confirming the use of the AMAP, participants entered the site at staggered intervals of 3 min to avoid interactions. They were free to explore according to their preferences and could take photos (“footprints”) with descriptions during their visit. The app automatically recorded their routes, GPS coordinates, and time spent, and participants uploaded these data upon completion for subsequent analysis.

2.2.2. Perceived Restorativeness Scale (PRS)

Following the site visit, participants immediately completed a questionnaire assessing the perceived environmental restorative qualities of the IGS. The questionnaire consisted of four sections: (1) demographic information (gender, age, educational background); (2) experience with parks and informal green spaces (frequency of visits, activity duration); (3) evaluation of perceived restorativeness scale (PRS) of IGS across 13 items [31,32], rated on a seven-point Likert scale (1 = not at all; 7 = totally) (Table 1 presents 13 items of PRS); and (4) willingness to revisit the site.
Table 2 and Table 3 provide the results of the reliability and validity analyses. To assess the internal consistency of the variables, Cronbach’s alpha was calculated, yielding a value of 0.83. This exceeds the acceptable threshold of 0.7, indicating strong reliability and consistency within the scale. In terms of validity, factor analysis was performed using the Kaiser–Meyer–Olkin (KMO) Measure and Bartlett’s Test of Sphericity via SPSS software v22.0 to examine the inter-item correlations. The KMO statistic was 0.88, within the desirable range of 0.8–0.9, signifying an adequate level of shared variance among the variables. Moreover, the Bartlett’s Test result was significant at p < 0.05, confirming that the original variables are correlated, thereby affirming the structural validity of the questionnaire.

2.3. Data Analysis

The data analysis consisted of two main parts: (1) analysis of spatio-temporal behaviors based on participants’ movement trajectories within the informal green space (IGS), focusing on metrics such as visit duration, path length, area of coverage, and clustering characteristics; and (2) examination of differences in perceived environmental restorativeness across participant clusters derived from the trajectory data.

2.3.1. Spatio-Temporal Path Analysis

The spatio-temporal paths of participants were visualized using GPS data from the “Six Feet” app by ArcGIS 10.8. Following the methodology of Huang et al. [49], four core indicators were identified to represent participants’ spatio-temporal behavior: trajectory duration, path length, coverage area, and coverage perimeter:
  • Trajectory duration represents the total time a visitor spent in the study area, calculated as the difference between the start and end times of the GPS-recorded trajectory;
  • Path length denotes the total distance traveled by each visitor, calculated as the sum of the distances between consecutive GPS coordinates;
  • Coverage area refers to the projected area of a visitor’s trajectory on the XY coordinate plane. The standard deviation ellipse was employed to encompass all trajectory points. Trajectory coverage maps were generated in ArcGIS based on the set of points for each trajectory;
  • Coverage perimeter is the perimeter of the ellipse that covers all trajectory points, serving as an indicator of the spatial characteristics of the visitor movement patterns.
Clustering analysis was applied using four key indicators to classify participants’ movement patterns within the IGS. Clustering is a widely used technique in spatial analysis and can be broadly categorized into partition-based, hierarchical, density-based, graph-based, and model-based methods. Among these, K-means clustering, a partition-based method, was chosen for this study due to its suitability for handling spatial data with overlapping clusters. K-means divides the dataset into K clusters by minimizing intra-cluster distances while maximizing inter-cluster distances. This method is particularly advantageous for detecting clusters that are not clearly separated, even when there is some overlap between them.
In contrast to density-based methods such as DBSCAN (Density-Based Spatial Clustering of Applications with Noise), which can merge overlapping clusters and are highly sensitive to parameter selection, K-means is more effective for identifying distinct movement patterns. Thus, K-means offers an optimal balance between computational efficiency and the ability to distinguish nuanced movement behaviors within the IGS environment.
The GIS clustering module was implemented using Python 3.9 with the Anaconda platform (version 4.0.15). The clustering algorithm was configured in Python to follow two criteria: (1) areas of high density, where cluster centers are surrounded by lower-density neighbors, and (2) large distances between dense data points to ensure clear separation between clusters. This approach allowed for effective categorization of participants’ spatial behavior, facilitating a deeper understanding of their movement within the IGS.
To confirm the clustering results, we used a one-way analysis of variance (ANOVA) to determine the statistical significance of the clusters.

2.3.2. Cluster Difference Analysis

When the ANOVA results were significant at the p < 0.05 level, we conducted an analysis of the differences in questionnaire responses among the different clusters. We used descriptive statistics and comparative analyses to look at variations in demographic characteristics, experiences with green spaces, and willingness to revisit. Additionally, we conducted Pearson correlation analyses to explore the relationships between participants’ perceived environmental restorativeness and their behavioral patterns within each identified cluster.

3. Results and Analysis

3.1. General Statistic

Table 4 summarizes the spatio-temporal trajectory indicators of 89 participants, including trajectory duration, path length, coverage area, and coverage perimeter. The data show that trajectory duration and path length are right-skewed, indicating a few visitors spent significantly more time and covered longer distances. Conversely, coverage area is left-skewed, with most visitors covering larger areas. The mean and median values for coverage perimeter are closely aligned, suggesting a more balanced distribution. The standard deviations indicate greater variability in trajectory duration and coverage area, reflecting diverse exploration behaviors among visitors.

3.2. Clusters Analysis

To understand the diversity in visitor behaviors, K-means clustering was applied based on four trajectory indicators: trajectory duration, path length, coverage area, and coverage perimeter. This clustering process resulted in three distinct clusters after several iterations. The validity of the clustering results was verified using analysis of variance (ANOVA), with all four indicators showing p-values less than 0.001, confirming the statistical significance and reliability of the clusters (Table 5).

3.2.1. Cluster 1 Analysis

Cluster 1, comprising nearly half of the sample, exhibited the widest coverage area (69,297.54 m2) and the largest perimeter (1023.41 m), while also having the shortest total browsing time (2153.15 s) and a moderate path length (1224.76 m). Figure 3 shows the trajectory maps for this cluster, revealing a pattern of fast, broad exploration, where participants moved quickly through the IGS with minimal stops or prolonged engagement in specific areas. The expansive paths suggest that visitors in this cluster prioritized covering as much ground as possible, focusing more on the overall environment rather than particular features. This behavior indicates a preference for rapid and extensive exploration, with limited in-depth interaction with the surroundings.

3.2.2. Cluster 2 Analysis

Cluster 2 exhibited a moderate browsing time (2589.78 s) but had the shortest path length (22,578.09 m2) and smallest coverage area (22,578.09 m2) and perimeter (675.83 m). Figure 4 illustrates the trajectory maps for this cluster, revealing that the paths are concentrated in specific sections of the IGS, particularly around key landscape features such as water bodies and shaded areas. These visitors appeared to focus on specific areas of interest rather than covering vast distances, indicating a targeted exploration approach where visitors concentrate on select features of the site rather than engaging in extensive exploration.

3.2.3. Cluster 3 Analysis

Cluster 3 exhibited the longest total browsing time (6913.00 s) and the longest path length (2293.55 m), with a substantial coverage area (67,374.82 m2) and perimeter (1008.76 m). Figure 5 shows the trajectory maps for this cluster, revealing a comprehensive exploration pattern where visitors traversed a wide range of the IGS, taking time to engage with various areas. These results suggest a more deliberate, in-depth exploration style, with visitors taking their time to experience a broad range of features within the IGS. This cluster reflects a comprehensive engagement with the space, likely providing a more immersive environmental experience.
The clustering results highlight three distinct visitor behavior patterns: Cluster 1 reflects fast, extensive exploration across a wide area; Cluster 2 represents moderate, focused exploration of specific regions; and Cluster 3 indicates slow, thorough exploration of a substantial portion of the IGS. These patterns provide valuable insights into how different visitor types interact with green spaces, which can inform future management and design strategies to cater to varied preferences and behaviors. Differences in spatio-temporal behavior also align with variations in perceived restorativeness across clusters.

3.3. Analysis of Cluster Differences

3.3.1. Green Space Usage and Overall Impressions Across Clusters

We compared the green space usage habits and willingness to revisit across the clusters (Table 6). Significant differences were found in green space usage habits and willingness to revisit across clusters. Participants in Cluster 1 demonstrated a balanced approach regarding both the frequency of visits and willingness to revisit, showing moderate familiarity with informal green spaces. In contrast, Cluster 2 respondents visited formal parks more frequently but had relatively lower familiarity with informal green spaces. Meanwhile, Cluster 3 respondents had a higher frequency of visits to informal green spaces but were more uncertain about their willingness to revisit. These differences highlight the need for tailored informal green space management strategies to cater to the unique preferences of different user groups.

3.3.2. Perceived Restorativeness Scale (PRS) Scores Across Clusters

Correlation analysis was conducted to examine the relationships between trajectory indicators (CI1–CI4: trajectory duration, path length, coverage area, and coverage perimeter) and perceived restorativeness variables (Table 1, 3.1–3.13) across clusters. Key correlations for each cluster are summarized below, highlighting differences in perceived restorativeness among respondents.
Table 7 highlights key differences in perceived restorativeness across the three clusters. Cluster 1 generally scored the highest in the “being away” subscale (3.1–3.5), particularly on items 3.4 (Mean = 5.47) and 3.5 (Mean = 5.43), indicating a stronger sense of escape from daily routines. This aligns with the “being away” component of ART, which refers to psychological distance from everyday demands. Visitors in this cluster, who explored larger coverage areas and had longer perimeters, seemed to achieve a greater sense of escape, likely facilitated by the opportunity to navigate wide, open spaces. Cluster 2 showed moderate scores overall, with lower ratings in fascination-related items like 3.6 (Mean = 4.17), but it matched Cluster 1 in item 3.9 (Mean = 5.04), indicating a similar perception of exploration opportunities. Cluster 3, despite the longest engagement time, scored lower in “being away” (3.3, Mean = 4.21), but had similar fascination scores to Cluster 1 (3.7, Mean = 4.79). It also scored higher on item 3.13 (Mean = 3.74), suggesting more mixed perceptions of the space’s appeal.
Figure 6, Figure 7 and Figure 8 present the correlation analysis of the variables for the indicators across three clusters. For Cluster 1, significant correlations were observed between trajectory indicators and perceived restorativeness variables. CI3 (coverage area) and CI4 (coverage perimeter) showed a strong positive correlation (r = 0.97), indicating that larger coverage areas tend to have longer perimeters. Among the PR variables, a strong positive correlation was found between items 3.6 and 3.2 (r = 0.60), suggesting that areas perceived as more engaging are also seen as more restorative. In contrast, negative correlations were observed between perceived boredom (3.11) and fascination-related items (3.12, r = −0.51; 3.13, r = −0.83), reflecting differing perceptions of the space’s restorativeness.
In Cluster 2, significant positive correlations were noted between CI2 (path length) and CI4 (coverage perimeter) (r = 0.72), indicating that longer paths correspond to larger coverage perimeters. Positive correlations between PR items 3.4 and 3.1 (r = 0.83) suggest that respondents in Cluster 2 associate restorativeness more strongly with feelings of escape. Negative correlations between perceived boredom (3.11) and restorativeness items like 3.12 (r = −0.66) further highlight contrasting views on the restorativeness of these spaces.
Cluster 3 demonstrated strong correlations between trajectory indicators CI3 (coverage area) and CI4 (coverage perimeter) (r = 0.98), consistent with findings in Cluster 1. Positive correlations were observed between PR items 3.6 and 3.8 (r = 0.71) (r = 0.71), suggesting a strong association between fascination and the desire for exploration. However, there were more varied correlations in Cluster 3, such as negative associations between some trajectory indicators and restorativeness items, indicating diverse perceptions of restorativeness within this cluster. This variability implies that while some visitors found the space fascinating and conducive to exploration, others may have perceived it as overstimulating or less compatible with their personal needs for restoration.
In summary, the correlation analysis highlights distinct psychological implications for each cluster based on their movement patterns and alignment with ART. Cluster 1 visitors benefit most from environments offering extent and fascination, while Cluster 2 visitors achieve restorativeness primarily through compatibility and psychological escape. Cluster 3 visitors experience mixed outcomes, with some benefiting from fascination, but others finding the environment less conducive to mental restoration. These insights suggest that tailoring the design and management of informal green spaces (IGSs) to meet these varied psychological needs could enhance their restorative potential for a broader range of users.

4. Discussion

This study investigates how visitors’ spatio-temporal behaviors in informal green spaces (IGSs) influence their perceived environmental restorativeness. By integrating data from a Visitor-Employed Photography (VEP) survey and post-visit perceived restorativeness assessments, we identified distinct variations in visitor behaviors, explored how these patterns relate to perceived restorativeness, and proposed strategies to enhance the design and management of IGS for maximizing their restorative potential. The discussion is structured into three sections: differences in spatio-temporal behaviors among clusters, the relationship between these behaviors and perceived restorativeness, and strategic recommendations for IGS optimization.

4.1. Differences in Spatio-Temporal Behaviors Among Clusters

We identified three distinct clusters of visitor behaviors, each exhibiting unique spatio-temporal patterns. The application of Visitor-Employed Photography (VEP) proved to be particularly valuable in capturing spatio-temporal behaviors in IGSs, which are typically less structured and less familiar than traditional parks. VEP provides a means of documenting participants’ subjective experiences, allowing for a deeper understanding of how specific landscape elements influence movement and engagement in informal green spaces. This method complements quantitative measures by offering a more nuanced perspective on visitor interactions with IGS.
Cluster 1 visitors demonstrated rapid, broad spatial exploration, covering large areas in a short time with the widest coverage area and perimeter, but the shortest total browsing time. This suggests a preference for open, navigable environments that encourage fast-paced exploration and provide a sense of freedom. These behaviors align with previous research indicating that expansive green spaces facilitate broader spatial movement and are perceived as more restorative due to their capacity to offer escape and fascination [12,31]. Furthermore, similar findings by Chang et al. [60] suggest that open and visually accessible spaces enhance feelings of safety and comfort, which may further encourage dynamic movement and exploration.
In contrast, Cluster 2 visitors displayed more focused, targeted exploration, with the shortest path length, smallest coverage area, and smallest perimeter, but moderate browsing time. This indicates a preference for specific landscape features within the IGS rather than general exploration, reflecting a more concentrated engagement with particular aspects of the environment. Visitors in this cluster are likely drawn to unique landscape elements or secluded spots that provide a sense of mental escape and stress relief. This pattern is consistent with Anderson and Minor [28], who emphasize the importance of distinctive environmental features in attracting and retaining visitor interest. Moreover, research by Fisher et al. [61] also suggests that specific landscape elements like water features enhance perceived restorativeness by promoting tranquility and escape from urban life.
Cluster 3 visitors engaged in slow, thorough exploration with the longest browsing time and path length, combined with a large coverage area and perimeter. This behavior suggests a more comprehensive engagement with the environment, where visitors take time to explore various facets of the space. Such visitors may seek diverse and rich environments that offer various stimuli, aligning with Sikorska et al. [15], who underscore the need for varied and immersive environments that promote prolonged engagement in green spaces. These findings contrast with studies that report quicker, less immersive interactions in similar settings [29], suggesting that certain landscape features may support deeper visitor engagement.

4.2. Relationship Between Behavior Patterns and Perceived Restorativeness

The correlation analysis between trajectory indicators and perceived restorativeness variables provides deeper insights into how spatio-temporal behaviors influence perceived restorativeness in IGSs. In Cluster 1, the strong positive correlation between coverage area (CI3) and coverage perimeter (CI4) suggests that larger, navigable spaces are associated with higher perceived restorativeness. Visitors in this cluster perceive environments that support extensive movement and exploration as more restorative. This finding is consistent with Kaplan’s Attention Restoration Theory [31], which argues that environments offering fascination and the experience of being away enhance psychological restoration. Negative correlations between perceived boredom and fascination-related items further highlight contrasting perceptions, indicating that dynamic, stimulating environments are essential for restorativeness. Arnberger et al. [62] emphasize that environments perceived as fascinating are more likely to capture attention and promote mental recovery.
These results underscore the importance of spatial diversity within IGS in promoting restorativeness, especially for Cluster 1 visitors who prioritize movement and exploration. To cater to these users, urban planners should focus on maintaining larger, navigable areas with meandering paths and diverse vegetation to encourage dynamic engagement with the environment. This strategy is consistent with research highlighting the role of environmental diversity in enhancing user satisfaction [28].
In Cluster 2, significant correlations between path length and perceived psychological restorativeness—such as feelings of escape and relief from routine—suggest that for these visitors, the restorative experience is less dependent on the physical attributes of the space and more about the psychological benefits provided by specific interactions with features. Incorporating elements that promote mental escape, such as quiet zones or reflective spots, may be more effective for this group. These findings align with studies emphasizing the importance of secluded, contemplative spaces in enhancing psychological well-being [5,30]. Unlike research focusing on general green space use [13], the results here highlight the importance of strategically designed elements to maximize perceived restorativeness.
For visitors in Cluster 2, who prioritize psychological escape, urban planners should incorporate secluded zones and quiet areas to provide mental relief. Placing benches near water features or small, sheltered areas for quiet reflection could offer opportunities for solitude and contemplation, similar to strategies implemented in London’s urban parks, where the inclusion of quiet areas enhances the restorative experience. Minimal interventions, such as directional signage, can help guide visitors without detracting from the informal, unstructured character of IGS.
Cluster 3 reveals a complex relationship between behavior patterns and perceived restorativeness, with strong associations between fascination and exploration but also some negative correlations between trajectory indicators and PR items. This indicates that visitors in this cluster have diverse expectations and preferences regarding restorativeness, with some favoring varied and stimulating environments and others preferring more straightforward, navigable spaces. These mixed results suggest that providing a balanced mix of features catering to different restorative needs can maximize the perceived benefits of IGS. This aligns with the findings by Anderson et al. [29], who found that a diverse range of green space attributes can cater to varied user preferences, enhancing overall satisfaction and perceived well-being.
To accommodate the varied preferences of visitors in Cluster 3, urban planners should design multi-functional spaces that allow for both active exploration and peaceful reflection. Walking trails that traverse varied landscapes and provide opportunities to pause for rest or reflection can effectively cater to this diversity, ensuring that the space meets a broader range of user needs.

4.3. Implications for Planning and Management of IGS

The findings of this study provide several strategic recommendations for urban planners and landscape architects, offering practical examples of how cities can integrate the insights from spatio-temporal behavior patterns to better design and manage IGS for diverse user needs.
First, cities should prioritize preserving spatial diversity within IGS, particularly when making updates or interventions [30,32]. Spatial diversity, including variations in terrain, vegetation, and open spaces, is essential for promoting exploration and enhancing the restorative qualities of IGS, especially for individuals who exhibit preferences for movement and discovery, as observed in Cluster 1. Rather than extensive modifications, an internal signage system could be implemented to highlight key features, such as wetland areas, main bird species, or different types of vegetation cover. For instance, the urban green space Amager Fælled in Copenhagen serves as an exemplary model by maintaining diverse vegetation and meandering paths that offer a range of natural landscapes, allowing visitors to engage with the environment freely. This approach effectively balances open space and natural diversity, thereby fostering an environment conducive to both dynamic exploration and psychological restoration.
Second, improving accessibility and navigability is crucial for those who value extensive exploration, with clear pathways and open spaces that encourage fluid movement throughout the IGS. Clear pathways and open spaces that facilitate fluid movement throughout IGS are important, but minimal management interventions—such as directional signage or limited vegetation control—can help maintain the informal nature of these spaces. Previous studies suggest that adding guiding signs along nearby roads can direct visitors to IGS [19,24]. Additionally, safety signs in wetland areas can enhance safety while maintaining the informal nature of the space. Cities such as London, where natural spaces like Hampstead Heath employ unobtrusive signage and minimal management, offer useful examples of how to balance navigability with maintaining the inherent wildness of the space. Similarly, safety signage in areas prone to hazards, such as wetlands, can enhance safety while preserving the informal nature of the environment. This supports findings from previous studies emphasizing the need for well-structured pathways to facilitate user engagement [24].
Third, incorporating restorative elements such as diverse vegetation, water features, and sheltered nooks can appeal to visitors seeking psychological escape and relaxation. The High Line in New York serves as an illustrative example of how strategic use of diverse vegetation and seating nooks can create restorative pockets within a densely urbanized area. For example, research by Fischer et al. [63] suggests that to enhance the landscape effects of IGS and provide a food source for wildlife, methods such as broadcasting flowers and grass seeds could be considered to help improve the ecological stability of IGS.
Finally, promoting awareness and inclusivity through community engagement and targeted programs is essential to increasing the familiarity and positive perception of IGS among all visitor groups. Public education initiatives aimed at highlighting the environmental and mental health benefits of IGSs, alongside community-led maintenance or stewardship programs, can strengthen the connection between residents and these spaces. This supports findings from Feltynowski et al. [41], which emphasize the role of community ties in the utilization and appreciation of green spaces.

5. Conclusions

This study highlights the importance of integrating spatio-temporal behavior data with perceived restorativeness assessments to enhance the understanding of the restorative potential of informal green spaces. The findings demonstrate that both physical attributes (such as coverage area and path length) and psychological experiences (such as feelings of escape and fascination) play crucial roles in shaping visitor experiences and their perceptions of restorativeness. Our findings reveal that visitors’ engagement with IGS—characterized by varied spatial coverage, path length, and duration—significantly affects their perception of restorativeness through distinct behavioral patterns. These patterns operate through different dimensions of environmental experience, such as psychological escape, fascination, and exploration, offering critical insights for urban planners and landscape architects aiming to design IGSs that accommodate diverse user needs and enhance urban well-being.
From a planning and management perspective, the findings suggest that enhancing the spatial diversity, accessibility, and ecological features of IGSs can significantly improve their utilization and restorative potential. Preserving spatial diversity while adding minimal interventions, such as signage or clear pathways, could maintain the informal nature of these spaces while making them more navigable and appealing to a wider audience. Incorporating restorative elements like diverse vegetation, water features, and quiet spaces for relaxation could further enhance the psychological benefits of IGSs. Additionally, promoting public awareness and community involvement is essential for increasing engagement with these spaces. Targeted programs and community education can help improve the positive perception of IGSs, supporting their integration into urban environments as valuable resources for well-being.
Moreover, this study supports prior research on public attitudes toward IGSs, showing that while some individuals appreciate the unstructured nature of these spaces, others may have reservations about their safety or accessibility. This underlines the need for careful planning and management strategies to optimize IGS usage while maintaining their unique character. In particular, Visitor-Employed Photography (VEP) proved valuable in capturing authentic and reflective evaluations of IGSs, providing participants with the opportunity to engage with and assess these spaces in a more personal manner. This approach, while useful, also highlights potential biases, as it relies on subjective participant perspectives.
However, VEP, while effective in offering personal insights into participants’ experiences, also introduces potential subjective biases. Participants may focus on elements that align with their preferences or prior beliefs, leading to selective representation of the IGS environment. These subjective perceptions may not fully reflect the broader user experience, which could influence the findings related to restorativeness. Future research could mitigate this bias by incorporating more objective measures, such as physiological data (e.g., heart rate or EEG) or additional mixed methods to balance personal impressions with more quantitative assessments.
Additionally, the sample primarily consisted of students within a narrow age range, which limits the generalizability of the findings. Future studies should expand to include a broader demographic, encompassing various ages, occupations, and cultural backgrounds, to capture a more comprehensive spectrum of perceptions and behaviors. In addition, the influence of seasonal and temporal variations on IGS usage remains underexplored; understanding these patterns could be pivotal in optimizing green space design for year-round engagement and restorative benefits. Future longitudinal studies could investigate how IGSs are utilized year-round, capturing the temporal changes and seasonal fluctuations that may affect their restorative potential. Understanding these patterns will be pivotal in optimizing green space design for year-round engagement and psychological benefits. Investigating these aspects further will refine strategies and provide more nuanced guidelines for maximizing the restorative potential of IGS in diverse urban contexts. Building on this, cross-cultural studies can help explore how different populations in diverse urban environments engage with IGS, adding a comparative dimension to the research. This could reveal cultural differences in the perception of restorativeness, as well as how environmental factors like vegetation, pathways, or facilities are valued across regions. Long-term monitoring of IGSs could also capture how perceptions of restorativeness evolve over time, particularly in the context of urban development and ecological changes.
In summary, this study provides a basis for future research to optimize IGS design and management strategies that integrate visitor behavior patterns and restorativeness perceptions, aiming to enhance user engagement and maximize restorative experiences in urban environments.

Author Contributions

Conceptualization, J.J. and H.W.; methodology, J.J. and S.C.; software, J.J. and S.C.; validation, J.J. and S.C.; formal analysis, J.J. and S.C.; investigation, J.J., R.M., S.C. and Z.Z.; resources, J.J. and H.X.; data curation, S.C.; writing—original draft preparation, J.J., R.M. and S.C.; writing—review and editing, J.J., R.M., H.X. and H.W.; visualization, S.C.; supervision, J.J.; project administration, J.J. and H.X.; funding acquisition, J.J. and H.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (32301646), MOE (Ministry of Education in China) Project of Humanities and Social Sciences (23YJCZH089), and Soochow University—the Suzhou Yuanke(su-sy) Collaborative Innovation Center of Architecture and Urban Environment (SY2022003).

Data Availability Statement

The data presented in this study are available on request from the corresponding authors due to privacy.

Acknowledgments

The authors acknowledge all the participants and administrators in this study.

Conflicts of Interest

Author Hong Xu was employed by the company Suzhou Yuanke Ecological Construction Group. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Study site: (a) Suzhou City, Jiangsu Province, China; (b) Four potential IGS sites; (c) The sample site.
Figure 1. Study site: (a) Suzhou City, Jiangsu Province, China; (b) Four potential IGS sites; (c) The sample site.
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Figure 2. IGS Site and Entrances.
Figure 2. IGS Site and Entrances.
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Figure 3. Trajectory maps for Cluster 1.
Figure 3. Trajectory maps for Cluster 1.
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Figure 4. Trajectory maps for Cluster 2.
Figure 4. Trajectory maps for Cluster 2.
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Figure 5. Trajectory maps for Cluster 3.
Figure 5. Trajectory maps for Cluster 3.
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Figure 6. A correlation analysis of the variables for the indicators in Cluster 1.
Figure 6. A correlation analysis of the variables for the indicators in Cluster 1.
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Figure 7. A correlation analysis of the variables for the indicators in Cluster 2.
Figure 7. A correlation analysis of the variables for the indicators in Cluster 2.
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Figure 8. A correlation analysis of the variables for the indicators in Cluster 3.
Figure 8. A correlation analysis of the variables for the indicators in Cluster 3.
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Table 1. Perceived Restorativeness Scale (PRS) [30,31].
Table 1. Perceived Restorativeness Scale (PRS) [30,31].
Subscale MembershipItems
Being away3.1 Being here is an escape experience.
3.2 Spending time here gives me a break from my day-to-day routine.
3.3 It is a place to get away from it all.
3.4 Being here helps me to relax my focus on getting things done.
3.5 Coming here helps me to get relief from unwanted demands on my attention.
Fascination3.6 This place has fascinating qualities.
3.7 My attention is drawn to many interesting things.
Extent3.8 I want to get to know this place better.
3.9 There is much to explore and discover here.
3.10 I want to spend more time looking at the surroundings.
Compatibility3.11 This place is boring.
3.12 The setting is fascinating.
3.13 There is nothing worth looking at here.
Table 2. Reliability analysis of Perceived Restorativeness Scale (PRS).
Table 2. Reliability analysis of Perceived Restorativeness Scale (PRS).
Cronbach’s AlphaN of Items
0.8313
Table 3. Validity analysis of Perceived Restorativeness Scale (PRS).
Table 3. Validity analysis of Perceived Restorativeness Scale (PRS).
Kaiser–Meyer–Olkin Measure (KMO) and Bartlett’s Test
KMO Measure of Sampling Adequacy0.88
Bartlett’s Test of SphericityApprox. Chi-Square758.58
df78
Sig.0
Table 4. General statistical analysis of spatio-temporal trajectory indicators.
Table 4. General statistical analysis of spatio-temporal trajectory indicators.
Title MinimumMaximumMeanMedianStd.
Trajectory duration (s)0.0010,732.003282.142294.002202.55
Path length (m)505.024008.381402.221259.86566.20
Coverage area (m2)10,545.9986,040.4656,813.5066,135.8422,696.50
Coverage perimeter (m)455.541126.15930.461008.00169.84
Table 5. ANOVA results based on differences in respondents’ spatio-temporal trajectories.
Table 5. ANOVA results based on differences in respondents’ spatio-temporal trajectories.
IndicatorCluster 1Cluster 2Cluster 3Test Score
Trajectory duration2153.152589.786913.00F = 125.25, p < 0.001 *** 1
Path length1224.761028.532293.55F = 97.29, p < 0.001 ***
Coverage area69,297.5422,578.0967,374.82F = 165.73, p < 0.001 ***
Coverage perimeter1023.41675.831008.76F = 156.46, p < 0.001 ***
1 *** p < 0.001.
Table 6. Summary of green space usage and willingness to revisit by cluster.
Table 6. Summary of green space usage and willingness to revisit by cluster.
CategoriesVariablesCluster 1Cluster 2Cluster 3Total
Frequency of visiting parksAlmost never5 (10.64%)0 (0.00%)5 (26.32%)10 (11.24%)
A few times a month23 (48.94%)18 (78.26%)12 (63.16%)53 (59.55%)
Once a week11 (23.40%)2 (8.70%)1 (5.26%)14 (15.73%)
More than 2–3 times a week8 (17.02%)3 (13.04%)1 (5.26%)12 (13.48%)
Daily0 (0.00%)0 (0.00%)0(0.00%)0 (0.00%)
Average time spent per park visit<15 min8 (17.02%)2 (8.70%)2 (10.53%)12 (13.48%)
15–30 min24 (51.06%)9 (39.13%)9 (47.37%)42 (47.19%)
30–60 min11 (23.41%)10 (43.47%)7 (36.84%)28 (31.46%)
>60 min4 (8.51%)2 (8.70%)1 (5.26%)7 (7.87%)
Familiarity with informal green spaces in citiesNot very familiar19 (40.43%)10 (43.47%)9 (47.37%)38 (42.70%)
Fairly familiar27 (57.44%)13 (56.53%)10 (52.63%)50 (56.18%)
Very familiar1 (2.13%)0 (0.00%)0 (0.00%)1 (1.12%)
Frequency of visiting IGSAlmost never19 (40.42%)9 (39.13%)4 (21.05%)32 (35.95%)
A few times a month18 (38.30%)6 (26.09%)14 (73.69%)38 (42.70%)
Once a week5 (10.64%)4 (17.39%)0 (0.00%)9 (10.11%)
More than 2–3 times a week5 (10.64%)4 (17.39%)1 (5.26%)10 (11.24%)
Daily0 (0.00%)0 (0.00%)0 (0.00%)0 (0.00%)
Average time spent per visit to IGS<15 min23 (48.94%)10 (43.47%)7 (36.84%)40 (44.94%)
15–30 min17 (36.17%)12 (52.18%)11 (57.90%)40 (44.94%)
30–60 min6 (12.76%)1 (4.35%)1 (5.26%)8 (9.00%)
>60 min1 (2.13%)0 (0.00%)0 (0.00%)1 (1.12%)
Willingness to revisitStrongly unwilling0 (0.00%)0 (0.00%)0 (0.00%)0 (0.00%)
Unwilling5 (10.64%)3 (13.04%)1 (5.26%)9 (10.11%)
Somewhat unwilling5 (10.64%)7 (30.44%)8 (42.11%)20 (22.47%)
Neutral13 (27.66%)3 (13.04%)1 (5.26%)17 (19.10%)
Somewhat willing14 (29.79%)6 (26.09%)6 (31.58%)26 (29.21%)
Willing6 (12.76%)4 (17.39%)3 (15.79%)13 (14.61%)
Strongly willing4 (8.51%)0 (0.00%)0 (0.00%)4 (4.50%)
Table 7. General statistical results of the three clusters.
Table 7. General statistical results of the three clusters.
ItemsCluster 1Cluster 2Cluster 3
MeanStd.MeanStd.MeanStd.
3.14.981.234.781.384.680.86
3.25.341.404.871.394.891.25
3.34.911.354.221.504.211.20
3.45.471.224.831.525.000.73
3.55.431.255.171.135.110.85
3.64.681.374.171.374.580.94
3.74.911.384.481.534.791.00
3.84.721.364.301.464.371.22
3.95.041.355.041.234.791.15
3.104.891.484.571.104.681.30
3.113.601.363.481.314.111.29
3.124.381.454.261.154.421.27
3.133.281.423.481.103.741.33
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Jiang, J.; Xu, H.; Ma, R.; Chen, S.; Wang, H.; Zheng, Z. What Is the Perceived Environmental Restorative Potential of Informal Green Spaces? An Empirical Study Based on Visitor-Employed Photography. Land 2024, 13, 1768. https://doi.org/10.3390/land13111768

AMA Style

Jiang J, Xu H, Ma R, Chen S, Wang H, Zheng Z. What Is the Perceived Environmental Restorative Potential of Informal Green Spaces? An Empirical Study Based on Visitor-Employed Photography. Land. 2024; 13(11):1768. https://doi.org/10.3390/land13111768

Chicago/Turabian Style

Jiang, Jiayi, Hong Xu, Ruochen Ma, Shi Chen, Huixin Wang, and Ziang Zheng. 2024. "What Is the Perceived Environmental Restorative Potential of Informal Green Spaces? An Empirical Study Based on Visitor-Employed Photography" Land 13, no. 11: 1768. https://doi.org/10.3390/land13111768

APA Style

Jiang, J., Xu, H., Ma, R., Chen, S., Wang, H., & Zheng, Z. (2024). What Is the Perceived Environmental Restorative Potential of Informal Green Spaces? An Empirical Study Based on Visitor-Employed Photography. Land, 13(11), 1768. https://doi.org/10.3390/land13111768

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