Research on Environmental Behavior of Urban Parks in the North of China during Cold Weather—Nankai Park as a Case Study

Abstract

The aging of the population is not only a global challenge, but it is also a major concern in the research on environmental behaviors. Urban green spaces are regarded as crucial for the well-being of the elderly. However, there is still a lack of in-depth investigation into the effect of spatial factors on the public activities performed by the elderly in urban parks in cold weather. Therefore, this study is aimed at filling this gap, with Nankai Park in Tianjin as the research object. In order to achieve this purpose, the behavioral patterns of elderly park users are mapped in this paper, based on participatory observation in combination with the collection of spatial data through continuous photography. To begin with, the park space is divided into 23 areas for correlation analysis. UCL Depthmap software is then used for park space syntax analysis, with Tangent used to evaluate the sunshine (shadow) factors. Specific indexes are established to quantify the spatial factors in each area, such as the shortest distance to the exit, the green space ratio, and facility density. GIS (Geographic Information System) is applied for data integration, and SPSS is applied to reveal the correlation between the behavioral data and the selected spatial factors. The key findings are as follows. (1) There are four space syntax indexes closely correlated with the activities that the elderly participate in. (2) The solar (overshadowing) conditions play an important role in the distribution of elderly park users. (3) There is no definitive relationship exhibited by the pattern of activities performed by the elderly with various factors such as number and diversity of seating facilities as well as the quantity and diversity of seating facilities. Finally, this analysis aims to explore research methodology that extends from qualitative observation to quantitative analysis. Future research will focus on the shaping of aging-friendly urban communities, which is expected to deepen our understanding of public activities held within urban parks in cold weather across the northern cities of China.

1. Introduction

As predicted by the World Health Organization (WHO), one-sixth of the world population will be aged over sixty by 2030 [1]. This demographic shift toward an aging population is not only a universal challenge but also a topic of societal interest [2,3,4] as “the elderly population group is increasing more than the other age groups, and at a faster rate in developing countries” [5,6]. In the relevant research, aging covers the population aged 60 or over [7]. However, the elderly as discussed in this paper belong to a wider category because some people retire, deteriorate in body functions, or help bring up their grandchildren before 60. The universal trend of the aging population is laid bare in initiatives such as the UN’s Decade of Healthy Ageing, which marks a collective effort invested to address the impact of this demographic trend. Increasingly, the challenge posed by the aging population has become the focal point of research on environmental behaviors and community studies [8,9,10]. For example, Liu et al. (2023) explored the demand of elderly pedestrians through Street View Imagery (SVI), and “proposed a novel index to assess pedestrian demand and walking environment based on the ratio of the number of pedestrians and the residential population” [11]. Zheng, Chen, and Guo (2021) analyzed the complex interrelationship between residential environments and quality of life among the elderly in various age groups. In addition, they evaluated the mediating role of individual behaviors (such as neighborhood interaction and outdoor exercise) in this relationship between the environment and health [12]. It is highlighted in an increasing number of studies that urban public space is crucial for the elderly in various aspects, such as spatial quality and vitality. Altuğ Turan and Malkoç True (2023), for instance, evaluated and highlighted the heightened importance of public spaces for the elderly aged over 65 in the post-pandemic era [13]. Similarly, Liu et al. (2023) explored the relationship between environmental quality, vitality, functionality, and the mental health of the elderly in public spaces [14]. In the study of S. Wang, Yung, and Sun (2022), accessibility and spatial quality were evaluated as the influencing factors in the extent to which public spaces are utilized by the elderly population in Hong Kong. It was demonstrated that the quality of open space was more important than accessibility for the visit of the elderly to public spaces, especially in a high-density city like Hong Kong [15]. In addition to the research on urban public space for the elderly, the neighborhood is also regarded as a critical scale for aging studies, providing a favorable setting for elderly residents to participate in activities [16]. In some contexts, this dynamic is closely associated with the public spaces located within or near these neighborhoods [17]. The growing interest in this field is reflected by the evident upward trend in research focusing on the elderly spatial behavior in neighborhoods.

Regarded as a significant contributor to public health [18], urban green spaces, to a large extent, are utilized by the elderly [6]. However, there are variations in the pattern of usage, which depends on the type of green space (e.g., playgrounds or active recreation spaces are utilized by different age groups) and its location in the urban landscape (e.g., young families vs neighborhoods with a large number of retirees). Li et al. (2023) discovered several influencing factors in the level of physical activities performed by the elderly in these spaces, such as nature (or greenery), safety, road (or path) conditions, and the aesthetics of the public space [19]. In the study of Julfikar Ali et al. (2022), the importance of urban parks was further emphasized by highlighting their positive role in “the improved physical health, mood and attention” of the elderly. Also, they argued for promoting the participation rate among the elderly through improved accessibility [20]. Zhai et al. (2021) applied GPS trackers and Actigraph accelerometers to assess the relationship between the behavior of the elderly and park facilities [21]. In some other studies, an investigation was conducted into the health benefits of green space [22], the perceived physical and mental well-being benefits of urban green space [23], the equitable access to these spaces [24], and the inequalities in their availability across different communities [25]. Moreover, a connection was established by Enssle and Kabisch (2020) between park visitation, social networks, and the well-being of the elderly [26].

In addition to recognizing the health benefits created by urban green spaces for the elderly, research has also highlighted temperature as a key influencing factor in their use of public spaces. Wang et al. (2023) discovered a correlation present between the intensity, content of activities, spatial satisfaction, thermal experience, and thermal adaptation behavior and the outdoor thermal perception of the elderly [27]. As indicated by Huang et al. (2022), the shaded open spaces in Hong Kong are more appealing for activities performed by the elderly due to the cooler microclimate created by them [28]. By evaluating the Outdoor thermal comfort (OTC) in the cold areas of China, An et al. (2021) discovered that “the elderly were well adapted to the environment by selecting a lower air temperature (Ta) in winter” [29]. Differently, Ma et al. (2021) analyzed the thermal perceptions of the elderly in an urban park in Xi’an, China, revealing that “elderly respondents with respiratory diseases showed a higher NPET” [30]. In this context, NPET is the neutral Physiological Equivalent Temperature, an indicator used to evaluate the level of thermal comfort. With complex meteorological conditions converted into a simple and understandable temperature value, it is comparable to the temperature experienced by people in their daily lives. Despite the above research results, it remains necessary to further explore how spatial factors shape the public lives of the elderly in colder climates. In some studies, PALM, MITRAS, and ENVI-met were applied to simulate the microclimate in urban space. Anders et al. (2023) evaluated how microclimate and outdoor thermal comfort are affected by the sustainable urban development adapted to climate change in Stuttgart, Germany. Through the advanced meteorological modeling system PALM-4U, they simulated the microclimate and outdoor thermal comfort of the Neckarpark development project during heat waves [31]. Maronga et al. (2020) mainly described the latest progress and applications of PALM model system 6.0 (Parallel Large-eddy Simulation Model) and found that it has been widely applied in various research fields, especially in urban environments [32]. Han et al. (2018) adopted the parallel large-eddy simulation (LES) model PALM to explore the exchange of reactive pollutants (NO, NO₂, and O₃) at the top of street canyons. It was revealed that the exchange of reactive pollutants is affected to a significant extent by the small-scale eddies on the roof layer and the high (or low)-speed stripes above the canyon [33]. Focusing on the effect of wind induced by buildings on rainfall distribution, Ferner et al. (2022) applied the MITRAS model to evaluate the heterogeneity of rainfall in urban neighborhoods. They analyzed the impact of these factors on rainfall patterns by simulating different meteorological conditions, wind speeds, rainfall amounts, wind directions, and domain configurations [34]. Salim et al. (2018) provided a detailed introduction to the theoretical basis and model dynamics of the micro-scale obstacle analysis meteorological model MITRAS v2.0, summarized the model theory of MITRAS v2.0, and mentioned future model expansion plans [35]. To evaluate the impact of neighborhood redesign on air temperature (Tair) cooling capacity, Crank et al. (2023) investigated the impact of redesigning a community in Phoenix on microclimate, through on-site measurement data (including the mobile micro-meteorological measurement vehicle MaRTy) and ENVI-met micro-scale modeling [36]. However, there is a lack of attention paid to the activities performed by the elderly in urban micro-green spaces during winter.

In Western countries such as the United Kingdom (UK), there are a variety of seasonal activities initiated by governments in public squares, such as those celebrating the Lantern Festival, Christmas markets, or Valentine’s Day festivities designed to attract a broad range of visitors. The picture is completely different in China, where many similar activities are launched spontaneously in public spaces such as urban parks. This contrast highlights the significant influence exerted by spatial factors on the activities performed by the elderly in Chinese urban parks. By evaluating the relationship between thermal sensation and comfort levels in Chinese urban parks situated in colder climates, Xu et al. (2018) identified the Universal Thermal Climate Index as suitable for analyzing the level of outdoor human thermal comfort in Xi’an [37]. However, there is still little research that focuses specifically on analyzing which spatial factors influence the activities of the elderly in colder weather across public spaces in China. This leads to the research question about how (and what) spatial factors influence the activities of the elderly in cold weather in the context of public life in Chinese cities.

This paper aims to close this gap by focusing on Nankai Park, located in Tianjin, which is a metropolitan city in the north of China. Given its central location and function as a vibrant neighborhood hub for urban activities, this park is considered particularly suitable for a case study. With spatial complexity, the park consistently attracts a considerable number of elderly people, which provides an ideal context for the study of the correlation between public activities and spatial factors. With a brief introduction to Nankai Park as the starting point, this paper elaborates on the methodology of research. Then, the research results, as obtained from spatial factors analysis and the co-relation analysis between the activities and the spatial factors, are presented. Furthermore, these results are discussed and extended to broader themes globally.

2. A Brief Description of the Nankai Park

Located north of Xi Shi Street, a major thoroughfare in Tianjin’s Nankai District, the Nankai Park covers an area that is roughly 250 m × 190 m (Figure 1). This park is adjacent to Nankai Middle School on the east, and at its southeast corner is a vibrant urban intersection. A tall office building stretches from the road south of the park, and residential buildings are located in the west of the park. There is an old residential neighborhood extending northward from the park (isolated with a wall). At its main entrance in the south is a prominent square (60 m × 55 m), and in the north of the square is a community center building. Nankai Park consists of multiple areas suitable for a variety of smaller activities, including sports fields (around 9 m × 9 m), a dance area (around 9 m × 20 m), and other flexible-use spaces. With a circular plane that is approximately 30 m in radius, the hill within this park provides a scenic backdrop behind the community center building. Enclosing the park, a dedicated walking trail allows the elderly to exercise. There are four exits in total throughout the park, one to the south, two to the east, and one to the west. These diverse spatial elements create a sense of both openness and more secluded areas in Nankai Park. Given this blend of characteristics, Nankai Park is considered an ideal site for exploring how the elderly use urban parks. It is representative of other similar parks built in the cities located in the northern cities of China.

3. Research Methodology

This research was conducted for seven days from 20 to 27 January 2024, with 20 January known as a bitterly cold day in the Chinese traditional calendar (大寒日: Major Cold Day, which means the coldest period of the year) (Figure 2). Accordingly, the data covered a seven-day period. The local temperatures recorded during the study fluctuated between −9 and 5 degrees Celsius. For this research, daily participatory observation was conducted from 7 a.m. to 5 p.m., according to the study of Gehl and Svarre (2013) and Low (2018) on participatory observation in public spaces [38,39]. By blending into park activities as regular visitors, researchers minimized the disruption to the elderly population under study when observing their behaviors. As far as this paper is concerned, the elderly population is defined as males aged over 60 and females aged over 55. The number of elderly visitors utilizing the walking trail and participating in activities across various park areas was meticulously recorded, while the locations and types of activity were documented on a park map (at approximately hourly intervals). Various visual cues such as appearance, activity posture, and attire were used to determine whether an individual complied with the criteria set for the elderly classification. Additionally, the movements of some elderly visitors who wandered beyond the designated walking trail were traced. Based on the observation of activity patterns, the park space was divided into 23 distinct areas (Figure 3) for the subsequent spatial behavior correlation analysis based on a certain sample size (n = 23).

The spatial factors of the park were explored, including space syntax, the distribution of sunlight (and shadow), and various spatial attributes like facility density and the characteristics of green spaces. To evaluate the spatial syntax from both visual and axial perspectives, Depthmap software was applied to analyze a range of metrics such as Choice (选择度), Integration (整合度), and Connectivity (连接度). As proposed by Bill Hillier (2007), space syntax refers to “a cluster of approaches to the analysis of spatial relations–mainly gamma, isovist and axial analyses” [40]. Pafka et al. (2018, p. 511) further explained these concepts as follows:

“While gamma analysis involves a focus on topological relations between cells, and isovist analysis involves fields of visibility, axial analysis extends this idea of lines of sight to calculate the minimum number of straight axes necessary to navigate the network of public spaces” [41].

Space syntax “focuses on the properties of the space and the relationships between space and movement rather than the morphology of spaces” [42,43]. At present, it is widely recognized as an effective tool of analysis for complex urban spatial relationships [44]. Depthmap refers to “an open-source and multi-platform spatial analysis software for spatial networks of different scales” [45]. According to on-site observations, the shadow factor (of the buildings around the park) affects the distribution of activities that elderly park visitors prefer. For a better understanding of this, sunshine conditions were thoroughly analyzed using Tangent (Tangent is a product based on the AutoCAD platform for architecture, structure, plumbing, HVAC, electrical, energy conservation, sunlight, daylighting, etc., and it is a CAD plug-in) at hourly intervals from 8 a.m. to 4 p.m.

A number of additional spatial factors were analyzed in accordance with the standards mentioned in Section 4.2.3. As a sort of travel map software, Baidu Map (online version, https://map.baidu.com/) was used to determine the distance between entrances and exits. After a comprehensive study of different activities and spatial factors, the collected data were input into ArcGIS 10.2. ArcGIS is a comprehensive geospatial platform. Then, SPSS was applied to conduct an in-depth analysis of the correlation between activities (conducted throughout the day from 8 a.m. to 5 p.m.) and spatial factors, including space syntax and other relevant elements (such as the shortest distance in meters to the park’s main entrance and exit and green space ratio) (Figure 3). Currently, SPSS (Statistical Product Service Solutions) is a type of software widely used for data analysis. It is particularly suitable for statistical analysis in the context of social science research. As an important function in SPSS, correlation analysis is usually conducted to investigate the relationship between two or more variables. The relationship between each X (elderly visitors’ activities) and each Y (spatial factors) was analyzed specifically. Through the statistical tools of Spearman and Pearson correlations, it was established whether there is any significant relationship present between the X and Y variables. With the correlations identified, the nature of these correlations was evaluated, and it was determined whether they were positive or negative. Furthermore, the magnitude of the correlation coefficients was calculated to gain insights into the strength of any observed relationships. Thus, the findings were summarized. Finally, graphic analysis was conducted to reveal the relationship between the activities of the elderly and overshadowing factors (i.e., geometric analysis pertaining to the surrounding buildings).

4. Research Results

4.1. Mapping and Statistics of Activities Performed by the Elderly

The collected data on activities performed by the elderly comprise location and activity type visualized in behavioral maps (Figure 4, Figure 5 and Figure 6). These maps indicate a close connection between the spatial environment in the park and the way in which the elderly engage with it. According to continuous observation, there are three distinct categories of activities: leisure, fitness-oriented pursuits, and social entertainment and recreation (

Table 1. The three types of activities performed by the elderly.

Activity Types	Activity
Leisure	Relaxing, sitting on benches, social contact, standing
Fitness activities	Physical training, equipment exercise, running, playing soccer, playing badminton, martial arts, Tai Chi
Social entertainment and recreation	Group dance, social dance, singing, performance, Peking Opera, playing cards, chess, playing with children

and

Table 2. The examples of activity types and their photos.

Leisure Activities
Relaxing	Sitting on benches	Chatting while standing together
Social Entertainment and Recreational Activities
Group dance	Singing	Peking Opera
Fitness-oriented Activities
Playing badminton	Playing soccer	Running

). Hourly figures (8 a.m. to 5 p.m.) provide more details on the types of activities undertaken, their frequency, and where in the park they tend to take place. A consistent pattern is identified that most activities are performed around the central squares and main building, with spatial distribution found to fluctuate in other park areas throughout the day.

Plenty of the activities performed in the park revolve around physical fitness, which begins with the exercise classes that take place near the main park building at 8 a.m. From 9 a.m. onward, the main square is converted into a hub of social and recreational activities. Meanwhile, at 10 a.m., there are a variety of activities performed near the main building and at the pavilion near the northeast exit. Also, there are groups of elderly visitors found practicing Tai Chi and other forms of exercise in a wooded area to the west and on a small square to the north (approximately 40 m by 13 m), located near the park’s perimeter. By 11 a.m., more elderly individuals visit the park for relaxation and social connection, spreading these activities across the central areas. At noon, despite the departure of some elderly visitors, many of them congregate either to the north of the main square near the community center or along the pavilion corridor near the northeast exit of the park.

At 2 p.m., the elderly start to congregate near the main building’s entrance to play card games. By 3 p.m., more elderly visitors arrive to play chess in the pavilion corridor near the park’s northeast exit. Some unwind in the central square, while others prefer the quietude of the northern hill or amongst the trees to the west. At 5 p.m., many start to depart, despite a few card games that continue.

4.2. Results of Spatial Factors Analysis

4.2.1. The Space Syntax Analysis

Space syntax analysis was carried out to examine a number of critical spatial properties in the park (Figure 7), which are visual connectivity, visual integration, axis choice, the degree of axis integration, and the degree of axis connectivity. Visual Connectivity is defined as the number of visually connected spaces in the system. Figure 7 indicates a higher level of visual connectivity in the south of the park (a relative value of more than 2000) compared to the north (a relative value of around 100). This is likely to result from the presence of a square near the major city intersections in the southeast, and from its openness to the main road to the south of the park. Visual integration is a measure of the extent to which a spatial element is aggregated or segregated from others in the system. It indicates not only the potential of a space to attract foot traffic but also its overall centrality. According to the analysis results, the areas of the park with higher visual integration, as found primarily in the south (a relative value of around 10–11), are more likely to attract pedestrian flow than those in the north (a relative value of around 4–5) due to greater accessibility, higher visibility, and a stronger central position. The degree of axis choice is defined as the frequency of path selection from one location in a space network to all the remaining locations. As shown in the figure, the path in the west of the square (a relative value of more than 1300) is higher than other potential routes around the square in the degree of axis choice, which is likely because it connects the park’s southern exits with the main building in the center of the park conveniently. Such paths are usually preferred by foot traffic, especially the elderly. In addition, the degree of axis integration is higher in the path in the west of the square compared to other spaces, which underscores their important role in the spatial layout of the park.

4.2.2. The Solar (Shadow) Analysis of the Park

Figure 8 shows the effect of solar (shadow) conditions in the park space, as reflected by the research results. For research, it was carefully considered how the activities of elderly park users are influenced by the shadows cast by buildings, both in and surrounding the park. As indicated by the solar (shadow) analysis, the buildings located in the southeast of the park, particularly the educational building of Nankai Middle School, cast significant shade over the square between 8 and 9 a.m. (among which a large portion of areas are below 0.15 h/every hour). From 10 a.m. to 2 p.m., the tall office building (29-story office building) to the south of Nankai Park casts its shadow across the main park square. As the residential buildings in the southwest affect the pattern of shade in the square in the afternoon (especially between 2 p.m. and 4 p.m.), the activities taking place in this central park area are considered to be an effective indicator of the shadow effect.

4.2.3. Other Spatial Factors

In addition to the space syntax and the shadow factor, several additional spatial factors in each area are analyzed in this study. These factors include environmental materials, green space coverage, etc. (Appendix A,

Table A1. The result of the other spatial factors (Source: Authors).

	Shortest Distance to the Main Entrance and Exit	Hard Ground Area Ratio	Number and Diversity of Seating Facilities	Table and Chair Combinations	Quantity and Diversity of Fitness Facilities	Green Space Ratio	Green View Rate
1	47	100	0	0	0	0	92
2	36	100	6	0	0	0	92
3	30	100	8	0	0	0	92
4	47	96	10	0	0	0	92
5	50	97	8	0	0	3	13
6	26	93	8	6	0	7	45
7	47	100	1	1	0	0	46
8	28	100	7	0	0	0	36
9	23	92	8	6	0	8	66
10	39	99	9	2	7	1	71
11	20	100	0	0	1	0	80
12	42	100	10	6	0	20	50
13	68	100	0	0	0	0	50
14	74	100	0	0	0	0	41
15	74	50	5	0	0	50	60
16	56	90	1	0	1	10	50
17	77	5	0	0	0	95	95
18	103	10	1	0	0	90	95
19	170	75	0	0	1	25	45
20	172	100	6	0	0	0	40
21	171	100	6	0	0	0	60
22	68	70	11	0	0	30	90
23	46	35	8	0	0	75	69

). This index aligns with the study of Meng (2022) [46], who analyzed the spatial factors in old urban residential communities. Referencing the visual diagram shown in Figure 9, a point-by-point explanation is made as follows.

• The shortest distance (in meters) to the park’s main entrance and exit was measured with Baidu Map.
• The hard ground area ratio, defined as the proportion of hardscape space available for activities in public spaces, was calculated by analyzing the hard ground materials of the park space on electronic maps and dividing it by the entire plot boundary at the base.
• The quantity and diversity of seating facilities, indicative of the quantity and diversity of seating options in the park, were calculated using the number and type of all forms of seating facilities in park spaces.
• The table and chair combination, referred to as the number of complete table and chair facilities in a public space, was observed and recorded.
• The quantity and diversity of fitness facilities available in the public space were observed and calculated.
• The green space ratio, defined as the proportion of public green space in the site area, was observed and calculated as Green space ratio = Green space area/Total space area (for each area).
• The green view rate, defined as the average proportion of greenery in the total field of view, was observed and calculated by averaging the proportion of greenery to the total field of view in four directions of a public space, with green viewing rate = green viewing rate in all four directions.

4.3. The Correlation Analysis between the Activities and the Spatial Factors

4.3.1. Space Syntax

The present study starts with an analysis of the relations between the activities performed by the elderly and the space syntax factors. Notably, a significant positive correlation (significant at the 0.01 level) is revealed between the number of visitors and the metric of visual connectivity, with the correlation coefficient reaching 0.662. In addition, the number of visitors exhibits a significant positive correlation (0.01 level) with visual integration (coefficient of 0.697), axis connectivity (coefficient of 0.634), and axis integration (coefficient of 0.638) (p < 0.01 means that the correlation is effective). Interestingly, there is no clearly defined relationship present between the activities performed by elderly visitors and the degree of axis choice.

4.3.2. Solar (Shadow) Analysis

According to the solar (shadow) analysis, a significant correlation exists between available solar (shadow) conditions and the activity distributions of the elderly in cold weather. Herein, two specific timestamps are focused on for illustration: midday and afternoon. As shown in Figure 10, there is a distinct division created in the square at 11:58 a.m. due to the expansive shadow cast by high-rise office buildings to the south of the park. One area attracts many elderly visitors for public activities, while the other is attractive to none. Then at 4:02 p.m., the square is bisected in a similar way by the shadow from residential buildings located in the southwest corner outside the park, as visually confirmed by the photo. There are no elderly visitors in the shadowed area, while there is a high concentration of activity in the sunlit section of the square (Figure 11).

4.3.3. Other Spatial Factors

The correlation analysis reveals whether the level of elderly activity in the park is affected by the spatial factors described in Section 4.2.3. According to the statistical results, there is no significant correlation present between the number of visitors and the following variables: the shortest proximity to the park’s main entrance/exit; hard ground area ratio; the number and diversity of seating facilities, tables, and chairs; fitness facilities; green space rate; and green view rate (see Appendix A,

Table A2. Spearman correlation analysis table between other spatial factors and number of visitors.

	Visual Connectivity	Visual Integration	Axis Connectivity	Axis Choice Degree	Axis Integration	Shortest Distance to the Main Entrance and Exit	Hard Ground Area Ratio	Number and Diversity of Seating Facilities	Table and Chair Combination	Quantity and Diversity of Fitness Facilities	Green Space Ratio	Green View Rate
Number of elderly visitors in an area	0.662 **	0.697 **	0.634 **	0.320	0.638 **	−0.361	0.111	0.367	0.178	−0.289	−0.240	0.105

* p < 0.05, ** p < 0.01.

). The correlation coefficient is close to zero for these factors, implying the absence of a direct relationship between the number of visitors and these specific elements. These findings illustrate that despite the attractiveness of these facilities to the elderly during certain periods of the day, there is no consistently discernible influence exerted by them on the overall level of activities throughout winter.

5. Discussion

This paper explores the activities engaged in by the elderly within parks in cold weather. Through both quantitative and qualitative methods, behavioral patterns are observed and the relevant spatial factors are evaluated to reveal the relationship between these elements. According to on-site observation, the park activities engaged in by the elderly are influenced by the degree of randomness and happenstance, but there is a certain level of consistency in the correlation with specific spatial factors.

According to the research results, the way elderly people interact with their surroundings is significantly affected by certain space syntax factors, such as visual connectivity, visual integration, axis connectivity, and axis integration. There is a preference shown by the elderly for environments with greater visual openness and attraction to a steady flow of people. For some, the park as a major draw in social aspects provides opportunities to establish connections with peers, engage in group activities, and socialize in a meaningful way. When visual openness is improved, the supervision of grandchildren is facilitated, which may substantiate the concept that an activity in a public space can lead to further activity. However, there are some elderly individuals who voluntarily engage in fitness activities (such as Taichi) or leisurely pursuits (such as playing cards) in areas with lower visual connectivity, such as the smaller northern square of the park. It is suggested that quieter spaces or more quiet activities are probably preferred by a subset of the elderly (Figure 12).

It is further indicated in this paper that a considerable proportion of the elderly are inclined to engage in entertainment or fitness activities in the central areas of designated areas. Usually, they expect to relax along the periphery of these areas. It is likely that this pattern is affected by the presence of relaxing facilities intended for rest and leisure, such as the benches located at the edges. Furthermore, some of them prefer playing chess alongside the exterior wall of the community center building. Similar to a shelter, this location is likely to create a sense of protection from potential disruptions.

As indicated by the observation, there is a significant correlation present between shadow conditions and the pattern of activities performed by the elderly in the square. Specifically, the elderly show a preference for remaining in sunlit areas during colder weather, which is consistent with the findings of previous research, such as “the long-term high sun exposure is positively related with better cognitive functioning” in the northeast cities of China [47]. However, it appears that the activity level is not significantly affected by other spatial factors such as green space ratio and green vision ratio. This is probably attributable to the winter season and the consequential lack of foliage. Similarly, there is a minimal impact made by the hardness of the ground, likely because the turf, which becomes firm in winter, continues to provide a suitable surface where the elderly can engage in fitness activities, but this is not the important reason why the elderly choose to use this space.

The findings of this paper provide significant insights that can be generalized to a broader context. Firstly, it is indicated that the design and layout of public spaces have a significant impact on the activity levels among elderly individuals in cold weather. The critical influencing factors include spatial factors and sun shadows. These findings are applicable not only to the specific city (Tianjin) studied but also to other areas with similar climatic conditions and spatial environments. By improving spatial structure, it is possible to enhance the activity levels among elderly individuals in cold weather, which promotes their physical health and enhances social interactions.

These findings can be further discussed in a broader socio-environmental context. For instance, deeper insights can be gained into elderly activity levels by understanding how public space characteristics correlate with socio-cultural factors, policy frameworks, community support systems, and urban green space funding management systems. Such contextualization underscores the multifaceted nature of how public spaces influence behavior and well-being.

For urban planners, architects, designers (or other design professionals), and policy makers, these findings provide a practical reference in terms of creating more aging-friendly, comfortable, inclusive, accessible, and resilient public spaces. There could be more active and engaged elderly populations during cold weather if the design strategies are implemented that prioritize spatial structure, architectural shelter, spatial distribution, and accessible resting areas (especially in the shadow area). Aside from improving the individual well-being of the elderly, this approach also reinforces community cohesion and social support networks.

The limitation of this paper lies in the fact that the investigations can be further broadened and contextualized. To better understand the research results, it can be contextualized within a broader social and environmental framework. Also, the activity levels of elderly individuals may be affected by such factors as socio-cultural influences, the physical conditions of the elderly, their social habits, and health. The conditions in the coldest weather can also be compared with those in other temperatures and cities, such as in summer and the southern cities. Valuable insights can be gained into the future practice of urban park planning and design through a comparative study focusing on park usage patterns and activities across different seasons and age groups.

6. Conclusions

This paper focuses on exploring the research methodology extended from qualitative observation to quantitative analysis. Through a combination of long-term observation, mapping, and SPSS statistical analysis, the relationship is evaluated between the activity levels of elderly individuals and the characteristics of public spaces during cold weather. It contributes to improving our understanding of public life in China, particularly that of the elderly. Parks and other types of urban green spaces play an essential role in urban life, as they create opportunities for daily leisure and relaxation. Focusing on the elderly, this paper is expected to promote the integration of the elderly into urban life. It was found that an effective sample size for statistical analysis can be determined by dividing public spaces based on activity intensity and conducting subsequent correlation analysis. Valuable insights are gained into the effect of park spaces on public life during winter in the northern cities of China. Specifically, it reveals the significant impact of topological spatial structure and sun shadows on the activities that elderly people engage in (especially the visual connectivity (coefficient of 0.662), visual integration (coefficient of 0.697), axis connectivity (coefficient of 0.634), and axis integration (coefficient of 0.638)). There is no definitive relationship exhibited by the pattern of activities performed by the elderly with various factors such as the quantity and diversity of seating facilities. It reminds designers to (1) focus on the spatial structure’s features of the park, (2) pay attention to the shadows cast by the buildings around the park, and (3) prioritize the design of small spaces in parks, such as those in front of the architecture within the park areas intended for recreational activities and the cornered areas intended for quiet fitness activities.

In the future, research can be conducted by paying close attention to the spatial factors and the social interaction in winter with ethnographical methods, so as to build an aging-friendly urban community. Additionally, it is crucial to understand the correlation between ambient temperature and the social engagement of the elderly. Through observations, interdependence is revealed between the activities of the elderly and their grandchildren, especially during the afternoon. With age-friendly park design incorporated into the cultivation of inclusivity for all generations, it can be better explored how spatial elements contribute to the interactions between the elderly and children during cold weather. Moreover, digital technologies such as eye tracking can be applied to the study of what spatial facilities may appeal to the elderly in parks.