The Role of Campus Green Space for Residents: Based on Supply–Demand of Recreation Services

Abstract

The campus is an important place for recreational activities among surrounding residents, which can alleviate the shortage of urban public green space (PGS). However, evidence is lacking on how much campus green space is complementary to the supply and demand of PGS. For this purpose, we chose Yangling, a university town in western China, as the study area. We compared perceived accessibility and the coupling coordination degree (CCD) of the supply and demand of PGSs for residents with different purposes before and after the COVID-19 pandemic, when the campuses were closed or reopened. After the campus reopened, the number of blocks that were able to reach their most frequently visited green spaces within 5 min had increased from zero to one (walking) and two to four (by bicycle). The proportion of blocks with a high level of CCD had increased from 28.6% to 42.9%. The reopening of campuses can significantly increase the perceived accessibility of PGSs within 5 min and 15 min by walking and bicycle, respectively, in central urban communities, but it was not significant in suburban communities. It also effectively improved the PGS supply of the block where it is located. For residents who aim to exercise, walk, go sightseeing, and communicate, its role was similar overall. For residents who aim to play with children, the campus green spaces could not bring significant improvements. In order to enhance the complementary role of green space on campus, it is important to improve its accessibility for adjacent blocks, increase inside footpath density, and add child-friendly facilities.

1. Introduction

Urban green space can provide cultural services such as education, cultural heritage, social relations, aesthetics, health, entertainment, and outdoor leisure for urban residents, which is important for human well-being [1,2,3,4]. Although Chinese cities have become greener than before [5], the per-capita park green space area in some small and medium-sized cities in the central and western regions still below the global average [6]. Campus is an important place for leisure and recreational activities for surrounding residents [7], which can alleviate the shortage of urban public spaces and green spaces [8]. During the COVID-19 pandemic, many campuses implemented measures to restrict personnel access in order to stop the spread of the virus. However, it provides us an opportunity to explore the complementary role of campus green spaces in urban green spaces, which has attracted the attention of some scholars [7].

The relationship between the supply and demand of green space has received extensive attention. Some studies were based on residents’ preference of green space or recreational purposes at the community level [9]. They found that individual socio-economic characteristics of residents—such as age, gender and visiting behaviors, etc.—affected their preferences and the sensitivity to the service of urban green spaces [9,10]. The others were based on objective indicators at the regional level, such as population density and accessibility [11,12,13]. They found the spatial imbalance of green space between supply and demand presented different patterns in new and old urban areas. In general, the green space was oversupplied in the new cities [14]. However, their coordinated degree of supply and demand was decreased from center to exurb [14]. In old cities, the supply of green space has been lower than demand overall [11,12]. Additionally, there was insufficient supply and demand in the city center, matching supply and demand in suburbs, and oversupply in the exurbs [11,12]. The spatial match of supply and demand often occurs in areas with a medium population density and high road connectivity, which are located in the centers of new cities and the suburbs of old cities [13,14,15,16]. While much recent research on the supply–demand of urban green space has focused on large cities, only a small portion of it has paid attention to small- and medium-sized cities.

Currently, studies have focused on the complementary role of specific types of green space on supply-demand relationships, including small neighborhood parks [17,18], greenways [19,20], and campuses [7,8,21]. Research has shown that small neighborhood parks and greenway conducive to improving the equity and accessibility of green space in high-density or old built-up areas, and they also play a complementary role in providing daily recreational services [10,17,18,19,20,21]. Some studies found that the green space supply on university campuses exceeded the students’ demand [22]. In addition, the opening campus green space was conveniently accessible to the surrounding residents and had the potential to meet the daily recreation demands of residents [8]. Areas with insufficient public green space can also benefit from the presence of campus green space [21]. Although these studies have revealed the role of specific types of green spaces, it is difficult to clearly quantify the contribution of them to the supply and demand relationship of urban PGS.

Some studies focus on urban residents and explore the accessibility and fairness of surrounding urban infrastructure to residents in gated communities. They found that the isolation of community space can cause differentiation of accessibility opportunities and inequality of accessibility public infrastructures [23,24,25]. This kind of community space isolation will lead to a segregation effect on daily activity space and the use of public spaces, especially for green spaces [26,27]. From a functional and spatial perspective, a university campus that is managed in a closed manner is both a gated community and a gated green space. Previous studies have mostly focused on residents within closed communities to explore the fairness of public spaces outside the community to different gated communities, but few have considered the potential contributions of gated campus green spaces to urban residents after they are opened. During the COVID-19 pandemic, many universities have closed their campuses to outside visitors in order to flatten their epidemic curves. This reduced the total supplements of green space for residents and increased the burden of urban parks [7]. This also creates an opportunity to quantify the contribution of campus green space.

However, the role of campus green spaces in public green space system is still not clear, especially for its supply and demand relationships. In response to this issue, the aim of this research was to explore changes in the perceived accessibility and the supply–demand relationship of green spaces under the conditions of whether campus green spaces were included in the public green space system or not during a COVID-19 lockdown. This study takes the built-up areas of Yangling, a university town in western China, as the study area. Though the coupling coordination degree (CCD), we compared the supply and demand of public green spaces (PGSs) for residents with different purposes through questionnaires and spatial analysis before and after the epidemic ended, considering whether the campuses were close to being public or reopened. This knowledge could help to identify the contribution of campus green space for city dwellers with different purposes and provide a planning basis for balancing the supply and demand of green space in similar university towns.

2. Materials and Methods

2.1. Study Area and Spatial Data

2.1.1. Study Area

This article selects the central urban area of Yangling (107°59′–108°08′ E, 34°14′–34°20′ N) as the research area based on the Yangling Urban and Rural Master Plan Revision (2017–2035) [28]. The central urban area of Yangling is located in the hinterlands of the Guanzhong Plain and has a total area of 61.31 km², accounting for approximately 46.23% of the total urban area of Yangling District. Based on the road network, the study area was divided into 14 blocks of similar size (Block A–Block N, Figure 1).

2.1.2. Spatial Data

Spatial data used in the study included district boundaries, road networks, and green space boundaries (

Table 1. Source of spatial data.

Data	Type	Source
District boundary	Vector polygon	Yangling Urban and Rural Master Plan Revision (2017–2035)
Road network	Vector line	OpenStreetMap (https://www.openstreetmap.org/, accessed on 27 May 2024)
Green space boundary	Vector polygon	Vectorized from Baidu Map (https://map.baidu.com, accessed on 27 May 2024)

).

2.2. The Perceived Accessibility of PGSs

Perceived accessibility is defined as the perceived potential to participate in spatially dispersed opportunities [29]. It reflects the expected usage behavior of residents towards green spaces [30,31]. In this study, we used perceived accessibility of PGSs to reflect the potential contribution of urban residents after the opening campus green spaces in subjective dimension.

Based on the residential green space satisfaction survey (Supplementary File S2), we identify the nearest-located and most frequented green spaces of each respondent before and after the campuses opening. Then, we calculated their average travel time to these green spaces, including walking mode (80 m/min, [32]) and bicycle mode (320 m/min, [32].

2.3. The Supply and Demand Subsystem of PGSs

When the campus restricted access during the pandemic, residents could not engage in daily recreational activities on the campus. As a result, the green space supply subsystem can be divided into the PGS supply subsystem and the campus green space supply subsystem (Figure 2). For instance, the PGS supply subsystem only includes parks which are accessible to residents when the campus is closed. On the other hand, the subsystem for campus green space supply includes parks and green spaces available to residents when there is no epidemic.

2.3.1. Indicators of the Supply and Demand Subsystem of PGSs

The green space supply subsystem consists of eight indicators. These include the number, range, shape, and types of green spaces; the facilities inside; their attractiveness; the coverage rate of green space services; and the overlap rate of green space services (Table 2).

The green space demand subsystem had five indicators, including population density, population structure, urbanization rate, residents’ satisfaction with PGS, and residents’ satisfaction with green space within the residential area (Table 3).

Table 2. The indicator of the green space supply subsystem.

Indicator	Effect Direction	Weight	Description
Green space number	+	17.32%	Number of the green space
Green space area	+	11.96%	Area of the green space
Green space shape	+	5.86%	The green space shape was quantified using the Landscape Shape Index:
			${LSI}_x={\displaystyle \frac{E}{2\sqrt{\pi A}}}$	(1)
			where LSIx denotes the shape index of green space x. E is the perimeter of the green space x; and A is the area of the green space x. The larger the LSIx is, the more complex is the shape of the green space x.
Green space facilities	+	10.83%	Green space facilities rank according to the Park Design Specification (GB51192-2016 [33]) in different types and sizes of parks (Supplementary File S1). According to this criterion, the better the facility, the higher the score.
Green space type	+	15.98%	This indicator was based on the Urban Green Space Classification Standard (CJJ/T85-2017 [34]) and evaluated the function from comprehensive to simple. Comprehensive Park: 5, Theme Park: 4, Community Park: 3, Campus Green Space: 2, Neighborhood Park: 1.
Green space attractiveness	+	13.51%	Based on the number of residents active in the PGS according to the PGS satisfaction survey (Supplementary File S3).
Green space service coverage rate (Gx)	+	18.63%	$G_x={\displaystyle \frac{{\sum }_{i=1}^n{S}_{dc}}{S_d}}\times 100\%$	(2)
			where Gx denotes the green space service coverage rate of block x. Sdc denotes the area within block x that is covered by the 15 min walking circles of PGS i. Sd denotes the area of block x; and n denotes the number of blocks of block x that are covered by PGSs.
Green space service overlap rate (Rx)	-	5.91%	$R_x={\displaystyle \frac{S_r}{S_d}}\times 100\%$	(3)
			where Rx denotes the green space service overlap rate of block x. Sr denotes the area of the overlap within block x that is covered by the service radius of each PGS. and Sd denotes the area of block x.

Table 2. The indicator of the green space supply subsystem.

Indicator	Effect Direction	Weight	Description
Green space number	+	17.32%	Number of the green space
Green space area	+	11.96%	Area of the green space
Green space shape	+	5.86%	The green space shape was quantified using the Landscape Shape Index:
			${LSI}_x={\displaystyle \frac{E}{2\sqrt{\pi A}}}$	(1)
			where LSIx denotes the shape index of green space x. E is the perimeter of the green space x; and A is the area of the green space x. The larger the LSIx is, the more complex is the shape of the green space x.
Green space facilities	+	10.83%	Green space facilities rank according to the Park Design Specification (GB51192-2016 [33]) in different types and sizes of parks (Supplementary File S1). According to this criterion, the better the facility, the higher the score.
Green space type	+	15.98%	This indicator was based on the Urban Green Space Classification Standard (CJJ/T85-2017 [34]) and evaluated the function from comprehensive to simple. Comprehensive Park: 5, Theme Park: 4, Community Park: 3, Campus Green Space: 2, Neighborhood Park: 1.
Green space attractiveness	+	13.51%	Based on the number of residents active in the PGS according to the PGS satisfaction survey (Supplementary File S3).
Green space service coverage rate (Gx)	+	18.63%	$G_x={\displaystyle \frac{{\sum }_{i=1}^n{S}_{dc}}{S_d}}\times 100\%$	(2)
			where Gx denotes the green space service coverage rate of block x. Sdc denotes the area within block x that is covered by the 15 min walking circles of PGS i. Sd denotes the area of block x; and n denotes the number of blocks of block x that are covered by PGSs.
Green space service overlap rate (Rx)	-	5.91%	$R_x={\displaystyle \frac{S_r}{S_d}}\times 100\%$	(3)
			where Rx denotes the green space service overlap rate of block x. Sr denotes the area of the overlap within block x that is covered by the service radius of each PGS. and Sd denotes the area of block x.

Table 3. The indicator of the green space demand subsystem.

Indicator	Effect Direction	Weight	Description
Population density	+	31.21%	Usual residents/area (person/km2) [35,36]
Population structure	+	19.46%	Proportion of elder population (elder than 65) and young population (younger than 14) in a region as a percentage of the total population of the region
Urbanization rate	+	17.01%	Population of urban residents/population of total residents [35]
Residential green spaces	-	18.48%	Residents’ subjective evaluation of green space in residential areas. The higher the score, the lower the demand for green space outside the residential area [37].
Green space facilities (resident evaluation)	+	13.84%	Based on residents’ scoring of PGSs in the residential green space satisfaction survey (Supplementary File S2)

Table 3. The indicator of the green space demand subsystem.

Indicator	Effect Direction	Weight	Description
Population density	+	31.21%	Usual residents/area (person/km2) [35,36]
Population structure	+	19.46%	Proportion of elder population (elder than 65) and young population (younger than 14) in a region as a percentage of the total population of the region
Urbanization rate	+	17.01%	Population of urban residents/population of total residents [35]
Residential green spaces	-	18.48%	Residents’ subjective evaluation of green space in residential areas. The higher the score, the lower the demand for green space outside the residential area [37].
Green space facilities (resident evaluation)	+	13.84%	Based on residents’ scoring of PGSs in the residential green space satisfaction survey (Supplementary File S2)

Based on the scores provided by six urban and rural planning experts on the importance of each indicator (Supplementary File S4), an AHP analysis was conducted to obtain the weights of six green space supply and demand subsystem indicators. The results passed the consistency test. The final weight of each indicator was calculated by averaging the weights from the six urban planning scholars of NWAFU (Table 2 and Table 3).

2.3.2. Questionnaire Survey

In order to obtain satisfaction with PGS’s recreation services and satisfaction with residential green spaces’ recreation services, two questionnaire surveys were conducted respectively in parks and residential areas. Both of them were finished offline from March to April 2023.

Both of the two questionnaires included respondents’ habits of using PGSs and the demographic characteristics of the respondents.

The main body of content of the two questionnaires was different. The residential green space satisfaction survey (Supplementary File S2) was about respondents’ evaluation of residential green spaces near where they were living. It considered infrastructure, landscape, and recreation. The PGS satisfaction survey (Supplementary File S3) was about respondents’ evaluation of the PGS that they were visiting at that time. The content was the same as that of the former.

2.4. Building the Coupling Coordination Degree (CCD) Model

In this study, we used the coupling coordination degree model to supply and demand relationships of PGS recreation services in the study area.

2.4.1. Data Standardization

Due to the different units of the indicators in the subsystems, the data were processed using the method of standardization of polarities for subsequent calculations and comparisons.

$$A_{i^{+}}={\displaystyle \frac{a_i-a_{min}}{a_{max}-a_{min}}}$$

(4)

$$A_{i^{-}}={\displaystyle \frac{a_{max}-a_i}{a_{max}-a_{min}}}$$

(5)

where A_i denotes the standardized value of the indicator and A_i ∈ [0, 1]; a_i is the value of indicator i in the subsystem; a_max and a_min respectively represent the maximum and minimum values of indicator i within the research range [38].

2.4.2. Model Building

Comprehensive evaluation index:

$$f\left(x\right)=W_1{A}_1+W_2{A}_2+\cdots +W_i{A}_i+\cdots W_n{A}_n$$

(6)

where f(x) is the comprehension evaluation index of the subsystem, indicating the degree of contribution of the subsystem to the supply and demand of the overall system; W_i is the weight of the indicator; A_i represents the standardized value of the indicator; and n is the number of indicators of the subsystem.

$$C=2\times {\left\{{\displaystyle \frac{f_1\left(x\right)\times f_2\left(x\right)}{{\left[f_1\left(x\right)+f_2\left(x\right)\right]}^2}}\right\}}^{{\displaystyle \frac{1}{2}}}$$

(7)

where C is the coupling degree of the subsystem and C ∈ [0, 1]; f_s(x) and f_d(x) are the comprehensive evaluation index of the green space supply subsystem and the green space demand subsystem, respectively [39,40,41].

$$T=\alpha f_s\left(x\right)+{\beta f}_d\left(x\right)$$

(8)

$$D=\sqrt{C\times T}$$

(9)

where T is the comprehensive coordination index of the subsystem, which indicates the overall synergy effect or contribution of the supply and demand subsystem, and T ∈ [0, 1]; α and β are the weights of the supply and demand subsystem because the supply of green space is equally important as the demand of residents, and α + β = 1, so α and β are 0.5; D represents the CCD of the system, and D ∈ [0, 1] [42,43,44].

2.4.3. Identification of the Type of Coordination

By using CCD and the comparisons of green space supply and demand, we classified the blocks into six coordination types (

Table 4. Types of coordination.

Coupling Coordination Degree	Type of Coordination *
	Abs(x) > σ		Abs(x) < σ
	fs(x) > fd(x)	fs(x) < fd(x)
0.40 ≤ CCD < 1.00	Demand lower than supply	Supply lower than demand	High coordination and matched PGSs supply and demand
0.00 ≤ CCD < 0.40	Lagging demand but higher supply	Lagging supply but higher demand	Both lagging supply and demand

* f_s(x) and f_d(x) are the comprehensive evaluation index of the green space supply subsystem and the green space demand subsystem, respectively. Abs(x) is the absolute value of f_s(x) and f_d(x). σ is the standard deviation of Abs(x) for each purpose.

, [44,45]).

2.4.4. CCD in Different Purposes

We analyzed the demand for green space among residents for various purposes, such as exercise, walking, communication, sightseeing, and spending time with children, considering the sample size and spatial distribution. Then, we calculated the CCD of PGS for each purpose. Since some interviewees have multiple reasons for visiting the park, it is necessary to calculate the CCD for each purpose separately. For example, if an interviewee visits a green space for both exercise and leisure walking, the CCD values for exercise and leisure walking will be calculated separately.

3. Results

3.1. The Differences of Perceived Accessibility of PGSs before and after Campus Reopened

As shown in Figure 3a,c, when the campus green space was not open, no blocks could reach their most frequently visited green spaces by walking within 5 min, 2 blocks could reach them by bicycle within 5 min, 2 blocks could reach them by walking within 15 min, and 5 blocks be reached by bicycle within 15 min. The others required more than 15 min to reach the most frequently visited green spaces.

After the campus reopened, the perceived accessibility of PGSs was significantly increased in the central part of the city but not in the suburban area (Figure 3b,d). The number of blocks that could reach their most frequently visited green spaces by walking within 5 min increased from 0 to1. The number of blocks that could reach their most frequently visited green spaces by bicycle increased from two to four. The number of blocks that can reach these spaces by walking within 5–15 min was still2, and the number of blocks that can reach by bicycle was still 5. However, two of these blocks were developed from the blocks that could reach the most frequently visited green spaces within 15–20 min when campuses were not open.

3.2. Spatial Pattern of Supply and Demand for PGSs

As shown in Figure 4, before the campus reopened for public, blocks with high levels of PGSs supply were concentrated in the central area and the southern riverside, where parks were located. After the campus reopened to the public, the supply of PGSs for Block B, Block E, and Block K where campuses were located, was increased. Two of these blocks overlapped with the blocks with a high supply level before the campus reopened.

As shown in Figure 4, the demand level of PGSs in the built-up Yangling was higher in Block B in the north, followed by Block E in the central area, and demand in other regions was at a similarly low level.

3.3. Relationship between PGS Supply and Demand before and after the Campus Reopened

The CCD of PGS supply and demand in the built-up Yangling area exhibited a spatial pattern of high center and low outside whenever before or after the campus reopened (Figure 5). Most of the blocks couldn’t accurately match the supply and demand of PGSs.

Before the campus reopened, only 28.6% of blocks had a high level of CCD, while 71.4% of blocks were unbalanced. In detail, seven of these blocks were both lagging supply and demand for PGSs (0 ≤ CCD ≤ 0.25). Two blocks had lagging supply but higher demand (0 ≤ CCD ≤ 0.20). Block K was lagging in demand but had higher supply (CCD = 0.37). The highly coordinated blocks only existed in the blocks in which PGSs were located (0.46 ≤ CCD ≤ 0.71). However, their demand for PGSs was lower than supply.

After the campus reopened, 42.9% of blocks had a high level of CCD, while 57.1% of blocks were uncoordinated. Block B, in which a campus is located, achieved high coordination and matched PGS supply and demand (CCD = 0.69), changed from lagging supply and demand (CCD = 0.20). Block K, in which a campus is located, achieved coordinated for PGSs supply and demand (CCD = 0.4), but demand was still lagging. The CCD of Block F, Block G, and Block H, which are adjacent to the neighborhood where the campus is located, had increased slightly.

3.4. Relationship between PGS Supply and Demand before and after the Campus Reopened for Different Visiting Purposes

The CCD of PGS supply and demand under eight recreation purposes in the built-up Yangling area was similar to the overall CCD and was between 0 and 0.78 (Figure 6).

For residents who used the spaces for exercise purposes, 8 of 12 blocks were uncoordinated before the campus reopened (Figure 7a,b). Five of these blocks had both lagging supply and demand for PGSs (0 ≤ CCD ≤ 0.16). Block B had lagging supply but higher demand (CCD = 0.20). Additionally, residents’ demand could be met through residential green spaces in Block F and Block G. The other three blocks were highly coordinated (0.40 ≤ CCD ≤ 0.68). Their demand for PGSs was lower than supply. After the campus reopened, Block B, in which a campus is located, achieved high coordination and matched PGS supply and demand (CCD = 0.71) from lagging supply but higher demand (CCD = 0.20). The changes in other blocks were not obvious.

For residents who used the spaces for walking purposes, 8 of 12 blocks were uncoordinated before the campus reopened (Figure 7c,d). Five of these blocks had both lagging supply and demand for PGSs (0 ≤ CCD ≤ 0.22). Two blocks lagged in supply but higher demand (0 ≤ CCD ≤ 0.20). Block K lagged in demand but higher supply (CCD = 0.37). The other four blocks were highly coordinated (0.43 ≤ CCD ≤ 0.69). Their demand for PGSs was lower than supply. After the campus reopened, Block B, in which a campus is located, achieved high coordination and matched PGS supply and demand (CCD = 0.68), a change from lagging supply and demand (CCD = 0.20). Block K, in which a campus is located, achieved coordination for PGS supply and demand (CCD = 0.4), but demand was still lower than supply. The CCD values of Block F, Block G, Block H, and Block J had increased slightly, which is adjacent to the neighborhood where the campus is located.

For residents who use these spaces for sightseeing purposes, six of eight blocks were uncoordinated before the campus reopened (Figure 7e,f). Two of these blocks lagged in both supply and demand for PGSs (0 ≤ CCD ≤ 0.18). Two blocks lagged in supply but had higher demand (0 ≤ CCD ≤ 0.20). Block I lagged in demand but had higher supply (CCD = 0.39). Additionally, residents’ demands could be met through residential green spaces in Block G. The other two blocks were highly coordinated (0.49 ≤ CCD ≤ 0.71). Their demand for PGSs was lower than supply. After the campus reopened, Block B, in which a campus is located, achieved high coordination and matched PGS supply and demand (CCD = 0.68), a change from lagging supply and demand (CCD = 0.20). The changes in other blocks were not obvious.

For residents who use these spaces for communication purposes, four of six blocks were uncoordinated before the campus reopened (Figure 7g,h). Two of these blocks lagged in both supply and demand for PGSs (0 ≤ CCD ≤ 0.06). Block B lagged in supply but had higher demand (CCD = 0.2). Block I lagged in demand but had higher supply (CCD = 0.35). The demand for PGSs in Block E was lower than supply (CCD = 0.68). Block D, in which a park is located, was coordinated and matched PGS supply and demand (CCD = 0.46). After the campus reopened, Block B, in which a campus is located, achieved high coordination and matched PGS supply and demand (CCD = 0.71), a change from lagging supply and demand (CCD = 0.20). Block D, in which a park is located, achieved higher coordination for PGS supply and demand (CCD = 0.49), a change from coordinated and matched supply and demand (CCD = 0.46). However, demand for PGSs was lower than supply. The changes in other blocks were not obvious.

For residents who are there with the purpose of recreation with children, five of seven blocks were uncoordinated before the campus reopened (Figure 7i,j). Three of these blocks lagged in both supply and demand for PGSs (0 ≤ CCD ≤ 0.26). Block I lagged in demand but had higher supply (CCD = 0.38). Block G lagged in supply but had higher demand (CCD = 0). Additionally, residents’ demand could be met through residential green spaces in Block M. After the campus opened, Block G, in which neither a campus nor a park is located, achieved higher coordination for PGS supply and demand (CCD = 0.16), a change from lagging supply and demand (CCD = 0). The changes in other blocks were not obvious.

4. Discussion

4.1. The Role of Campus Green Spaces

The effect of opening up campus green spaces on improving residents’ perceived accessibility varies between urban and suburban areas. The reopening of campuses can significantly increase the perceived accessibility of PGSs within 5 min and 15 min by walking and by bicycle in central urban communities, but the improvement was not significant in rural communities. Based on the interview records of the questionnaire survey, we found that suburban residents (located in Block A, Block B, and Block C) had a sense of awe and identity gap towards campuses and were more willing to avoid nearby campus green spaces and visit other, farther PGSs, resulting in subjective spatial isolation. However, central urban residents use the campus green space nearby when it is open. This is inconsistent with previous studies on low- and middle-income groups’ low perceived accessibility due to landscape preferences, health, safety, transportation costs, etc. [29,30,31]. Studies have shown that the spatial accessibility of low-income groups such as rural residents is usually lower than the overall level [46], and they were more vulnerable to changes in physical park access [47]. This study found similar results from perceived accessibility dimension. Although this study found that the opening of campus green spaces can alleviate the supply–demand relationship of public green spaces, the poor perceived accessibility of these residents will exacerbate the inequality of urban green spaces, making it difficult for campus green spaces to effectively improve the fairness of PGSs in neighboring suburban or rural communities. Currently, many newly built universities are located on the outskirts of cities, with their campuses mosaiced in suburban or rural communities. However, relevant research only considered urban communities in both mega-cities and small cities. Future research needs to focus on the differences in cognitive accessibility of campus green spaces between urban and rural residents, as well as their formation mechanisms.

Our results showed that the campus green space effectively improved the physical PGSs supply of the block where it is located, achieved a balance between supply and demand, and improved the coordination of supply and demand. Campus green spaces play a similar role as neighborhood parks in large cities, particularly in high-density urban areas. They provide a space for the daily cultural and sports activities of the local residents [10,13,22,48].

Our results indicated that the campus green spaces contribute to improving the coordination of supply and demand among adjacent blocks, although the impact was not statistically significant. This was different from studies performed in large cities, which found that campus green spaces were similar to greenway which enhanced green space connectivity in urban regional scale and significantly improved green space equity in adjacent neighborhoods [19,20,21]. Similar conclusions have only been found in some large cities, such as a study in Santiago de Chile that showed that campuses do not help to mitigate vegetation inequality in urban communities, they simply tend to replicate the uneven distribution structure of vegetation in intra-city communities, which seems to be caused not only by the size of the city, but rather by a systematic inequitable distribution of vegetation intrinsically linked to multiscale drivers [49]. For small cities such as Yangling, this may be due to the underdeveloped road network and low density of residential areas, so it is still difficult to cover the living circle of most residents, even including campus green spaces in PGSs.

4.2. The Supply–Demand Relationships of Green Spaces under Different Visiting Purpose

Our results showed that the spatial pattern of supply and demand of green space for exercise, walking, and recreation is similar to the overall situation. However, purposes of sightseeing, communication, and recreation with children were different from this. On the one hand, exercise and walking account for a large proportion of the sample (17.16% and 30.36%), which directly affects the overall trend of supply and demand, and similar conclusions have been observed in other studies [3]. On the other hand, this is closely related to the difference in the demand for space for sightseeing, communication and recreation with children, reflected by the high proportion of water bodies and vegetation cover for sightseeing, high proportion of open spaces for communication, and amusement equipment for children’s sensory experience. Even though many previous studies used CCD to quantify the supply-demand relationship of UGSs, the large spatial extent and a large population made them hard to pay attention to people with different purposes [39,41,42,43,44]. This study used a small city as a study area and obtained highly representative samples with a lower sample size. The differences in PGS supply and demand relationships between different target populations under the same green space supply were identified, expanding the application scenarios and reference value of CCD.

In addition, the impacts of the opening of campus green space on the supply and demand of recreational services for visitors with various purposes were different. For residents using these spaces for exercise, walking, sightseeing, and communication, the opening of campus green space could improve the supply level of the site and achieve supply and demand balance and coordination. These findings were similar to those of a study in large cities during the COVID-19 pandemic [2]. With research suggesting that the main reason for both Chinese and Western residents to visit parks is to exercise, open campuses could provide stronger support for meeting this recreational purpose [50]. For visitors with children, the opening of the campus green space could not bring significant improvements. This could be because the campus is large enough to accommodate people walking and because each campus contains at least a playground that can meet visitors’ demand for exercise. Additionally, many campuses contain water bodies, a large amount of vegetation, and many open spaces, making them able to meet the needs of space for sightseeing and communication. However, the design of the campus is mainly aimed at teachers and students, and less consideration is given to meeting the needs of children, so it does not contribute much to the recreational needs of children [51].

4.3. Recommendations for Enhancing Campus Green Space to Address Urban PGS Imbalance

Our findings suggest that to better integrate campus green spaces into the urban PGS system and improve coordination, cities should consider policies, management, accessibility, and infrastructure factors.

Policies regarding public access to campus spaces vary globally. While campuses are often an integral part of urban green spaces in developed countries [52], closed campuses are still common in developing countries [8]. Local policies should promote public use of campus spaces. Effective cross-sectoral coordination is necessary to transform campus green space into a valuable asset for city governments, addressing the imbalance between green space supply and demand [49]. For instance, in China, universities often have higher administrative levels than local governments, limiting the effectiveness of local government policies on universities. Additionally, our study underscores the importance of fostering a sense of belonging and reducing the perceived exclusivity of college campuses among suburban and rural residents with lower income or education levels to enhance public use of campus green spaces. This effort will require initiatives by both the government and colleges to promote accessibility and inclusiveness, making campuses open to vulnerable groups both physically and psychologically.

The success of campus green spaces hinges on accessibility and infrastructure. Research indicates that accessibility is a significant factor influencing residents’ use of green spaces, ranking highest among various factors [53]. Ensuring infrastructure support, such as campus accessibility, is crucial for integrating campus green spaces into the broader urban green space system. Creating open university towns and implementing concepts like city parks can facilitate deeper integration between the city and the campus [52,54]. Diversifying campus infrastructure to meet the needs of different populations is also essential. This includes building all-age-friendly facilities (e.g., for children citizens) and multi-purpose recreational equipment [51], which can cater to a wide range of recreational needs. Such measures ensure that the campus serves not only faculty and students but also the broader community.

4.4. Limitations

Due to the lack of public transportation data, this study determines the service radius of a 15 min walk based on the classification of PGSs and the surrounding road network, which may have a bias. Except for the Bolan Park, all the PGSs in the study area are free green spaces without walls. Additionally, the public transport network in the study area is time-limited (7:00–19:00), and the area is only covered by main roads—in contrast with large cities—so the current estimation bias of the park service area is acceptable. In future research, according to the different modes of transportation of each park—especially the new transportation modes such as shared electric bicycles in small- and medium-sized cities—the service radius can be calculated to provide a more objective basis for planning.

Our study area was a university town located in western China. It has a low population density, with near-zero population growth from 2019 to now, and is expected to decline in the future [35,36]. The green spaces’ supply–demand relationships in this study may differ from those of university towns in eastern China, which have seen a net population inflow in recent years [36]. Therefore, the comparative study of expanding the study area or expanding the spatial scale in the future will have better reference values for campus green space planning under different population development trends.

5. Conclusions

The supply and demand of PGSs were uncoordinated and mismatched in most of the blocks, exhibiting a spatial pattern of coordinated supply and demand in the central areas but one of oversupply and uncoordinated supply and demand in the edge areas with low supply and low demand. The supply and demand of PGSs for exercise and walking were similar to the overall pattern. It was lagging in demand but higher supply for sightseeing, communication and playing with children. Additionally, the demand of sightseeing and playing with children could be met in some of the surrounding areas.

The reopening of campus green spaces on improving residents’ perceived accessibility varies between urban and suburban areas. The reopening of campuses can significantly increase the perceived accessibility of PGSs within 5 min and 15 min walking and bicycling in central urban communities, but the improvement was not significant in suburban or rural communities. Similarly, the reopening of campus green space effectively improved the PGS supply of the block where it is located, achieved a balance between supply and demand, and improved the coordination of supply and demand. In addition, the campus green spaces help to improve the degree of supply and demand coordination of adjacent blocks but cannot significantly improve the matching relationship between supply and demand. For residents who aim to exercise, walk, go sightseeing, and communicate, the campus green spaces help to improve the degree of supply and demand coordination and matching for the area in which the campus is located. For residents who aim to play with children, the campus green spaces could not bring about significant improvements.

In future planning, for the whole city’s sustainability, the new green space should be located on the east–west edge of the city, improving the accessibility of the southern wetland park, which will help improve the coordination of supply and demand of urban PGS. For campuses, it is important to improve accessibility for adjacent blocks, design landscapes based on resident’s preferences, increase the density of footpaths, and add child-friendly facilities. In addition, colleges should pay more attention to the surrounding rural communities, enhancing the attractiveness and sense of belonging to them to increase their perceived accessibility. It can be seen that for small- and medium-sized university towns with similar situations, the accessibility and infrastructure of campus were the key to improve their sustainability. After that, the campus will meet the demand of more people with various recreational purposes and promote the coordination of the supply and demand of urban PGS.