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Article

A Comprehensive Evaluation of Supply and Demand in Urban Parks along “Luck Greenway” in Fuzhou

by
Yu Zheng
1,*,
Shan Wang
2,
Jinli Zhu
2,
Shuo Huang
2,
Linli Cheng
2,
Jianwen Dong
2 and
Yuxiang Sun
3,*
1
Department of Environmental Design, School of Fine Arts, Minjiang University, Fuzhou 350108, China
2
College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China
3
Department of Human Resources Management, School of Business and Management, Jilin University, Changchun 130021, China
*
Authors to whom correspondence should be addressed.
Sustainability 2023, 15(3), 2250; https://0-doi-org.brum.beds.ac.uk/10.3390/su15032250
Submission received: 11 January 2023 / Revised: 20 January 2023 / Accepted: 21 January 2023 / Published: 25 January 2023
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Abstract

:
A sustainable urban park should have balanced green space (GS) supply and demand (SAD). A knowledge gap exists to reveal parameters that can indicate the relationship between the supply of GS services and the demand of public health needs. In this study, three primary indicators and 12 secondary indicators were selected to build a comprehensive evaluation system on SAD in the GSs of 14 parks along the “Luck Greenway” in Fuzhou. Parks were categorized and assessed for their ecological service functions, public health demands, and current public health needs. Remote evaluation and field survey were both used to collect data for quantifying functional supply and needs, respectively. It was found that factors, such as the fitness of sports service facilities, vegetation coverage, natural confluence, and mental health, impacted the comprehensive quality of supply services in urban parks. The unbalanced “multi-center” distribution of the coupled evaluation values revealed the mismatch in SAD. This study aimed to provide guidance on planning the health-promoting GS landscape by balancing SAD and maintaining ecological environment protection.

1. Introduction

An urban park comprises green and blue spaces (GBSs), which are both important components in a multi-functional urban ecosystem [1,2]. GBSs provide spaces of nature in built-up regions of a city to function as cultural ecosystem services [3,4]. Experiencing GBSs can be perceived as a way to improve the physical and mental health of visitors, which will further result in the alleviation of work stress and the enhancement of perceived happiness [5,6,7]. Urban parks are a type of urban green infrastructure with essential facilities that provide a sense of public well-being and quasi-public goods [8]. GBSs obtain functions that meet residents’ multi-level needs and the diversity of physical activities of urban inhabitants [9].
Visiting urban parks can benefit public health by reinforcing the physical, psychological, and social health states of people [10,11,12]. This benefit has been demonstrated mainly in urban landscapes with spatial heterogeneous arrangements of GBSs from neighborhood-scale to city-scale levels [8,13,14]. GBSs often provide accessibility to neighboring green spaces (GSs) for a special group of people or in certain types of ecosystem services [15,16]. The fragmentation of the urban green space (UGS) is widespread in rapidly urbanizing areas [17,18], which leads to a continuous reduction in ecosystem service capacity. Landscape fragmentation can also lead to an imbalanced trade-off of supply and demand (SAD) for ecosystem services (ESs) [16,19] and a mismatch between landscape space and type [20]. Relevant studies have quantified services in urban parks as GIs to mediate the SAD balance through assessing quality, green equity, and accessibility to nature [21,22,23]. The SAD trade-off of GSs is an important dependence that urban planning and decision making must consider [24,25,26]. The balance of SAD also helps to rationally allocate GSs to improving social well-being and sustainability [27,28,29]. Current studies, however, mostly emphasize the partial distribution of either supply or demand [25,26,27,28,29] rather than considering their balance. Landscape parameters are important indicators that allow users to perceive UGS services and residents’ health and well-being [30,31,32,33].
The development of Big Data technology brings a diversified stream of spatial data that can be used for spatial analysis [34,35]. It activates a new methodology to assess the distribution of behaviors and preferences for park experiences and health-oriented visits [36,37,38]. It can also enable the spatial assessment of the diurnal distribution of park visitors and help to identify the frequency of visits in neighboring GSs based on cellphone records [39,40]. Compared to conventional field investigation, it is easier to refine data and analyze their meaning [41]. The number of points of interest (POIs) about service facilities within a park reflect the population and activity intensities around the park to a certain extent, which can reveal the health service pressures within the service area of each park [42]. It can also utilize more granular units in statistical analysis and spatial representation at the city scale [34]. Therefore, it is possible to refine a spatiotemporal representation of public demand using Big Data for planning the health-enhancing quality of urban parks.
Urban areas provide safe and convenient facilities for the public to engage in active physical activities [43,44]. Perceptions toward the use of GBSs in parks enhance the happiness and comfort of users and promote the development and improvement of all-round public health [35,45,46,47]. Services that can benefit public health are mainly a result of commercial, sports, and public facilities (neither commercial nor sport services) [48,49]. Commercial service facilities can improve the quality of residents’ cultural life and create a rich community life that promotes the health of the population [50]; sports facilities help improve urban health and meet residents’ needs [51]; and public service facilities meet the diverse needs of urban residents, thereby improving the physical and mental health of the population. The soundness of these three types of service facilities characterizes the distribution pattern and density of activities in relation to public health needs. Thus, the public demand for health and well-being is crucial as it relates to the idea that GBSs can be estimated based on spatializing health-oriented distributions, behaviors, and preferences.
The concept of the “ecological service function” of GSs includes, but is not limited to, the Common International Classification of Ecosystem Goods and Services (CIECI), Intergovernmental Science—Policy Platform on Biodiversity and Ecosystem Services (IPBES), and the evaluation index system of ecological service functions in China. These mainly refer to the compound functions of supply, regulation, culture, and support [52]. These concepts are mostly examined through the study of GSs at the macro to fine scales [53]; however, health-related factors have rarely been fully integrated. The pandemic has created a need to construct healthy cities with essential technical guidance to plan health-oriented GSs. This guidance is framed by ecological sensitivity, which refers to the ecological issues that may occur in the ecosystem or ecological environment in a certain area in response to various natural and anthropogenic disturbances [54]. Landscape parameters can be used as a way to gauge ecological sensitivity for evaluating the functions of services in urban parks [55,56].
Health benefits refer to the improvement of health resulting from the interaction with nature. Many studies have incorporated matrices to evaluate the health benefits of GSs in urban parks [57,58]. Demand is growing for the health benefits that result from interactions with nature [59,60,61]. An interdisciplinary methodology can be established based on new access to data, shifting the focus from describing spatial distribution [62,63] toward estimating cultural ecosystem services (CESs) to improving public health [64,65,66]. Therefore, it is important to establish comprehensive evaluation metrics for urban park quality that comprise assessments of CES perspectives towards parks, spatial distribution, landscape scales, and functional outcomes, etc. [67,68].
In this study, Fuzhou was chosen as the study area, where a total of 14 parks were selected along a GBS transect. Parks were categorized in different types according to a local planning protocol; hence, they could be analyzed for ecological service functions, public health demands, and their current health service status. Depending on the findings of these scattered observations, we expected to build a comprehensive evaluation model to assess the quality of GS landscapes through indices that promote SAD balance and meet public needs for health improvement. This study aimed to provide a blueprint for planning and designing health-promoting urban parks with balanced SAD while protecting the ecological ecosystem.

2. Methodology

2.1. Methodology Framework

A layout of the theoretical framework is shown in Figure 1.

2.2. Study Area and Sites of Data Collection

Fuzhou is the capital city of Fujiang province, China. It has five districts, two county-level cities, and six counties. Significant efforts have been put into building or improving four promenades that have distinct characteristics, namely the “Luck Greenway”, “Culture Greenway”, “Fu Forest Trail”, and “Pleasure Greenway”. Luck Greenway is located along a geographical gradient throughout the north-to-south transect of Fuzhou, which looks like a backbone of the local landscape across alternating blue and green patches. Thus, it was named “Luck Greenway” due to the homophone of a Chinese character “桥” (i.e., “ridge” in English). The total walking length is 44.6 km, linking Guangming Port Park and Fuzhou Forest Park. The main walking section has a length of 36.6 km, with an additional 8 km that includes all of the branching paths. A total of 14 urban parks have been constructed along the promenade, which were selected as our study region for this study (Figure 2).

2.3. GS Types of Urban Parks

GSs are classified as four types according to The Standard for Classification of Urban Green Space (CJJT85-2017) [69]. Detailed types of classified parks are shown in Table 1.

2.4. Parameter Assessment

2.4.1. Assessment of the Ecological Service Function

According to previous findings in similar studies [55,56], landscape indicators gauging ecological sensitivity were chosen to assess the ecological service functions of urban parks in this study. Five selected factors included slope, elevation, natural confluence, vegetation coverage, and land-use type. We used scores from expert ratings and analytic hierarchy process (AHP) methods to weight the coefficients of each factor. The final score was rated using the “grid calculator” function of the ArcGIS (v10.6) software [55,56,70] to superimpose and visualize indices used for calculating the ecological sensitivity (Table 2). Subsequently, the ecological service functions of parks can be mapped along the Luck Greenway landscape.

2.4.2. Assessment of Public Need

Service facilities that have remarkable impacts on public health were chosen as the POI data source in objective parks. Three indicators were adapted to assess public needs, namely the average levels of soundness in commercial, sports, and public service facilities. Records of POIs and spatial vector data were collected from urban parks along Luck Greenway from the Open Data Platform of Baidu by crawling using Python [34,71]. Data were screened and cleaned using ArcGIS software (v.10.6) to generate the POI density map. Stratified data were treated by “reclassification” and demands on public health and hierarchy could be mapped in the designated area. Finally, on-site investigations were used to collect field data as a base on which data were remotely evaluated and distributions were verified.

2.4.3. Assessment of Health Service Functions

Among all needs that the public may wish GSs to provide, those used for health benefits were taken to be the most important [72]. To ensure that the most intended meanings can be retained, we designed questionnaires based on three secondary indicators, namely the mental, physical, and social states of health. Another 15 third-level indicators were embedded to each of these secondary indicators (Supplementary Materials). The use of human data reported by participants has been determined to require ethical approval, and this was granted on 17 March 2019 (ES-ERC-2019-001). Questionnaires were used for random surveys at different crossroads of parks from 12 September to 31 October 2021. Every survey started at 7:00 a.m. and ended by 11:00 a.m. and then continued from 3:00 p.m. to 7:00 p.m. A total of 150 copies of questionnaires were used in each park; finally, 2100 copies were sent out, and 2,034 of them were returned (reclaiming efficiency: 96.9%). Every subject was asked to report self-evaluated scores to rate scales of reliability and validity, which were then both higher than 0.6 and 0.5, respectively. Therefore, the data visualization function in ArcGIS was used to map the spatial distribution of health service functions in parks. Again, the conducted data were verified in accordance with field investigations.

2.4.4. Comprehensive Quality Assessment Using Multi-Factor Analysis

The AHP in ArcMap is a proven method used to deal with complex decision making and assist in identifying decision criteria. The advantage of drawing comparisons of decision criteria to reach accurate quantitative-scale weights, rather than the conventional arbitrary allocation of single weights, is apparent [55]. The study aimed to explore how to incorporate the results of ecological services to functionally evaluate the comprehensive quality of urban parks. The GIS-AHP method was employed to carry out the selection and coupling analysis of comprehensive quality evaluation factors of urban parks, as well as data verification in combination with field investigations.
The AHP method was used based on the Standard Evaluation Standard for Park City for selecting evaluation factors [73,74]. To determine the coefficients of weighted factors, we interviewed 32 experts in the relevant fields of landscape architecture and urban planning to rate scores by self-reporting on questionnaires. Blanks were asked to be filled by eight professors, eight associate professors, eight lecturers, and eight doctors. A model established using the hierarchical database was used to calculate the factorial weights using AHP.
Based on data collected at this stage, a comprehensive quality evaluation system was established to quantify the influence of urban park experiences on public health with three primary indicators and 12 secondary indicators (Table 2). The sensitivity of the ecological service and the satisfaction in meeting public health needs were evaluated remotely. To evaluate the park’s health service function, data were firstly obtained by self-reporting on questionnaires and visualized using the weighted values for each park (Table 3). Finally, we conducted a stacking calculation based on the weights with the ARCGIS “grid calculator”, yielding a comprehensive quality evaluation map of urban parks along the “Luck Greenway”.

2.5. Calculation and Statistics

The sensitivity of the ecological service (Ses) was calculated:
S e s = ∑ i = 1 j S e i × A i
where Sei is the sensitivity level (extremely low sensitivity = 1, low sensitivity = 2, medium sensitivity = 3, high sensitivity = 4, and extremely high sensitivity = 5) in the i region of the objective urban park; Ai is the ratio of the area in region i to that of the total. Products were summed for the whole park as a result. The satisfaction to meet public health needs (Sphn) by visiting a park was calculated:
S p h n = ∑ i = 1 j S a i × N i j
where Sai is the evaluated level of satisfaction of needs for public health (extremely low satisfaction = 1, low satisfaction = 2, medium satisfaction = 3, high satisfaction = 4, and extremely high satisfaction = 5) by experiencing an urban park grid i; the objective park was divided to j mosaics of grids; Ni is the number of grids that had the same level of satisfaction.

3. Results

3.1. Assessment of Ecological Service Functions

As shown in Figure 3 and Table 4, comprehensive parks were assessed to have the highest score in the ecological service function, being 92.11%, 51.99%, and 102.80% higher than that for community parks, special parks, and ribbon gardens, respectively. Factors of slope, elevation, aspect, and vegetation coverage had higher impacts than other factors on the comprehensive ecological service functions of this type of park. On-site surveys confirmed that the unique topographic features and the rich vegetation in Fuzhou Forest Park and Jinji Mountain Park had geographical components which restricted public access and protected the overall ecological environment of the parks. It was built-up areas and the high ratio of hard landscapes in parks that impaired the local ecological environment.
The overall scores of ecological service functions in special parks were higher than those in other types of parks. Among the factors, natural confluence and vegetation coverage had higher impacts on this type of park. Among different types of parks, Fuzhou Zoo was estimated to have better overall functions of ecological services owing to its diverse vegetation and the large area of water bodies. Gucheng Park had a large number of buildings, which contributed toa high score in terms of artificialization. This was reflected in unbalanced ratios of alternatively hard and soft landscapes, which resulted in poor ecological service functions.
The overall ecological service function was lower in community parks. Among all factors, natural confluence and vegetation coverage, had a larger impact on this type of park. A lower evaluation reflected the small area and low vegetation coverage of these community parks. Yangxia Sponge Park had a shorter history compared to most of other parks. Planted vegetation and a variety of facilities did not have comprehensive functions, resulting in poor ecological service functions.
The overall function of ecological services was low in ribbon gardens. The openness values of revetments and hard landscapes were estimated as negative contributions to the ecological service function of the Xindian River Waterfront Park, Beijiang Riverside Park, and Jin’an River Park.

3.2. Public Health Needs

Figure 4 and Figure 5 show the spatial distribution patterns for the public health needs of the urban parks along Luck Greenway. Areas with extremely high and high health needs levels were concentrated in the four parks of Hot Spring Park (a comprehensive park), Yangxia Sponge Park (a community park), Guangming Port Park (a special park), and Jin’an River Park (a ribbon garden). On-site verification showed that these parks provided complete basic service facilities that were attractive to people in need of recreation activities.
Based on the classification type, ribbon gardens were given the highest score in the overall service function, being 56.0%, 77.74%, and 77.75% higher than those of the comprehensive, special, and community parks, respectively (Table 5). Ribbon gardens also had higher coverage rates of facilities in commercial, sports, and public services. A comparison of the mean values of the coverage rate for facilities of sport services showed the following ranking order: ribbon gardens > comprehensive parks > community parks > special parks. Field studies revealed that the types of services provided by special parks, such as Dengyun Reservoir and Fuzhou Zoo, were undiversified. This indicated the limited efforts devoted to the optimization and improvement of service facilities in these parks. Again, ribbon gardens outperformed comprehensive, special, and community parks in terms of the mean coverage rates of public service facilities. The on-site survey confirmed that community parks, such as Chiqiao Park, had undiversified environments that lacked basic service facilities. It revealed a ranking order of commercial service facilities’ coverage rate as follows: ribbon gardens > comprehensive parks > special parks > community parks. The on-site survey also showed that ribbon gardens, such as the Xindian River Waterfront Park, were close to urban watersheds and areas covered by road networks, offering denser commercial service facilities.

3.3. Evaluation of Health Service Functions

The evaluation scores of the different types of parks in health service functions varied significantly (Figure 6, Figure 7 and Figure 8). The evaluation scores of special parks varied greatly. Among the parks, Jinji Mountain Park, Fuzhou Forest Park, Children’s Park, and Dengyun Reservoir were scored best in terms of health service functions, whereas Chiqiao Park, Xindian River Waterfront Park, Hot Spring Park, Yangxia Sponge Park, and Gucheng Park had relatively poor scores (Figure 6). The health service function score of Fuzhou Zoo was lower than that of the Children’s Park. Comprehensive parks were given 8.37%, 4.14%, and 4.89% higher scores than special parks, ribbon gardens, and community parks, respectively.
The health service function score was estimated to be higher in Jinji Mountain Park, Fuzhou Forest Park, and Dengyun Reservoir in terms of mental health (Figure 7). To be more specific, scores in alleviating sadness, relieving tension or anxiety, and enhancing concentration were observed, but low scores were also observed in alleviating loneliness and improving recognition ability (Figure 8). Hot Spring Park and Xindian River Waterfront Park had serious problems of artificialization and a high ratio of hard landscapes, and were highly affected by artificial activities; therefore, their effects on relieving mental stress were low (Figure 8).
The health service function score was estimated to be higher in Jinji Mountain Park, Fuzhou Forest Park, Dengyun Reservoir, and Children’s Park in terms of physical health (Figure 7). Among these factors, parks had high scores in services in terms of relieving fatigue, improving sleep quality, and enhancing vitality. Relatively low scores were found with regard to relieving physical pain and improving body shape (Figure 8).
The health service function score was estimated to be higher in Fuzhou Children’s Park, Jinji Mountain Park, and Jin’an River Park in terms of social interaction, parent–child communication, and enhancing willingness to socialize in terms of social health (Figure 7). In summary, spatial heterogeneity existed among the 14 parks along the Luck Greenway in terms of health service functions. However, the sample parks were scored higher than the four in multiple evaluation factors of health service functions, indicating satisfactory health service functions overall.
Health function service scores were mapped to reveal a “dual-center” pattern in the evaluation of the health service functions of parks along the Luck Greenway (Figure 9). Areas with extremely high levels of health service functions were shown to locate in Jinji Mountain Park and Forest Park. They were accompanied with rich natural resources of vegetation, relieving the mental pressure of people subjected to mountain climates and thereby improving the health service functions of these parks.

3.4. Comprehensive Quality Evaluation of Urban Parks

The comprehensive quality evaluation of the 14 parks along the Luck Greenway showed a “multi-center” pattern (Figure 10). Extremely high and ordinary high quality areas were concentrated in comprehensive parks and special parks, respectively (Figure 10). For example, these regions included Jinji Mountain Park and Fuzhou Forest Park, which were located on montane landforms such as comprehensive parks with diverse sights, well-developed facilities, and complex and diverse types of spaces that provide visitors with various experiences. The extremely low and ordinarily low evaluation areas were located in ribbon gardens and community parks, and tended to be “marginalized”. For example, Jin’an River Park, a ribbon garden, was not fully constructed, leading to its relatively poor score in ecological and health service functions and the satisfaction of public health needs. Chiqiao Park and Yangxia Sponge Park, as community parks, had larger areas of water and higher openness of revetment, but they had shortcomings in vegetation coverage and construction, failing to fulfill visitors’ needs in terms of daily exercise and entertainment.
In general, comprehensive quality was evaluated in various types of urban parks and GSs along the Luck Greenway in Fuzhou (Table 6). The public health needs did not match the supply and demand of urban park service functions, while the spatial distribution of parks was uneven (Figure 10).

4. Discussion

Our on-site verification showed that, despite possessing unique topographic features, Fuzhou Zoo had apparent problems of artificialization in its eastern part. The local environment was messy owing to poor management. Therefore, its scores in terms of health functions were found to be low. Parks that had high vegetation coverage rates and diverse types of vegetation also had a large water area, high openness of revetments, and a low ratio of hard landscapes, such as those in the Dengyun Reservoir. These characteristics accord with the landscape attributes of northern parks [33,46]. This type of park landscape was suggested to fulfill people’s needs to enjoy the atmosphere near waters and feel the release of stress [17,47]. Jinji Mountain Park and Fuzhou Forest Park were two typical mountain-type hotspots with a complete construction of various trail facilities that can offer people a visual experience with lush greeneries. They also had unique mountain climates and topographic features, in addition to longer distances of trails for hiking that could greatly improve physiological functions. These nature landscape metrics together account for restorative effects for the people who visited these two parks [61,75].
Gucheng Park was determined to have a low promotion effect with regard to physiological functions, which was accounted for by the fact that the park had an overall high ratio of hard landscapes, low vegetation coverage, and undiversified service facilities. The urbanized regions of a city relate to the high density of built-up zones, which has been fully demonstrated to act as the precondition of perception toward negative moods [76,77]. This is because hard landscapes tend to evoke the perception of stress by respondents and, in contrast, the nature in the city would counter these types of perceptions of negative emotions [78]. Understory environmental factors generate responsible driving forces to make people perceive positive moods in relation to nature or negative moods in relation to impervious surfaces [79]. Recreational services accounted for the perceived well-being of people across different ages, as demonstrated by the high demand scores in the Jasmine Terrace, Lancheng Plank Road, and Children’s Fun Park. These parks could fulfill the public’s needs for daily socializing and parent–child interactions; hence, they enhanced the willingness of the public to socialize [80]. This was also the reason why the scores for Gucheng Park and Yangxia Sponge Park were relatively poor. Yangxia Sponge Park is a community park, and it was poorly equipped in terms of basic service facilities. Instead, apparent bare-soil lands were left with random arrangements, leading to large swaths of weedy areas. These heavily impacted visitors’ willingness to enjoy the natural view and reduced their need for social interaction.
From the perspective of the coupling of SAD, an evaluation of the public health needs of urban parks was essentially a demand-side analysis, while evaluations of the current status of ecological and health service functions were essentially a supply-side analysis. The unbalanced “multi-center” distribution of the coupled evaluation values provided evidence on the mismatch between SAD. This then led to an extremely unbalanced comprehensive service and affected the equity of the overall layout of park GSs [23,63]. The relevant research found it difficult to evaluate the SAD relationship because of a challenge in targeting different research objects at different research scales, which together made the research indicators unclear [81]. The number of POIs in this study based on service facilities could comprehensively estimate the range and levels of urban residents’ health needs from a macro perspective. However, most of relevant pieces of research were only conducted on the basis of the SAD balance concept of urban infrastructure configuration to evaluate the spatial fairness of urban park green space [64,81]. Therefore, it is difficult to ensure that the construction of service facilities could both meet the public health needs and protect the ecological environment. A good ecological environment status was the main basic guarantee for the health service function of the park GSs [55,56]. This study aimed to build a comprehensive quality evaluation index system of an urban park GS based on three primary indicators (including twelve secondary indicators), so that it could better solve the problems caused by different research objects, research scales, and research index choices between the supply and the demand. Based on the comprehensive quality evaluation, the study expected to provide a clearer and more comprehensive plan for the rational allocation of urban GSs.
This study recommended accurate suggestions in terms of planning and designing the health services of urban parks based on the balance of SAD. The fitness of sports service facilities was found to have a greater impact on the service function of the park to meet public health needs. This concurs with previous findings in Perth [51]. This was the main reason that the demands of public health in urban park GSs along the Luck Greenway presented a multi-center pattern of distribution. Vegetation coverage and natural confluence factors had high impacts on the overall ecological service function of the park. It was found that these factors are called "regulatory factors affecting GS health benefits" [82,83]. They regulated the intensity of green space health benefits by influencing the behavior of people using the park [32]. This was also an important way to interpret the health benefits of GSs and to improve the health benefits of urban park GSs, which should be addressed in future works.
There are some limitations in this research. This study only took the Luck Greenway as a study area in Fuzhou. Local GSs had 14 parks of different types but applicative cases should be much more complicative than what we reported here. There were many factors affecting the comprehensive service functions of urban parks, such as planning, medicine, ecology, psychology, environmental science, economics, etc. These together make it difficult to single out the factors that are more important. In the future, with the growing demand for residents’ health and the new requirements for the optimization and improvement of the living environment, the research will consider the further integration of the multi-source data environment based on the clarification of the relationship between the spatial characteristics of urban GS ecosystem services and the matching of supply and demand at the level of residents’ health needs. On the premise of clarifying the balance among urban GS ecosystem services, the research will consider researching and summarizing the spatial form, functional structure, and element organization of efficient multi-dimensional UGS services.

5. Conclusions

From the perspective of the balance between the supply and demand of urban park green space, GIS and AHP were used to evaluate the comprehensive quality of the “Luck Greenway” urban park from the three aspects of ecological service function, public health demand, and park health service function. It was advisable to focus on the improvement of the vegetation coverage of the strip gardens and community parks in the parks along the “Luck Greenway” and the delineation of the natural water system buffer zone to form a landscape corridor. This could effectively improve the overall ecological service function of the park.
In detail, our results suggest that it is necessary to optimize sports service facilities in the special parks and community parks with low POIs. It was also necessary to optimize basic service facilities and vegetation in the “non-center” areas for the evaluation of health service functions. The function to enjoy sports facilities has been mentioned in similar studies with topics that are relevant to ours. However, our study confirms this propose, which can be referred to by more works for studying and planning sustainable urban parks with the desired functions for strengthened sports.
The current situation of the unbalanced SAD results from the reduced public health needs and park service functions. Park GSs along the “Luck Greenway” should be spatially arranged in a systematic grid of basic service facilities. The improvement of the natural environment and infrastructure quality of parks could better meet the health needs of urban residents and improve the overall health service quality of the park. The worst of the COVID pandemic is over, but the risks that threaten public health are unlikely to be diminished in the foreseeable future. We assert that any future budget for urban park planning needs to consider the assessment and improvement of services to maintain and promote the public health of users. Urban planning for urban park construction should be controlled by municipal budgets to extend the total area of green spaces without clear and guided planning for a joint purpose to involve services in health promotion.
In addition, future prospects are suggested based on our findings. Firstly, our study provides details on the description of the methodology to evaluate SAD in the urban parks of Fuzhou. This topic should be considered in other cities if sustainability in local parks and waters are pursued in continuous urban planning. Our methodology and design in this study should be extended to other cities subjected to more various landforms and climates. Secondly, we found an imbalance in the SAD of urban parks in Fuzhou, but we did not quantify the dose-dependent perception and preference of users toward the insufficient supply of green space for functional services. The emotional attitudes of visitors are crucial for quantifying perceptual evaluations on the needs of people, and novel instruments and approaches are required in future works. Finally, the sustainability of urban parks cannot be separated from economic evaluations with regard to budget and outcome. The balance in SAD also needs new evaluations involving economic and financial factors. The current pool of municipal funds used for public impact decisions to plan the new construction of parks and public perceptions toward the needs of users are important for the growing confidence of new investments to support urban planning among private firms. More socioeconomic consequences need to be examined in future work regarding the imbalance of SAD.

Supplementary Materials

The following supporting information can be downloaded at: https://0-www-mdpi-com.brum.beds.ac.uk/article/10.3390/su15032250/s1, Questionnaire on health benefits of parks.

Author Contributions

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

Funding

This research was funded by Research on Health-Oriented Improvement of Urban Green Spaces’ Multi-functions from the Perspective of Big Data, General Program of Natural Science Foundation of Fujian Province (grant number 2020J01836), and the “Study on the Improvement of Quality and Functions of Scenic Recreational Forest in Fuzhou City” in the Forestry Science Research Project of Fujian Provincial Department of Finance (grant number: Fujian Forestry Science Memo no. 9 of 2020).

Data Availability Statement

The materials and the data that support the findings of this study are available from the corresponding author, Yu Zheng.

Acknowledgments

Wenxiao Li, Hongrui Shao, and Xiaoqiu Lin were acknowledged for their help in image processing.

Conflicts of Interest

The authors declare that they have no conflict of interest.

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Figure 1. Graphical representation of overall methodology.
Figure 1. Graphical representation of overall methodology.
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Figure 2. The study site “Luck Greenway” (font lines in red) in Fuzhou and the distribution of parks along the landscape transect.
Figure 2. The study site “Luck Greenway” (font lines in red) in Fuzhou and the distribution of parks along the landscape transect.
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Figure 3. Spatial distribution of ecological service functions of urban parks along “Luck Greenway” in Fuzhou.
Figure 3. Spatial distribution of ecological service functions of urban parks along “Luck Greenway” in Fuzhou.
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Figure 4. Spatial density of point of interest (POI) in urban parks around “Luck Greenway” of Fuzhou.
Figure 4. Spatial density of point of interest (POI) in urban parks around “Luck Greenway” of Fuzhou.
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Figure 5. Spatial distributions of public health needs for health demand and hierarchical demand in urban parks around the “Luck Greenway” of Fuzhou.
Figure 5. Spatial distributions of public health needs for health demand and hierarchical demand in urban parks around the “Luck Greenway” of Fuzhou.
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Figure 6. Weighted scores of the health service functions of parks around the “Luck Greenway” of Fuzhou. Data were collected from self-reported scores on questionnaires.
Figure 6. Weighted scores of the health service functions of parks around the “Luck Greenway” of Fuzhou. Data were collected from self-reported scores on questionnaires.
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Figure 7. Differences between parks along the “Luck Greenway” in Fuzhou by health service function.
Figure 7. Differences between parks along the “Luck Greenway” in Fuzhou by health service function.
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Figure 8. Differences between parks along Fuzhou’s “Luck Greenway” by type of health service function.
Figure 8. Differences between parks along Fuzhou’s “Luck Greenway” by type of health service function.
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Figure 9. Spatial distribution map of the health service functions of parks along Fuzhou’s “Luck Greenway”.
Figure 9. Spatial distribution map of the health service functions of parks along Fuzhou’s “Luck Greenway”.
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Figure 10. Spatial distribution map of the comprehensive quality evaluation of urban parks along the “Luck Greenway” in Fuzhou.
Figure 10. Spatial distribution map of the comprehensive quality evaluation of urban parks along the “Luck Greenway” in Fuzhou.
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Table
Table 1. Green spaces in urban parks along “Luck Greenway” in Fuzhou.
Table 1. Green spaces in urban parks along “Luck Greenway” in Fuzhou.
Park TypeType CodeName of Park
Comprehensive parkG11Jinji Mountain Park, Fuzhou Forest Park, Hot Spring Park
Community parkG12Chiqiao Park, Yangxia Sponge Park, Qinting Lake Park
Special parkG13Fuzhou Children’s Park, Guangming Port Park, Gucheng Park, Dengyun Reservoir, Fuzhou Zoo
Ribbon gardenG14Jin’an River Park, Xindian River Waterfront Park, Beijiang Riverside Park
Table
Table 2. Weights of indicators used for the comprehensive quality evaluation of urban parks along the “Luck Greenway” in Fuzhou.
Table 2. Weights of indicators used for the comprehensive quality evaluation of urban parks along the “Luck Greenway” in Fuzhou.
IndicatorPrimary IndicatorSecondary Indicator
NameWeightNameWeight
Ecological service functionEcological sensitivity0.4534Elevation0.0154
Slope0.0147
Aspect0.0177
Natural confluence0.1508
Vegetation coverage0.1518
Land-use type0.1079
Health service functionsHealth benefits0.3267Mental health0.3856
Physical health0.3526
Social health0.2618
Public health needsService facility coverage0.2198Public service facility coverage0.6232
Commercial service facility coverage0.2395
Sports service facility coverage0.1373
Note: CR = 0.0706, consistency check passed.
Table
Table 3. Intervals of assigned values for ecological sensitivity, public health benefits, and service facility coverage.
Table 3. Intervals of assigned values for ecological sensitivity, public health benefits, and service facility coverage.
Primary IndicatorIntervals of Assigned Value
12345
Ecological sensitivity1.2513–2.30982.3098–2.86842.8684–3.38293.3829–3.91213.9121–5.0000
Health benefits0.9999–1.24811.2481–2.26822.2682–3.02643.0264–3.77083.7708–4.5152
Service facility coverage18.9711–19.888319.8883–20.704620.7046–21.667621.6676–22.863022.8630–23.8111
Table
Table 4. Evaluation of ecological service functions of urban parks along “Luck Greenway” in Fuzhou based on ecological sensitivity.
Table 4. Evaluation of ecological service functions of urban parks along “Luck Greenway” in Fuzhou based on ecological sensitivity.
Type of ParkSample ParkSensitivityMean Value of TypeOverall Score of Park Rank of Park
Extremely LowLowMediumHighExtremely High
12345
Comprehensive parkJinji Mountain Park7.3%11.8%40.4%32.4%8.1%2.67033.22202
Fuzhou Forest Park6.3%18.9%27.0%28.2%19.6%3.35901
Hot Spring Park57%43%---1.43008
Community parkChiqiao Park67%33%---1.39001.330010
Yangxia Sponge Park100%----1.000013
Qinting Lake Park32%55%14%--1.84006
Special parkFuzhou Children’s Park39.1%49.9%16.0%0.07%-1.75681.87184
Guangming Port Park27.1%38.4%27.1%0.08%-1.85525
Fuzhou Zoo6.8%36.8%38.3%16.7%1.4% 2.69103
Gucheng Park100%----1.000013
Dengyun Reservoir26.3%34.2%10.5%2.6% 1.36609
Ribbon gardenXindian River Waterfront Park50%50%---1.31671.50007
Jin’an River Park88%12%---1.120012
Beijiang Riverside Park67%33%---1.330010
Table
Table 5. Evaluation of the public health needs of the urban parks along “Luck Greenway” in Fuzhou.
Table 5. Evaluation of the public health needs of the urban parks along “Luck Greenway” in Fuzhou.
Type of ParkName of ParkSports Service Facilities
Coverage		Public Facility
Coverage		Commercial Service Facility
Coverage		Public Health
Needs		Rank of Type
ScoreMeanScoreMeanScoreMeanScoreMean
Ribbon gardenXindian River Waterfront Park2.00005.66701.00001.84801.00006.72201.00002.37001
Jin’an River Park11.00002.54502.22203.1110
Beijiang Riverside Park4.00002.00003.5003.0000
Comprehensive parkJinji Mountain Park2.64202.75201.05701.43561.01921.14541.05801.51902
Fuzhou Forest Park1.00001.00001.00001.0000
Hot Spring Park4.61502.25001.41702.5000
Special parkFuzhou Children’s Park1.12501.89101.00001.13341.00001.13341.00001.33343
Guangming Port Park3.33001.66701.16702.6670
Fuzhou Zoo1.00001.00001.00001.0000
Gucheng Park2.00001.00001.00001.0000
Dengyun Reservoir1.0000 1.0000 1.0000 1.0000
Community parkChiqiao Park1.00002.33301.00001.13331.00001.13331.00001.33334
Yangxia Sponge Park4.00002.00002.00002.0000
Qinting Lake Park2.00001.00001.00001.0000
Table
Table 6. Multifactor coupling analysis of the comprehensive quality evaluation of urban parks along the “Luck Greenway” in Fuzhou.
Table 6. Multifactor coupling analysis of the comprehensive quality evaluation of urban parks along the “Luck Greenway” in Fuzhou.
Type of ParkSample ParkWeighted Comprehensive ScoreRankMean Value of TypeRank of Type
Comprehensive parkJinji Mountain Park9.472518.83931
Fuzhou Forest Park9.35012
Hot Spring Park7.695410
Special parkFuzhou Children’s Park8.537848.09442
Guangming Port Park8.50625
Fuzhou Zoo7.637814
Gucheng Park8.02227
Dengyun Reservoir7.76816
Ribbon gardenXindian River Waterfront Park7.7920118.07223
Jin’an River Park7.81809
Beijiang Riverside Park8.60653
Community parkChiqiao Park7.5870127.65444
Yangxia Sponge Park7.338113
Qinting Lake Park8.03818
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Zheng, Y.; Wang, S.; Zhu, J.; Huang, S.; Cheng, L.; Dong, J.; Sun, Y. A Comprehensive Evaluation of Supply and Demand in Urban Parks along “Luck Greenway” in Fuzhou. Sustainability 2023, 15, 2250. https://0-doi-org.brum.beds.ac.uk/10.3390/su15032250

AMA Style

Zheng Y, Wang S, Zhu J, Huang S, Cheng L, Dong J, Sun Y. A Comprehensive Evaluation of Supply and Demand in Urban Parks along “Luck Greenway” in Fuzhou. Sustainability. 2023; 15(3):2250. https://0-doi-org.brum.beds.ac.uk/10.3390/su15032250

Chicago/Turabian Style

Zheng, Yu, Shan Wang, Jinli Zhu, Shuo Huang, Linli Cheng, Jianwen Dong, and Yuxiang Sun. 2023. "A Comprehensive Evaluation of Supply and Demand in Urban Parks along “Luck Greenway” in Fuzhou" Sustainability 15, no. 3: 2250. https://0-doi-org.brum.beds.ac.uk/10.3390/su15032250

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