Spatial Pattern and Equity Evaluation of Urban Park: A Case Study of Shinan District, Qingdao

doi:10.21203/rs.3.rs-2224925/v1

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Spatial Pattern and Equity Evaluation of Urban Park: A Case Study of Shinan District, Qingdao

https://doi.org/10.21203/rs.3.rs-2224925/v1

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Urban parks play a distinctive and important role in satisfying residents’ demands on leisure and recreation, and thus have become the focus of research in the field of urban planning and sustainable development. The measurement of the equity of the spatial pattern of urban park plays an important role in optimizing the construction of urban parks. In this paper, the administrative streets of Shinan District of Qingdao City were taken as the spatial unit. Three aspects of urban park (supply quantity, landscape quality, and accessibility measures) were analyzed by the principal component analysis, two-step moving search method, and coupled coordination analysis. Results show that (1) Administrative streets have the most significant differences in accessibility measures and the least differences in landscape quality. Badaguan Street has the highest indexes in the number of urban parks supply and accessibility measures, and Zhuhai Road Street has the highest indexes in landscape quality. (2) On the whole, the coupling coordination of the spatial pattern of urban parks in Shinan District is poor, among which the coordination level of Badaguan Street is the highest and has moderately coordinated. Our results provide a valuable reference for sustainable urban design and planning.

Accessibility

Urban Parks

Spatial Pattern

Fairness Assessment

Urban parks are a valuable public resource that not only contribute to the improvement of the urban biological environment and the quality of life of city dwellers, but also play a significant role in the long-term sustainability of urban development ^{[1, 2]}. The number, size, and spatial layout of parks and green spaces directly affect the quality of the urban environment and the living standards of residents ^[3].

Numerous studies have demonstrated that cities with more green space can offer greater health advantages and enhance the standard of living for their citizens ^{[4, 5]}. Examples include minimizing the urban heat island effect, lowering blood pressure, cortisol levels, and anxiety, and boosting emotions and self-esteem ^[6–9]. Additionally, green spaces are linked to social advantages such as creating place attachment and intergroup trust ^[10,11]. By 2030, the urban population will be close to 5 billion, and the metropolitan region would cover 1.5 million square kilometers, according to the United Nations. But as urbanization quickly advances, it also brings population increase and land expansion ^{[12, 13]}, which causes an uneven spatial distribution of land resources. Urban green equity has received a lot of attention over the last 30 years and is currently a contentious social topic ^[14]. The connotation of urban park space equity can be divided into broad sense and narrow sense. In a broad sense, equity highlights the fact that urban residents not only have equitable access to public green resources, but also to the development of public green spaces, which is mostly studied in the subject of politics ^[15]. The allocation of public green resources like urban parks in terms of space is the narrower definition of public green space equality that receives more attention in this study.

Researchers both domestically and overseas have looked into how fair urban parks are. Xiong Huijin ^[16] used the technique of network analysis to analyze the accessibility of parks and green spaces in Nanchang. Shi Tuo ^[17] used the method of combining network analysis and buffer zone to analyze the accessibility of urban parks in Shenyang.Kong Jian Yu brought scene availability into the utilitarian assessment of metropolitan green space, however the openness computation embraces the expense distance strategy, which makes it challenging to analyze the openness of green space between urban areas on a level plane ^{[18, 19]}; Jim Yuan takes Lorentz bend and Gini coefficient as pointers to quantify the consistency of metropolitan green space dispersion ^[20]. In addition, many scholars use landscape ecology theories to quantitatively analyze the spatial distribution patterns of green space, and use various statistical methods to measure the spatial connectivity and evenness of the space^[21–23].

At present, the equity of urban parks is evaluated by various factors such as the number of parks, the quality of parks, and the accessibility of parks ^[24]. Spatial accessibility refers to how easy it is for residents to overcome a specific resistance to reach another service facility, and it is an important criterion to measure the reasonable spatial layout of urban service facilities, which has been widely used in studies ^[25–27]. There are not many studies on the quality of urban parks to evaluate their fairness ^[28].Scholars have previously looked into the various aspects of a park's design and appearance from different perspectives to evaluate the quality of urban park, such as its landscape pattern, species level, and community level^[29,30]. This paper aims to provide a comprehensive analysis of the park's quality from a perspective of landscape pattern.

According to this perspective, this study takes the Shinan District of Qingdao as its research area, analyzes from the three dimensions of urban park supply quantity, landscape quality, and accessibility measurement, and thoroughly employs the principal component analysis method, two-step mobile search method, coupling and coordination analysis, and other methods to evaluate the fairness of the spatial pattern of urban park, in order to provide reference for the optimal allocation and planning layout of the spatial pattern of urban park green space.

2.1. Study Area

Shinan District is a typical Qingdao urban area. As a research sample, it offers some reference value for the future logical design of urban parks. Statistics show that Qingdao's Shinan District has a permanent population of 486600 people and a total size of around 30.01 square kilometers (data source: the seventh census and the 2020 statistical yearbook of Shinan District of Qingdao). Administrative streets are chosen as spatial units for study in order to simplify the collection and analysis of data (Fig. 1).

2.2. Data Collection and Processing

The multi—source data used in this paper mainly include: 1) The administrative boundary of Shinan District and the area separated by administrative streets (data sources: 2020 statistics yearbook of Qingdao Shinan District, (qdsn.gov.cn)); 2) The quantity, size, entrances and exits, and geographic location of urban parks in Shinan District in 2020 (Fig. 2) (data source: Google high-definition remote sensing picture, Qingdao Municipal Bureau of Landscape Architecture and Greening);3) Shinan District 2020 road network (data source: open street map); 4) Shinan District administrative streets and residential areas population data (data sources: seventh population census, Qingdao Shinan District 2020 statistical yearbook, and sixth population census).

The data prepossessing this paper mainly includes:1) According to the 2019 Urban Green Space Planning Standard (GBT51346, 2019), combined with the residents' travel threshold, we divide the service radius of urban parks and level(Table 1); 2) The Shinan District road network data for 2020 were obtained using QGIS software, and the data were validated using Google high-definition remote sensing images and field investigation.3) To calculate the seventh census administrative street population data, use the data from of the sixth census administrative streets. The population data of a residential area is estimated using "the population data of this geographic unit/the number of residential areas in this spatial unit." 4) Using the SPSS software platform, principal component analysis and coupling coordination analysis are conducted.

Table 1

Basic criteria for classification of urban park levels
scale(hm²)	number(%)	level	service radius/m
≥ 50.0	2(10.5%)	comprehensive park I	5000
20.0—50.0	0	comprehensive park II	3000
10.0—20.0	1(5.3%)	Comprehensive Park III	2000
5.0—10.0	6(31.6%)	Community park I	1000
1.0—5.0	6(31.5%)	Community Park II	500
0.4—1.0	4(21.1%)	sightseeing park	300

3.1. Evaluation method of supply quantity

The size of urban parks is a crucial factor in determining the extent of their services ^[31]. The evaluation indicators of the supply quantity of parks mainly include the number of parks, green space area, green area per capita, and urban park green space coverage rate. In this study, administrative streets are utilized as spatial units and variables, and the number, area, per capita green area, and green coverage rate of urban parks are used to examine the fairness of the spatial pattern of urban parks.

3.2. Evaluation method of landscape quality

The landscape pattern index, which is based on the notion of landscape ecology, is used in this study to quantitatively assess the landscape quality of urban parks ^[32,33]. The foundation for selecting an index is based on its descriptive power, flexibility to the study aims, interdependence, and capacity for both vertical and horizontal comparison in real-world settings ^[34]. Based on this, Table 2 displays the landscape indicators used for this study ^[35]. Among them, largest Patch Index, Effective Mesh SizeSplitting Index, and Aggregation Index are positive indicators; all others are negative indicators. The Fragsts is used to calculate the landscape index, and then the principal component analysis method is used to integrate the results of each landscape index, based on the assumption that ArcGIS will be used to rasterize the distribution map of urban park green space ^{[36, 37]}.

3.3. Evaluation method of accessibility

The fairness of the arrangement of urban park is significantly influenced by the accessibility of urban parks ^[38]. The demand index and accessibility level serve as the foundation for measuring the fairness of the spatial distribution of urban parks ^[39]. Based on this, this study selects a two-step mobile search approach that computes accessibility by taking distance attenuation and supply and demand factors into account ^[40]. The average accessibility of all residential areas on the street is used to convey the accessibility results of the administrative street scale.

3.4. Coupling coordination analysis

The phenomenon known as coupling occurs when two (or more) systems or motions impact one another through a variety of interactions ^[41]. The quantity of urban parks supply, the quality of the landscape, and the accessibility assessment results may all be taken into account coupling coordination analysis. ^[42].

Table 2

Types of selected landscape indicators and their meanings
Type	Variable	Meaning
Area and density of patches	Patch Density	The number of patches per unit area in a landscape
Area and density of patches	Largest Patch Index	Describe the degree of impact of the largest patch
Shape of patches	Landscape Shape Index	Measures the complexity of the plaque shape.
	Patch Area-Weighted Mean	Measuring the spatial complexity
	Shape Index Mean	Indicates the complexity of the spatial shape
Spatial configuratio-n of the landscape	Landscape Division Index	Describe the degree of dispersion of the patches
	Effective Mesh Size	Describe the spatial scale of the landscape
	Splitting Index	Describe the degree of dispersion of the patches
	Aggregation Index	Describe the degree of aggregation of the patches

Table 3

Results of the number of urban parks supplied in shinan district
Street name		Park Area/hm²	Per capita green area/m²	Proportion of green space/%	Comprehensive indicators
Badaguan Street	36125	178.64	83.81	22.31%	0.60
Badahu Street	65948	0.48	0.09	0.22%	0.01
Badaxia Street	36160	8.08	4.30	2.40%	0.05
Jiangsu Road Street	53030	13.46	2.62	10.32%	0.08
Jinmen Road Street	35599	82.80	10.95	18.61%	0.20
Hong Kong Middle Road Street	51389	0.00	0.00	0.00	0.00
Yunnan Road Street	75619	0.00	0.00	0.00	0.00
Zhanshan Street	18791	0.00	0.00	0.00	0.00
Zhongshan Road Street	21316	4.06	1.14	2.39%	0.04
Zhuhai Road Street	50136	5.30	1.46	1.35%	0.02
Jinhu Road Street	42530	0.00	0.00	0.00	0.00

4.1. Supply Quantity

The comprehensive index of supply of urban parks in Badaguan Street performs best, followed by Jinmen Road Street, and the comprehensive indicators of Badahu Street performed poorest, per the results of the comprehensive index of quantity (Table 3). The outcome is influenced by the size of urban parks and the quantity of year-round occupants living on administrative streets. Badaguan Street has the greatest concentration and coverage of urban parks, and that all streets have low population densities, leading to the highest comprehensive index; Hong Kong Middle Road Street, Yunnan Road Street, Zhanshan Street, and Jinhu Road Street do not have any urban parks and have comprehensive indices of zero; Badahu Street has the fewest and broadest urban parks and has the most population, giving it the lowest comprehensive index. Therefore, only by looking at the supply of urban parks, it is clear that the spatial distribution of parks in Shinan District's administrative streets is drastically different and has significant differences.

4.2. Landscape quality

The fragmentation of the landscape mostly reflects the heterogeneity in urban park quality. According to an analysis of patch area and density from the standpoint of landscape fragmentation, each administrative unit's variation in urban park area and density is relatively small (Fig. 3 (a)), with a higher prevalence of large urban parks along Badahu Street and Zhuhai Road Street. The urban parks along Badaguan and Jinmen Road Street have the most complicated shapes and the most fragmented landscapes of the three indicators representing the structure of the patches (Fig. 3 (b)). The degree of spatial aggregation of the urban park is reflected in the spatial layout of the landscape (Fig. 3(c)). The spatial distribution is more dispersed overall and the fragmentation of urban parks is higher in Badaguan Street, Jiangsu Road Street, and Zhongshan Road Street. The aggregation index of Badaguan Street, Badaxia Street, and Zhuhai Road Street is higher, indicating that their urban park coverage areas are more concentrated in local area.

Determine each administrative street's overall quality indicators using the principal component analysis method. The comprehensive scores and rankings of the urban parks' landscape quality in each administrative street are shown in Fig. 4. While Zhongshan Road Street has the weakest landscape quality, Zhuhai Road Street and Badahu Street have good comprehensive quality. Urban parks in each administrative street have varying degrees of quality.

4.3. Reach-ability measure

As shown in Fig. 5, the accessibility indexes of Badaguan Street and Zhuhai Road Street are better. Badaguan Street has the highest park area and smaller population, so the accessibility results are the best. Due to the tiny population within each tier's service area and the ability of each tier to cover the majority of Zhuhai Road Street, the accessibility index of Zhuhai Road Street is second only to Badaguan Street. Because the service area of the nearby city parks cannot spread to Zhanshan Street, the accessibility index of Zhanshan Street is 0. To some extent, it reflects the inconvenience of urban residents within that street to reach the urban parks within the service area.Shinnan District contains a number of administrative streets, such as Zhanshan Street, Badahu Street, Badaxia Street, and Hong Kong Middle Road Street, that have a condensed service area with radiating parks. Overall, the accessibility results for the western area of the Shinnan District are relatively good.

4.4. Coupling coordination analysis

According to Fig. 6, the administrative streets with intermediate coordination only include Badaguan Street; the streets with primary coordination include Jinmen Road Street and Zhuhai Road Street; Jiangsu Road Street is the street with the least amount of coordination; there are two streets with mild disorder; three streets with moderate maladjustment; and two streets with severe maladjustment. As a result, the Shinan District's comprehensive level of urban park green space is not high, and there are significant discrepancies between administrative streets, leading to an uneven distribution of resources.

Based on the findings of this paper, Planning strategies have been proposed to reduce the disparity in the spatial arrangement of urban parks.First, from the perspective of the number of parks, In administrative roadways with few city parks, like Hong Kong Middle Road Street, Yunnan Road Street,

Zhanshan Street, and Jinhu Road Street, more parks should be added. The south of the city has a high development density, which limits the amount of land resources that are available. Making the most of vacant land and expanding small urban park green spaces based on residential areas. On the one hand, merging the existing green space resources, on the basis of which the nearby green spaces are designed and integrated to develop huge park.

Second, from the standpoint of park quality, if we want to reduce the degree of difference in their quality, on the one hand, we should start with the original urban parks themselves and reduce the difference by increasing the area of the park green space and expanding the functions of park use; on the other hand, we should construct new urban parks with higher park quality in administrative streets with poor park quality.

Last but not least, from the perspective of accessibility, the primary influencing elements in this study are the geographic location of parks, their size, and the proximity to residential areas. As a result, increasing the number of urban parks within a specific radius, with the residential area at its center, can increase accessibility of urban parks. On the other hand, increasing the service area of existing urban parks can also boost accessibility of urban parks.

However, there is still a certain degree of deficiency in this paper. Because the population data of residential areas in the study area is macro level statistics based on big data, it is impossible to accurately calculate the number of permanent residents in residential areas, and there is a certain error, so the population data lack accuracy. Since the service area of urban parkland at the urban junction around the study area is not fully considered, it will have some impact on the accessibility results within the spatial unit. The measurement method used in this paper is based on macro-level big data, and since urban residents are the main users of urban parks, the lack of micro dimensions such as urban residents' demand for urban park use and usage evaluation can limit the research results. Thus, more consideration should be given to the above factors in future studies.

With the help of geographic information system, taking administrative streets as spatial units, this study takes the number of park green space, street green space area, per capita green space area, green space proportion, etc. as quantitative equity evaluation indicators; Taking the area, density, shape and landscape spatial configuration of patches as the evaluation indicators of quality equity; The service scope of urban park green space is used as an indicator to measure the accessibility of residential areas. According to the above three dimensions, the coupling and coordination analysis of the fairness of the spatial pattern of urban park green space in Shinan District is carried out, and the coupling and coordination index of different streets is obtained. The results show that Badaguan street has the highest comprehensive index in the measurement of green space supply and accessibility; Zhuhai Road Street performs best in the landscape quality index. The results of all indicators show that Badaguan street has the highest coupling level, and Hong Kong Middle Road Street and Yunnan Road Street have the lowest coupling level.

The fairness of urban green space has been widely concerned by scholars. The fairness of urban park green space pattern is of great significance for ecological development and urban construction. In the era of big data, we can obtain more abundant and diverse data to assist research, and also provide more plans and ideas for the development of green equity. The micro scale of this study stays on the residential area. In the future research, we can reduce the scale to the urban residents themselves, and more accurately formulate the optimization scheme and system of the fairness of park green space. At the same time, when selecting and integrating various indicators, we can choose a reasonable integration method according to the actual situation of different regions. At the same time, we can form a certain reference mode in the suggestions of optimizing park green space, which can be used for reference and utilization by future urban planners.

Conflicts of interests

All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.

Date availability statement

All data generated or analysed during this study are included in this published article.

Funding

This work was funded by the Open Fund of innovation institute for Sustainable Maritime Architecture Research and Technology (iSMART), Qingdao University of Technology (No. C2020-037).

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Spatial Pattern and Equity Evaluation of Urban Park: A Case Study of Shinan District, Qingdao

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Abstract

Figures

1. Introduction

2. Materials And Methods

2.1. Study Area

2.2. Data Collection and Processing

3. Research Methods

3.1. Evaluation method of supply quantity

3.2. Evaluation method of landscape quality

3.3. Evaluation method of accessibility

3.4. Coupling coordination analysis

4. Results And Analysis

4.1. Supply Quantity

4.2. Landscape quality

4.3. Reach-ability measure

4.4. Coupling coordination analysis

5. Discussion

6. Conclusions

Declarations

References

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