The Coupling Coordination and Influencing Factors of Urbanization and Ecological Resilience in the Yangtze River Delta Urban Agglomeration, China

Abstract

Twenty-six cities in the Yangtze River Delta urban agglomeration were taken as the research object, and this study comprehensively evaluated urbanization quality and ecological resilience from 2005 to 2020. On this basis, the spatiotemporal evolution characteristics and main influencing factors of the coupling relationship between urbanization and ecological resilience were systematically explored using a coupling coordination model and panel Tobit regression model. The results can be summarized as follows: (1) from 2005 to 2020, the quality of urbanization in the Yangtze River Delta urban agglomeration continued to grow, the level of ecological resilience grew slowly and fluctuated, and the development among municipalities tended to be balanced. (2) The overall coupling coordination degree of urbanization and ecological resilience showed a continuous increasing trend, and the coupling coordination type changed from basic coupling coordination to good coupling coordination. The number of cities with lagging urbanization quality decreased significantly; spatially, the gap in the coupling coordination degree between municipalities narrowed, and the cities with good coupling gradually clustered. (3) The results of the panel Tobit regression showed that the differences in the spatial evolution of coupling coordination mainly resulted from the interaction of drivers such as real utilized foreign capital, per capita GDP, carbon emission intensity, the proportion of science and technology expenditure to fiscal expenditure, the ratio of per capita disposable income of urban and rural residents, fixed asset investment in municipal utility construction, and the index of ecological land area ratio. In the future, the coupling coordination degree of urbanization and ecological resilience should be improved based on the type of coupling coordination according to local conditions, and the seven influencing factors should be carefully examined to accelerate the high-quality integrated development of the Yangtze River Delta.

1. Introduction

Global climate change and urbanization have increased rapidly and cities, with high-density populations and development, have shown systemic sensitivity and vulnerability to these changes [1,2]. In the early stage of urbanization, quantity and speed were emphasized at the expense of coordinated development and quality evaluations, which further aggravated ecological and environmental pollution [3]. This situation has decreased the ability of urban ecosystems to mitigate unexpected risks, leading cities to gradually become sources of various high-risk disasters [4]. Therefore, the coordination of urbanization and the ecosystem has become important for urban sustainable development [5]. Enhancing the capacity of cities to manage and prevent unexpected and hazardous events has become a new hotspot with theoretical and practical challenges for scholars in urban research [6,7]. The urbanization level in China has significantly increased since the reform and opening up. According to statistics, China’s urbanization rate increased from 17.92% to 63.89% between 1978 and 2020 but was accompanied by increasingly serious ecological and environmental problems such as industrial pollution, water quality degradation, and urban flooding [8]. Resilience has attracted widespread attention, as cities are at increased risk of natural disasters and environmental damage [9]. In the 14th Five-Year Plan in 2021, China emphasized “improving the quality of urbanization development” and proposed “building resilient cities” for the first time, further demonstrating that resilience has become an important criterion for urban safety [10]. In 2022, the 20th report of the Communist Party of China mentioned “strengthening urban infrastructure construction and building liveable, resilient, and smart cities”. The relationship between urbanization and the ecological environment is a pair of key contradictions in the field of human–land relationships throughout the process of urban development [11]. Only when urbanization and urban ecological resilience develop in harmony can we achieve high-quality socio-economic development. Thus, there is great academic and social value in exploring the coupling and coordinated relationship between urbanization quality and ecological resilience and elucidating the key influencing factors for achieving integrated and high-quality development in the region.

The word “resilience” is of Latin origin and originally means “to return to the initial state” [12]. It was first used in ecology by Holling as an indicator for measuring the stable state of an ecosystem, namely, the ability of an ecosystem to recover to a stable state after suffering shocks and disturbances [13]. In recent years, globally, the frequent occurrence of climate disasters and increased risks of public emergencies have driven the concept of urban resilience, in which interest has rapidly grown and become widespread [14]. An urban system is a complex adaptive system in which the ecosystem is only one subsystem [15]. Therefore, ecological resilience is one of the important dimensions of urban resilience [16]. This paper defines “ecological resilience” as the ability of urban ecosystems to withstand ecological risk shocks, adapt to developmental changes, recover quickly, and learn to improve urban ecosystem functions when disturbed by uncertain disaster risks.

In urbanization and ecological resilience research, many studies have been conducted on the relationship between urbanization and the ecological environment. Existing studies have objectively confirmed the complex interactions between urbanization and the ecological environment [17]. The process of urbanization is influenced by the dynamics of interactive stress and coupling that occur between the various aspects of urbanization and ecosystems [18]. Previous studies have measured these dynamics from the perspective of coupling and coordination [19,20]. Most results suggest that their interactions result in a nonlinear coupling relationship with an “inverted U-shaped” curve [21]. Overall, the academic community has accomplished much in the field of urbanization–ecological environment relationships. With the increasing application of resilience theory in urbanization research, academics have begun carrying out productive exploration of urbanization and ecological resilience based on the resilience perspective. Ding and Liu used the spatial Durbin model to demonstrate the “inverted U-shaped” relationship between urbanization and ecological resilience and showed that urbanization has a spatial spillover effect on ecological resilience [22]. Furthermore, Li et al. constructed a “potential-connectivity-resilience” adaptive ecological risk assessment framework and found that the level of ecological resilience first gradually declines and then recovers as the stage of urban development increases [23]. Some scholars have also considered the coupling and coordination of urbanization and ecological resilience. For example, Wang et al. [24] found that in the Pearl River Delta region, where economic and social levels are high, the coupling coordination between the two systems showed an overall decreasing trend, while in the Ningxia region of the arid zone, the coupling coordination between the two systems showed a steadily increasing trend [25]. In terms of the factors influencing the coordinated development of urbanization and ecological resilience, as mentioned above, the few current studies on the coupling coordination of urbanization and ecological resilience are limited to empirical analyses of the spatial and temporal variation in the coupling coordination degree. At present, research on these factors is only in the preliminary stage. Zhang et al. used the grey correlation model to rank the factors influencing the coupling coordination between urbanization and urban resilience, and the correlation degrees of the influencing factors decreased in the following order: the level of economic development, social security system, emergency communication capacity, risk response capacity, population density, and government investment in disaster response [26].

In summary, while previous studies have focused on urban resilience, few studies have discussed the coupling and coordination relationship between urbanization and the ecological environment from a resilience perspective, especially regarding the mechanism and direction of influencing factors between the two systems, which needs further exploration. This study focuses on one of the important dimensions of urban resilience, ecological resilience. On this basis, this study takes 26 cities in the Yangtze River Delta urban agglomeration as the study area and comprehensively evaluates ecological resilience based on four dimensions of urbanization quality: “population-economy-spatial-social” and three levels of “stability-adaptability-dissipation”. This paper innovatively broke down urban ecological resilience into three important levels, namely, stability, adaptability, and dissipation, and constructed an evaluation index system of ecological resilience based on this. The spatial and temporal analysis of the coupling and coordination between urbanization and ecological resilience is discussed using a coupling coordination degree model. Furthermore, the factors and relationships affecting the degree of coupling and coordination between urbanization and ecological resilience are analyzed via a panel Tobit regression model. A strategy for the coupling and coordination between urbanization quality and ecological resilience is proposed based on the results of the study to provide a basis for policies related to the sustainable and high-quality integrated development of the Yangtze River Delta urban agglomeration. This study aims to provide empirical references for the formulation of policies related to sustainable and high-quality integrated development of the Yangtze River Delta urban agglomeration.

2. Materials and Methods

2.1. Study Area

The Yangtze River Delta urban agglomeration is an important intersection of the Belt and Road and the Yangtze River Economic Belt. According to the Yangtze River Delta Urban Agglomeration Development Plan (2014–2020) adopted by the State Council, the study area covers three provinces and one city in Shanghai, Jiangsu, Zhejiang, and Anhui, including 26 municipalities (Figure 1) [27]. One of the most developed regions in China, the Yangtze River Delta urban agglomeration is developing rapidly [28], with abundant natural resources [29]. By 2020, the urbanization rate of the Yangtze River Delta urban agglomeration reached 76.2%, 12.3 percentage points higher than the national average (data source: National Bureau of Statistics). The Yangtze River Delta urban agglomeration is the most densely populated and economically developed region in China, as well as being a group of towns with the highest level of urbanization and the highest urban density [30]. However, the intensive exploitation of land resources has greatly increased the ecological risk in cities in the future [31], and the construction of the Shanghai–Nanjing–Hangzhou industrial bases has also made the contradiction between urbanization and environmental quality in the Yangtze River Delta increasingly acute [32]. Zhang et al. conducted a study on the coordination between development intensity and habitat quality in the Yangtze River Delta integrated region and found that the development intensity index of the Yangtze River Delta integrated region increased from 0.3833 in 2005 to 0.7833 in 2020, and the habitat quality decreased from 0.5049 in 2005 to 0.4937, indicating that the contradiction between development intensity and habitat quality will further intensify, and the integration of eco-green and high-quality development will face a greater challenge [33]. In addition, Zhang et al. compared the three major urban agglomerations of Beijing–Tianjin–Hebei, the Yangtze River Delta, and the Pearl River Delta and found that the Yangtze River Delta urban agglomeration has consistently lower economic–environmental harmonization, while at the same time, the coupled harmonization of this urban agglomeration has the fastest rate of change [34]. In comparison, it is more representative and typical to choose the Yangtze River Delta urban agglomeration as the study area for the coupling and coordination of urbanization and ecological resilience. Therefore, taking the Yangtze River Delta urban agglomeration as the research object, the coordination relationship between urbanization quality and ecological resilience level and the factors influencing these two variables are explored, which can help improve the urban prevention and control of sudden disasters and build a green, safe, resilient, sustainable, and high-quality integrated urban agglomeration to improve the reference.

2.2. Research Methods

2.2.1. Construction of the Evaluation Index System

The development of urbanization involves multiple aspects, such as population development, land expansion, industrial development, and social construction [35,36,37]; thus, this study constructs a comprehensive evaluation index of urbanization quality from four dimensions: demographic, economic, spatial, and social [27]. Population-related indicators of high-quality new urbanization were selected for urban population size, the scale of the regional labor force [38], and population quality. In the dimension of economic urbanization, regional economic vitality and consumption vitality were measured from the following four aspects: the regional industrial structure, people’s living standard, the local financial level, and the marketization level. In the selection of spatial urbanization dimension indicators, the degree of construction for regional land development and utilization, infrastructure, and economic capacity were considered. For the social urbanization dimension, indicators characterizing people’s well-being and cultural construction were chosen to measure high-quality improvements to infrastructure and basic public services.

Some scholars have used net primary production as the elastic index [15] or an ecological network mode [39] to evaluate ecological resilience, while others have based their models on the DPSIR framework [40]. In most studies, ecological resilience evaluation index systems were built based on the connotation dimensions of resistance, adaptability, and recovery [25,41,42] or on the characteristic dimensions of resilience such as defense capacity, response capacity, and learning capacity [43]. By integrating the previous research results, this study deconstructs ecological resilience into three dimensions: the ecological stability level of background resources, ecological adaptability to issues affecting green security, and the effectiveness of ecological strategies involving solubility for pollution prevention and control.

Based on the above analysis, the indicators were further screened on the basis of existing research results, combined with the actual situation of the Yangtze River Delta urban agglomerations, and accounting for the principles of applicability, scientificity, operability, and data continuity.

Finally, two comprehensive evaluation index systems were formed: one for measuring the urbanization quality index system, which includes 14 basic evaluation indexes from the four dimensions of population urbanization, economic urbanization, spatial urbanization, and social urbanization (

Table 1. Urbanization quality evaluation index system.

Target Layer	Guideline Layer	Indicator Layer	Unit	Indicator Type	Indicator Weights (%)	Source of Indicator
Urbanization quality	Population urbanization	Population urbanization rate	%	+	5.950	[27]
		Proportion of population employed in nonagricultural industries	%	+	9.332	[35,38]
		Number of students enrolled in higher education per 100,000 people	People	+	9.990	[36]
	Economy urbanization	Disposable income per capita	CNY	+	7.192	[44]
		Value added of tertiary industry as a proportion of GDP	%	+	5.854	[36]
		Local general public budget revenue per capita	CNY	+	4.927	[38]
		Total retail sales of social consumer goods per capita	CNY	+	5.260	[27]
	Space urbanization	Land urbanization rate	%	+	7.693	[45]
		Road area per capita	km/km2	+	11.936	[27]
		Fixed asset investment per unit built-up area	One hundred million CNY/km2	+	7.364	[35]
	Social urbanization	Number of beds in medical and health institutions per 10,000 people	Piece	+	4.695	[35]
		Public library collections per 10,000 people	One thousand volumes	+	7.446	[27]
		Teacher–student ratio in compulsory education	%	+	5.061	[46]
		Number of public transportation vehicles per 10,000 people	Vehicle	+	7.300	[27]

); and the other for measuring the ecological resilience level, which includes 9 basic evaluation indexes in 3 aspects: ecological stability, ecological adaptability, and ecological solubility (

Table 2. Ecological resilience evaluation index system.

Target Layer	Guideline Layer	Indicator Layer	Unit	Indicator Type	Indicator Weights (%)	Source of Indicator
Ecological resilience level	Ecological stability	Arable land per capita	m2	+	15.281	[20]
		Water resources per capita	m3	+	8.439	[47]
		Forest coverage rate	%	+	18.153	[48]
	Ecological adaptability	Park green land area per capita	m2	+	9.962	[41,49]
		Natural gas pipeline density	km/km2	+	8.982	/
		Drainage pipes density in built-up areas	km/km2	+	8.632	[50]
	Ecological solubility	Centralized treatment rate of sewage treatment plants	%	+	10.556	[41]
		Comprehensive utilization rate of industrial solid waste	%	+	10.818	[50]
		Harmless disposal rate of domestic waste	%	+	9.177	[51]

). To be clear, the indicator type “+” refers to a positive indicator and “−” refers to a negative indicator.

2.2.2. CRITIC Weighting Method

This paper used an objective assignment method to calculate the weight coefficients of the urbanization and ecological resilience evaluation index system to reduce interferences from subjective factors and better reflect the utility of evaluation indicators. CRITIC (criteria importance through intercriteria correlation) is an objective weight evaluation method first proposed by Diakoulaki [52]. This calculation method considers not only the influence of the index variation degree on the weight but also the conflict among indicators. The former is expressed in the form of standard deviation; the larger the standard deviation is, the greater the fluctuation of indicator data and the higher the indicator weight. The latter is expressed in the form of a correlation coefficient; if there is a strong positive correlation between two indicators, then the conflict is smaller and the indicator weight is lower.

The amount of information is calculated for each indicator:

$$C_j={\sigma }_j{\sum }_{j=1}^n(1-r_{ij})$$

(1)

The weights of each indicator are calculated:

$${\omega }_j=\frac{C_j}{{\sum }_{j=1}^n{C}_j}$$

(2)

The overall evaluation index of each city is calculated:

$$U_{1\lambda i}={\sum }_{j=1}^n{\omega }_j \times X_{\lambda ij}, U_{2\lambda i}={\sum }_{j=1}^n{\omega }_j \times X_{\lambda ij}$$

(3)

where $\lambda =1,2,3,\dots ,16$ denotes the year; $i=1,2,3,\dots ,m$ denotes the regions of the Yangtze River Delta urban agglomeration;$j=1,2,3,\dots ,n$ denotes the $j_{th}$ evaluation indicator; $C_j$ denotes the influence degree of the $j_{th}$ evaluation indicator on the index system; ${\sigma }_j$ is the standard deviation of the $j_{th}$ evaluation indicator; $r_{ij}$ represents the correlation coefficient between the $i_{th}$ evaluation index and the $j_{th}$ evaluation index; ${\omega }_j$ is the objective weight of the $j_{th}$ evaluation index; $U_{1\lambda i}$ is the comprehensive urbanization quality index o in the $\lambda$ year $i$ region of the Yangtze River Delta urban agglomeration; and $U_{2\lambda i}$ is the composite index of the ecological resilience level of the Yangtze River Delta urban agglomeration in the $\lambda$ year $i$ region.

2.2.3. Coupling Coordination Degree Model

In the field of physics, coupling refers to the phenomenon of two or more systems interacting with each other through their own and external effects [17]. The coupling degree is used to describe the degree of impact between systems. Therefore, the coupling degree model is chosen to reveal the resonance relationship between urbanization quality and the ecological resilience level [48]. The specific calculation formula is as follows:

$$C=2\times {\left[\left(U_1\times U_2\right)/{\left(U_1+U_2\right)}^2\right]}^{1/2}$$

(4)

In the above equation, $C$ is the coupling degree, and the larger its value is, the stronger the interaction and influence between the systems; $U_1$ is the composite evaluation index of urbanization quality; and $U_2$ is the comprehensive evaluation index of ecological resilience level.

Although the coupling degree model can calculate the degree of interaction and influence between urbanization and ecological resilience, it cannot easily reflect the overall level of “synergy” between these two systems. Therefore, the coordination degree model is introduced to discuss the degree of coupling and coordination between the two systems of urbanization quality and ecological resilience level; its model formula is as follows:

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

(5)

$$D=\alpha U_1+\beta U_2$$

(6)

In the above equation, $T$ is the comprehensive coordination index and $D$ is the coupling coordination degree of urbanization quality and ecological resilience level. The higher the degree of coupling coordination, the stronger the degree of interconnection and interdependence between systems [53]. $\alpha$ and $\beta$ are underdetermined coefficients, which can be interpreted as the relative importance of the two subsystems. In this study, the urbanization quality of cities is as equally important as the ecological resilience level; therefore, $\alpha$ and $\beta$ have values of 0.5 [54]. Based on the results of other studies [24,55] combined with the actual coupling and coordination results of the Yangtze River Delta urban agglomeration, the coupling and coordination types of urbanization and ecological resilience were classified into the following 4 major categories and 12 subcategories (

Table 3. Classification of coupling coordination degree types of urbanization and ecological resilience.

Type	Coupling Coordination Degree (D)	Subclass  (${\mathbf{S}\mathbf{u}\mathbf{b}}_1,{\mathbf{S}\mathbf{u}\mathbf{b}}_2,{\mathbf{S}\mathbf{u}\mathbf{b}}_3······{\mathbf{S}\mathbf{u}\mathbf{b}}_{12}$)	${\mathit{U}}_1$$\mathbf{with} {\mathit{U}}_2$ Relative Size
High quality coupling coordination	$0.9<D\le 1.0$	High quality coordination–lagging urbanization quality (${\mathrm{S}\mathrm{u}\mathrm{b}}_1$)	${U_2-U}_1>0.1$
		High quality coordination–lagging ecological resilience (${\mathrm{S}\mathrm{u}\mathrm{b}}_2$)	$U_1-U_2>0.1$
		High quality coordination (${\mathrm{S}\mathrm{u}\mathrm{b}}_3$)	$0\le \left|U_1-U_2\right|\le 0.1$
Good coupling coordination	$0.7<D\le 0.9$	Good coordination–lagging urbanization quality (${\mathrm{S}\mathrm{u}\mathrm{b}}_4$)	${U_2-U}_1>0.1$
		Good coordination–lagging ecological resilience (${\mathrm{S}\mathrm{u}\mathrm{b}}_5$)	$U_1-U_2>0.1$
		Good coordination (${\mathrm{S}\mathrm{u}\mathrm{b}}_6$)	$0\le \left|U_1-U_2\right|\le 0.1$
Basic coupling coordination	$0.5<D\le 0.7$	Basic coordination–lagging urbanization quality (${\mathrm{S}\mathrm{u}\mathrm{b}}_7$)	${U_2-U}_1>0.1$
		Basic coordination–lagging ecological resilience (${\mathrm{S}\mathrm{u}\mathrm{b}}_8$)	$U_1-U_2>0.1$
		Basic coordination (${\mathrm{S}\mathrm{u}\mathrm{b}}_9$)	$0\le \left|U_1-U_2\right|\le 0.1$
Coupling dissonance	$0<D\le 0.5$	Coupling dissonance–urbanization quality hindered (${\mathrm{S}\mathrm{u}\mathrm{b}}_{10}$)	${U_2-U}_1>0.1$
		Coupling dissonance–ecological resilience hindered (${\mathrm{S}\mathrm{u}\mathrm{b}}_{11}$)	$U_1-U_2>0.1$
		Coupling dissonance (${\mathrm{S}\mathrm{u}\mathrm{b}}_{12}$)	$0\le \left|U_1-U_2\right|\le 0.1$

).

2.3. Data Sources and Preprocessing

2.3.1. Data Sources

Since the 11th Five-Year Plan, the Yangtze River Delta urban agglomeration has entered a stage of rapid economic development. At the same time, during the period from 2005 to 2020, accompanied by high economic growth and rapid urbanization, the ecological security was facing increasing threats and the contradiction between resources–environment and economic development was becoming more and more prominent in the Yangtze River Delta urban agglomeration [30]. Therefore, we chose 2005–2020 as the study period.

In this study, panel data such as urbanization quality evaluation indicators, ecological resilience level evaluation indicators, and influence factor variables of 26 cities in the Yangtze River Delta urban agglomeration from 2005 to 2020 were used as the research samples. Social statistical data were obtained from the China Urban Statistical Yearbook (2006–2021), the China Urban Construction Statistical Yearbook (2006–2021), and the statistical yearbooks and bulletins of the 26 cities over the years; some missing data and outliers were accounted for by the average values of adjacent years or provinces. Data on the administrative divisions of the Yangtze River Delta urban agglomeration were obtained from the Resource and Environmental Sciences and Data Center (http://www.resdc.cn, 3 March 2023) [56]; the base map was not modified based on 2015 data. The arable land area was mainly taken from the Land Change Survey Data (2005–2014) and the Sharing Application Service Platform for Land Survey Results (https://gtdc.mnr.gov.cn, 7 March 2023) (2015–2016). Due to substantial adjustments to the criteria for identifying arable land in the “Third National Land Resource Survey”, there are interface problems with the date results of the “Second National Land Resource Survey”. The carbon emission data of the Yangtze River Delta urban agglomeration from 2005 to 2019 were obtained from the Carbon Emission Accounts & Datasets (CEADs) [57] and the carbon emission data of 2020 were obtained by interpolation.

2.3.2. Data Preprocessing

Different indicators often have different properties, orders of magnitude, units of magnitude, etc. To eliminate the influence of dimensional differences among indicators on the data analysis results and address comparability issues between the data, this paper adopts the polarization method to normalize and preprocess the original statistics of the indicators and convert the original data into standardized values with no order of magnitude differences in the range of [0, 1].

The positive indicator normalization formula is:

$$X_{\lambda ij}=\frac{x_{\lambda ij}-X_{min}}{X_{max}-X_{min}}$$

(7)

The negative indicator normalization formula is:

$$X_{\lambda ij}=\frac{X_{max}-x_{\lambda ij}}{X_{max}-X_{min}}$$

(8)

where $\lambda =1,2,3,\dots ,16$ denotes the year; $i=1,2,3,\dots ,m$ denotes the regions of the Yangtze River Delta urban agglomeration; $j=1,2,3,\dots ,n$ represents the evaluation index; and $x_{\lambda ij}$ denotes the original statistical value of the indicator in the $\lambda$ year $i$ region. $X_{\lambda ij}$ denotes the normalized standard values of the $j_{th}$ indicator in the $\lambda$ year $i$ region; $X_{max}$ and $X_{min}$ denote the maximum and minimum values of the $j_{th}$ indicator in all regions in all years, respectively.

3. Results

3.1. Overview of Urbanization Quality and Ecological Resilience Level

As shown in Figure 2, the urbanization quality and ecological resilience level of the Yangtze River Delta urban agglomeration from 2005 to 2020 were comprehensively evaluated based on the above process. During the study period, the urbanization quality and ecological resilience levels as a whole showed an increasing trend to varying degrees. To better analyze the spatial pattern and dynamic evolution characteristics of the urbanization quality and ecological resilience level in the 26 cities in the Yangtze River Delta urban agglomeration, we used ArcGIS10.8 to visualize them at four time points, 2005, 2010, 2015, and 2020. The specific results are as follows:

3.1.1. Spatiotemporal Evolutionary Characteristics of Urbanization Quality

In terms of the time dimension, Figure 2 shows that the overall level of urbanization quality in the Yangtze River Delta urban agglomeration improved significantly between 2005 and 2020, and the comprehensive index of urbanization quality reached 0.51 in 2020, more than twice as high as that in 2005. The growth rate (

Table 4. Average annual growth rate of urbanization quality in 26 cities in the Yangtze River Delta urban agglomeration (unit: %).

City	Shanghai	Nanjing	Wuxi	Changzhou	Suzhou	Nantong	Yancheng	Yangzhou	Zhenjiang	Taizhou (Jiangsu)
rate	2.55	2.47	3.32	3.96	3.84	4.45	4.30	4.26	4.20	4.34
City	Hangzhou	Ningbo	Jiaxing	Huzhou	Shaoxing	Jinhua	Zhoushan	Taizhou (Zhejing)	Hefei	Wuhu
rate	4.60	4.75	4.67	4.83	4.78	4.88	4.88	4.93	5.86	5.78
City	Ma’anshan	Tongling	Anqing	Chuzhou	Chizhou	Xuancheng
rate	6.35	6.59	8.77	9.21	9.69	8.69

) shows that the urbanization quality of all cities in the Yangtze River Delta urban agglomeration has reached a positive growth trend during the study period, indicating that since the 11th Five-Year Plan, the cities in the Yangtze River Delta urban agglomeration have experienced strong and active economic and social development, continuous optimization and upgrading of industrial structure, and continuous improvement of residents’ living standards. Furthermore, the region has vigorously promoted infrastructure construction, and public service facilities have gradually improved. From the perspective of spatial patterns, Figure 3 shows that the difference in the comprehensive evaluation index of urbanization quality within the urban agglomeration is gradually narrowing; the areas with a high comprehensive index of urbanization quality are mainly concentrated in central cities such as Shanghai, Nanjing, Wuxi, and Hangzhou. The overall distribution trends for Shanghai and Nanjing are “dual-core leading”. Since Shanghai and Nanjing are the only mega-city and super-city, respectively, in the Yangtze River Delta Urban Agglomeration Development Plan (2016–2020), they have obvious location advantages and strong comprehensive economic strength.

A comprehensive analysis of the spatial and temporal evolution of urbanization quality reveals that the top three growth rates are in Chizhou, Chuzhou, and Anqing in Anhui Province. Shanghai and Nanjing, which have high urbanization quality composite indexes, have relatively low growth rates. This finding indicates that there may be a negative correlation between the growth rate and the comprehensive index of urbanization quality in the Yangtze River Delta urban agglomeration. That is to say, cities with relatively high growth rates generally have low comprehensive indexes of urbanization quality, which also confirms that “the progression of urbanization in the Yangtze River Delta urban agglomeration has converged spatially” [58].

3.1.2. Spatiotemporal Evolutionary Characteristics of Ecological Resilience Level

In terms of time series, Figure 2 shows that the composite index of ecological resilience is higher than the urbanization quality of 26 cities in the Yangtze River Delta urban agglomeration, and the overall ecological resilience level had a slow, fluctuating increase during the period 2005–2020, increasing from 0.40 in 2005 to 0.54 in 2020.

Table 5. Average annual growth rate of ecological resilience level in 26 cities in the Yangtze River Delta urban agglomeration (unit: %).

City	Shanghai	Nanjing	Wuxi	Changzhou	Suzhou	Nantong	Yancheng	Yangzhou	Zhenjiang	Taizhou (Jiangsu)
rate	3.33	1.73	1.02	2.23	−0.26	1.87	1.86	2.07	2.12	1.41
City	Hangzhou	Ningbo	Jiaxing	Huzhou	Shaoxing	Jinhua	Zhoushan	Taizhou (Zhejing)	Hefei	Wuhu
rate	1.13	2.51	1.05	2.03	0.77	0.70	1.70	1.25	0.73	1.50
City	Ma’anshan	Tongling	Anqing	Chuzhou	Chizhou	Xuancheng
rate	1.21	4.16	6.56	5.76	1.65	4.39

shows the growth rate of the ecological resilience level of 26 cities in the Yangtze River Delta urban agglomeration. Differences can be found regarding the evolution of the time series of ecological resilience of different cities. Urbanization contributed to rapid growth in the urban resident population in Suzhou, which reduced the per capita occupancy, resulting in a negative growth rate; however, the remaining 25 cities showed different degrees of positive ecological resilience level growth, indicating that cities with slowly fluctuating growth occupy a dominant position [47]. From the spatial structure perspective, Figure 4 shows that the level of ecological resilience of the Yangtze River Delta urban agglomeration is spatially unbalanced. From 2005 to 2020, the spatial pattern of the ecological resilience in the Yangtze River Delta urban agglomeration had a “high in the southwest and low in the central part” distribution [41]. Specifically, central cities such as Shanghai, Nanjing, and Suzhou generally had lower overall ecological resilience levels due to lower ecological stability, while cities in southern Anhui and Zhejiang generally had higher ecological resilience levels due to better ecological stability.

The combined spatiotemporal evolution pattern of ecological resilience in the Yangtze River Delta urban agglomeration shows that the continuous promotion of rapid urbanization will cause increased pressure on regional resource consumption and ecological and environmental loads. With the vigorous promotion of high-quality urbanization in the Yangtze River Delta urban agglomeration, measures such as the optimization of urban landscaping, the construction of public services and infrastructure, and the strengthening of pollution control intensity and ecological protection, etc., will help to improve the level of regional urban ecological resilience.

3.2. Analysis of the Coupling Coordination Degree between Urbanization and Ecological Resilience

3.2.1. Temporal Evolutionary Characteristics of Coupling Coordination Degree

Overall, the coupling coordination degree of urbanization quality and ecological resilience level of the Yangtze River Delta urban agglomerations showed a slowly rising trend from 2005 to 2020, indicating that along with the improvement of urbanization quality, the ecological resilience level also realized synchronous improvement in the Yangtze River Delta urban agglomeration, and the interaction degree between the two systems was continuously enhanced. According to the changes in the coupling coordination degree, the coupling coordination development of the Yangtze River Delta urban agglomeration can be roughly divided into two stages. The first stage is from 2005 to 2016, which is the basic coupling coordination stage. It is also a period of rapid increase in the coupling coordination degree, with significant growth in urbanization quality and a small increase in the ecological resilience level. The second stage is the good coupling coordination stage from 2017 to 2020; the quality of urbanization maintains steady growth, while the level of ecological resilience fluctuates, and so the growth of the coupled coordination degree in this period slows. Figure 5 shows that the difference in the coupling coordination degree among cities in the Yangtze River Delta urban agglomeration gradually decreased during the study period. The difference rate gradually decreased from 72.67% in 2005 to 17.24% in 2020, indicating that the development within the Yangtze River Delta urban agglomeration gradually became balanced and that high-quality integrated development achieved certain results.

3.2.2. Spatial Differentiation Characteristics of the Coupling Coordination Degree

Based on the classification criteria of the coupling coordination degree in Table 3, the coupling coordination classification results of 26 cities in the Yangtze River Delta urban agglomeration are shown in Figure 6. In 2005 (Figure 6a), the coupling coordination development level of urbanization and ecological resilience in the Yangtze River Delta urban agglomeration was low, and the coupling coordination degree of most cities just reached the level of basic coupling coordination. In terms of spatial distribution, Shanghai, central Jiangsu, southern Jiangsu, Zhejiang, Hefei, and southern Anhui formed contiguous basic coupling coordination development areas. However, northern Jiangsu, central Anhui, and Xuancheng in southern Anhui were all in the coupling dissonance stage. In 2010 (Figure 6b), the degree of coupling coordination in the Yangtze River Delta gradually increased, with 25 cities entering the state of coordinated development, among which Hangzhou took the lead in achieving good coupling coordination. However, Anqing was still in coupling dissonance due to its low socioeconomic level, with a per capita GDP of only CNY 18,604 in that year, which caused it to rank at the bottom of the 26 cities. Furthermore, its development of urbanization quality was poor and severely lagged behind the local ecological resilience level. By 2015 (Figure 6c), the coupling coordination degree between urbanization and ecological resilience in the Yangtze River Delta urban agglomeration had been greatly improved, with all cities achieving coordinated development. The number of good coupling coordination cities had increased from 1 to 10 in 2010; these cities gradually formed two belt-like distribution patterns comprising coastal cities and inland cities, which were connected by inland cities in Jiangsu and Zhejiang. By 2020 (Figure 6d), the gap in the coupling coordination degree among cities in the Yangtze River Delta urban agglomeration had been significantly narrowed. Moreover, the coupling coordination degree between urbanization and ecological resilience for most cities had reached the good coupling coordination stage, leaving only Yancheng, Taizhou, Jiaxing, and Anqing in the basic coupling coordination stage due to their poor locations, poor economic foundations, slow development of high-quality urbanization, and failure to adequately consider ecological security during economic development. In general, driven by the radiation of central cities such as Shanghai, Nanjing, and Hangzhou, the socioeconomic level of neighboring cities grew rapidly. These cities especially benefited from the continuous optimization and adjustment of their industrial structure, the gradual improvement of infrastructure, and enhanced awareness of ecological environmental protections; these factors promoted the coupling coordination between urbanization quality and ecological resilience level and gradually formed the good coupling coordination cities.

3.2.3. Characteristics of and Changes in Coupling Coordination Types

According to the urbanization types of 26 cities in the Yangtze River Delta urban agglomeration in 2000, 2005, 2015, and 2020, as shown in

Table 6. Types of coupling coordination between urbanization and ecological resilience in the Yangtze River Delta urban agglomeration in 2005, 2010, 2015, and 2020.

City	2005	2010	2015	2020
Shanghai	${\mathrm{S}\mathrm{u}\mathrm{b}}_8$	${\mathrm{S}\mathrm{u}\mathrm{b}}_8$	${\mathrm{S}\mathrm{u}\mathrm{b}}_5$	${\mathrm{S}\mathrm{u}\mathrm{b}}_5$
Nanjing	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_8$	${\mathrm{S}\mathrm{u}\mathrm{b}}_5$	${\mathrm{S}\mathrm{u}\mathrm{b}}_5$
Wuxi	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$
Changzhou	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$
Suzhou	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_5$
Nantong	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$
Yancheng	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$
Yangzhou	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$
Zhenjiang	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$
Taizhou (Jiangsu)	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$
Hangzhou	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_4$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$
Ningbo	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$
Jiaxing	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$
Huzhou	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_4$	${\mathrm{S}\mathrm{u}\mathrm{b}}_4$
Shaoxing	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$
Jinhua	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_4$	${\mathrm{S}\mathrm{u}\mathrm{b}}_4$
Zhoushan	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$
Taizhou (Zhejiang)	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_4$	${\mathrm{S}\mathrm{u}\mathrm{b}}_4$
Hefei	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$
Wuhu	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$
Ma’anshan	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$
Tongling	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_9$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_6$
Anqing	${\mathrm{S}\mathrm{u}\mathrm{b}}_{10}$	${\mathrm{S}\mathrm{u}\mathrm{b}}_{10}$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$
Chuzhou	${\mathrm{S}\mathrm{u}\mathrm{b}}_{10}$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_4$
Chizhou	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_4$	${\mathrm{S}\mathrm{u}\mathrm{b}}_4$
Xuancheng	${\mathrm{S}\mathrm{u}\mathrm{b}}_{10}$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_7$	${\mathrm{S}\mathrm{u}\mathrm{b}}_4$

below, we know the following:

During the study period, the coupling coordination development types of different cities in the Yangtze River Delta urban agglomeration comprised the three major categories of good coupling coordination, basic coupling coordination, and coupling dissonance, for which there were seven specific subclasses: good coordination–lagging urbanization quality (${\mathrm{S}\mathrm{u}\mathrm{b}}_4$), good coordination–lagging ecological resilience (${\mathrm{S}\mathrm{u}\mathrm{b}}_5$), good coordination (${\mathrm{S}\mathrm{u}\mathrm{b}}_6$), basic coordination–lagging urbanization quality (${\mathrm{S}\mathrm{u}\mathrm{b}}_7$), basic coordination–lagging ecological resilience (${\mathrm{S}\mathrm{u}\mathrm{b}}_8$), basic coordination (${\mathrm{S}\mathrm{u}\mathrm{b}}_9$), and coupling dissonance–urbanization quality hindered (${\mathrm{S}\mathrm{u}\mathrm{b}}_{10}$). These subclasses displayed some spatial and temporal heterogeneity. Overall, the Yangtze River Delta urban agglomeration has a good ecological background and rich ecological resources [59]; therefore, most cities have a high level of ecological resilience that is above the level of high-quality urbanization construction. From 2005 to 2020, as the coupling coordination between urbanization and ecological resilience systems in the Yangtze River Delta urban agglomeration showed a trend of continuous improvement, the number of coupling coordinated development type cities gradually increased, the number of cities with coupling coordination for lagging urbanization significantly decreased, and the number of cities with coupling dissonance shrank from the initial three to zero, but the changes in the types of coupling coordination were not large, mostly switching between adjacent types, indicating that the overall spatial pattern of coupling coordination within the Yangtze River Delta urban agglomeration is relatively stable.

Specifically, in 2005, the types of coupling coordination between urbanization and ecological resilience in the Yangtze River Delta urban agglomeration covered four categories: basic coordination–lagging urbanization quality (${\mathrm{S}\mathrm{u}\mathrm{b}}_7$), basic coordination–lagging ecological resilience (${\mathrm{S}\mathrm{u}\mathrm{b}}_8$), basic coordination (${\mathrm{S}\mathrm{u}\mathrm{b}}_9$), and coupling dissonance–urbanization quality hindered (${\mathrm{S}\mathrm{u}\mathrm{b}}_{10}$). Among them, more than half of the 26 cities were in the coupling coordination type ${\mathrm{S}\mathrm{u}\mathrm{b}}_7$. In the remaining cities, only one city, Shanghai, was in the coupling coordination type of ${\mathrm{S}\mathrm{u}\mathrm{b}}_8$, and seven cities, including Nanjing, Wuxi, and Changzhou, etc., were in the ${\mathrm{S}\mathrm{u}\mathrm{b}}_9$ coupling coordination type between urbanization and ecological resilience. The coupling coordination of three cities, Anqing, Chuzhou, and Xuancheng, remained at the stage of ${\mathrm{S}\mathrm{u}\mathrm{b}}_{10}$. By 2010, only Anqing was still in the coupled dissonance stage (${\mathrm{S}\mathrm{u}\mathrm{b}}_{10}$); the urbanization and ecological resilience in Chuzhou and Xuancheng both entered the basic coordination stage, and their coupling coordination type changed to ${\mathrm{S}\mathrm{u}\mathrm{b}}_7$. Nanjing’s coupling coordination type changed from ${\mathrm{S}\mathrm{u}\mathrm{b}}_9$ to ${\mathrm{S}\mathrm{u}\mathrm{b}}_8$. Furthermore, the number of cities with lagging ecological resilience had increased to two, which were Shanghai and Nanjing. The number of cities with the basic coordination type of ${\mathrm{S}\mathrm{u}\mathrm{b}}_9$ increased to nine. Hangzhou, which had the ${\mathrm{S}\mathrm{u}\mathrm{b}}_4$ type of coupling coordination, took the lead in the stage of good coordination development between urbanization and ecological resilience. In 2015, the urbanization and ecological resilience of 26 cities in the Yangtze River Delta urban agglomeration all entered the coordinated development stage, and the number of cities with good coupling coordination increased significantly from 1 to 11; the remaining cities belonged to the basic coupling coordination type. By 2020, with the implementation of the integrated development strategy of the Yangtze River Delta, which enabled high-quality urbanization development, the coordination between the two systems of urbanization and ecological resilience was significantly enhanced, and the coupling and coordination of most cities had entered the stage of good coupling coordination. At the same time, the gap between the quality of urbanization and the level of ecological resilience in the cities of the Yangtze River Delta gradually narrowed, and the number of cities with lagging urbanization shrank to seven, of which Anqing was ${\mathrm{S}\mathrm{u}\mathrm{b}}_7$ and the remaining six cities were ${\mathrm{S}\mathrm{u}\mathrm{b}}_4$.

4. Factors Influencing the Coupling Coordination Degree

4.1. Variable Selection and Model Construction

4.1.1. Variable Selection

Urbanization and ecological resilience are two complex systems that are driven and constrained by each other, and their coupling coordination degree is simultaneously influenced by many factors. On the basis of a comprehensive analysis of existing studies [15,51,60] and full consideration of the real environment and data availability, this study used the coupling coordination degree between urbanization and ecological resilience ($D$) as the explained variable; explanatory variables were selected from seven dimensions, including economic openness, economic density, green and low carbon, science and technology innovation, urban-rural coordination, public service, and ecological endowment, to comprehensively examine the extent of their impacts on the coupling coordination development of urbanization and ecological resilience.

In terms of the level of economic openness, the amount of actual foreign investment utilized can reflect the degree of openness and influence of a region on the international community [61]. Generally, the scale of foreign capital utilization has a positive impact on the high-quality development of the regional economy [62], but the high energy consumption, high pollution, and low technology industrial projects associated with foreign investment utilization in various regions can also pose a threat to the regional ecological environment [63]. In terms of the level of economic density, the average regional GDP was selected as a representation index. Ecological resilience increases with GDP growth [15], so the higher the GDP created per unit of land area, the better the economic efficiency of land use [51], and the economic development level has a significant positive influence on the coupling of urbanization and ecological efficiency [64], which can effectively promote the high-quality development of regional cities and towns and enhance the regional ability to resist sudden ecological disasters.

In terms of green and low-carbon levels, carbon emission intensity was chosen as the influencing factor indicator, as the reduction in carbon emission intensity and the promotion of new urbanization development can be realized synergistically [45]. The reduction in carbon emission intensity is conducive to forcing and promoting the green and low-carbon transformation of economic structure, achieving the goal of “double carbon” and fundamentally improving environmental quality. In terms of the science and technology innovation level, the proportion of science and technology expenditure in fiscal expenditure can characterize the regional science and technology innovation capacity, and improving the level of science and technology investment can effectively promote regional science and technology development [63]. In terms of the coordination level between urban and rural areas, the per capita disposable income ratio of urban and rural residents was taken as a characteristic factor. In the process of coordinated urban-rural development, the regional urban-rural income gap ratio reflects the level of high-quality coordinated development between urban and rural areas. The larger the gap is, the more obvious the regional ecological environment gap will be, and the worse the coordination between overall urbanization and ecological resilience becomes.

In terms of the public service level, the municipal public infrastructure level reflects the level of urban public service [65], so the fixed asset investment in municipal utility construction was selected as the representation index. On the one hand, the increase in fixed investment in municipal utility facilities can improve the quality of urban infrastructure supply and operational efficiency and improve the urban living environment; on the other hand, it can improve the level of urban risk resistance and strengthen the ability to forecast and early warn of major risk predictions. In terms of the ecological endowment level, the ecological land area ratio index was chosen as a characterization index. Ecological land has important ecosystem service functions and plays a principal role in maintaining ecological balance and guaranteeing the ecological security of the territory [66]. In this study, ecological land refers to arable land, garden plot, forest land, grassland, and unused land.

To reduce the magnitude and attenuate the effect of variable heteroskedasticity, the explained and explanatory variables were simultaneously processed by taking their natural logarithms. The descriptive statistics of each influencing factor variable are shown in

Table 7. Descriptive statistics, N = 416.

Variable Type	Specific Factors	Original Value Unit	Maximum Value	Minimum Value	Average Value	Standard Deviation
Economic Opening	Actual utilization of foreign capital ($x_1$)	Ten thousand dollars	14.52	7.797	11.594	1.292
Economic Density	Land per capita GDP ($x_2$)	Ten thousand yuan/km2	11.019	4.892	8.233	1.108
Green and Low-carbon	Carbon emission intensity ($x_3$)	t/ten thousand yuan	2.599	−1.237	0.373	0.606
Science and Technology Innovation	Proportion of science and technology expenditure in fiscal expenditure ($x_4$)	%	2.641	−3.045	0.908	0.974
Urban-rural Coordination	Per capita disposable income ratio of urban and rural residents ($x_5$)	/	1.172	−1.563	0.742	0.257
Public Services	Fixed asset investment in municipal public facilities construction ($x_6$)	Ten thousand yuan	15.99	9.291	12.956	1.330
Ecological Endowment	Ecological land area ratio index ($x_7$)	%	4.81	3.068	4.277	0.212

.

4.1.2. Panel Tobit Regression Model

The values of the explanatory variable of this study, the coupled coordination between urbanization and ecological resilience, range from 0 to 1 and are limited dependent variables, according to the basic principles of the Tobit model [67]. Therefore, a panel Tobit regression model for constrained dependent variables was constructed to empirically analyze the factors influencing the coupling and coordinated development of urbanization and ecological resilience in the Yangtze River Delta urban agglomeration. The specific expression of the model is as follows:

$$D_{it}=c+{\delta }_1{x}_{1it}+{\delta }_2{x}_{2it}+{\delta }_3{x}_{3it}+{\delta }_4{x}_{4it}+{\delta }_5{x}_{5it}+{\delta }_6{x}_{6it}+{\delta }_7{x}_{7it}+{\epsilon }_{it}$$

(9)

In the above equation, $D_{it}$ is the natural logarithm of the coupling coordination between urbanization and ecological resilience in the $i$ region of the Yangtze River Delta urban agglomeration in year $t$; $c$ is the constant term; ${\delta }_k$ is the regression coefficient of each explanatory variable; and ${\epsilon }_{it}$ is the random error term.

4.2. Analysis of Empirical Results

Panel Tobit regression analysis was conducted with the help of Stata 17 software, and the results of the likelihood ratio chi-square test of the model showed a likelihood ratio statistic of 411.36 and a significance p-value of 0.000 < 0.05, indicating that the panel Tobit regression model had a good fit. It can effectively reflect the influence of various factors on the coupling coordination degree between urbanization and ecological resilience in the Yangtze River Delta urban agglomeration. The regression results are shown in

Table 8. Panel Tobit regression results for factors influencing the coupling coordination degree of urbanization and ecological resilience in the Yangtze River Delta urban agglomeration.

Variables	Regression Coefficient	p	Standard Error
Constants	−0.84823	0.000 ***	0.09474
Actual utilization of foreign capital ($x_1$)	−0.01455	0.002 ***	0.00467
Land per capita GDP ($x_2$)	0.02895	0.000 ***	0.00539
Carbon emission intensity ($x_3$)	−0.02873	0.000 ***	0.00647
Proportion of science and technology expenditure in fiscal expenditure ($x_4$)	0.04519	0.000 ***	0.00442
Per capita disposable income ratio of urban and rural residents ($x_5$)	−0.06262	0.000 ***	0.01451
Fixed asset investment in municipal public facilities construction ($x_6$)	0.01904	0.000 ***	0.00418
Ecological land area ratio index ($x_7$)	0.02603	0.139	0.01758

Note: ***, **, and * represent 1%, 5%, and 10% significance levels, respectively.

.

According to the regression results, except for the ecological land area ratio index ($x_7$) variable, all the explanatory variables pass the significance level test of 1%. Among them, the land per capita GDP ($x_2$), the proportion of science and technology expenditure in fiscal expenditure ($x_4$), the fixed asset investment in municipal public facilities construction ($x_6$), and the ecological land area ratio index ($x_7$) variables had positive effects on the coupling coordination degree of urbanization and ecological resilience, while the actual utilization of foreign capital ($x_1$), the carbon emission intensity ($x_3$), and the per capita disposable income ratio of urban and rural residents ($x_5$) variables had a negative impact on the coupling coordination between urbanization and ecological resilience.

• Specifically, at present, the eco-efficiency level of the introduction of foreign investment in the Yangtze River Delta urban agglomeration is low; the proportion of manufacturing enterprises among foreign-invested enterprises remains high, due to the low level of eco-efficiency of foreign investment introduced into the Yangtze River Delta urban agglomeration; and the actual utilization of foreign capital ($x_1$) factor has a regression coefficient of −0.01455. This indicates that the increase in real utilized foreign capital may cause a decrease in the coupling coordination of urbanization and ecological resilience, which hinders the coordinated development of urbanization and ecological resilience to a certain extent.
• The regression coefficient of the land per capita GDP ($x_2$) factor has a regression coefficient of 0.02895, which means that the higher the level of economic efficiency of land use, the higher the level of urban economic development, and the correspondingly stronger the ability to cope with disaster risks; therefore, the increase in economic density can significantly promote the coordinated development of urbanization and ecological resilience.
• The regression coefficient of the carbon emission intensity ($x_3$) factor has a regression coefficient of −0.02873, indicating that with the promotion of energy-saving and carbon-reduction related policies and technologies, the reduction in carbon emission intensity to promote regional green and low-carbon transformation will be beneficial to the increase in coupling coordination.
• The proportion of science and technology expenditure in the fiscal expenditure ($x_4$) factor has a regression coefficient of 0.04519, implying that the improved level of science and technology innovation not only promotes the high-quality development of regional urbanization but also improves the ability of cities to cope with sudden ecological disasters, thus significantly promoting the coordinated development of urbanization and ecological resilience.
• The per capita disposable income ratio of urban and rural residents ($x_5$) has a regression coefficient of −0.06262, reflecting that the more coordinated urban-rural development is, the more effective the regional integrated development and the better the coupling coordination between urbanization and ecological resilience. This means that the lower the per capita disposable income ratio of urban and rural residents, the higher the quality of regional urban-rural integrated development and the stronger the awareness of urban and rural residents of ecological environmental protection, which are also more conducive to the coupled and coordinated development of urbanization and ecological resilience.
• The fixed asset investment in municipal public facilities construction ($x_6$) factor has a regression coefficient of 0.01904, which shows that higher-level infrastructure construction can effectively support the high-quality development of regional urbanization and simultaneously improve the adaptability and solubility of the regional ecological environment. Therefore, improving the level of public services can significantly promote the coupling coordination development of urbanization and ecological resilience.
• The ecological land area ratio index ($x_7$) factor has a regression coefficient of 0.02603, but it does not pass the significance level test of 10%, which means there is a positive but statistically insignificant correlation between ecological endowment and coupling coordination degree. Assuming that other conditions remain unchanged, optimizing the regional land use structure and improving the ecological land area ratio index are also conducive to promoting the coupling and coordinated development between urbanization and ecological resilience systems.

5. Discussion and Conclusions

Taking 26 cities in the Yangtze River Delta urban agglomeration as the research object and by adopting the CRITIC weighting method, coupling coordination degree model, and panel Tobit regression model, this study explored the spatial and temporal patterns of the coupling coordination degree between urbanization and ecological resilience in the Yangtze River Delta urban agglomeration from 2005 to 2020, revealed the influence mechanism of the coupled and coordinated development of urbanization and ecological resilience, and drew the following main conclusions:

From 2005 to 2020, the comprehensive evaluation index of urbanization quality in the Yangtze River Delta urban agglomeration increased significantly. This is consistent with the findings of Peng et al. [68], but there exist certain differences from the results of “Convergence club” by Zhang et al. [69]. Additionally, the differences in cities gradually narrowed and tended to balance development, which confirms that “the progression of urbanization in the Yangtze River Delta urban agglomeration has converged spatially” [55]. The comprehensive index of higher urbanization quality in the Yangtze River Delta urban agglomeration was mainly concentrated in the eastern part of the Yangtze River Delta urban agglomeration, Shanghai, Nanjing, Wuxi, and Hangzhou, showing the overall spatial distribution characteristics of the “dual core leadership” for Nanjing and Shanghai. This is consistent with Sun et al.’s (2018) research results “the eastern part have much higher urban state carrying capacity values than the western ones significantly” [70]. The comprehensive assessment index of ecological resilience increased slowly and fluctuated. In terms of spatial structure, the ecological resilience level of the Yangtze River Delta urban agglomeration had a spatial disequilibrium type, showing the distribution characteristics of “high in the southwest and low in the centre”, but the differences between different cities were gradually reduced and tended to be balanced. From the time dimension, the trend of urban ecological resilience is similar to that of urban resilience in the Yangtze River Delta urban agglomeration in previous studies [51,69]. However, based on the spatial perspective, the spatial patterns presented have different results, that the level of urban resilience in the Yangtze River Delta urban agglomeration exhibits a spatial pattern of “being highest in the east, comparatively lower in the middle, and the lowest in the west” [69].

From 2005 to 2020, the overall coupling coordination degree of urbanization and ecological resilience showed a slow upward trend, developing from basic coupling coordination to good coupling coordination; spatially, the gap in the coupling coordination degree between 26 cities in the Yangtze River Delta urban agglomeration narrowed significantly, and cities with good coupling coordination gradually clustered, which means that the integrated development of the Yangtze River Delta achieved certain results. Overall, the coupled coordination degree of urbanization and ecological resilience in this study is consistent with the spatial and temporal change characteristics of urbanization and urban resilience coordination degree. Both of them show an upward trend in the overall level of coupling coordination degree, with regional integration replacing multi-level differentiation, and the high-class area shows regional integration [68]. For coupling coordination types, the number of cities with the coupling coordinated development type increased significantly, while the number of coupling coordinated cities with lagging urbanization significantly decreased, mainly in the western region (Anqing, Chuzhou, and Xuancheng). Unlike the existing research results that land development intensity generally lags behind urban toughness level [51], in this study, cities with lagging ecological resilience started to appear mainly in the eastern region (Shanghai, Nanjing, and Suzhou), and the number of coupling dissonance cities shrank to zero.

The coupling coordination degree between urbanization and ecological resilience in the Yangtze River Delta urban agglomeration is jointly influenced by the factors driving the actual utilization of foreign capital, the land per capita GDP, the carbon emission intensity, the proportion of science and technology expenditure in fiscal expenditure, the per capita disposable income ratio of urban and rural residents, the fixed asset investment in municipal public facilities construction, and the ecological land area ratio index. The spatiotemporal variation in the coupling coordination degree among the 26 cities is the result of the interaction of the above seven factors. This is consistent with the results of Zhang et al.’s [26] analysis of the factors affecting coupling coordination based on the gray correlation model.

Based on the above conclusions, the following insights are obtained:

First, the spillover effect of Shanghai, Hangzhou, Nanjing, and other central cities should be fully recognized and utilized to promote the coupling coordination integrated development of urbanization and ecological resilience in the Yangtze River Delta urban agglomeration. With the continuous advancement of the integrated development of the Yangtze River Delta, Shanghai, Hangzhou, and Nanjing should further strengthen their role in radiation leadership and give full play to their role as the core cities in institutional innovation, economic development, scientific and technological innovation, and urban governance. In addition, it is necessary to eliminate the constraints of administrative boundaries, give full play to the role of the market and society in resource allocation, strengthen the integration of geographic and industrial boundaries to promote the expansion of public services and ecological green, and lead and drive the high-quality integration of the Yangtze River Delta urban agglomeration in all aspects.

Second, the coordination of urbanization and ecological resilience coupling should be improved according to local conditions. Cities with lagging ecological resilience, such as Shanghai, Nanjing, and Suzhou, should consolidate their advantages in high-quality urbanization, fully exploit their resources, and increase investment and construction in the ecological environment, social management, scientific and technological innovation, and infrastructure to improve their ecological resilience. For cities with lagging urbanization, such as Anqing, Chuzhou, and Xuancheng, which have relatively weak economic bases, it is necessary to avoid disorderly expansion and “hollowing out” in the pursuit of rapid urbanization; instead, these cities should adhere to the new type of urbanization development that is intensive, efficient, green, and ecological.

Third, the seven internal factors influencing the coupling coordination degree between urbanization and ecological resilience should be fully examined, and the upgrading of economic development, science and technology innovation, green low-carbon and public services, etc., should be taken as strategic value choices to lead the integration of the Yangtze River Delta. A profound understanding of market demand can accelerate the attraction of overseas high-tech industrial investment to promote industrial transformation and upgrading. Simultaneously, the cooperation among cities in the Yangtze River Delta regarding ecological environmental protection should be deepened to jointly build a community for ecological environmental protection, scientifically guide the promotion of new-type urbanization and ecological safety in the Yangtze River Delta urban agglomeration, and accelerate integrated and high-quality development.

6. Future Outlook and Deficiencies

This study has explored the spatial and temporal changes in the coupled and coordinated relationship between urbanization quality and urban ecological resilience in the more developed Yangtze River Delta urban agglomeration during the period from 2005 to 2020 and has quantitatively explored the influencing factors of the degree of coupled coordination. In this paper, we have also provided arguments and suggestions for optimizing the coordinated development of urbanization and ecological resilience in the Yangtze River Delta city cluster and the high-quality development of regional integration.

However, since the research data used in this paper are statistical data, this study still has limitations. Therefore, in the next step, we intend to select a longer time scale to use long-term observation data instead of statistical data to further explore the construction of urbanization quality and ecological resilience evaluation indexes. Based on this, it could be better to study the coupled and coordinated development changes between urbanization and the quality of ecological resilience at different stages or to compare the coordinated development differences between urbanization and ecological resilience among different urban agglomerations. Meanwhile, the influencing factors of the coupling coordination degree of other dimensions need to be further discussed.