Functional Measurements, Pattern Evolution, and Coupling Characteristics of “Production-Living-Ecological Space” in the Yangtze Delta Region

Abstract

Based on the “Production-Living-Ecological Space” evaluation system, we hereby form its functional index and take the results of corresponding functional measurement to analyze the spatial pattern, functional evolution, and coupling characteristics of the “Production-Living-Ecological Space” of the Yangtze Delta Region. The results show that: (1) From the spatial pattern, the production space is mainly distributed in the plain areas. The living space is concentrated in the dense urban areas along the Yangtze River, the East Sea, and the East Jiangsu–Gansu Line. The ecological space is concentrated in mountainous hill areas. (2) From the spatial transformation, production space expands slightly, living space continues to expand, and ecological space shrinks significantly. (3) The functionality of “Production-Living-Ecological Space” exhibits a high level in hilly mountainous areas and a low level in plains, with an overall downward trend. Notably, the core cities within the Yangtze Delta Region have experienced the most significant decline in functionality. (4) The natural environment is the decisive factor for the overall pattern of “Production-Living-Ecological Space”, while economic and social development is the core driving force of the evolution of the spatial pattern, and regional integration is the catalyst of the evolution of the spatial pattern. (5) The coupling coordination of “production-ecology” is exceptionally strong, with the living function holding an overwhelmingly dominant position.

1. Introduction

Global urbanization has been booming since the 21st century, and more than half of the population now resides in the city. Urbanization has contributed significantly to economic development and improved the quality of life of the population, but it has also led to several issues, including deteriorating environmental conditions, overstretched cultivated land supplies, and diminished ecosystem functions [1,2,3,4]. This process puts a lot of strain on the Earth’s ecological system and poses several challenges. Therefore, it has become a hot topic of growing concern across the globe to figure out ways to lessen the adverse effects of rapid urbanization on ecosystems and encourage the coordinated development of urbanization and ecosystems. The 2030 Agenda for Sustainable Development, Future Earth, and the World Urban Forum all stress that the urbanization process should progress in harmony with the ecological environment and be compatible with the carrying capacity of resources and the environment [5]. China is the biggest developing nation in the world, and it is distinguished by a huge population, a high population density, imbalanced development, rapid urbanization, a sizable economy, and significant strain on the environment and resources. Hence, with the theme of “Production-Living-Ecological Space”, we conduct a quantitative study in the Yangtze Delta Region.

Since the reform and opening up in 1978, China’s industrialization and urbanization have developed quickly, leading to fast economic and social development. After the 1990s, China continued to promote urbanization and sped up the development of urban built-up areas, but at the same time, causing drastic changes in land use and serious ecological and environmental problems, like a rapid rise in the urban population and a rapid expansion on the urban scale. As a result, the interaction between humans and the land is marked by extreme disharmony, which is exemplified by the competition that is intensifying among the uses of production, living, and ecological space [6]. China is currently undergoing a rapid urbanization process and aiming toward a sustainable development vision. However, in this sense, there are primarily two problems:

(1)

How to promote high-quality development of urbanization and ecological protection of the environment.

(2)

How to build high-quality development of urbanization on the basis of the regional resource and environmental carrying capacity according to local conditions [7].

The Chinese government actively responds to international calls and takes the initiative to participate in environmental governance. For instance, the Chinese Ministry of Environmental Protection officially launched the TEEB (The Economics of Ecosystems and Biodiversity) national process in 2013 and jointly prepared the China–TEEB Action Plan with the Chinese Academy of Sciences in 2014. The Chinese government recently proposed building “an intensive and efficient production space, a livable and moderate living space, and a beautiful ecological space”, and this method of spatial division is in line with the widely acknowledged “Production-Living-Ecological Space” concept for sustainable development [8,9], a new instrument for carrying out spatial planning. In actuality, areas should always be split into three different categories of spaces: “production space, living space, and ecological space” [10]. A land use type often serves one or more functions, including production, living, and ecology [11]. Production space mainly has a production function, including the provision of industrial, agricultural, and service products, requiring cultivated land, industrial land, and commercial land. Living space is dominated by living function, where people carry out daily activities to meet their needs for living, consumption, and recreation, requiring residential land, public service land, and square land. Ecological space is a space dominated by ecological function, mainly providing forested land, grassland, water, and other ecological products and services [12].

Currently, researchers from various disciplines have conducted comprehensive studies on the topic of PLES, examining it from multiple angles. Regarding the broader theoretical aspects of PLES, the works of Liu and Wang et al. offer a thorough examination of its essence and structure [13,14]. Liao et al. have delved into its issues of spatial conflict [15]. In-depth investigations into the classification and assessment of PLES spaces have been conducted by Dang et al., Liu et al., and Fang et al. [16,17,18]. Detailed discussions on PLES site categorization have been presented by Zhang et al. and Chen et al. [19,20], while Fang et al. and Zhang et al. have focused on its carrying capacity [21,22]. Li et al. tackled the challenge of functionally identifying PLES [23], and extensive research into the reorganization of PLES has been carried out by Zhu et al., Lv et al., Pan et al., Xu et al., Xi et al., and Long et al. [24,25,26,27,28,29]. On the aspect of functional measurement, Liu et al. developed a framework for the classification and evaluation of PLES, analyzing the spatial and temporal dynamics of these functions in China from 1990 to 2010 [17]. Huang et al. thoroughly explored the concept and significance of PLES [30], and Stanley et al. examined the effects of global change on the ecological spatial functions of urban areas [31]. Bian et al. effectively answered the question of how PLES functions can be kept in balance [32]. Lorenzen et al. studied the socio-economic transformation of living and ecological spatial functions in Mexico’s Mixteca Alta region in terms of socio-economic transformation in living and ecological spatial functions [33]. Leblond studied the problem of conflict among ecological, living, and production functions in the farming area of the Phetchabun region [34]. Paracchini et al. explored the ecological transformation of forests, and the multifunctionality of PLES land use [35]. Kovács-Hostyánszki studied PLES land and functional changes caused by pollination [36], and Liu and Sun explored the spatial distribution of its functional quality [37]. From a regional viewpoint, Tomlinson et al. studied Great Britain’s land use change of PLES using integrated administration and control system data [38]. Wei et al. investigated the coupling coordination measure and pattern evolution of PLES in the Jiangsu Province rural [39]. Gao et al. investigated the alteration of land use function and its ecological implications in Xiong’an New Area [40]. Wang and Tang examined the orderly and adaptive evaluation of the PLES subsystem in rural Chongqing using the entropy value method and the coupling coordination degree model, and they also looked at the spatial and temporal characteristics and patterns of overall functional coupling and coordination in the area [41]. For the purpose of analyzing the evolutionary traits and influencing factors of PLES systems in Chinese resource-based cities using the coupling coordination degree, Dou et al. used the entropy weighting method to determine index weights and construct an evaluation index system of the coupled and coordinated development of PLES [42]. On the whole, relatively few studies by scholars from outside China are fully consistent with the PLES theme, and most of their studies focus on how to deal with the spatial conflict among ecological space and production and living space [33,34], the impacts of climate change on PLES as well as its functions [31,36], and how to better utilize PLES land use data to study social issues [35,38]. There are two main types of research methods used by Chinese scholars on PLES topics, one is a functional study based on land use data [17,43], and the other is a study using the PLES functional system evaluation index system [39,41]. In terms of spatial scale, most of the studies on spatial functions by Chinese scholars have focused on the macroscopic scale of provincial units and the microscopic scale of county units, and less on the mesoscopic scale of municipal administrative units [17,40]. Meanwhile, in terms of research regions, Chinese scholars tend to concentrate on small- and medium-sized urban clusters or individual cities, rarely conducting research on mega-city clusters [15,43]. In terms of research content, although Chinese scholars have viewed the coupling relationships of various functional spaces, there have been relatively few studies on the internal triple spatial coupling relationships of mega-city clusters, and there has not yet been a thorough investigation of the two–two coupling relationships in triple spatial clusters [41]. Additionally, there are few findings yet in the research on the role of PLES based on land use due to the relatively large data needs.

Therefore, due to the availability of data, this study chooses to conduct an in-depth analysis of PLES evolution in the Yangtze Delta Region over three periods since the 21st century, and to reveal the problems among the spaces through coupled coordination tools. Specifically, this study attempts to answer the following questions:

(1)

What are the characteristics of the spatial distribution of PLES in the Yangtze Delta Region, and how has PLES in the Yangtze Delta Region changed in extent since the 21st century?

(2)

What are the distributional characteristics of the functional coordination of PLES in the Yangtze Delta Region, and how has PLES in the Yangtze Delta Region changed in terms of overall functional coherence since the 21st century?

(3)

What patterns exist in the coupling coordination of PLES in the Yangtze Delta Region, and how has the level of coupling and coordination among these spaces evolved since the 21st century?

The study also attempts to make the following contributions to the existing PLES spatial studies:

Firstly, this study explores spatial and temporal pattern evolution of the Yangtze Delta Region and analyzes the underlying causes for significant local changes using remote sensing images from three time periods, 2000, 2010, and 2018, with land use data and visualizes the changes in functional spatial areas based on GIS (Geographic Information System) spatial analysis methods.

Secondly, based on the logical structure of PLES, we analyze the spatial differentiation of the functionality of “Production-Living-Ecological Space” and other heterogeneous pattern characteristics and summarize the causes of differentiation of the functionality of PLES. It is crucial to investigate the spatial relationships within PLES in order to plan regional territorial space and promote regional sustainability [44]. Some scholars have previously determined a coupling coordination index by an entropy method to measure the coupling coordination relationship among production space, living space, and ecological space in a study area. In this research, we construct a model to measure the coupling and coordination of PLES functions in the study area based on the classification and evaluation system of PLES from the perspective of land use, and explore the “production-living”, “production-ecology”, and “production-living” functions. The model will explore the spatial interactions between “production-living”, “production-ecology”, and “living-ecology” in the PLES in the region, so as to make constructive suggestions for the coordinated development of PLES in the Yangtze Delta Region and the sustainable development planning of urban clusters in developing countries. The results of this study will offer helpful recommendations for the coordinated growth of the Yangtze Delta Region and the planning of urban clusters in other developing nations.

Thirdly, this study chooses the Yangtze Delta Region as the research object in response to the paucity of studies on mega-city clusters of municipal administrative units in the field of PLES. In the meantime, this region is distinguished by a high population density, numerous cities, favorable socioeconomic conditions, rapid development, and significant regional integration. In order to better understand the conflict between land supply and demand and the potential for sustainable development within the city cluster, it is useful to examine the spatio-temporal pattern evolution, functional differentiation, and coupling coordination characteristics of the Yangtze Delta Region. On this basis, this study can provide a reference for decision making on the optimal layout of the Yangtze Delta Region’s PLES and also serve as a guide and construction plan for the land use and spatial planning of city clusters in other developing countries around the world.

2. Materials and Methods

2.1. Study Areas

The Yangtze Delta Region, situated at the estuary of the lower reaches of the Yangtze River in eastern China, is a sprawling mega-city cluster. This cluster encompasses 41 cities across Shanghai, Jiangsu, Zhejiang, and Anhui provinces, covering an expansive area of 210,700 km² (Figure 1). The region’s geographical layout presents a contrast between the low-lying plains in the east and north and the mountainous terrain in the south. The Yangtze Delta Region’s economic and urban development levels are among the highest in China, marked by advanced regional integration; among them, Shanghai, Hangzhou, Suzhou, Nanjing, Ningbo, Wuxi, and Hefei are core cities with high economic and urbanization levels. Currently undergoing a critical phase of transition and upgrade, the Yangtze Delta Region confronts challenges like improving autonomous innovation, alleviating resource and environmental limitations, and advancing reform and development. In response, there has been a shift towards high-quality development: productive space is intensively and efficiently developed, living space is made more livable and moderate, ecological space is enhanced to be beautiful and pleasant, and a coordinated approach is adopted for all spaces. The PLES research in this region offers crucial lessons for land planning and governance in mega-city clusters globally.

2.2. Methodology

2.2.1. Evaluation System of the Function of the “Production–Living–Ecological Space”

Land can be categorized into three groups based on how it is used: production, living, and ecological land. Production land is defined as land that is used for agricultural production, while living land is defined as land that is primarily used for human habitation, such as urban land, and ecological land is defined as land with ecological functions that are necessary for the accomplishment of production and living functions. Each type of land is split into four classes according to its functional strength and integrity and is given a score of 5, 3, 1, and 0, respectively. These classes are based on variations in the primary and secondary functions of land production, living, and ecology [17].

In ArcGIS, the “Production-Living-Ecological Space” is calculated using the raster approach. The specific calculation steps are as follows: (1) Use the standard in

Table 1. Classification and score of land use based on “Production–Living–Ecological Space“.

Class I		Class II		Production	Living	Ecological
Code	Name	Code	Name	Land	Land	Land
1	Cultivated land	11	Water Field	3	0	3
		12	Dryland	3	0	3
2	Woodland	21	Forested land	0	0	5
		22	Shrubland	0	0	5
		23	Thinned forest land	0	0	5
		24	Other woodland	0	0	5
3	Grassland	31	High-coverage grassland	0	0	5
		32	Medium-coverage grassland	0	0	5
		33	Low-coverage grassland	0	0	5
4	Water area	41	River and canal	3	0	1
		42	Lake	0	0	5
		43	Reservoir pond	1	0	1
		45	Mudflat	0	0	5
		46	Beach land	0	0	5
5	Urban and rural, industrial	51	Urban land	3	5	0
	and mining, residential land	52	Rural residential land	3	5	0
		53	Other construction land	3	3	0
6	Unused land	61	Sandy land	0	0	5
		63	Saline land	0	0	5
		64	Marshland	0	0	5
		65	Bare land	0	0	5
		66	Bare rock texture land	0	0	5
		67	Others	0	0	5

The scoring criteria refer to [17], using a three-level assignment system of 1, 3, and 5, with a maximum score of 5, a minimum score of 1, and a score of 0 for lack of function.

to assign the original data to the ground class. (2) Convert the assigned vector data into raster data. (3) The selection of grid size in this study is primarily influenced by the dimensions of the research area. To ensure that each grid encompasses multiple land use types and accurately represents the region’s overall features, the study referenced relevant research [17,43] and compared the outcomes using 1 km, 2 km, and 3 km grids. Based on this comparison, a 2 km grid size was selected as the most appropriate for the analysis. (4) The regional mean value of the land utilized in the Yangtze Delta Region was determined using a 2 km grid. (5) Create a map depicting the Yangtze Delta Region’s spatial arrangement.

2.2.2. Production–Living–Ecological Spatial Function Index Measurement Model

Function describes the qualities and propensities of objects and systems with particular links and relationships both within and externally. The term PLESI (Production–living–ecological spatial function index) refers to all PLES attributes, including its role in ensuring its own needs and its role in assisting and cooperating with other entities or systems [13]. The PLESI, which is based on the logical structure of PLESI [45], is created and calculated as:

PLESi = 0.25 × PSIi + 0.25 × LSIi + 0.5 × ESIi

where PLESi is the PLES spatial function index of area i, PSIi is the production spatial index of area i, LSIi is the living spatial index of area i, and ESIi is the ecological spatial index of area i. The larger the value of PLESI, the higher the functional level of the area, and the smaller the value, the lower the value.

PSI (Production Space Index):

The PSI, or Production Space Index, represents the spatial dimension or area allocated for production activities. This can encompass urban land, rural residential land, manufacturing hubs, agricultural lands, and any other space where primary production activities occur. The index provides a quantitative measure to evaluate the intensity or efficiency of land use for production purposes.

LSI (Living Space Index):

The LSI, or Living Space Index, refers to the space allocated for human habitation and daily life. This includes residential areas, recreational spaces, commercial districts, and any areas where people carry out their day-to-day activities. It can be used to assess the quality and adequacy of living conditions, reflecting urban planning and development strategies.

ESI (Ecological Space Index):

The ESI, or Ecological Space Index, indicates the area designated for preserving natural ecosystems and biodiversity. This can consist of protected areas, water field, grassland, parks, conservation zones, and other spaces that prioritize ecological preservation and environmental sustainability. The index helps to quantify the commitment and effectiveness of ecological conservation measures in a given region.

2.2.3. Coupling Coordination Model

Production function is the basic function of regional space, which can support regional life function development economically and materially while simultaneously impairing and degrading ecological function. The realization of regional ecological function can be influenced by the fulfillment of life function, which not only meets the needs of everyday living and social interaction but also serves as a vital complement to production function. The foundation of regional space is ecological space, which offers a critical assurance for the accomplishment of production and living functions. The coupled interaction between PLES spatial functions of the region promotes and coerces each of them and has a significant impact on the growth and evolution of regional space. Based on relevant research findings [46,47,48,49] and the actual circumstances of this study, we first calculated the degree of coupling between the two functions of the PLES in the region, and then we measured the coupling coordination index. This information will help us understand the degree of coupling between the “production-living”, “living-ecology”, and “production-ecology” functions. The formula is as follows:

$$C={\left[\frac{4U_i{U}_j}{{\left(U_i+U_j\right)}^2}\right]}^{\frac{1}{2}}$$

(1)

$$D=\sqrt{CT}$$

(2)

$$T=\alpha U_i+\beta U_j$$

(3)

(1) where C is the functional coupling degree of U_i and U_j, and U_i and U_j are production function, life function, or ecological function, respectively, C∈ [0, 1]; (2) where D is the coupling coordination index, D∈ [0, 1]; (3) where T represents the overall effect and level of U_i and U_j, α and β represent the proportion of U_i and U_j’s contribution to the integrated system, i.e., weights, respectively, α + β = 1. The greater the degree of coupling coordination, the more coordinated the development and evolution between the functional spaces, and the fewer the conflicts. On the contrary, the smaller the degree of coupling coordination, the more uncoordinated the development and evolution between the functional spaces, and the more contradictions. Finally, referring to the related research results [41,50,51], the coupling coordination degree is classified into six types in the context of this study (

Table 2. The classification of CCD of regional “Production-Living-Ecological Space” spatial function index.

Coupling Coordination	Type of Coupling Coordination	Features
D∈ [0, 0.2]	Severe disorder	Excessive development of regional production functions has led to the squeezing of regional living and ecological space, poor livability of living space, and a series of ecological problems.
D∈ [0.2, 0.4]	Moderate disorder	The regional production function still occupies an absolute dominant position, while the living function is gradually promoted, and the ecological problems arising from living pollution are more serious.
D∈ [0.4, 0.5]	Endangered disorder	The production function of the region declines and the living function begins to increase, while ecological problems arising from production and living pollution begin to appear.
D∈ [0.5, 0.6]	Basic coordination	The development rate of the region is slowing down, the production mode is transforming from rough and inefficient to intensive and efficient, and the ecological problems caused by living and production activities are starting to be paid attention to and restored.
D∈ [0.6, 0.8]	Excellent coordination	Regional ecological restoration has achieved certain results, living and production activities tend to be coordinated, and the overall habitat environment has been greatly improved.
D∈ [0.8, 1.0]	High quality coordination	The “Production-Living-Ecological Space” spatial functions of the region promote each other, which can meet the needs of different interests and achieve an orderly development of the regional spatial system.

).

2.3. Data Sources

Land use data for the Yangtze Delta Region were generated using Landsat5 TM, Landsat7 ETM+, and Landsat8 OLI images with a 30 m resolution from the years 2000, 2010, and 2018 (

Table 3. Data sources.

Data Name	Resolution	Date Sources
China National Land Use/Cover Change Dataset (CNLUCC)	30 m	https://www.resdc.cn/DOI/DOI.aspx?DOIID=54 (accessed on 30 June 2021)

). Employing basic image processing and the land use/cover classification system of the Chinese National Ecological Remote Sensing Monitoring, along with additional resources like land use maps and remote sensing image interpretation through the EDARS platform, the data were segmented into six primary categories: cultivated land, woodland, grassland, water area, construction land (encompassing urban–rural, industrial, and residential areas), and unused land. This was further divided into 23 secondary categories specific to the Yangtze Delta Region. The accuracy of these data, verified through fieldwork, exceeded 85%, meeting the requirements of the study.

3. Results Analysis

3.1. The Evolution of the Spatial Pattern of the “Production-Living-Ecological Space”

3.1.1. Spatial Pattern of Production Space

Overall, the Yangtze Delta Region’s production space from 2000 to 2018 has a greater distribution in the plains and a decreased distribution in hilly and mountainous regions, primarily in the northern regions of Jiangsu and Anhui, with sporadic distribution south of the Yangtze River. Jianghuai Plain, Huaihai Plain, and the places along the Yangtze River Plain are where most of the production space is located, which is essentially comparable with the main production areas of rice and other food crops in the Yangtze Delta Region (Figure 2 and Figure 3). The area of production land has been on an expanding trend, expanding from 226219 km² in 2000 to 229752 km² in 2018 (

Table 4. Land use area variations.

Space Class	Year	Area (km2)
Production space	2000	226,219
	2010	227,987
	2018	229,752
Living space	2000	31,263
	2010	42,374
	2018	48,026
Ecology space	2000	321,527
	2010	310,491
	2018	306,153

). Between 2000 and 2018, the production space shrank in core cities along the Yangtze River, such as Shanghai (−1.25%), Suzhou (−0.9%), and Wuxi (−0.15%), while all other municipalities expanded, including Yancheng (17.14%), Ningbo (13.22%), Nantong (8.89%), Taizhou (8.87%), and other coastal cities have the most significant expansion in production space area (

Table 5. Contribution degree of production space change of cities from 2000 to 2018.

Region	Contribution Degree	Region	Contribution Degree	Region	Contribution Degree
Yancheng	17.14%	Taizhou (JS)	1.44%	Ma’anshan	0.33%
Ningbo	13.22%	Huzhou	1.41%	Wuhu	0.24%
Nantong	8.89%	Chizhou	1.14%	Zhenjiang	0.24%
Taizhou	8.87%	Jiaxing	1.07%	Changzhou	0.08%
Lishui	8.20%	Lianyungang	0.94%	Bengbu	0.06%
Wenzhou	6.15%	Suqian	0.79%	Hefei	0.01%
Xuzhou	5.64%	Chuzhou	0.77%	Huaibei	0.00%
Huai’an	4.34%	Nanjing	0.71%	Bozhou	−0.01%
Shaoxing	4.26%	Lu’an	0.68%	Huangshan	−0.02%
Hangzhou	3.37%	Yangzhou	0.65%	Wuxi	−0.15%
Quzhou	3.13%	Huainan	0.55%	Fuyang	−0.33%
Jinhua	2.74%	Tongling	0.52%	Suzhou	−0.90%
Zhoushan	1.95%	Anqing	0.50%	Shanghai	−1.25%
Xuancheng	1.85%	Suzhou (AH)	0.34%

(Due to the duplication of the names of the cities, in this study, Jiangsu province’s Suzhou city is named Suzhou, Anhui province’s Suzhou city is named Suzhou (AH), Zhejiang province’s Taizhou city is named Taizhou, and Jiangsu province’s Taizhou city is named Taizhou (JS)).

). Jianghuai Plain, Huaihai Plain, Yangtze Delta Plain, North Anhui Plain, and along the Yangtze River Plain in central Anhui have all been significant grain-producing regions for centuries. Additionally, the state has strictly regulated the Three Zones and Three Lines (it was established by the General Office of the CPC Central Committee in December 2016, where the three zones refer to urban, agricultural, and ecological spaces, and the three lines refer to the urban development boundary, permanent basic agricultural land, and ecological protection red line.) over time and strengthened the protection of cultivated land, which has led to a small expansion in the production space area in the region. At the same time, the alteration of development strategies of Yangtze River developed cities like Shanghai and Suzhou and the rapid development of manufacturing industries in Ningbo and Nantong have also led to changes in the area of production space in the region [52].

The area of production space increased by 1768 km² between 2000 and 2010, with the majority of this growth occurring in non-Yangtze Delta core cities like Yancheng, Xuzhou, Lishui, Nantong, Huai’an, and Taizhou. Production space shrank in central Yangtze Delta cities like Shanghai, Wuxi, and Changzhou. The area of production space increased by 1765 km² between 2010 and 2018, with the areas of Ningbo, Yancheng, Taizhou, Nantong, and Wenzhou expanding the most. The areas of production space decreased in Shanghai, Suzhou, Tongling, Hefei, and Bozhou.

3.1.2. Spatial Pattern of Living Space

In general, dense urban areas near rivers, beaches, and places along the East Longhai account for the majority of the living space in the Yangtze Delta Region from 2000 to 2018, which is essentially compatible with the spatial distribution of towns in the region (Figure 4). The Yangtze Delta central region exhibits a large-scale regional expansion, whereas its peripheral regions exhibit a more modest point-like expansion concentrated on the urban core. Living space has increased in all cities, from 31,263 km² in 2000 to 48,026 km² in 2018 (Table 4), and the increases have been relatively large in Suzhou (8.62%), Shanghai (8.5%), Ningbo (4.94%), Nantong (4.46%), Hangzhou (4.01%), Hefei (3.97%), Nanjing (3.95%), and Wuxi (3.42%) (

Table 6. Contribution degree of living space change of cities from 2000 to 2018.

Region	Contribution Degree	Region	Contribution Degree	Region	Contribution Degree
Suzhou	8.62%	Changzhou	2.80%	Suzhou (AH)	1.28%
Shanghai	8.50%	Taizhou (JS)	2.59%	Bozhou	1.16%
Ningbo	4.94%	Yangzhou	2.43%	Xuancheng	1.15%
Nantong	4.46%	Huai’an	2.41%	Zhoushan	1.05%
Hangzhou	4.01%	Suqian	2.35%	Huainan	0.93%
Hefei	3.97%	Chuzhou	2.01%	Huaibei	0.92%
Nanjing	3.95%	Huzhou	1.88%	Ma’anshan	0.89%
Jinhua	3.88%	Lishui	1.85%	Chizhou	0.78%
Jiaxing	3.42%	Zhenjiang	1.83%	Bengbu	0.75%
Wuxi	3.42%	Quzhou	1.63%	Lianyungang	0.65%
Wenzhou	3.26%	Lu’an	1.57%	Huangshan	0.51%
Xuzhou	3.16%	Fuyang	1.50%	Tongling	0.32%
Taizhou	3.09%	Wuhu	1.48%	Yancheng	0.27%
Shaoxing	2.98%	Anqing	1.36%

). This trend is consistent with the Yangtze Delta Region’s recent rapid urbanization and the substantial growth of urban areas [52]. Smaller increases are found in the cities of Yancheng (0.27%), Tongling (0.32%), Huangshan (0.51%), and Lianyungang (0.65%).

In particular, the amount of living space increased dramatically between 2000 and 2010, growing by 11,111 km², and it performed so across all cities, albeit it was mostly concentrated in the Yangtze Delta Region’s key cities of Suzhou, Shanghai, Ningbo, Nantong, Wuxi, and Nanjing. Smaller rises can be seen in Zhoushan, Huangshan, Tongling, and other hilly cities with low resident populations. Living space increased by 5652 km² between 2010 and 2018, with the majority of these relatively high increases occurring in the core Yangtze Delta cities of Shanghai, Hangzhou, Hefei, Suzhou, and Ningbo. The regions with smaller growth rates are mainly cities with relatively large mountainous areas, including Huangshan, Chizhou, Ma’anshan, and Anqing. At the same time, living space began to expand in Yancheng, Lianyungang, Tongling, and other places.

3.1.3. Spatial Pattern of Ecological Space

The Yangtze Delta Region’s ecological space from 2000 to 2018 is primarily spread in the hilly mountainous south of the river (Figure 5), while the northern portion is dispersed in lake water bodies and low mountainous regions. The ecological land area has decreased over time, from 321,527 km² in 2000 to 306,153 km² in 2018 (Table 4), and the ecological space area has decreased in all municipalities except Zhoushan City. This decline is inextricably linked to Zhoushan City’s ongoing efforts to protect the environment, including the “Blue Bay Regulation” project that was started in 2016 and the construction of the “Marine Garden City” that was proposed in 2017 [53]. The cities of Suzhou (9.36%), Shanghai (7.92%), Nantong (4.56%), Hangzhou (4.34%), Hefei (4.30%), Nanjing (4.28%), Wuxi (3.71%), and Xuzhou (3.42%) had large reductions, and those with relatively small area reductions were Yancheng (0.16%), Tongling (0.34%), Lianyungang (0.38%), Huangshan (0.56%), Chizhou (0.85%), and Ma’anshan (0.97%) (

Table 7. Contribution of each city to ecological spatial change from 2000 to 2018.

Region	Contribution Degree	Region	Contribution Degree	Region	Contribution Degree
Suzhou	9.36%	Yangzhou	2.63%	Suzhou (AH)	1.39%
Shanghai	7.92%	Huai’an	2.61%	Bozhou	1.26%
Nantong	4.56%	Suqian	2.55%	Xuancheng	1.26%
Hangzhou	4.34%	Ningbo	2.40%	Huaibei	1.00%
Hefei	4.30%	Taizhou	2.31%	Huainan	1.00%
Nanjing	4.28%	Chuzhou	2.18%	Ma’anshan	0.97%
Jinhua	4.21%	Huzhou	2.04%	Chizhou	0.85%
Wuxi	3.71%	Lishui	2.01%	Bengbu	0.81%
Xuzhou	3.42%	Zhenjiang	1.99%	Huangshan	0.56%
Jiaxing	3.37%	Quzhou	1.77%	Lianyungang	0.38%
Shaoxing	3.09%	Lu’an	1.71%	Tongling	0.34%
Changzhou	3.04%	Fuyang	1.63%	Yancheng	0.16%
Wenzhou	2.94%	Wuhu	1.60%	Zhoushan	−0.21%
Taizhou (JS)	2.80%	Anqing	1.48%

).

A total of 11,036 km² of ecological space was lost between 2000 and 2010, with Suzhou, Shanghai, Ningbo, Wuxi, Nanjing, Hefei, and Hangzhou serving as the core cities of the Yangtze Delta Region, with the largest municipal areas and densest populations, while Zhoushan, Huaibei, Huangshan, and Tongling have the smallest loss of ecological land areas and least dense populations. From 2010 to 2018, the overall ecological space is still further reduced, with an area of 4338 km², except for Lianyungang, Ningbo, Yancheng, Zhoushan, and Tongling, where the ecological space is expanded, and all cities have a reduced ecological area. In addition, Shanghai, Hangzhou, Hefei, Suzhou, Nantong, Jinhua, Chuzhou, Lishui, Lu’an, and other cities have a larger reduction, while Huangshan, Chizhou, Ma’anshan, Anqing, and other cities with more hilly and mountainous areas and smaller municipal areas have a smaller reduction.

3.2. Functional Spatial and Temporal Evolution of the “Production-Living-Ecological Space” in the Yangtze Delta Region City Cluster

Based on the scores of production space, living space, and ecological space, the PLES spatial function indices were calculated through the PLESI model to evaluate the level of PLES spatial functions in the Yangtze Delta Region from 2000 to 2018; the mean value of the spatial functional index of the Yangtze Delta Region decreased from 2.253 to 2.222, and in general, the functional level of the plain areas was relatively low, while the functional level of the hilly mountains was higher (Figure 6). In terms of administrative units, the functional index value of Lishui is the largest in all years and is greater than 2.4. Huangshan, Quzhou, and Xuancheng are primarily hilly mountainous areas with ecological functions—primarily food production—and highly developed secondary and tertiary industries—which means that their functional index values are also quite substantial and belong to the high-value area. Due to Shanghai’s high population density and the fact that the majority of land use building in this city is made up of living and producing space with only a small amount of ecological space, Shanghai has the lowest value of the function index across all years. The Yangtze Delta Region’s economic, urban, and densely populated areas, particularly Nanjing, Suzhou, Wuxi, Changzhou, and Yangzhou, have function index values that are generally low for all time intervals. Additionally, the functional indices throughout the middle and lower sections of the Yangtze River as well as along the Qiantang River significantly grew from 2000 to 2018, which is inextricably tied to the region’s recent ecological advancement. From a comprehensive standpoint, the enhancement of ecological environment quality in a region can lead to an expansion in its ecological space and an improvement in functional indices. Conversely, an increase in ecological space and improved functional indices reciprocally contribute to further amelioration of the region’s ecological environment quality. Examining this dynamic from a more nuanced and specific angle, the Yangtze Delta Region has prioritized the implementation of significant ecological restoration projects as a means of advancing the development of the Yangtze River Economic Belt, in accordance with the river management concept of “to step up conservation of the Yangtze River and stop its over development”. Shanghai, for instance, has finished 17 projects, including sludge treatment projects in the Lingang Special Area, Chenjia Town of Chongming District, Songjiang District, Jiading District, and Fengxian District, which have gradually brought the ecological environment along the Yangtze River back to normal levels [54]. Additonally, Hangzhou City began the “Three Rivers and Two Banks” ecological landscape protection and construction project in 2011, closing and moving 12 sand quarries and 14 wharves within the main drinking water source area while promoting the transformation of industries along the river, developing humanistic tourism, and constructing a golden ecological tourism line integrating landscape and cultural landscape [55].

The Yangtze Delta Region’s functional level of the PLES overall exhibited a considerable decline during the period of 2000 to 2018, with negative growth in the region’s core, riverine, and coastal areas, and locations where urban clusters are more developed (

Table 8. Variation value of the functional index.

Administrative Unit	Province	2000–2010	2010–2018	2000–2018
Anqing	Anhui	−0.004	−0.001	−0.006
Bengbu	Anhui	−0.004	−0.004	−0.008
Bozhou	Anhui	−0.002	−0.006	−0.008
Chizhou	Anhui	−0.005	−0.003	−0.008
Chuzhou	Anhui	−0.006	−0.011	−0.017
Fuyang	Anhui	−0.003	−0.013	−0.016
Hefei	Anhui	−0.013	−0.011	−0.023
Huaibei	Anhui	−0.006	−0.024	−0.03
Huainan	Anhui	−0.009	−0.012	−0.021
Huangshan	Anhui	−0.002	−0.001	−0.003
Lu’an	Anhui	−0.002	−0.007	−0.009
Ma’anshan	Anhui	−0.022	−0.007	−0.029
Suzhou (AH)	Anhui	−0.003	−0.006	−0.009
Tongling	Anhui	−0.011	0.004	−0.007
Wuhu	Anhui	−0.011	−0.006	−0.017
Xuancheng	Anhui	−0.004	−0.003	−0.007
Changzhou	Jiangsu	−0.049	−0.005	−0.053
Huai’an	Jiangsu	−0.028	−0.008	−0.036
Lianyungang	Jiangsu	−0.014	−0.027	−0.042
Nanjing	Jiangsu	−0.053	0.021	−0.033
Nantong	Jiangsu	−0.03	−0.037	−0.067
Suqian	Jiangsu	−0.021	−0.005	−0.025
Suzhou	Jiangsu	−0.075	0.026	−0.049
Taizhou (JS)	Jiangsu	−0.051	−0.012	−0.063
Wuxi	Jiangsu	−0.027	−0.005	−0.031
Xuzhou	Jiangsu	−0.015	−0.009	−0.023
Yancheng	Jiangsu	−0.051	−0.035	−0.086
Yangzhou	Jiangsu	−0.032	−0.006	−0.038
Zhenjiang	Jiangsu	−0.022	−0.007	−0.029
Shanghai	Shanghai	−0.061	0.061	0
Hangzhou	Zhejiang	−0.006	−0.008	−0.014
Huzhou	Zhejiang	−0.025	−0.013	−0.038
Jiaxing	Zhejiang	−0.071	−0.009	−0.063
Jinhua	Zhejiang	−0.024	−0.006	−0.03
Lishui	Zhejiang	−0.011	−0.009	−0.02
Ningbo	Zhejiang	−0.145	0.061	−0.084
Quzhou	Zhejiang	−0.01	−0.011	−0.021
Shaoxing	Zhejiang	−0.019	−0.006	−0.025
Taizhou	Zhejiang	−0.053	0.004	−0.049
Wenzhou	Zhejiang	−0.035	0.003	−0.032
Zhoushan	Zhejiang	−0.037	−0.059	−0.097

). In particular, from 2000 to 2010, all cities’ PLESI indices decreased, with Ningbo experiencing the largest decline (0.145) and the least amount of change in other cities, which is associated with a rapid loss of coastal ecological space brought on by the reclamation of Hangzhou Bay New Zone [56]; Shanghai (0.061), Ningbo (0.061), and Ningbo (0.062), Ningbo (0.061), Suzhou (0.026), and Nanjing (0.021) cities saw greater index value growth between 2010 and 2018, whereas Jiaxing (−0.009), Tongling (0.004), Taizhou (0.004), Wenzhou (0.003), and other cities with relatively small resident populations saw less significant index growth. Zhoushan (−0.059), Nantong (−0.037), Yancheng (−0.035), Lianyungang (−0.027), Huaibei (−0.024), Fuyang (−0.013), Huzhou (−0.013), Taizhou (JS) (−0.012), and other locations also experienced negative growth, although the decline is only marginal.

3.3. Motivation of the Functional Level Differentiation of the “Production-Living-Ecological Space”

The spatial patterns of the PLES in the Yangtze Delta Region and their functional levels vary by region, and the natural environment, urban economic development, and urbanization level are the key influencing variables. The Yangtze Delta Region’s general spatial layout of PLES is determined by the natural environment. Plains predominate in the Yangtze Delta Region’s northern and eastern areas, whereas hills and mountains predominate in the southern and western areas. While the ecological land is primarily located in the high mountains in the southwest, the regions suited for living and production are primarily concentrated in the Yangtze Delta Plain along the eastern coast and rivers. Economic and social development are the main forces behind the PLES spatial pattern’s emergence in the Yangtze Delta Region. The Yangtze Delta Region’s central area serves as the primary distribution hub for the city cluster’s secondary and tertiary industries. The eastern coastal and riverine areas of the city cluster’s economic development are spatially superior to the inland areas in the northwest. The supply and demand for urban construction land are out of balance, which is one of many problems brought on by economic and social expansion. As a result, the PLES in the area is evolving spatially with a focus on places beyond the core region. In addition, the inclusion of five key metropolitan regions in the Yangtze Delta Region City Cluster Development Plan and the publishing of the Yangtze Delta Regional Plan in 2010 have created fresh opportunities for the expansion of the Yangtze Delta Region city cluster. The Yangtze Delta Region city clusters have rapidly urbanized while occupying a sizable amount of productive and ecologically significant land, altering the original spatial relationships between the PLES areas and resulting in escalating spatial conflicts between production, living, and ecology in the region.

3.4. The Coupling and Coordination Characteristics of the PLES

3.4.1. The Coupling Characteristics of “Production-Living” Space

The Yangtze Delta Region’s “production-living” spatial coupling coordination is defined by a high level in the northern plains and the eastern central Yangtze Delta cities, and a low level in the southern steep mountains, in terms of spatial dimension. For example, Shanghai, Jiaxing, Wuxi, Zhenjiang, Nanjing, Changzhou, and Taizhou (JS) in the central region of the Yangtze Delta; Xuzhou, Suqian, Lianyungang, and Huai’an in northern Jiangsu; Fuyang, Bozhou, Suzhou (AH), and Huaibei in northern Anhui; and southern Anhui, western Zhejiang, and southern Zhejiang are in a high level of coordinated coupling, while southern Anhui, western Zhejiang, and southern Zhejiang are in a low level of coordinated coupling (Figure 7).

The Yangtze Delta Region’s spatial coupling coordination of “production-living” exhibits a declining trend over time. In total, 41 cities’ average level falls from 0.69 to 0.64. Suzhou City moves from outstanding coordination to high-quality coordination between 2000 and 2010, whereas Jinhua City shifts from moderate dissonance to near discord. These cities also have large increases in coupling coordination values between 2000 and 2010: Suzhou, Jinhua, Nantong, and Wuxi, with Jinhua moving from moderate to close to dissonance and Suzhou changing from excellent coordination to high-quality coordination. In comparison to the previous ones, the coupling coordination of the cities of Hefei, Tongling, Huainan, Yancheng, and Bengbu greatly reduced and all decreased by one stage. In Zhoushan, Taizhou, Quzhou, Wenzhou, and Jinhua, the coupling coordination values increased from 2010 to 2018, but they dramatically declined in Lianyungang, Tongling, Yancheng, Xuzhou, and Suqian. Yangzhou experiences a relatively minor deterioration, although it does so from a stage of exceptional coordination to one of high-quality coordination.

3.4.2. The Coupling Characteristics of “Production-Ecology” Space

The “production-ecology” coupling coordination process is fundamentally a struggle and conflict between production space and ecological space, and excessive production function development can result in encroachment on ecological space and the weakening of some ecological functions. According to the results, the overall coordination is at a high level, and the high-frequency values of the production–ecology coupling coordination are in the range of 0.8 to 1. Except for a few cities, the Yangtze Delta Region’s “production-ecology” function coupling coordination degree exhibits a high spatial distribution characteristic in the spatial dimension. These places include central Anhui Province, Nantong, Yancheng, and Huai’an City in Jiangsu Province, and Ningbo, Shaoxing, and Jinhua City in Zhejiang Province. The “production-ecology” function coupling coordination is always at a low level in Shanghai, Huangshan, and Lishui. (Figure 8).

The high-value area of “production-ecology” function coupling coordination showed an upward trend in the time dimension from 2000 to 2018, and the average level across 41 cities climbed from 0.77 to 0.78. In particular, there was a significant increase in coupling coordination between 2000 and 2010 in the northern Anhui and northern Jiangsu regions, with Lianyungang, Fuyang, Bozhou, Yangzhou, Suzhou (AH), Bengbu, Huabei, and Yangzhou coupling coordination increasing by one stage over the previous stage. The degree of “production-ecology” function coupling coordination in Jiaxing, Zhoushan, Nantong, Huabei, and Taizhou cities decreased by one stage compared to the previous phase between 2010 and 2018. The degree of overall “production-ecology” function coupling coordination changed relatively little between 2010 and 2018, while In Jiaxing, Zhoushan, Nantong, Huabei, and Taizhou (JS), it declined substantially more and decreased by one grade in comparison to the previous one in Zhoushan and Jiaxing. In Suqian, Taizhou, Ningbo, Lianyungang, Wenzhou, Tongling, and Anqing, the coupling coordination rose significantly more, with Taizhou and Suqian increasing by one level compared to the previous one. No changes were visible in Shanghai, Jinhua, Huainan, or Chuzhou.

3.4.3. The Coupling Characteristics of “Living-Ecology” Space

The term “living-ecology” occurs most frequently between 0.6 and 0.8, and the degree of coordination of this function coupling shows a trend where the high-value area keeps changing into a middle and high-value area while the middle-value area gradually changes into a middle and low-value area. This suggests that in the match between both living space and ecological space, living space is winning more often than ecological space. In the spatial dimension, the coordination degree of “living-ecology” function coupling shows low distribution characteristics in the southwest hilly mountains and relatively high distribution characteristics in other regions, among which Huai’an, Wuxi, Ningbo, Suqian, Zhoushan, Shaoxing, and other cities have a relatively high coordination degree of “living-ecology” function coupling. Huai’an, Wuxi, Ningbo, Suqian, Zhoushan, Shaoxing, and other cities have a relatively high degree of coordination of “living-ecology” functions, and are in a high-quality coordinated coupling state overall. The cities of Lishui, Shanghai, Huangshan, Quzhou, Chizhou, and Xuancheng have relatively low values of “living-ecology” function coupling coordination, and are in a low level of coordination coupling (Figure 9).

The overall characteristics of high coupling coordination areas are changing with time, whereas those of low and medium coupling coordination areas are advancing. Between 2000 and 2010, the importance of “living-ecology” function coupling coordination increased dramatically in the northern part of Yangtze Delta, including Xuzhou and Nantong, which increased by one stage in comparison to the previous stage. The value of “living-ecology” function coupling coordination decreased in Huangshan, Chuzhou, Xuancheng, Lu’an, and Anqing, with Huangshan, Chuzhou, Xuancheng, and Ma’anshan decreasing by one stage compared to the previous period, and Lishui and Shanghai experiencing much smaller and more stable changes. Only Quzhou, Taizhou, and Zhoushan experienced a small increase between 2010 and 2018, while Shanghai, Lishui, Jinhua, and Wenzhou experienced a subtle change. All other cities had small declines, with Xuzhou, Yancheng, Taizhou, Nantong, Hefei, Nanjing, Chizhou, and Jiaxing declining by one stage in comparison to the prior cities. Only Shanghai, Lishui, Jinhua, and Wenzhou stayed unaltered.

The functions of production and living are those that ensure residents’ fundamental needs for both yield and residing, and they have long been in the process of complementing one another. The production function establishes the financial and material groundwork for residents to maintain their livelihoods and raise their standards of living, while the continued development of the living function offers human and technical assurance for production. The “production-living” function’s coupling coordination has a high-frequency range of 0.8 to 1.0, but there are also some low-frequency ranges, as the data show. The high-frequency area of “living-ecology” function coupling coordination is in the range of 0.6–0.8. As can be seen, the amount of “production-ecology” functional coupling coordination is often higher than that of “production-living” and “living-ecology” within the same period (Figure 10).

4. Discussion

The study of the functions and spatiotemporal evolution of PLES is a fundamental task in the preparation of territorial spatial planning. Studying PLES’ functional measurement, pattern evolution, and coupling properties can serve to clarify the optimal coordination of PLES’ direction, broaden the theory of its optimal allocation, and give useful references. This study investigates the factors influencing regions with significant area changes and visualizes the spatiotemporal pattern evolution of the Yangtze Delta Region city cluster based on land use data. Based on the PLES functional index, we examine the pattern and course of its evolution in the Chinese mega-city cluster, investigate the degree of coupling coordination between the two geographical areas, and then determine how PLES interacts with its surroundings. The Yangtze Delta Region has excellent natural circumstances, a high population quality and urbanization level, and a high level of regional integration, but its internal growth is still unequal to some extent. In the Yangtze Delta Region city cluster, for instance, the ecological space exhibits a similar center-edge pattern with production and living spaces, but they also form a distinct “misalignment” relationship, with the ecological space of the central cities with larger production and living spaces being smaller and less coupled with the ecological space. With smaller manufacturing and housing areas, the ecological spaces in outlying cities have larger areas and are generally more integrated with adjacent spaces. This negative link suggests that the scope of urban expansion and the intensity of development is unlikely to be proactively managed during the new wave of urbanization building. Future ecological space in the Yangtze Delta Region’s key cities is projected to shrink, and the struggle with available land for production and habitation will intensify. Therefore, each city in the region should be evaluated according to the PLES function, pattern evolution, and type of coupling coordination in order to achieve sustainable and coordinated development of the PLES within the Yangtze Delta mega-city cluster and to provide development experience for other large city clusters in developing countries. According to the result, we further put forward three suggestions to form a better PLES patter and achieve sustainable development goals:

(1)

For areas with large production–living space (PLS), but poor ecological function and dysfunction between PLS and ecological space (like Shanghai), the rational planning of production land is crucial to prevent a reduction in ecological space caused by over-development, thereby safeguarding arable land from encroachment. To achieve this, it is essential to transform the economic development model and phase out high-polluting and high-emission industries while simultaneously enhancing the environmental carrying capacity. Furthermore, the region should promote coordinated and synergistic growth with the Yangtze Delta Region, leveraging its scientific, technological, and human resource advantages. Additionally, financial and technological support should be extended to peripheral cities to foster their development. Furthermore, the region must maintain a beneficial synergy between industrial reform and industry transfer to outlying cities. The total urban population should be kept under control, and there should be restrictions on the development of transitional real estate [5]. Three Zones and Three Lines planning should be expedited in terms of ecological space, and the region should also establish and improve the targeted ecological compensation mechanism in the wetland ecological demonstration areas, such as Qingpu and Chongming District in Shanghai, and expedite the ecological protection and restoration projects of mountains, water, forest areas, and restoration initiatives to assure the steady expansion in ecological space, leading in the region’s PLES development in a coordinated manner.

(2)

For areas with small PLS, large ecological space, high functional value, but dis-coordination between living space and production space (like Hangzhou and Jinhua), the development of unused land in this region should be supported by strict adherence to environmental preservation, and efforts should be made to embrace eco-friendly land development and use practices. Reduced development should be carried out on arable land [57]. To encourage urbanization at a county level, the region should rationally develop residential areas and expedite the building of transportation and other facilities. In terms of ecology, this area should keep up its current ecological infrastructure without overusing it. Such regions have a significant potential for overall sustainable development, and the coupling coordination within the PLES tends to move up to a greater level of coordination.

(3)

For areas with small PLS, large ecological space, high functional value, but dis-coordination in PLES (like Lishui and Huangshan), the “ecological-economic gap” makes it challenging to coordinate the development of ecological functions and economic development, which results in poor overall coupling coordination among the PLES sectors. Therefore, in the future, it is important to choose the development strategy that will work best for these locations given the local conditions, avoiding both over-development, which will drastically diminish the amount of ecological space left in the area, and slow development, which will only cause population reduction and a low rate of urbanization. Regarding production space, given the limited plains and arable land in the area, there is a pressing need to enhance farmland infrastructure and expedite the development of high-standard special agriculture. This will facilitate the creation of a core area that ensures food security and an efficient supply of vital agricultural products within the Yangtze Delta Region. Moreover, the region should proactively welcome the transfer of industries from central cities in the Yangtze Delta Region and accelerate the development of industrial parks to optimize production space. In terms of living space, the area should prioritize infrastructure building while actively pursuing livelihood initiatives to support local residents’ employment, ensure farmers’ financial returns, further enhance public service systems like the social economy and housing security, strengthen county-level classification guidance for urbanization, and encourage urbanization in the immediate vicinity [58]. Within the parameters of the ecological red line, green and ecological sectors like tourism and ecological agriculture should be moderately expanded. Only reasonable development based on the principle of “moderate” can overcome a situation of being constrained by natural conditions and achieve sustainable and coordinated development of PLES [59].

However, this research is not without shortcomings. Firstly, this study selected raw data with a 30 m resolution due to limitations in data access and funding constraints. However, it is anticipated that as conditions permit, future research will employ higher resolution data to achieve greater accuracy. We extend our gratitude for the insightful feedback that has significantly improved the manuscript’s quality and readability. Secondly, the research is concentrated exclusively on examining the developmental status and limitations of each city within the Yangtze Delta Region, specifically in relation to land use classification and the evaluation system of Production, Living, and Ecological Spaces (PLES). This approach is inadequate as the regional space is a complex and integrated system comprising natural resources, ecological environment, economy, and society [60]. While this study sheds light on the current situation of the three spatial areas and their interaction within each city, it is not comprehensive. For instance, the land use classification data only offer a rough analysis of surface buildings’ spatial categories and fail to differentiate between various properties, such as office buildings and residential construction land belonging to the tertiary industry. To mitigate errors and delve deeper into the interaction and coupling coordination mechanisms of the three spatial functions in a region, as well as to design an optimized pathway for their harmonious development, our future research will integrate methodologies used by other scholars in studying the Yangtze Delta Region’s Production, Living, and Ecological Spaces (PLES). This includes employing tools like the Geographic Detector to unearth deeper intrinsic relationships between spatial functions [61]. Additionally, we will use the entropy weighting method and the Analytic Hierarchy Process (AHP) to construct a more precise functional evaluation model, analyzing specific socio-economic development aspects [41]. Learning from international research methods on similar subjects [62,63], we plan to use multiple models to assess these functions in other major cities in China and globally [64]. This approach aims to offer more constructive development recommendations for their future growth.

5. Conclusions

In this study, we have developed spatial functional indices within the framework of the PLES evaluation system, taking into account the Chinese government’s increasing commitment to ecological and arable land protection. Our research is primarily focused on the Yangtze Delta Region, where we employ the results of PLES functionality measurements to address key questions:

(1)

What are the characteristics of the spatial distribution of PLES in the Yangtze Delta Region, and how has PLES in the Yangtze Delta Region changed in extent since the 21st century?

(2)

What are the distributional characteristics of the functional coordination of PLES in the Yangtze Delta Region, and how has PLES in the Yangtze Delta Region changed in terms of overall functional coherence since the 21st century?

(3)

What patterns exist in the coupling coordination of PLES in the Yangtze Delta Re-gion, and how has the level of coupling and coordination among these spaces evolved since the 21st century?

Answer to question (1):

(1)

Spatial pattern of PLES. From 2000 to 2018, the production space is primarily concentrated in the northern Jiangsu and Anhui provinces, the Jianghuai Plain, Huaihai Plain, and along the Yangtze River Plain; the living space is primarily concentrated in the dense urban areas along the river, coastal, and East Longhai areas, which is primarily consistent with the location of the main production areas of rice and other food crops in the Yangtze Delta Region. Similar to the distribution of the third largest forest area in China, the ecological space is primarily dispersed in the high mountainous regions south of the Yangtze River.

(2)

Evolution of the PLES pattern. Between 2000 and 2018, there was a general expansion trend in production space due to the recent emphasis on arable land protection and the promotion of the Yangtze Delta Region’s integration construction. Since most of the arable land in the region is situated in non-core cities north of the Yangtze River, the implementation of regional coordination policies and the promotion of the region’s integration have utilized less-developed interior areas as sites for industrial transfer, resulting in an ongoing reduction in production space in core cities and an ongoing expansion in production space in non-core cities during this period. Among them, the established riverside cities like Shanghai, Suzhou, and Wuxi have reduced the area of production space, whereas Yancheng, Nantong, Taizhou, and Lishui have increased it. The ecological space dramatically shrunk between 2000 and 2018, with a large portion of the decline occurring in the plain areas where the population is concentrated and a smaller portion occurring in the hilly and mountainous areas where the population is sparse. Although Suzhou, Shanghai, Nantong, Hangzhou, Hefei, Nanjing, Wuxi, and other Yangtze Delta core cities have experienced more ecological space loss than other core cities, the overall ecological space loss has been reduced as a result of the region’s increased focus on environmental protection in recent years. Zhoushan is the only city whose size has somewhat increased.

Answer to question (2):

(1)

Spatial-temporal divergence of the PLES functions. The spatial pattern reveals a high degree of functionality in the mountainous highlands and a relatively low level of functionality in the plains. In terms of administrative units, Quzhou and Huangshan cities also have higher functional index values, which are part of the high-value area, primarily for hilly mountainous areas with ecological functions and primarily for food production. Lishui has the largest functional index value across all years. Shanghai has the lowest function index values across all years, and Jiaxing, Suzhou, Wuxi, Nanjing, Changzhou, and Jiaxing have similarly low function index values across all periods. These areas are low value, primarily economic, urban, and densely populated in the Yangtze Delta Region city cluster. The average value of the Yangtze Delta Region’s spatial function index declined from 2.253 to 2.222 yearly between 2000 and 2018, according to the temporal pattern. Ningbo, Suzhou, Jiaxing, Shanghai, Nanjing, and other cities in the Yangtze Delta Region central area are major regions with negative growth in the functional index from 2000 to 2010; from 2010 to 2018, the regions with positive growth in the functional index expanded, and the functional index of Shanghai, Ningbo, Suzhou, Nanjing, Jiaxing, and other cities in the Yangtze Delta central area increased to varying degrees, among which coastal cities including Zhoushan, Nantong, Yancheng, and Lianyungang had severe population declines.

(2)

The dynamics of the spatial and functional level of differentiation of PLES. The natural environment, socioeconomic development, and degree of regional integration are the key determinants of noticeable regional disparities. The Yangtze Delta Region’s PLES is determined by a number of factors, the natural environment being one of them. The main factor influencing the evolution of the PLES’ spatial pattern in the Yangtze Delta Region is its economic and social development, and its evolving spatial PLES pattern is fueled by regional integration.

Answer to question (3):

(1)

Functional coupling of the PLES. On the whole, the level of functional coupling and coordination of “production-ecology” is higher than that of “production-living” and “living-ecology” in the same period. Living–production–ecology is only loosely spatially coupled. The eastern Yangtze Delta Region’s core cities and northern plains have high spatial distribution features in terms of “production-living” function coupling coordination level, whereas the southwest’s steep mountains exhibit low spatial distribution characteristics. With the exception of a few cities, the spatial distribution of “production-ecology” function coupling coordination is strong. The “living-ecology” function coupling coordination degree exhibits low distributional characteristics in southwest hilly mountain areas and relatively high distributional characteristics in other areas. In the time dimension, except for the increasing trend of “production-ecology” function coupling coordination, both “production-living” and “living-ecology” function coupling coordination degrees show an increasing trend of “production-ecology” function coupling coordination. In addition to the increasing trend of the “production-ecology” function coupling coordination level, the “production-living” and “living-ecology” function coupling coordination levels additionally display the rising trends of the high-value area to the medium–high value area and the middle-value area to the middle–low value region. This tendency and the evolution of the PLES pattern show that the living function dominates other functions when rotating between the living space and other venues.