Functional Measurements, Pattern Evolution, and Coupling Characteristics of “Production-Living-Ecological Space” in the Yangtze Delta Region
<p>Schematic diagram of the study area. ((<b>a</b>): China’s provincial administrations; (<b>b</b>): topography of the Yangtze Delta Region; (<b>c</b>): municipal administrative units in the Yangtze Delta Region).</p> "> Figure 2
<p>Production spatial pattern of the Yangtze Delta Region from 2000 to 2018.</p> "> Figure 3
<p>Spatial pattern variations of production space in the Yangtze Delta Region from 2000 to 2010 and 2010 to 2018.</p> "> Figure 4
<p>Living spatial pattern of the Yangtze Delta Region from 2000 to 2018.</p> "> Figure 5
<p>Ecological spatial pattern of the Yangtze Delta Region from 2000 to 2018.</p> "> Figure 6
<p>Spatial Functionality Index of the Yangtze Delta Region from 2000 to 2018.</p> "> Figure 7
<p>Production–living spatial coupling status in the Yangtze Delta Region from 2000 to 2018.</p> "> Figure 8
<p>Production–ecology spatial coupling status in the Yangtze Delta Region from 2000 to 2018.</p> "> Figure 9
<p>Living–ecology spatial coupling status in the Yangtze Delta Region from 2000 to 2018.</p> "> Figure 10
<p>Frequency diagram of functional coupling coordination index distribution.</p> ">
Abstract
:1. Introduction
- (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].
- (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?
2. Materials and Methods
2.1. Study Areas
2.2. Methodology
2.2.1. Evaluation System of the Function of the “Production–Living–Ecological Space”
2.2.2. Production–Living–Ecological Spatial Function Index Measurement Model
2.2.3. Coupling Coordination Model
2.3. Data Sources
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
3.1.2. Spatial Pattern of Living Space
3.1.3. Spatial Pattern of Ecological Space
3.2. Functional Spatial and Temporal Evolution of the “Production-Living-Ecological Space” in the Yangtze Delta Region City Cluster
3.3. Motivation of the Functional Level Differentiation of the “Production-Living-Ecological Space”
3.4. The Coupling and Coordination Characteristics of the PLES
3.4.1. The Coupling Characteristics of “Production-Living” Space
3.4.2. The Coupling Characteristics of “Production-Ecology” Space
3.4.3. The Coupling Characteristics of “Living-Ecology” Space
4. Discussion
- (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].
5. Conclusions
- (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?
- (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.
- (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.
- (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.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
References
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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 |
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. |
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) |
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 |
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% |
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% |
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% |
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 |
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Zhu, J.; Shang, Z.; Long, C.; Lu, S. Functional Measurements, Pattern Evolution, and Coupling Characteristics of “Production-Living-Ecological Space” in the Yangtze Delta Region. Sustainability 2023, 15, 16712. https://doi.org/10.3390/su152416712
Zhu J, Shang Z, Long C, Lu S. Functional Measurements, Pattern Evolution, and Coupling Characteristics of “Production-Living-Ecological Space” in the Yangtze Delta Region. Sustainability. 2023; 15(24):16712. https://doi.org/10.3390/su152416712
Chicago/Turabian StyleZhu, Jiaheng, Zhengyong Shang, Cheng Long, and Song Lu. 2023. "Functional Measurements, Pattern Evolution, and Coupling Characteristics of “Production-Living-Ecological Space” in the Yangtze Delta Region" Sustainability 15, no. 24: 16712. https://doi.org/10.3390/su152416712