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Article

To Preserve Green Buffer under Polarization and Diffusion Effects of a Fast-Developing Megalopolis

1
Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 401122, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Land 2022, 11(5), 724; https://doi.org/10.3390/land11050724
Submission received: 1 April 2022 / Revised: 6 May 2022 / Accepted: 10 May 2022 / Published: 11 May 2022

Abstract

:
The polarization and diffusion effects of landscape patterns are important features of megalopolis development. Under the urbanized effects, green space is a key spatial unit in delivering vital ecosystem services for sustainable urban planning. However, currently, fast urban developing is swamping the green space. In this study, by tracing landscape pattern changes of a fast-developing megalopolis, the Chengdu-Chongqing Megalopolis in the southeast of China, and using land-use data from 1980 to 2020, we aimed to determine the polarization and diffusion effects of the megalopolis and their impacts on the green space within and between the cities. We found that: (1) during the past four decades, spatial expansion of the megalopolis mainly occupied grassland and farmland, triggering an increase in landscape fragmentation; (2) based on socio-economic indicators, the spatial-attraction network analysis showed a significant polarization effect; however, based on the natural landscape, this analysis demonstrated a more scattered pattern; (3) importantly, the megalopolis developed at quite a similar pace, which caused the green rural area between the central cities demonstrating an encroached trend by the urbanization. To promote sustainability of the fast-developing megalopolis, we suggest that the boundary of the green space should be broadened to form a green network in which natural green space and urban green space are interconnected, improving the connectivity of habitats within the megalopolis for urban biodiversity. Our study implied that maintaining the green buffer shall be considered in advance for sustainable megaregional planning and establishing resilience of the fast-developing megalopolis.

1. Introduction

Since Gottmann firstly put forward the concept of “megalopolis” in 1957 [1], studies of megalopolises have been developed for decades. Originally, a megalopolis was termed as a composition of a central city as a core and its suburb areas as radiating around, with compact spatial organization, close economic ties, and high integration between them [2,3]. Currently, the term has been extended to a group of large-scale cities. With the fast development of the megalopolis, homogeneous urbanization within the megalopolis increases, which triggers competition for land resources and boosts the influence of the central city on the surrounding areas [4]. Therefore, without good planning, fast economic development will soon be swamping the green space within and between the cities, especially in developing countries.
Since the 21st century, megalopolises have developed very fast as a new form of urbanization. Back in 1950, only New York and Tokyo had a population of over 10 million. However, by 2025–2030, it is estimated that around 630 million people will live in approximately 40 megalopolises around the world. Although the megalopolis is an invention of the West, it has become a reality in the East. Japan’s capital Tokyo will still be the largest among them, followed by Delhi and Shanghai. The list is dominated by cities in Asia, but several in Latin America and Africa will grow rapidly as well. In addition to these megacities, about 400 million people will live in cities of 5–10 million people, and just over one billion people are expected to be living in cities of one to five million. However, most of the world’s urban population will still live in cities of less than one million people [5].
As urbanization develops around the world, the green space in the urban environment becomes a crucial component of natural ecosystems, providing numerous ecosystem services and playing an important role in sustainable megalopolis development and improvement of human well-being. The urban green space not only offers important harbors but also improves the connectivity of fragment habitats [6], which have been increasingly recognized as one of the most crucial elements in sustainable urban planning [7]. However, in recent years, with the spread of urbanization, the rural land has been a focus of contention on resource utilization. A key issue is that urbanization is quickly radiating into rural areas. Consequently, it is a common phenomenon that urbanization always occupies the surrounding green space (mainly farmland and grassland) [8,9]. Following rural land-use changes, the reduction and fragmentation of natural habitats have become a big threat to biodiversity [10]. Thus, how to preserve and restore the green space in a developing megalopolis is a primary target of sustainable urban planning [11].
By integrating the natural habitat into urban planning, the study of megalopolises has been an interdisciplinary subject. Since the 1990s, research on land use and land cover (LULC) has been combined with the megalopolis study, which quickly became one of the key subjects in the field of global change [12]. Since then, the theory of megalopolis has been continuously integrating knowledge from other fields, such as ecosystem ecology, landscape ecology, sociology, climate change, regional study, and geographic information systems (GIS), which provided a new explanatory framework for urban researchers to understand the urbanization under the background of global change. Recently, with the rapid growth of global urbanization, tracing the historical change of urban and rural LULC is fundamental in understanding how to arrange green space in urban planning [13].
Throughout the history of urban LULC changes, polarization and diffusion effects of landscape patterns appeared as the important features of megalopolis development. To demonstrate the effects, urban dynamics and its associated natural land patterns using spatial information technology with geographical information systems (GIS) has been a research hotspot [14,15,16,17]. In the studies of polarization and diffusion effects of megalopolises, a series of landscape pattern metrics have been used as important indicators to examine these effects and their potential impacts on the urban green space [15]. The landscape metrics can directly reflect the morphological complexity, fragmentation, aggregation, connectivity, richness, and evenness of landscape patches [18], some of which are closely related to ecological effects, and thus, they can effectively quantify the polarization and diffusion effects caused by landscape changes resulting from urban expansion.
China is the biggest developing country around the world and, thus, is the most active region with rapid growth of urban agglomeration and fast development of economy and urbanization [19]. Accordingly, the studies of urban agglomeration emerged in China after 1964 [3]. Currently, unprecedented urbanization is emerging across China, which is characterized by very high population density, declined natural land, and fast urbanization [19]. Based on the classical urban agglomeration theory, Zheng [20] argued that China’s urban agglomeration can be summarized as a spatial model of decentralized regional agglomeration. In other words, the growth of the urban agglomeration is accompanied by the interaction of spatial agglomeration and diffusion following land-use transformation [21]. Under the booming development of urbanization in China, the megalopolises are forming at an unprecedented pace. However, most of the current research on urban agglomeration and megalopolises depends on theories and practices from the developed regions, and thus, the relevant studies on developing regions are urgently needed [13].
Therefore, based on the land use data of the Chengdu-Chongqing Megalopolis during the past forty years, this study was motivated to systematically analyze land-use changes and landscape patterns of the Chengdu-Chongqing Megalopolis. We aim to explore the spatio-temporal dynamics of the landscape patterns and identify the urban polarization and diffusion effects and their impacts on the green space in the megalopolis. This study will not only contribute to promoting the synergy and complementarity of the Chengdu-Chongqing Megalopolis but also provide a perspective for urban planning of the fast-developing megalopolises.

2. Materials and Methods

2.1. Study Area

The Chengdu-Chongqing Megalopolis is the largest urban agglomeration located in the inland of West China, which is the fourth pole of China’s economy after Beijing-Tianjin-Hebei, the Yangtze River Delta and the Great Bay area of Guangdong-Hong Kong-Macao. According to the latest national development strategy, the development planning for the Chengdu-Chongqing megalopolis jumps to one of the most important national economic zones in China. Presently, the megalopolis has developed into an obvious urban agglomeration, with a large-scale spatial structure and development model [22]. However, one key problem needed to be addressed in the near future is unbalanced and uncoordinated regional development. How to realize collaborative development with complementary advantages and, meanwhile, how to maintain the green space within the megalopolis would be the keys to solving the bottleneck of sustainable development of the Chengdu-Chongqing Megalopolis.
In the megalopolis, Chengdu is the capital city of the Sichuan province, and Chongqing is one of the four municipalities directly governed under China’s Central Government. The distance between the two cities is around 200 km. Both the population and GDP of the megalopolis account for about 90% of the total of Sichuan and Chongqing. The study area covers all cities in Chongqing and associated cities in Chengdu, with a total area of about 239,000 m2. Chengdu and the city proper of Chongqing are the two central cities of the Chengdu-Chongqing Megalopolis. The scope and location of the study area are shown in Figure 1. Table 1 shows the basic information about the Chengdu-Chongqing Megalopolis. Referring to the published yearbooks, we selected the four most important indicators of urban socio-economic development, including population, GDP, urbanization rate, and urban green space areas.

2.2. Land Use/Land Cover

The remote sensing data of land use/land cover in the study area, with a spatial resolution of 1 km, including eight periods in 1980, 1990, 1995, 2000, 2005, 2010, 2015, and 2020 were collected (Figure 2). The data set was provided by the Data Center for Resources and Environmental Sciences, the Chinese Academy of Sciences (RESDC) (http://www.resdc.cn, accessed on 10 January 2022).

2.3. Methods

2.3.1. Land-Use Transfer Matrix

In this study, a land-use transfer matrix was applied to indicate the structural characteristics of land-use patterns as well as the transforming area and direction between various types. The formula is [23,24]:
S i j = S 11 S 1 n S n 1 S n n
where S is the area of land-use type; n is the number of land-use types; i and j are the land-use types before and after the transfer; Sij represents the area of class I land converted to class j land at the beginning of a certain period.

2.3.2. Landscape Metric

Landscape metrics were used to indicate the landscape composition, structure and spatial characteristics in the study area. Referring to relevant studies [18], some landscape metrics (Table 2) were selected to represent landscape patterns. All calculations were carried out by Fragstats 4.2 [25].

2.3.3. Gravity Model

The influence of the city on the surrounding areas is positively correlated with the scale of the city and negatively correlated with the distance between cities [26]. The Gravity Model (GM) is widely used to study the interactions (space attractions) between social identities [27]. In this study, space attractions between cities were calculated as follows [28,29]:
G a b = k M a M b D 2 a b
where Gab is the interaction between cities a and b, Ma and Mb are the corresponding weights, and Dab is the Euclidean distance between the central points of these cities, k is the gravity constant, and k = 1 in this study. For example, when calculating the space attraction of GDP between two cities, Ma and Mb are the corresponding GDPs. There is supplementary material explaining how to calculate space attraction between two example cities (Appendix A).

3. Results

3.1. Land Use/Land Cover Dynamics of the Chengdu-Chongqing Megalopolis

3.1.1. Area Variations of Different Land Use/Land Cover Types

The areas of various land-use types of Chengdu-Chongqing Megalopolis from 1980 to 2020 were counted (Table 3). In general, four land-use types (farmland, woodland, grassland, and water body) were found to mostly dominate, accounting for more than 95% of the total area. However, the proportion of natural patches was found to be less than 50%, indicating that the natural ecosystem in this area is shrinking. Further, the area of farmland and grassland decreased, while the area of construction land increased year by year, and the increasing rate was accelerated, reflecting the acceleration of urban expansion. However, the woodland area began to increase after a slight fluctuation from 1980 to 2000, which reveals that those measures such as the Program of Converting Farmland to Forest played a great positive role in the restoration of woodland. In addition, the area of water body showed an increasing trend, while the change of unused land is not obvious. The reason could be that the construction of reservoirs along rivers in the region led to an increase in the water body area.
Figure 3 shows that the rise of woodland and construction land came from the reduction in farmland and grassland, indicating that the expansion of urban land was mainly achieved by sacrificing farmland and grassland. With the acceleration of urbanization, the area of construction land increased sharply, and the growth in the recent ten years from 2010 to 2020 alone exceeded that in the previous 30 years. From 1980 to 1990, farmland decreased significantly while construction land increased significantly. From 1990 to 1995, farmland and grassland were found to have declined, while woodland and construction land increased. From 1995 to 2000, a significant decrease was observed in woodland, and a significant increase was observed in grassland and construction land. From 2000 to 2015, farmland decreased significantly, but woodland and construction land increased. From 2015 to 2020, grassland decreased significantly, but woodland and construction land increased. Among the changes in land use, woodland increased significantly from 2015 to 2020, which shows that the effects of woodland restoration in this region were obvious after the implementation of the Program of Converting Farmland to Forest. At the same time, it also shows that woodland attracted more attention than grassland in the process of ecological restoration and protection.

3.1.2. Results of Land-Use Transfer Matrix

A land-use transfer matrix (Figure 4) of the study area was analyzed for two periods, from 1980 to 2000 and from 2000 to 2020. The results showed that the main transfer types from 1980 to 2000 were found as farmland-to-construction land, grassland-to-woodland, and farmland-to-water area. From 2000 to 2020, the main transfer types were found as farmland-to-woodland, farmland-to-construction land, and grassland-to-woodland. In addition, the results of the land-use transfer matrix demonstrated that the growth of construction land mainly came from farmland, while the growth of woodland mainly came from farmland and grassland.

3.1.3. Area Variation Rate

Figure 5a showed that the construction land area variation rate in the Chengdu-Chongqing Megalopolis increased from an average of 21.3 km2/a from 1980 to 1990 to 561 km2/a from 2015 to 2020, and the growth rate accelerated significantly from 2005 to 2020. The construction land area variation rate in Chengdu and the surrounding sub-cities were higher than those of Chongqing. The main contribution of the urban spatial expansion of the Chengdu-Chongqing Megalopolis came from Chengdu and its surrounding sub-cities. The area variation rate in Chengdu was found to be slightly higher than that of the proper city of Chongqing, and the growth rate in Chongqing showed a slowing trend. The growth rate of construction land in the city proper of Chongqing accounted for about 70% of that in Chongqing, including its surrounding cities. The growth rate of construction land in Chengdu accounted for about 40% of that in both Chengdu and surrounding cities. The grassland area variation rate (Figure 5b) in the Chengdu-Chongqing Megalopolis decreased sharply from 2010 to 2020, with a reduction rate of 1490 km2/a, and almost all of the contribution came from cities around the city proper of Chongqing. The woodland variation rate (Figure 5c) was found to have fluctuated in the last forty years. The growth rate of woodland in Chongqing increased significantly from 2015 to 2020 and was higher than that accounting for the Chengdu-Chongqing Megalopolis, while the woodland in Chengdu and its surrounding sub-cities decreased slightly. However, no change in woodland was found in both central cities, except for a slight growth trend that was observed from 2015 to 2020. The farmland variation rate (Figure 5d) in the Chengdu-Chongqing Megalopolis fluctuated greatly, but generally, it showed a decreasing trend. Furthermore, on the one hand, the farmland in Chongqing was found to have a slight increasing trend from 2015 to 2020, and on the other hand, the most serious loss of farmland was found in the Chengdu Plain, which would be one of the reasons why the growth rate of Chengdu and surrounding cities was found faster than that of Chongqing.

3.2. Landscape Pattern Changes of the Megalopolis

Results of landscape pattern analyses (Table 4) showed that the Number of Patches (NP), The Mean Patch Area (AREA-MN) and Edge Density (ED) of the Chengdu-Chongqing Megalopolis showed an increasing trend, indicating that the landscape fragmentation of the Chengdu-Chongqing Megalopolis increased. However, from 2015 to 2020, the landscape fragmentation began to slow down. Both the Shannon Diversity Index (SHDI) and Shannon Evenness Index (SHEI) reflect the landscape structure. The results showed that although SHDI was low with little change, it can still reflect the trend of a slight increase in the landscape diversification of the Chengdu-Chongqing Megalopolis. SHEI showed a slight growth trend, indicating that the landscape structure in this area tended to change evenly.
Table 5 showed that during the past 40 years, farmland was always the dominant land-use type of the Chengdu-Chongqing Megalopolis, and its proportion (PLAND) exceeds 50%, followed by the woodland landscape type, while the proportion of unused land was the smallest. The proportion of farmland and grassland decreased gradually, and the proportion of construction land increased, which is consistent with the above law of land-use change. The number of farmland patches (NP) fluctuated but showed a downward trend in general, indicating that the fragmentation increased. The Shape Index (SHAPE) was used to quantify the patch shape complexity and showed that the shape of farmland was the most complex, followed by woodland, and the shape of water area and unused land was the simplest. Since 2015, the shape complexity of woodland has increased significantly, while that of grassland has decreased.

3.3. Space Attraction between the Cities

The space attraction between cities (Figure 6) reflected the differences in socio-economic and land-use factors among them. The Chengdu-Chongqing Megalopolis demonstrated an obvious polarization effect in terms of GDP, population, and urban green space, forming a radiating system in an urban social and economic network centered near Chengdu and the city proper of Chongqing. The spatial attraction of the urbanization rate showed a regional administrative differentiation, and the more attractive areas were concentrated in the east of Chongqing. The variance of the urbanization rate of each city in the Chengdu-Chongqing was much smaller than that of population and GDP, so the spatial attraction of the urbanization rate was mainly affected by distance. The spatial attraction of the water body showed a single-center pattern with the city proper of Chongqing as the core. The spatial attraction of grassland showed the spatial pattern of urban agglomeration at the northeast and west of the Chengdu-Chongqing, and further, the cities with higher spatial attractiveness were mainly found along the edge of urban agglomeration. In addition, the areas with high spatial attractiveness of woodland were mainly found in the edge areas of the urban agglomeration. A spatial attraction network centered near Chongqing was formed within the urban agglomeration. The spatial attractiveness of the farmland distribution pattern was closely related to the elevation of topography, and the areas with higher attractiveness were concentrated in the central region, where the terrain is relatively flat.

4. Discussion

By synthetizing our results of the LULC and landscape structural changes over 40 years, the urban agglomeration of the Chengdu-Chongqing Megalopolis demonstrates a clear polarization effect, the gap between urban and rural regions is expanding, and the dominant position of the central cities is more and more obvious. However, the diffusion effects of the central cities on the rural region were also found. Under the coupling role of polarization and diffusion effects of the fast-developing dual-core megalopolis, the green space between the cities is gradually occupied by the urbanization. Although the current proportion of the occupied area is not large, the penetrating trend showed that we do need to carry out a measurement in advance to perverse or restore the green buffer for sustainable urban construction in the future because the green buffer has been realized as fundamental for urban resilience.

4.1. Polarization and Diffusion Effects of Land-Use Pattern

Spatial polarization and diffusion are the two typical phenomena of urban development. Spatial polarization refers to the formation of gathering centers of social and economic elements within a certain range, while spatial diffusion is a process of coordinated development between cities through social and economic interactions [30]. In this study, the urban spatial expansion of the Chengdu and Chongqing showed a strong trend of concentrating in the higher-level cities, and the central cities of Chengdu and Chongqing show an obvious status of polarization. Such a spatial polarization effect was particularly evidenced in terms of population, GDP, and construction land. After entering the twentieth century, China is facing more and more serious issues of regional spatial polarization, regional imbalance development, and regional dysfunctional conflicts in the megalopolises, especially along the coastal area. Now, the trend is extending quickly to the west. Globally, in the past two decades, the world has been experiencing its population increasingly concentrated in urban areas. Although this trend is not new, it will speed up at a remarkable rate in the years to come. A study estimated that, by 2050, urbanization combined with the overall growth of the world population could increase the urban population by about 2.5 billion people, which will further strengthen the polarization of global cities [31]. Therefore, rising spatial polarization of global urbanization is one of the defining trends of global changes after the 21st century [32,33].
Under the polarization effect, an “under-developing” zone has been formed between the two cities. Since the “under-developing” zone mostly remains a natural attribute, it plays a key role in buffering the negative impacts of urbanization and gives the megalopolis the capability of resilience against environmental changes. We believe that the development of the “under-developing” green zone will be one of the key areas for the sustainable development of the Chengdu-Chongqing and other megalopolises around the world. In addition, under the radiation from the central cities, the diffusion effect of the urban landscape to the surrounding sub-cities has also emerged. Although the polarization effect of the two central cities was found to have strengthened in recent years, the coupling role of both polarization and diffusion effects acted as the main driver in shaping the “under-developing” zone within the megalopolis and will be stronger in the future.
In addition, the topography of the Chengdu-Chongqing Megalopolis would be one of the main reasons for shaping the polarization effect and the “under-developing” zone. Unlike the sprawl of other Chinese megalopolises, e.g., the Beijing-Tianjin-Hebei Megalopolis, the Yangtze River Delta Megalopolis, and the Guangdong-Hong Kong-Macao Bay Area, the development of the Chengdu-Chongqing Megalopolis tends to be scattered due to topographic constraints. The megalopolis is located in the southwest mountainous area with limited resources. Under these conditions, the concentration of urban land is more conducive to improving the resource utilization efficiency [34]. The terrain of the two central cities is distinct. Although most surrounding sub-cities of Chengdu are on hills, the Chengdu central city lies on the plain. However, most parts of the entire Chongqing city lie on mountainous terrain. The complex and diverse terrain causes the urban landscape to form a scattered pattern connected by traffic corridors. In general, combining the exclusive topography and the spatial polarization–diffusion coupling effects, the large-scale fast development of the megalopolis demonstrates a negative impact on the natural landscapes, which directly will lead to the reduction in the natural buffer area and ecological connectivity facing serious risks of ecosystem de-services [35].

4.2. Defining Green Buffering Spatial Unit and Its Boundary

In terms of global changes, megalopolises and large cities must develop a sustainable and resilient environment to cope with the changes. Uncertainties relating to urbanization revolve around the issues of risk management, which entails managing the consequences of urban overcrowding. For instance, without the natural buffer, urbanization indeed would increase the risk of amplification and transmission of infectious diseases and pandemics. Thus, the green space would be one of the most important functional units in megaregional planning. Originally, the urban green space was defined as any vegetation found within the urban environment [36], and this concept placed particular emphasis on urban, which meant it did not include rural vegetation. However, our research showed that the size and distribution of the within-urban green space were closely related to the scale and planning of urban development, and the unnatural green space within cities showed an obvious polarization effect, meaning that the within-urban green space alone may not be enough in functioning as the buffering role against the negative impacts of urbanization under the fast development.
As an important part of improving the living environment and well-being, the green buffer space between the cities shall become a bridge between the urban and natural landscape, serving not only human beings but also other natural organisms. Thus, the between-city green zone will play a key role in buffering the negative impacts of urbanization. Therefore, we propose that the unit of the between-city green space shall be clearly defined in urban planning by figuring out its boundary between the central cities when conducting the megaregional plan. Accordingly, in the Chengdu-Chongqing Megalopolis, the marginal cities and the natural “under-developing” zone between the central cities allow the full advantages of a natural landscape and act as an ecological buffer zone between densely populated areas. Increasing the quality of the between-city green space can make up for the loss of the semi-natural within-city green space caused by urban intensive and compact development [34]. In addition, the ecological corridor in the natural green space can help to improve landscape continuity and biodiversity. In particular, the green development of a megalopolis needs to reasonably plan for the ecological green core area and give full functions to its ecological barrier and ecosystem service, which would be the key to building a sustainable and low-carbon city. Therefore, we argue that planning a complex green space attraction network and enhancing the connectivity and spatial attraction between natural green space and urban space is fundamental to sustainable development of megacities in the future. The green areas in the urban areas and suburbs would be used as recreation parks to improve the living quality of the city. The rural green areas would be used as ecological buffers to mitigate the negative impact of urbanization, especially the areas between the two central cities, which would be an important part of maintaining ecological stability.

4.3. Suggestions for Sustainable Development of the Chengdu-Chongqing Megalopolis and the Like

Sustainable megaregional planning guides us in the direction of where our debate needs to go. It would be misleading to imply that because China has a successfully planned economy, the government should have coherent megaregional planning for resilience and sustainable urban development. Actually, practical challenges of embedding sustainable designs into China’s megaregional planning do exist. Even now, although China’s government has already planned some major ecological zones in megaregional planning, they are still just concepts rather than practices. The real problem is that the ecological functional zones as independent spatial units do not yet integrate into urban agglomerations, and the policy does not exactly follow the zones. Unlike Europe’s Spatial Development Perspectives, Chinese megaregional planning was not yet clearly planned based on spatial units of the green natural area; rather, it was on the administrative province or city considering economic issues. Therefore, the policies and plans for urban agglomeration cannot be implemented properly for sustainable development.
The sound management of urbanization is a key issue for overall balance. The unprecedented acceleration indeed poses huge challenges in terms of sustainable urban development. This issue is more or less taken into consideration in Western countries but completely overlooked in other parts of the world and particularly in Africa or Latin America [37,38,39]. In China, we need to have a real national spatial plan. The current policies are based on economic data and population density and growth rates, as well as the physical landscape. Urbanization, which for a long time has been uncontrolled, is now subject to more strategic planning, but its advances are still insufficient in relation to the magnitude of this phenomenon. The megacities create a new urban dynamic, as supersized cities are seen as the new engine of the global economy, connecting the flow of goods. However, the current pattern of urbanization has all too often resulted in urban sprawl, low productivity, segregation, exclusion, and congestion. Although urbanization has the potential to make cities more prosperous and countries more developed, many of them all over the world are unprepared for the multidimensional challenges linked to the acceleration of this process. The loss of density in urban areas over the last two decades demonstrates that demographic and spatial expansions go hand in hand. Less dense cities bring higher infrastructure costs, worsened mobility and destroyed agricultural land. As stated by the UN Habitat World Cities Report 2016 [40], the current urbanization model is unequivocally unsustainable in many respects.
Although ecological restoration measures such as returning farmland to forest have been used to a certain degree, with the acceleration of urban expansion and construction in the two most recent decades, human activities are the most direct driving force for the evolution of the landscape pattern. It causes Chengdu and Chongqing to face the risk of ecological degradation. When the cities exceed the carrying capacity of the natural environment, the disappearance of natural systems cannot be reconstituted [19]. Thus, how to promote urban development on the premise of reducing ecological risk and finding the balance between social development and ecological protection is the key to the green development of the Chengdu-Chongqing Megalopolis and the like in the future.
After many times of joint and separate governance, administrative barriers hinder the integrated development to a certain extent [21]. Coordinated development and complementary advantages are important driving forces in promoting the integration of the Chengdu-Chongqing Megalopolis to a higher level. Results of this study suggest that, overall, the landscape pattern evolution of the Chengdu-Chongqing Megalopolis in the last forty years has shown obvious convergence, and the spatial development lacks functional complementarity. However, there is development potential for balancing the urban planning and ecological protection in the central cities. Therefore, we put forward the following suggestions:
(1)
The coordinated developing mode shall be highly promoted in the central city area by thoroughly reconciling the urbanizing process, forming a complementary cooperation for economic development of the dual-core megalopolis;
(2)
The homogeneous competition within the megalopolis shall be avoided by the functional partition of the central cities and their surroundings. The functional partition can be promoted by negotiating the cities’ planning and clarifying the development orientation of the central cities and surrounding cities. In addition, combined with the fact that Chongqing is mountainous and hilly, located at the Three Gorges Reservoir Area, it should play the leading role of ecological protection of the Chengdu-Chongqing Megalopolis. Chengdu and its surrounding cities are mostly located over the plain areas, and managers should pay attention to the protection of farmland and build urban green spaces. Therefore, a collaborative and complementary ecological protection network of the Chengdu-Chongqing Megalopolis is highly suggested;
(3)
At the same time as economic development is being planned, the “under-developing” zone between the two core cities shall be well considered in designing the green space as the ecological buffer for the megalopolis by preserving and restoring its natural and rural attributes. The development of the “under-developing” zone would be the key area for the sustainable development of the Chengdu-Chongqing Megalopolis in the future;
(4)
The between-city green space shall be defined as an independent spatial unit in the mega-regional planning, and the boundary of the green space should be broadened to form a green network in which natural green space and urban green space are interconnected, improving the connectivity of habitats within the megalopolis for urban biodiversity. The green space shall be considered as a key functional spatial unit (the “green core”) in megaregional planning.

5. Conclusions

During the past 40 years, the LULC of the Chengdu-Chongqing Megalopolis has changed significantly. Urban expansion is mainly at the expense of farmland and grassland. It is worth noting that the woodland area began to increase in the recent years, which indicates that measures such as returning farmland to forest and afforestation play great roles in the restoration of woodland in the Chengdu-Chongqing Megalopolis and also illustrates that the current ecological and environmental protection policies pay more attention to woodland rather than grassland. Meanwhile, the polarization and diffusion effect of the urban landscape pattern obviously emerged, especially for construction land. The spatial attraction in terms of population and GDP also demonstrates the polarization effect in the megalopolis. However, the spatial attraction of the natural landscape is mainly concentrated at the edge of the megalopolis; however, the natural landscape between the central cities lacks attractiveness. Moreover, we point out that urban planning should clearly define the between-city green space as an independent unit and expand the boundary of the green space to increase the ecological buffering function in the megalopolis, which can play a key role in enhancing the resilience capability of the cities. However, so far, Chinese megaregional planning has not yet clearly planned the green natural area as an independent functional spatial unit, but it has been carried out in the administrative provinces or cities considering economic issues. Therefore, the relevant policies and plans for urban agglomeration shall be considered properly in advance for sustainable urban development. Finally, we suggest that while strengthening the complementary, coordinated development of the Chengdu-Chongqing Megalopolis or the like, the leading role of central cities in regional development should be promoted. Importantly, as the within-city green space is increasingly polarized, the between-city green space shall be well-defined as a spatial unit in the megaregional planning to build a sustainable Chengdu-Chongqing Megalopolis and the like in the future.

Author Contributions

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

Funding

This research was funded by The Three Gorges’ follow-up scientific research project from Chongqing Municipal Bureau of Water Resources, grant number 5000002021BF40001.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

The calculation of space attraction between two cities was supported by ArcGIS 10.2. According to Formula (2), Ma and Mb are socio-economic and land use indicators of city pairs (see Table A1). The Euclidean distance between the central points of two cities was calculated by ‘calculate geometry’ in ArcGIS 10.2 based on the center points’ coordinates. The calculation steps are as follows:
  • Step1: Set appropriate geographic and projection coordinates;
  • Step2: Extract the center point of each city according to the geometric boundary of the study area;
  • Step3: Calculate the distance of city pairs according to ‘calculate geometry’.
Table A1. Parameter values of gravity model. Data source: published yearbooks and land use/land cover data from the Data Center for Resources and Environmental Sciences, the Chinese Academy of Sciences (RESDC) (http://www.resdc.cn, accessed on 10 January 2022).
Table A1. Parameter values of gravity model. Data source: published yearbooks and land use/land cover data from the Data Center for Resources and Environmental Sciences, the Chinese Academy of Sciences (RESDC) (http://www.resdc.cn, accessed on 10 January 2022).
IdCityCenter Point CoordinateGDP
(Million RMB)
Urban Green Space Area (ha)Population (Ten Thousand)Urbanization Rate (%)Water Body Area (km2)Grassland Area (km2)Woodland Area (km2)Farmland Area (km2)
1Chengdu103.933339430.6536337317,01347,987165874.4125351432207957
2Zigong104.961157529.222513471428553029254.0956194583706
3Luzhou105.454527528.532851052081724143352.0014839044826846
4Deyang104.428923931.13438142336731135653.8910124610444130
5Mianyang104.701603431.849115762856810248854.13187315674798866
6Suining105.47034630.631484761346351131951.52123786354286
7Neijiang104.884436629.646912461433456437050.589785564830
8Leshan103.566474629.208775951863424432753.36204102856515749
9Nanchong106.204478431.196442392322841064449.72273252137710,318
10Meishan103.6492430.065423211380283830047.8313639917044461
11Yibin104.635718128.571078142602610745751.1918345643977946
12Guangan106.663275830.424845021250336132543.2615314012254664
13Dazhou107.645740331.365495092041489157447.14165126060618766
14Yaan102.662691729.91594183724165315448.37126456379042209
15Ziyang105.118001930.0987701778193025044.1563542695203
16The city proper of Chongqing106.500966829.5119355619,24360,068211578.52621802744617,770
17Wanzhou108.401008930.70648688971244315768.92876339281717
18Kaizhou108.380208831.27723661536129312050.573154813272054
19Liangping107.713821330.6579682649310886450.1381284751218
20Qianjiang108.71874529.3772706424511724959.18181871413710
21Wulong107.703939829.377963732248383649.27322281776791
22Chengkou108.730196231.88857417552062041.1686171814786
23Fengdu107.82482729.886828093357405649.215417112971341
24Dianjiang107.431548330.2548004744511766549.251672101249
25Zhongxian107.910446330.3375000542811057248.27811286651298
26Yunyang108.851208331.0405144846314719352.8811082212011472
27Fengjie109.38618530.893728673235157549.536580819891197
28Wushan109.896102831.11971131893004643.39674541662725
29Wuxi109.351208331.50882991102973940.312351023791044
30Shizhu108.293340230.092753921713873957.8994471547923
31Xiushan109.013559528.492716723018835045.34192271527574
32Youyang108.8115628.858604432015156142.192655932051270
33Pengshui108.259197629.35256542454765348.252525324171177
Table A2. The data details of the city pairs chosen in Figure 6.
Table A2. The data details of the city pairs chosen in Figure 6.
LevelOrderGDPUrban Green SpacePopulationUrbanization RateWater BodyGrasslandWoodlandFarmland
City PairGabCity PairGabCity PairGabCity PairGabCity PairGabCity PairGabCity PairGabCity PairGab
High11–478191–469,0261–4116.1719–251.4716–129.068–14339.538–1432333–118456
21–1047001–1637,3221–1099.4120–331.311–106.8926–27230.153–1130647–158333
31–1642391–1027,25716–1265.592–71.211–45.0310–14194.9931–32239916–127905
416–12229516–319,6312–747.7031–321.1416–94.755–14171.6220–3317052–77898
51–5212116–1219,2571–1645.4124–251.089–124.5218–26166.1413–1816121–107105
Medium616–318081–516,97216–341.3325–300.973–114.2117–26160.998–1115661–46466
716–9125316–214,21616–938.1618–260.9116–34.1513–18138.4016–3150616–35491
81–8117916–914,1621–535.3023–250.916–93.8027–28121.8221–3314714–55271
916–211762–711,13516–731.6419–240.898–103.064–5111.7710–1414429–125207
101–7117016–711,0813–1130.7727–280.8116–63.021–14108.4320–32133416–95140
1116–1111421–710,5127–1530.7123–300.7917–262.9627–2988.0832–3313136–95001
1216–111154–585271–729.451–40.794–52.7217–1886.391–1411776–154815
131–6105516–11836616–626.7023–240.7716–112.5926–2984.214–511242–114738
1416–6102516–6834916–226.457–150.7426–272.4813–1775.601–1010989–134714
154–59601–979594–525.0021–330.7416–72.4313–2671.3327–28109816–154185
162–79031–677651–1524.801–100.712–72.401–570.818–10106113–183609
173–118421–275841–624.3726–270.708–112.3531–3262.201–510515–93574
181–157911–8757216–1523.9717–260.699–132.3522–2959.8927–29101116–73469
191–97793–1168746–923.2122–290.661–52.0717–3059.6416–2195516–113220
201–1176516–460999–1222.6428–290.651–162.0318–2259.2216–128702–33112
2116–137231–15553516–1322.3521–230.637–152.0322–2656.3828–298651–53080
221–26952–11543316–1122.0620–320.635–91.9913–2255.6516–1383116–63015
2316–1567716–1354082–1121.5018–220.611–81.9217–2754.7326–278288–112880
2416–462416–1552491–921.0417–180.5716–131.8928–2950.6722–2982116–132867
252–115981–1150641–820.1717–250.5616–251.875–1349.1613–227878–102825
2616–2457616–550289–1319.2517–190.518–141.868–1045.1823–3078116–22819
271–145692–349116–1517.2426–290.5016–231.851–1041.0516–117477–112594
Low2816–556816–2447532–315.526–150.4910–141.8418–2740.075–147041–152473
291–34601–345171–213.8513–180.4717–251.8126–2837.1221–236939–152094
3016–84361–1436681–1113.1023–330.4516–151.7711–1435.281–867712–132075
317–1537016–2336585–912.262–110.4523–251.7013–2733.541–46612–151997
3216–173666–933391–1411.8127–290.446–151.675–833.283–86411–71845
332–336516–830997–1111.444–50.422–111.655–931.0816–336111–161831
3416–233569–1230588–1010.793–110.4116–81.5422–2730.9523–335933–71806
356–93537–15292216–510.6617–300.4016–21.4920–3230.7911–1458913–191722
3616–103335–9266216–410.4622–260.381–141.4718–2930.3418–265881–81701
3716–193181–12233012–139.4713–190.3727–281.4523–3029.7616–557516–51628
389–123149–1321448–119.4312–240.3716–211.448–1129.5526–295741–91619
3916–213124–921441–39.332–30.341–61.433–1127.655–135605–61612
401–1230716–10213816–249.2532–330.346–121.3825–3027.2730–335541–61572
4116–253064–619723–78.7512–160.321–91.3626–3026.3713–2954216–241493
428–1130616–2018984–68.7319–230.3213–171.3616–1426.1713–175334–91486
438–102837–11188416–88.4130–330.3112–131.2816–526.1516–235327–81485
441–132633–7180516–238.4119–300.2918–261.2613–1926.0116–85126–121467
455–92591–1317804–97.9920–310.2913–261.255–1025.6013–2650113–171427
467–112528–11163416–107.9526–280.297–111.201–424.8825–304906–71372
479–1324716–1914916–77.826–90.2916–51.2013–2924.1713–194644–61360
484–62426–1514631–127.7924–300.291–71.1832–3323.979–1343511–151340
496–152268–1013276–127.618–100.2816–101.064–1423.905–84347–101315
5013–1821916–2113022–157.5718–190.287–81.0613–2023.6816–3242816–231313
514–91892–8127713–187.4220–300.2816–171.0620–3323.6318–2242216–81242
5213–1718816–2212751–137.2218–290.2813–181.0313–1422.6516–144214–151226
534–101645–6120716–217.0716–240.262–31.0217–2221.465–94025–151176

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Figure 1. Map of the study area. On the map, Chengdu and Chongqing are the two central and largest cities in this megalopolis.
Figure 1. Map of the study area. On the map, Chengdu and Chongqing are the two central and largest cities in this megalopolis.
Land 11 00724 g001
Figure 2. Land use/land cover map of the Chengdu-Chongqing Megalopolis.
Figure 2. Land use/land cover map of the Chengdu-Chongqing Megalopolis.
Land 11 00724 g002
Figure 3. Statistics of area variation of land-use types.
Figure 3. Statistics of area variation of land-use types.
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Figure 4. Results of the land-use transfer matrix analysis (from 1980 to 2000 and from 2000 to 2020).
Figure 4. Results of the land-use transfer matrix analysis (from 1980 to 2000 and from 2000 to 2020).
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Figure 5. Area variation rate of different land-use types in the Chengdu-Chongqing Megalopolis. (a) Construction land area variation rate; (b) grassland area variation rate; (c) woodland area variation rate; (d) farmland area variation rate.
Figure 5. Area variation rate of different land-use types in the Chengdu-Chongqing Megalopolis. (a) Construction land area variation rate; (b) grassland area variation rate; (c) woodland area variation rate; (d) farmland area variation rate.
Land 11 00724 g005
Figure 6. Space attraction between cities. Only cities with the top 10% attraction are shown on the map. High: top 1%; medium: top 1%–top 5%; low: top 5%–top 10%. (For more details, please refer to Table A1 and Table A2).
Figure 6. Space attraction between cities. Only cities with the top 10% attraction are shown on the map. High: top 1%; medium: top 1%–top 5%; low: top 5%–top 10%. (For more details, please refer to Table A1 and Table A2).
Land 11 00724 g006
Table 1. Composition and socio-economic data of the Chengdu-Chongqing Megalopolis (data source: published yearbooks).
Table 1. Composition and socio-economic data of the Chengdu-Chongqing Megalopolis (data source: published yearbooks).
IdCityCenter Point CoordinatePopulation (Thousand)GDP (Million RMB)Urbanization Rate (%)Urban Green Space Area (ha)
Central city1Chengdu103.9333 E30.6536 N16,5811,701,26574.4147,987
Cities
around
Chengdu
2Zigong104.9612 E29.2225 N2922142,84954.095530
3Luzhou105.4545 E28.5329 N4329208,12652.007241
4Deyang104.4289 E31.1344 N3561233,59153.897311
5Mianyang104.7016 E31.8491 N4877285,62054.138102
6Suining105.4703 E30.6315 N3189134,57351.523511
7Neijiang104.8844 E29.6469 N3700143,33050.584564
8Leshan103.5665 E29.2088 N3271186,33153.364244
9Nanchong106.2045 E31.1964 N6435232,22249.728410
10Meishan103.6492 E30.0654 N2995138,02047.832838
11Yibin104.6357 E28.5711 N4573260,18951.196107
12Guangan106.6633 E30.4248 N3251125,04443.263361
13Dazhou107.6457 E31.3655 N5741204,14947.144891
14Yaan102.6627 E29.9159 N154172,37948.371653
15Ziyang105.1180 E30.0988 N250377,78044.151930
Central city16The city proper of Chongqing106.5010 E29.5119 N21,1531,924,27278.5260,068
Cities
around the city proper of
Chongqing
17Wanzhou108.4010 E30.7065 N156997,06868.922443
18Kaizhou108.3802 E31.2772 N120553,58250.571293
19Liangping107.7138 E30.6580 N64549,32450.131088
20Qianjiang108.7187 E29.3773 N48824,51659.181172
21Wulong107.7039 E29.3780 N35722,42149.27838
22Chengkou108.7302 E31.8886 N198552041.16206
23Fengdu107.8248 E29.8868 N55633,54249.21740
24Dianjiang107.4315 E30.2548 N65044,48349.251176
25Zhongxian107.9104 E30.3375 N72142,76548.271105
26Yunyang108.8512 E31.0405 N93046,25952.881471
27Fengjie109.3862 E30.8937 N74532,31449.53515
28Wushan109.8961 E31.1197 N46318,87743.39300
29Wuxi109.3512 E31.5088 N38911,01740.31297
30Shizhu108.2933 E30.0928 N38917,10557.89387
31Xiushan109.0136 E28.4927 N49730,12745.34883
32Youyang108.8116 E28.8586 N60820,11542.19515
33Pengshui108.2592 E29.3526 N52924,51048.25476
Table 2. Landscape pattern metrics and description.
Table 2. Landscape pattern metrics and description.
MetricDescription
Proportion of landscape
(PLAND)
The basic measure of landscape composition, the percentage of patch area of a certain type in the total landscape area
SHAPEMeasure patch boundary shape complexity
Edge density (ED)The ratio of patch edge to total landscape area reflects the degree of landscape fragmentation
Shannon diversity index (SHDI)Measuring landscape habitat diversity
Shannon evenness index (SHEI)Measuring landscape uniformity
Number of patches (NP)The number of patches of a certain type reflects the degree of landscape fragmentation
Table 3. Area of different land-use types in the Chengdu-Chongqing Megalopolis from 1980 to 2020 (unit: km2).
Table 3. Area of different land-use types in the Chengdu-Chongqing Megalopolis from 1980 to 2020 (unit: km2).
YearFarmlandWoodlandGrasslandWater BodyConstruction LandUnused Land
1980131,94676,96425,01129172231200
1990131,65676,93725,02529962444211
1995131,29577,53524,53129902710208
2000131,08376,85125,06430053057209
2005130,04377,44024,84030273712207
2010129,36077,54724,75431364191282
2015127,97577,40024,70532855624281
2020127,96379,98420,21134947324293
Table 4. Results of landscape pattern metrics at the landscape level.
Table 4. Results of landscape pattern metrics at the landscape level.
YearNPAREA_MNEDSHDISHEI
19801456416436.84191.03240.5762
19901460116396.86391.03750.5791
19951454616456.83151.03960.5802
20001457816416.88151.04760.5847
20051469816286.91031.05770.5903
20101487316096.94251.0680.596
20151526215687.05781.08920.6079
20181525215677.04051.08710.6067
Table 5. Results of landscape pattern metrics at the class level.
Table 5. Results of landscape pattern metrics at the class level.
19801990
TypeFarmlandWoodlandGrasslandWater BodyConstruction LandUnused LandFarmlandWoodlandGrasslandWater BodyConstruction LandUnused Land
PLAND55.145532.166310.45311.21910.93240.083655.024332.155010.45891.25211.02140.0882
NP33614754367314571234853368475736661488123488
SHAPE51.70520.57846.96741.57391.53431.493251.93620.58766.97661.57561.69671.4959
19952000
PLAND54.873432.40510.25251.24961.13260.086954.784832.119110.47521.25591.27760.0873
NP33604733363814891240863381472836121495127587
SHAPE52.005220.297.06651.5761.99471.502851.74120.5167.00571.57472.07721.5003
20052010
PLAND54.350132.365210.38161.26511.55140.086554.064432.409810.34561.31071.75160.1179
NP336947973637148813228534084802365014991380134
SHAPE52.153120.40836.89631.60732.35061.505252.007419.43017.47511.67952.43841.4206
20152020
PLAND53.485632.348410.32521.37292.35050.117453.437733.44788.46661.46483.05720.1259
NP3455480336531523169513332464625394915191787126
SHAPE53.08919.42917.44851.71622.71141.422156.619424.23544.2821.75913.43841.6435
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MDPI and ACS Style

Li, X.; Zhang, J.; Huang, J.; Lin, W.; Wu, S.; Ma, M. To Preserve Green Buffer under Polarization and Diffusion Effects of a Fast-Developing Megalopolis. Land 2022, 11, 724. https://doi.org/10.3390/land11050724

AMA Style

Li X, Zhang J, Huang J, Lin W, Wu S, Ma M. To Preserve Green Buffer under Polarization and Diffusion Effects of a Fast-Developing Megalopolis. Land. 2022; 11(5):724. https://doi.org/10.3390/land11050724

Chicago/Turabian Style

Li, Xiaohong, Jiuhong Zhang, Jinxia Huang, Wenhao Lin, Shengjun Wu, and Maohua Ma. 2022. "To Preserve Green Buffer under Polarization and Diffusion Effects of a Fast-Developing Megalopolis" Land 11, no. 5: 724. https://doi.org/10.3390/land11050724

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