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Article

Study on the Characteristics and Influencing Factors of Land Use Changes in the Metropolitan Fringe Area: The Case of Shenzhen Metropolitan Area in China

by
Shuhan Deng
,
Yihui Huang
and
Hongsheng Chen
*
School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
*
Author to whom correspondence should be addressed.
Land 2023, 12(9), 1724; https://doi.org/10.3390/land12091724
Submission received: 3 August 2023 / Revised: 27 August 2023 / Accepted: 30 August 2023 / Published: 5 September 2023
(This article belongs to the Special Issue Land Development and Socio-Spatial Differentiation in Metropolitan Fringe Areas)
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Abstract

:
With the development of the regional economy, the metropolitan area has gradually shifted from the rapid development stage of concentrating on the central city to the stage of coordinated and integrated regional development. This trend has brought new development opportunities to the metropolitan fringe area; however, due to the differences in resource endowment and the complex relationship between different levels of government, the metropolitan fringe area inevitably has contradictions and imbalances in economic and social development. There has been extensive research on land use and urban governance in the metropolitan area, but less attention has been paid to the metropolitan fringe area, and it is difficult to quantitatively characterize the complex interactions between various forces in this area. This paper summarizes the spatial pattern and spatiotemporal characteristics of construction land use in the fringe area of Shenzhen metropolitan area based on the 30 m resolution land cover dataset from 2000 to 2020, and analyzes the driving factors affecting the changes of construction land use through logistic regression. The results show that the overall land use in the study area is shifting from cropland and forest land to urban and rural construction land. With different stages of development, the rate of land change varies greatly from one period to another. Three factors, population density, lighting index and distance to highway, have a significant correlation with the changes in built-up land across the region, while the boundary effects of administrative boundaries show some variation in the impact of urban land expansion at different economic levels. Finally, we put forward that reducing the negative impact of administrative divisions on the integration of resources in different cities is important for realizing the synergistic development of the Shenzhen metropolitan area.

1. Introduction

With the rapid advancement of urbanization and the deepening of economic globalization, the way in which the urban system is organized and its spatial structure are changing, the spatial phenomenon of urban groups is emerging in more and more countries and regions, and metropolitan areas, city clusters and metropolitan belts are becoming the high-level spatial organization forms of the world’s urbanization process [1]. After nearly 40 years of rapid development in China, with the rapid development of industrialization and urbanization, the spatial interaction between cities and regions has been increasing, giving birth to a number of metropolitan areas with global impact [2]. At present, China has entered a new stage of regional spatial development dominated by metropolitan areas, and the development of metropolitan areas has gradually shifted from the rapid development mode of central city agglomeration in the past to the stage of coordinated and integrated regional development [3,4]. The strategy of coordinated regional development has brought new development opportunities to the metropolitan fringe area, and a large number of people and enterprises have moved in.
However, cases from different areas around the world show that socioeconomic tensions and imbalances are prevalent in metropolitan areas [5]. This problem is particularly pronounced in the metropolitan fringe area [6]. The complexity of the situation at the metropolitan fringe area is due to, on the one hand, the intense mobility of factors and high frequency of cross-border activities within the metropolitan area have broken down traditional administrative and spatial boundaries [7]; on the other hand, the fact that the fringes are characterized by the different administrative districts to which they belong and the differences in their management policies and in their socio-economic development. The metropolitan fringe areas are considered to have great potential for economic development, but they are also relatively mixed with land use structure and landscape, and lack of planning.
Research on metropolitan areas has been a hot topic in academia in recent years. Many studies have investigated various aspects of metropolitan area characteristics, such as population growth [8], spatial expansion [9,10], driving forces [11,12], and metropolitan governance [13,14]. Recently, an increasing number of studies have attempted to explore the spatial changes in metropolitan areas, and a large number of studies have quantitatively measured various spatial change processes, dynamics, and patterns within metropolitan areas through the use of remote sensing image identification techniques and the establishment of assessment indicators [15,16]. However, there are fewer studies on land use changes in the metropolitan fringe areas, and a few studies focus on identifying the urban–rural fringe of metropolitan areas [17,18]. It is important for the integrated development of the metropolitan area to alleviate the development imbalance in the border areas and to promote the unified formulation of urban planning and land use policies.
In the past, research on the metropolitan fringe areas has focused more on regional cooperation, and less on land use change [19,20]. Exploring the mechanism of urban land expansion in the metropolitan fringe area is an important way to observe the phenomenon of unbalanced development of this region. The research methods of urban land expansion mechanism mainly include multiple linear regression (MLR) [21,22], system dynamics (SD) [23,24], analytic hierarchy process (AHP) [25], structural equation modeling (SEM) [26], logistic regression [27,28], and so on. Logistic regression allows the regression problem for the dependent variable to be treated as a discontinuous variable, which does not require a linear relationship between the dependent and independent variables. When used in conjunction with GIS, it can effectively reflect the spatial characteristics of the variables and can be used for driver analysis [29]. In terms of factors influencing urban land expansion, socioeconomic factors are more active and easier to measure. There have been many research results which mainly involve population growth [11], economic development [30,31,32] and industrial structure [33,34]. Administrative boundaries, as city limits and dividing lines between cities, have an impact on the process of urban land expansion while impeding the flow of factors such as economy, information and population, especially at the metropolitan fringe areas [35]. Administrative boundaries, as artificial abstract geographic elements, are the limits of sovereignty of neighboring countries or the boundaries of authority for efficient management of micro-regions. The connotation of administrative boundaries in China is much richer. In the process of urbanization, the macro-policy of industrial layout, and the household registration system have shaped the administrative boundary into an invisible high wall, hindering the efficient flow of factors such as economy, labor, and information. Exploring the urban expansion process in the metropolitan fringe area needs to fully grasp the role of administrative boundary elements. However, the difficulty of quantitatively describing abstract spatial geographic elements has made the study of the administrative boundary elements of urban land expansion a major puzzle.
To summarize, the existing studies have contributed to the land use management and socioeconomic development of metropolitan areas and urban agglomerations, but scholars still pay less attention to the land use studies of metropolitan fringe areas. Meanwhile, the existing literature mainly focus on socioeconomic aspects and pay less attention to administrative boundaries, when exploring the factors of urban construction land expansion. The Shenzhen Metropolitan Area is located in the Guangdong-Hong Kong-Macao Greater Bay Area in southern China, and is one of the most economically active regions in China. Shenzhen and its neighboring cities of Dongguan and Huizhou have close economic ties, so the edge of the Shenzhen metropolitan area is a typical junction area with unbalanced regional development and prominent human–land conflicts [36]. Therefore, this paper analyzes the land use cover data on both sides of the administrative boundary of Shenzhen, Dongguan, and Huizhou to verify three hypotheses: (1) the scale and speed of urban land expansion in the metropolitan fringe areas are different due to different resource endowments and development stages; (2) the driving factors for urban land expansion in the metropolitan fringe areas are similar; (3) due to the fact that they are divided into different administrative districts at different stages of development, the impact of the boundary effect on the expansion of urban land use in the metropolitan fringe area will be more and more significant. The influence of border effect on the expansion of urban construction land is characterized by spatial differentiation. This paper focuses on analyzing the land use structure changes and influencing factors in the fringe areas of Shenzhen metropolitan area and comparing the land use changes in the fringe areas of different cities, exploring and analyzing the characteristics and laws of land use changes in the fringe areas of Shenzhen metropolitan area and its core influencing factors, in order to explore how to make the administrative boundary areas of Shenzhen metropolitan area better respond to the integration process of metropolitan area development and provide coping ideas for the administrative boundary areas of other similar metropolitan areas. The study is aimed at exploring how the administrative boundary area of Shenzhen metropolitan area can better cope with the integration process of metropolitan area development and provide ideas for other similar metropolitan area administrative boundary areas.

2. Methods

2.1. Research Area

The study area was selected to be immediately adjacent to the administrative boundary of Shenzhen City on both sides of the streets or towns, including Shenzhen City, Dongguan City, and Huizhou City (Figure 1). The total land area of the region is 3631.44 km2, and the number of populations in 2020 is 17,844,700. The study area is located on the east bank of the Pearl River Estuary in the south-central part of Guangdong Province, southeast of the Guangdong-Hong Kong-Macao Greater Bay Area. Over the past 40 years of China’s reform and opening up, the Guangdong-Hong Kong-Macao Greater Bay Area has created a miracle of development and become one of the important engines of China’s economy. The Shenzhen metropolitan area is the most economically dynamic area in the Guangdong-Hong Kong-Macao Greater Bay Area, with a strategic position and its importance. The beginning of cooperation between Shenzhen and its neighboring cities of Dongguan and Huizhou can be traced back to 2008, when the State Council approved the “Outline of the Plan for the Reform and Development of the Pearl River Delta (2008–2020)”, which put forward the requirement of accelerating the integrated development of Shenzhen, Dongguan, and Huizhou, and the relevant regional development plans and policies began to strengthen the guidance of cross-city synergistic development, and the subsequent deepening of the three places’ cooperation [37]. Shenzhen, Dongguan, and Huizhou have some of the highest degrees of marketization in China; their private economies are developed, and private enterprise and private capital are active, presenting the characteristics of “big market and small government”, and the Yangtze River Delta, Beijing, Tianjin, and Hebei regions show obvious differences. As early as 2006, in order to seek new development space, Shenzhen enterprises have begun to spontaneously seek technical and market cooperation with neighboring regions, traditional manufacturing enterprises (producing machinery, toys, and instruments, etc.) have relocated out, and some of the advantageous industries of the leading enterprises have also continued to expand outward. At the same time, the number of Shenzhen residents moving to neighboring areas to buy property has increased significantly, and Shenzhen, Dongguan, and Huizhou residents commute more and more frequently. And the edge of the Shenzhen metropolitan area this area has become an important area connecting the three cities. Recent years have seen expansion of urban construction land in the study area, resulting in the rapid development of urban and rural construction land area.
The basic characteristics of Shenzhen, Dongguan, and Huizhou (2021) are as follows: In the early years, Shenzhen’s development was driven by the transfer of manufacturing industries from Hong Kong, and after entering the 21st century, Shenzhen gradually began its industrial transformation, with the focus of industrial investment shifting to high-tech industries [38]. Shenzhen currently has the strongest economy among the three cities, with a per capita GDP of CNY 173,600 in 2021, and also has the highest population density, with 8851 people per square kilometer. After 2008, the successful transformation of Shenzhen further strengthened industrial ties with Dongguan and Huizhou, and a trend of the proliferation of Shenzhen settlements to Dongguan and Huizhou began to appear. Dongguan is now dominated by manufacturing, with the secondary industry accounting for 58.21% of the city’s GDP. The per capita GDP of Dongguan is CNY 103,200, and the population density is 4259 people per square kilometer. Huizhou City has the weakest economy among the three cities, with a GDP per capita of CNY 82,100 and a population density of 426 people per square kilometer.

2.2. Data Sources

The eight periods of land use cover data (1985–2020, one period every five years) used in this paper were obtained from the China Annual Land Cover Dataset (CLCD) [39]. The dataset was obtained from Landsat remote sensing images by random forest classifier and correction based on logical inference, with a spatial resolution of 30 m. The land use types were divided into nine categories: cropland, forest, shrub, grassland, water, ice, barren, impervious, and wetland. Population density data were obtained from the Worldpop global population raster dataset (https://www.worldpop.org/ (accessed on 25 February 2023)), with a spatial resolution of 100 m, and other required data in Table 1.

2.3. Research Methods

2.3.1. Center-of-Mass Migration

The center-of-mass migration method is a method for describing the spatial transformation of geographic objects. The center of mass reflects the geographic center and high-density part of the spatial elements, and its positional shift can reflect the overall spatial distribution change of the geographic object [27]. The formula for the coordinates of the center of mass is as follows:
X = ∑ i = 1 n S i × X i S
Y = ∑ i = 1 n S i × Y i S
where X and Y represent the coordinates of the center of mass of all construction land patch area in a given region. X i and Y i represents the geometric center point coordinates of construction land patch area i ; S i is the land area of construction land patch area i ; S is the total land area in the study area.

2.3.2. Logistic Regression Analysis of Influencing Factors

Logistic regression analysis model has been applied to the study of land use/cover change drivers in recent years, which can accurately screen out the factors that have a significant influence on the occurrence of changes in feature types [40,41]. It mainly includes four types of parameters: regression coefficient, Wald statistic, significance level, and standard deviation, and the formulas are as follows:
T = 1 ,   C o n v e r s i o n   f r o m   o t h e r   l a n d   t y p e s   s u c h   a s   c r o p l a n d   t o   c o n s t r u c t i o n   l a n d 0 ,   N o   c h a n g e s   f r o m   o t h e r   l a n d   t y p e s   t o   b u i l d i n g   l a n d   h a v e   o c c u r r e d
I n P 1 − P = β 0 + β 1 x 1 + β 2 x 2 + … + β n x n
where T indicates whether construction patches are expanding, i.e., whether the sample sites were converted from non-built-up other land types to built-up land from 1985–2020; P represents the probability of a change in the T ; x 1 , x 2 , …, x n is the n influences on the outcome T ; β 1 , β 2 , …, β n is the partial regression coefficient of the logistic regression. ArcGIS 10.2 was utilized to randomly sample 10,000 sample data throughout the study area, and then spatial assignment of the driving factors was performed to extract the values of the independent variables and the dependent variable to establish a binary regression model. The change of construction land in the study area from 1985 to 2020 was used as the dependent variable, and the values of 1 and 0 were assigned to expansion and no significant change, respectively. Administrative boundary effects were characterized by the regression coefficients of the distance of the sample points from the administrative boundaries of Shenzhen City with Dongguan City and Huizhou City ( X 1 ). The administrative boundary effect is mainly manifested in the shielding effect, that is, the urban infrastructure, production factors, service system, and other aspects of the city to the center of the agglomeration; the coefficient is positive. With the enhancement of the intermediary effect, cross-border activities in the border area increase, and the frequent flow of materials and information makes the border area become an area where enterprises and capitals seek the optimal location and pursue the maximum profit, which will further lead to an increase in economic and construction activities in the border area, in which case the coefficient will change into a negative one.
According to the actual situation of the study area and data accessibility, and referring to the existing research results to set other driving factors from both socioeconomic and location aspects, among which: population density ( X 2 ) and lighting index ( X 5 ) were selected for socioeconomic factors, and distance from highway ( X 3 ) and distance from water system ( X 4 ) were selected for location factors. Higher population densities and areas with higher light indices mean that urban sprawl is more likely to occur. Road traffic affects people’s mobility, and the closer a place is to a highway, the more accessible it is to the outside world. The factor of proximity to roads is also an important driver of urban sprawl. Distance to waterways as a natural environmental factor also has a real impact on urban land expansion.
Due to the large terrain undulation in the study area, the values of population density or lighting index were 0 in some areas, so they were deleted, and finally, 9831 sample data were obtained. The spatial attribute information was extracted and imported into SPSS Statistics 24, and the logistic regression model was used for the correlation analysis of urban expansion drivers.

3. Results

3.1. Characteristics of Spatial and Temporal Changes of Land Expansion in the Fringe Areas of Shenzhen Metropolitan Area

3.1.1. Spatial and Temporal Characteristics of Territorial Urban Expansion

From 1985 to 2020, the land use patterns of the study area underwent significant changes, mainly manifested in the transformation of arable land to construction land types and the large-scale expansion of urban built-up areas (Figure 2). The total area of built-up land in the whole region grew from 27.60 km2 in 1985 to 733.298 km2 in 2020, an expansion of 26.57 times, with an average annual expansion rate of 20.16 km2/a. With the advancement of the urbanization process, the average annual expansion rate of the built-up area and the intensity of the expansion at each stage changed constantly, and reached the highest value in 1995–2000, which was 35.90 km2/a (Table 2).
According to the changes in the scale and expansion rate of construction land in each period, the land use in the fringe areas of the Shenzhen metropolitan area can be divided into three stages, namely, “non-construction land is dominant—rapid growth of construction land—slowdown in the growth of construction land”.
Non-construction-land-use-dominated stage: 1985–1990. The overall scale of urban land use in the study area was at a relatively low level, and land use changes were mainly characterized by the conversion of forest land to cultivated land. The expansion rate of construction land was also slow, with a total increase of 13.88 km2 in the area of construction land during 1985–1990, with an expansion intensity of 10.59%. This period was the beginning stage of economic growth in the study area, with land development in the central urban area as the main focus and slow economic development in the fringe areas, hence the slow urban expansion.
Stage of rapid growth of construction land: 1990–2005. The overall pattern of land use in the fringe area of Shenzhen metropolitan area has changed dramatically, with urban construction land expanding rapidly at an average rate of 30.33 km2/a, especially from 1995 to 2000, when it was as high as 34.07 km2/a. From 1990 to 2005, the land use changes were mainly manifested in the conversion of cultivated land and forested land into construction land, with a total increase of 454.91 km2 in the area of construction land and an expansion rate of 1234.63%. During this period, the economy of Shenzhen and its neighboring areas continued to grow at a high rate. During this period, Shenzhen’s rapid economic growth, rapid construction of transportation and urban infrastructure, and the influence of the central city on the peripheral areas became stronger and stronger. Along with the rapid economic growth, the urban development of the central city gradually approached saturation, so the land in the peripheral areas ushered in high-speed expansion. The adjacent areas of Shenzhen’s neighboring cities have also gradually begun to be subjected to Shenzhen’s economic radiation, and a large number of enterprises have been transferred from the central city to the fringe areas, resulting in the rapid development of the secondary industry in the fringe areas, and generating a huge demand for construction land.
The stage of slowing down the growth of construction land: 2005–2020. The speed and intensity of urban construction land expansion in the fringe areas of the Shenzhen metropolitan area declined significantly compared with the previous period, to only 13.09 km2/a, with a total increase of 196.29 km2 of construction land. Basically, Shenzhen reached the point of exhaustive utilization of land resources at this stage, with only a small amount of space left in the whole city for construction. The development of land in the Dongguan and Huizhou areas of the Shenzhen metropolitan area was also basically completed.

3.1.2. Spatial and Temporal Characteristics of Urban Expansion by Administrative District

Figure 2 and Figure 3 show the spatial and temporal characteristics of urban expansion in each administrative region. In the study area, the construction land in Shenzhen grew at a high rate from 1990 to 2005, and after 2005, there was less available land left, and the growth of construction land was extremely slow. The growth trend of Dongguan area is similar to that of Shenzhen, but Dongguan has more abundant developable land resources than Shenzhen, and still maintains a low growth rate after 2005. Spatially, in the Dongguan area in the 1990–2000 period, the construction on the land along the highway quickly spread along the molding, the distribution of the extension of the integration of cross-district transportation arteries. From 2000 to 2005, the construction continued to expand outward over a large area, Chang’an Town—Shajing Street—Songgang Street, Fenggang Town—Pinghu Street, leading to further integration.
Figure 4 presents the results of center of mass migration for the three areas of Shenzhen, Dongguan, and Huizhou. The results of the center of mass migration analysis show that the spatial offset distance of the center of mass constructed in the fringe areas of the Shenzhen metropolitan area over the past 30 years is relatively limited. In the Dongguan area, due to the early rapid expansion of Fenggang Town-Pinghu Street, the center of mass shifted substantially to the southeast during 1985–1995. After 2005, with the gradual depletion of land resources and the rapid development of Dongguan Songshan Lake area, the center of mass shifted to the northwest year by year. The center of mass migration in Shenzhen is relatively small, and the center of mass has moved eastward in the last century due to the large amount of development in Longgang area, and the center of gravity of development in the fringe areas of Shenzhen gradually migrated westward after 2000 due to the establishment of Longhua District and Guangming District, and the overall migration changes are slower and shorter due to the limited land available for development in the city. The center of gravity migration in Huizhou area shows a trend of moving southwestward and closer to Shenzhen year by year.

3.2. Analysis of the Influencing Factors of Urban Expansion in the Fringe Areas of Shenzhen Metropolitan Area

3.2.1. Territorial Urban Expansion Drivers

In order to reveal the heterogeneity among administrative regions and summarize the differences in administrative boundary effects under different regional synergy models, this paper first carries out a full-area driving mechanism analysis, and then further screens for the driving factors that have a significant impact on the construction expansion of Shenzhen, Dongguan, and Huizhou. The results of the domain-wide regression are shown in Table 3, the overall correct rate of model prediction is 77.2%, the Cox–Snell R2 is 0.306 and the Nagelkerke R2 is 0.424. The regression equation is given by:
P = e x p ( − 3.663 + 0.034 × X 1 + 0.142 × X 2 − 0.567 × X 3 − 0.138 × X 4 + 0.618 × X 5 ) 1 + e x p ( − 3.663 + 0.034 × X 1 + 0.142 × X 2 − 0.567 × X 3 − 0.138 × X 4 + 0.618 × X 5 )
Table 3 shows that X 2 , X 3 , and X 5 have significant influence on urban construction land expansion. Among them, population density, lighting index, and distance from administrative boundaries were positively correlated with the logistic regression relationship of building land expansion, while distance from highway and distance from water system were negatively correlated with urban building land expansion. In Table 3, population density has the highest correlation, and the Wald statistic is 331.829, indicating that the higher the intensity of non-agricultural activities, the more significant the urban land expansion. Distance from highway is negatively correlated with the expansion of construction. This can also be seen from the spatial distribution of construction in the previous section. The factor of light index and distance from highway also has a significant effect on urban expansion in the study area, with Wald statistics of 233.082 and 212.479, indicating that the higher the intensity of non-agricultural industrial activities and the closer the distance from the highway, the more significant the expansion of urban land is. The regression coefficient of distance from the administrative boundary is positive, and the Wald statistic is smaller, only 16.915, which indicates that from the perspective of the whole area, the closer to the administrative boundary of Shenzhen City, the less significant urban land expansion, but this factor has little influence compared with other indicators.

3.2.2. Factors Affecting Urban Sprawl in the Administrative Districts

The regression results for each administrative region are shown in Table 4 with overall correct model predictions of 76.0%, 75.4%, and 83.2%, respectively. The pseudo R2 values are all greater than 0.25.
As shown by the Wald statistic, population density and distance to highway are the common main drivers of construction expansion in the fringe areas of the Shenzhen metropolitan area, which are more consistent with the drivers in the whole study area. At the same time, the driving effects of distance to administrative boundary and distance to water system in the three regions show some differences due to the different natural geographic conditions, socioeconomic development stages, and land management policies in each region. The role of administrative boundary effect varies within each administrative region.
The expansion of construction in the Shenzhen area is not significantly affected by its distance from the administrative boundary, mainly because of the scarcity of developable land resources in Shenzhen, while at the same time, the city is developing at a very fast pace, requiring a large amount of land. The degree of land development and utilization in Shenzhen is very high; excluding the designated ecological protection areas, the construction land was basically developed as early as around 2005, so the geographic location of the land has little influence on whether it is converted into construction land. At the same time, although Shenzhen is the most economically powerful city in the study area, there is imbalance in its internal development, the attractiveness of the center of Shenzhen (such as Nanshan District and Futian District) is significantly higher than that of other areas in the study area, with respect to its marginal areas. Therefore, administrative boundaries have no significant effect on the marginal areas of Shenzhen. In addition, the table shows that there is a correlation between the distance from the highway and the expansion of construction land in Shenzhen, with a Wald statistic of 39.229. Since the house prices in the peripheral areas of Shenzhen are much lower than those in the central area of Shenzhen, many young people who want to settle down in Shenzhen choose to buy a house in the peripheral areas of the city and work in the central area. Therefore, in order to facilitate commuting to work, homebuyers have higher requirements for the transportation convenience of the place where they live. Areas on both sides of the highway have greater accessibility than other areas and are therefore given higher priority for development as building land [42,43].
The construction expansion of Dongguan city area has a certain negative impact on its distance from the administrative boundary. Combined with the spatial distribution map of construction land in the previous section—although there is a certain scale of construction land fusion in the border area of Dongguan and Shenzhen, such as Chang’an Town-Shajing Street-Songgang Street, Fenggang Town-Pinghu Street, etc.—more construction land in Dongguan area is still laid out around the northern Songshan Lake annex. At the same time, the table demonstrates that the distance from the highway has a very significant correlation with the expansion of construction land in Dongguan, and the Wald statistic is as high as 125.679, which is the highest among the three cities. In Dongguan near the Shenzhen area, the closer the highway land is, the more likely it is to be converted into construction land. Dongguan and Shenzhen’s economic and trade exchanges are very close, and there are many industrial developments to be undertaken as a result of the spillover from Shenzhen. The land on both sides of the highway is more convenient to Shenzhen and is therefore prioritized for development [44].
The opposite is true for the construction expansion of the Huizhou area and its distance from the administrative boundary, which has a negative coefficient and a positive effect. This indicates that the expansion of construction land in Huizhou has a more significant trend toward the Shenzhen border. In terms of economic strength, there is a large gap between Huizhou and Shenzhen, so Huizhou’s need for Shenzhen’s economic radiation is also much stronger. Although the economic strength of Huizhou is relatively weak, it is the largest city in the area of the three cities, and its housing prices are far lower than Shenzhen and Dongguan. With the development of the metro in Shenzhen metropolitan area, part of Huizhou is also able to directly reach the hinterland of Shenzhen. Therefore, settling in Huizhou near Shenzhen has also become the choice of many young people working in Shenzhen, and a large number of real estate developments have appeared in the border areas of Huizhou [45].

3.3. Discussion

This study summarizes the characteristics of land use change in Shenzhen metropolitan fringe area, and explores different influencing factors of urban expansion in the fringe area, which enriches the research perspective of the metropolitan area. In terms of research methodology, existing studies focus on analyzing the regional scope of city clusters and metropolitan extension zones involving multiple large cities [46], whereas the scope of this study is at the small scale of the fringe area of the metropolitan area and involves three cities, namely one large core city and two non-core cities. Meanwhile, in terms of the research content, existing studies focus on analyzing the impact of administrative boundaries on regional integration [19,47], while this paper comprehensively analyzes the impacts of edge cities, regional transportation, regional development strategies, etc., on urban land use changes, taking into account the special characteristics of the research object’s location. In addition, this study focuses on the influence factor of administrative boundaries, which is a very important factor that has a very important impact in multiple urban border areas, especially in China. Therefore, the inclusion of this factor can better reveal the causes of land use changes in the fringe areas of metropolitan areas.
The analysis of the above results shows that although the topography and location of the three administrative districts in the fringe area of the Shenzhen metropolitan area are similar, the land use changes have shown great differences over the past 35 years. Dongguan and Shenzhen have been expanding their construction land extremely quickly in the past 30 years, and the developable land is basically depleted, with some clusters showing a remarkable trend of mutual integration. The Huizhou cluster has developed relatively slowly and still retains a large amount of arable land resources. This is mainly due to the differences in geographic location and urban structure. In terms of geographic location, Shenzhen is adjacent to Hong Kong, on the one hand, to undertake the transfer of Hong Kong industries. At the same time, Shenzhen is the main implementation area of China’s reform and opening-up policy, so a large amount of land in Shenzhen has been transformed into construction land under the combined impetus of policy and market. Dongguan is located along the Pearl River estuary, with Guangzhou and Shenzhen, two mega-cities, in the middle, receiving the radiation of the rapid economic development of the two cities. Huizhou, on the other hand, has a less obvious location advantage, despite bordering Shenzhen to the southwest, it is more geared towards the mountainous and economically underdeveloped inland hinterland of northern Guangdong. In addition, it is worth emphasizing that, as the core engine of the metropolitan area of Shenzhen City, in its own development, there is strong western and weak eastern development [48]. Dongguan City, located in the northwest of Shenzhen, is more accessible to Shenzhen’s high-tech, industry-intensive areas such as Nanshan, etc., while Huizhou, located in the northeast of Shenzhen and the Longgang and Dapeng districts of Shenzhen. Longgang district itself is mainly industrial, compared to technology enterprises, and it is more difficult to generate industrial transfer (spillover benefits are limited). Therefore, Dongguan City can naturally undertake to Shenzhen development dividends, while Huizhou is difficult to develop. This has been corroborated by past studies [36]. Secondly, in the cities’ structures, Shenzhen and Dongguan are upholding the concept of multi-center structure in urban development; even the urban fringe areas also have larger growth poles [49]. Furthermore, the Huizhou fringe area is located far away from the economic center of Huizhou [50]. This is also one of the important factors affecting land use in the border areas of Huizhou and Shenzhen.
The main factors influencing the shift in land use for construction in the fringe areas of the Shenzhen metropolitan area are population density, lighting index, and distance from highways. On the one hand, determining land demand through population remains the core of land development policy in the fringe areas of the Shenzhen metropolitan area. In China, the key to overall land use planning is population size, structural projections, and land demand projections, which is consistent with previous studies [51]. On the other hand, in the Shenzhen metropolitan area, which is highly marketized and has an active economy and trade, proximity to highways means that factor flows are more convenient, and the demand for land for construction naturally grows. This is also argued by relevant studies in regions with similar situations to the Shenzhen metropolitan area [52]. Due to the differences in land policies and management of different administrative organizations, the main factors influencing the expansion of construction land vary from one administrative region to another. This is especially true for the factor of distance from administrative boundaries. Administrative districts are the basic unit of China’s construction land target allocation and integrated management, so administrative boundaries are also important for the flow of land elements [53]. In the early development of the fringe areas of the Shenzhen metropolitan area, construction land was sporadically distributed. When there is no regional synergistic division of labor, the administrative boundary mainly shows the shielding effect. With the increase of economic development factors flow, Dongguan, Huizhou near the border of Shenzhen appeared construction land clusters integration, the border effect is manifested in the construction of land, population and other factors in the vulnerable administrative boundary side of the agglomeration. As Dongguan’s economy has gradually develops and grows, seeking new development and creating a new growth pole at Songshan Lake, it is no longer clustered on the administrative side of the border.
In order to reduce the obstacles posed by administrative boundaries to the flow of factors between regions, the concept of cross-regional control and spatial control tools have gradually become the theoretical consensus and practical choice of governments at all levels [54], but the integration of the Shenzhen metropolitan area has been experiencing some practical difficulties at present. The three cities in the Shenzhen metropolitan area have already established a cross-border consultation system with joint meetings as the main body, and the multi cooperation mechanism still mainly stays at the level of dialog and consultation. Shenzhen, Dongguan, and Huizhou are three cities with complex administrative divisions. With regard to economic development, Shenzhen’s city and district governments act as the main body; in Dongguan, the towns and streets are the main body; and in Huizhou, the high-tech zones, development zones, and management committees are the dominant areas [37]. Differences in the administrative level of the economic development entities in the three cities of Shenzhen, Dongguan, and Huizhou have significantly affected the motivations and effectiveness of cooperation in each area [51].

4. Conclusions

This paper has systematically summarized the spatial and temporal evolution of construction land in the fringe region of the Shenzhen metropolitan area from 1985 to 2020, and verified three hypotheses by analyzing the driving mechanism of urban expansion, leading to the following conclusions:
The temporal characteristics of construction land changes in the fringe region of Shenzhen metropolitan area present a unified feature: “non-construction land is dominated—construction land grows rapidly—construction land growth slows down”. There are some differences in the spatial evolution: sporadic distribution of construction land from 1985–1990, integration along the inter-regional transportation arteries in 1990–2000, integration of large-scale clusters at the junction of Shenzhen and Dongguan in 2000–2005, and a small amount of filling of the remaining land in 2005–2020.
According to the results of logistic regression analysis, urban expansion in the fringe areas of the Shenzhen metropolitan area has a strong correlation with three factors: population density, lighting index, and distance from highway. The factors affecting urban expansion in geographically neighboring administrative regions are generally the same but also show some differences.
Logistic regression coefficients of distance from administrative boundary are negative in Dongguan area, positive in the Huizhou area, and show no correlation in the Shenzhen area. When there is no regional synergistic division of labor, the administrative boundary mainly shows the shielding effect. As the level of regional horizontal division of labor increases, the boundary effect manifests itself as the agglomeration of construction land, population, and other elements on the weaker side of the administrative boundary, while there is no such phenomenon on the stronger side of the administrative boundary.
Due to the limitation of the accuracy of the original Landsat remote sensing monitoring data, the classification of land use types in China’s annual land cover dataset is relatively coarse, and subsequent studies can further utilize remote sensing data with higher precision interpretation, or try to combine it with other data types to carry out a more in-depth analysis of construction land with different functions. Secondly, this paper has attempted to construct a logistic model, and initially discuss the factors influencing the expansion of construction land in the border area of Shenzhen metropolitan area. It then further analyzed the correlation with the changes in the distribution of socioeconomic factors, such as population density and industrial activities, in order to provide systematic suggestions for the scientific control of the junction area.

Author Contributions

Conceptualization, H.C. and S.D.; methodology, validation, and data curation, S.D.; writing—original draft preparation, S.D.; writing—reviewing and editing, H.C. and Y.H. All authors have read and agreed to the published version of the manuscript.

Funding

This project was funded by the Shenzhen Science and Technology Program (20220810112113001).

Data Availability Statement

Not applicable.

Acknowledgments

Authors would like to acknowledge the anonymous reviewers for their constructive comments.

Conflicts of Interest

The authors declare that they have no conflict of interest.

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Figure 1. The location of the study area. Source: author’s drawing.
Figure 1. The location of the study area. Source: author’s drawing.
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Figure 2. Land use in fringe areas of the Shenzhen metropolitan area (1985–2020). Source: author’s drawing.
Figure 2. Land use in fringe areas of the Shenzhen metropolitan area (1985–2020). Source: author’s drawing.
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Figure 3. Changes in land use for construction in the study area of Shenzhen, Dongguan, and Huizhou, 1985–2020. Source: author’s drawing.
Figure 3. Changes in land use for construction in the study area of Shenzhen, Dongguan, and Huizhou, 1985–2020. Source: author’s drawing.
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Figure 4. Changes in center-of-mass migration in the Shenzhen metropolitan area, 1985–2020. Source: author’s drawing.
Figure 4. Changes in center-of-mass migration in the Shenzhen metropolitan area, 1985–2020. Source: author’s drawing.
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Table 1. Different types and source of the data used in this study.
Table 1. Different types and source of the data used in this study.
Data TypeData SourceWebsite LinkYear
Land use dataChina Annual Land Cover Datasethttps://zenodo.org/record/5210928 (accessed on 23 February 2023)1985–2020
Population densityWorldpop global population raster datasethttps://www.worldpop.org/ (accessed on 25 February 2023)2020
Distance from roadOpenStreetMaphttps://www.openstreetmap.org/ (accessed on 26 July 2022)2020
Distance to water system
Lighting indexA Prolonged Artificial Nighttime-light Dataset of China (1984–2020)https://dx.doi.org/10.11888/Socioeco.tpdc.271202 (accessed on 12 February 2023)2020
Table 2. Urban construction expansion in the fringe areas of the Shenzhen metropolitan area, (1985–2020).
Table 2. Urban construction expansion in the fringe areas of the Shenzhen metropolitan area, (1985–2020).
PeriodBase Year Area
(Km2)		Target Year Area
(Km2)		Expansion Scale
(Km2)		Expansion Rate
(Km2/a)		Expansion Strength
(%)
1985–199026.21 40.09 13.88 2.78 10.59
1990–199540.09 162.64 122.54 24.51 61.13
1995–2000162.64 332.97 170.33 34.07 20.95
2000–2005332.97 495.00 162.04 32.41 9.73
2005–2010495.00 590.80 95.80 19.16 3.87
2010–2015590.80 643.00 52.20 10.44 1.77
2015–2020643.00 691.29 48.29 9.66 1.50
Table 3. Logistic regression results of area-wide drivers in the fringe areas of Shenzhen metropolitan area.
Table 3. Logistic regression results of area-wide drivers in the fringe areas of Shenzhen metropolitan area.
FactorVariablesβSEWaldSig.Exp(β)
X 1 Distance from administrative boundary0.0340.00816.915<0.00011.035
X 2 Population density0.1420.008331.829<0.00011.153
X 3 Distance from road−0.5670.039212.479<0.00010.567
X 4 Distance to water system−0.1380.02628.300<0.00010.871
X 5 Lighting index0.6180.040233.082<0.00011.855
Constant−3.6630.216288.594<0.00010.026
β is the regression coefficient, SE is the standard error, Wald is the chi-square value, df is the degrees of freedom, Sig. is the significance, and Exp(β) is the odds.
Table 4. Logistic regression results of drivers in Shenzhen, Dongguan, and Huizhou cities.
Table 4. Logistic regression results of drivers in Shenzhen, Dongguan, and Huizhou cities.
AreaVariableβSEWaldSig.Exp(β)
ShenzhenDistance from administrative boundary0.0360.0232.4430.1181.037
Population density0.1230.010144.216<0.00011.131
Distance from road−0.3820.06139.229<0.00010.682
Distance to water system−0.2220.05317.604<0.00010.801
Lighting index0.6740.07093.167<0.00011.962
DongguanDistance from administrative boundary0.0550.01124.149<0.00011.056
Population density0.2070.015180.628<0.00011.229
Distance from road−0.8070.072125.679<0.00010.446
Distance to water system−0.1400.03515.976<0.00010.870
lighting index0.4430.07435.439<0.00011.557
HuizhouDistance from administrative boundary−0.0860.02512.0660.0010.918
Population density0.1150.02521.475<0.00011.122
Distance from road−0.5570.07752.258<0.00010.573
Distance to water system0.1030.0712.1210.1451.109
Lighting index0.7840.09273.220<0.00012.190
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Deng, S.; Huang, Y.; Chen, H. Study on the Characteristics and Influencing Factors of Land Use Changes in the Metropolitan Fringe Area: The Case of Shenzhen Metropolitan Area in China. Land 2023, 12, 1724. https://doi.org/10.3390/land12091724

AMA Style

Deng S, Huang Y, Chen H. Study on the Characteristics and Influencing Factors of Land Use Changes in the Metropolitan Fringe Area: The Case of Shenzhen Metropolitan Area in China. Land. 2023; 12(9):1724. https://doi.org/10.3390/land12091724

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Deng, Shuhan, Yihui Huang, and Hongsheng Chen. 2023. "Study on the Characteristics and Influencing Factors of Land Use Changes in the Metropolitan Fringe Area: The Case of Shenzhen Metropolitan Area in China" Land 12, no. 9: 1724. https://doi.org/10.3390/land12091724

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