*Article* **Assessing the Rural–Urban Transition of China during 1980–2020 from a Coordination Perspective**

**Shiwei Zhang 1,2, Jinghui Zhao 3,\*, Yanfeng Jiang 4,\*, Ali Cheshmehzangi <sup>2</sup> and Wenbin Zhou <sup>5</sup>**


**Abstract:** Under the context of global rapid urbanization, exploring the dynamics of rural–urban transition in China can provide valuable experience for the Global South. In this study, we evaluate the rural–urban transition in China, from 1980 to 2020, based on socioeconomic data and a rural– urban transition coordination model by constructing a rural–urban development and integration index system. We identify the state and transition types, and we present optimization paths. The results show that, since the reform and opening-up, the rural–urban development index (URDI) in China has gradually expanded among regions while the rural–urban integrated index (URII) has experienced a trend of decline followed by an increase. Over the past 40 years, the spatial distribution characteristics of the ∆*URDI* have been "south high–north low", while the ∆*URII* has had a balanced spatial distribution. Over the first two decades of the past 40 years, the rural–urban transition in eastern coastal China was more coordinated, while regions with less coordination showed a twotiered distribution pattern; over the last two decades, the coordination degree has increased. Over the past 40 years, the spatial distribution of high coordination presents "T-shaped" coastal and riverside characteristics. The transition types and coupling relationships of state regions are identified. Finally, optimization pathways are proposed for each type to further promote rural–urban integration.

**Keywords:** rural–urban transition; urban and rural integration; urban and rural relations; rural and urban disparities; China

### **1. Introduction**

Rural recession has become a global phenomenon with the rise in urbanization and industrialization [1,2]. In the Global South, developmental inequality is especially acute within cities and the countryside [3–5]. Under the influence of urban expansion, although the rural–urban spatial relationship has evolved with boundaries that are gradually blurred [6,7], a significant rural and urban divide still exists [8,9]. The United Nations has proposed the 2030 Agenda for sustainable development goals (SDGs), which promotes construction of sustainable cities, revitalization of the countryside, and enhancement of rural–urban linkages as keys to realizing sustainable rural–urban development [10,11].

China's rural–urban development has undergone rapid change since the 1980s [12]. This transition has influenced the transformation of rural–urban relations and human–land relations. China's social and economic development has rapidly changed with the urbanization rate and the share of non-agricultural economy has risen steadily. However, rural–urban imbalanced development has also grown into one of the most significant imbalances in China [13]. To address this imbalance and underdevelopment of rural areas, China's central governments have proposed several strategies for rural–urban integrated

**Citation:** Zhang, S.; Zhao, J.; Jiang, Y.; Cheshmehzangi, A.; Zhou, W. Assessing the Rural–Urban Transition of China during 1980–2020 from a Coordination Perspective. *Land* **2023**, *12*, 1175. https://doi.org/ 10.3390/land12061175

Academic Editors: Li Ma, Yingnan Zhang, Muye Gan and Zhengying Shan

Received: 18 April 2023 Revised: 24 May 2023 Accepted: 25 May 2023 Published: 1 June 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

development over the past two decades [14]. As urbanization progresses, promoting land expansion to boost economic growth has been gradually running into a bottleneck as urban areas transition from incremental to stock development [15,16]. In the future, reducing rural–urban disparity and realizing rural–urban integrated development will become one of the important development paths in China [17].

In the early stage, theoretical exploration of rural–urban divide and transition has focused on the transformation of rural–urban economic relations, such as the dual-sector [18], Ranis–Fei [19], and Jorgensen [20] models. Moreover, in terms of rural–urban spatial structure, the polarization trickle-down effect [21], the center-periphery paradigm [22], and the Desakota model [23] have provided the theoretical foundation for rural–urban spatial relations. Under the context of rapid urbanization, scholars have studied rural–urban transition from various perspectives. The topics have included migration, industry, and landscape [24–28]. Furthermore, land use transition, human–land–industry systems, and rural–urban territorial systems have been applied to the analysis of rural–urban transition [29–32].

Recent studies have examined rural–urban transition from the view of rural–urban linkages [33–35], but little attention has been given to the dynamics of rural–urban diversity. In terms of spatial scale, these studies have focused on the economic zone, urban agglomerations, and country [36–39]. The time scale of these studies has been relatively small, which has lacked the depiction of comprehensive transition characteristics of rural–urban transitions. Existing research has focused on the overall characteristics of urban and rural areas but lacked discussion of the transition characteristics presented. Therefore, there remains to be a gap in understanding the rural–urban transition between rural–urban development and rural–urban integration, particularly from the perspective of exploring coupling relationships. To reveal rural–urban transition accurately, it is necessary to reflect the level of urban and rural development while emphasizing the gap between urban and rural individuals.

Rural–urban transition in China is of international significance and can provide valuable references for other developing countries. Since the reform and opening-up in 1978, China's social and economic development has been highly compressed in time and complex in content [37]. It has only taken 44 years to cross the threshold from low-income to high-income countries. Rural–urban transformation has been enormous, with the level of urbanization soaring from 17.92% to 63.89% [39,40]. Therefore, the issues that have arisen in China's rural–urban transition are instructive for other countries, especially Asian countries in the Global South.

Given the size of China's territory and the regional imbalance, it is necessary to examine the rural–urban transition at the national level. To fill the gap in rural–urban transition research with small temporal scales, in this study, we conduct a national-scale study of the rural–urban transition from 1980 to 2020. In this study, we also construct an evaluation index system, i.e., the urban–rural development index (URDI) and urban–rural integration index (URII), which not only measures the absolute level of rural–urban systems but also reveals rural–urban relative differences. The objectives of this study are: (1) to explore the characteristics and spatial patterns of the URDI and URII values in China, during 1980–2020; (2) to measure the intensity of rural–urban transition and its coordination degree in this period and to determine whether this relationship has any regional and temporal differences; (3) to identify the state and transition types during this period; and (4) to discuss implications and optimization pathways for each transition type.

### **2. Methodology**

#### *2.1. Conceptual Framework*

The essence of rural–urban development is to enhance the living and production standards of urban and rural residents within a region. This is the foundation for maintaining the functioning of a rural–urban territorial system. Rural–urban integration is the difference between the levels of urban and rural development within a region. It is the key

factor that determines the coordinated development of the rural–urban territorial system. Rural–urban development and rural–urban integration are interdependent. Improving the level of rural–urban integration can unlock the potential for economic growth, which positively affects rural–urban development [14]. positively affects rural–urban development [14]. The levels of rural–urban development and integration are representations of the rural–urban state at a specific point in time (Figure 1). They jointly determine the type of rural–urban state at that point in time, although they differ from each other to some extent.

The essence of rural–urban development is to enhance the living and production

standards of urban and rural residents within a region. This is the foundation for maintaining the functioning of a rural–urban territorial system. Rural–urban integration is the difference between the levels of urban and rural development within a region. It is the key factor that determines the coordinated development of the rural–urban territorial system. Rural–urban development and rural–urban integration are interdependent. Improving the level of rural–urban integration can unlock the potential for economic growth, which

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**2. Methodology** 

*2.1. Conceptual Framework* 

The levels of rural–urban development and integration are representations of the rural–urban state at a specific point in time (Figure 1). They jointly determine the type of rural–urban state at that point in time, although they differ from each other to some extent. The transition from one state to another is examined by measuring the coupled coordination of rural–urban state changes within one period. The transition intensity is an indicator that quantifies the degree of rural–urban state changes at a specific time stage [13,41]. The type of state at the beginning and the end of the transition stage affects the intensity of the transition at that stage. In general, the URDI is low and the URII is relatively high in State 1. During transition stage B, which is the period of rapid urbanization, the URDI rises rapidly and the URII falls. In State 2, the URDI reaches an elevated level, but the URII is low. Upon entering transition stage B, the rural–urban disparity narrows, the URII rebounds to a high level, and the URDI is maintained at an elevated level. A high-quality rural–urban transition is achieved when both the URDI and the URII improve and increase in concert. A high-intensity rural–urban development transition accompanied by a lowintensity rural–urban integration transition or a high-intensity rural–urban integration transition combined with a low-intensity rural–urban development transition cannot form a high-quality rural–urban transition. The transition from one state to another is examined by measuring the coupled coordination of rural–urban state changes within one period. The transition intensity is an indicator that quantifies the degree of rural–urban state changes at a specific time stage [13,41]. The type of state at the beginning and the end of the transition stage affects the intensity of the transition at that stage. In general, the URDI is low and the URII is relatively high in State 1. During transition stage B, which is the period of rapid urbanization, the URDI rises rapidly and the URII falls. In State 2, the URDI reaches an elevated level, but the URII is low. Upon entering transition stage B, the rural–urban disparity narrows, the URII rebounds to a high level, and the URDI is maintained at an elevated level. A high-quality rural–urban transition is achieved when both the URDI and the URII improve and increase in concert. A high-intensity rural–urban development transition accompanied by a low-intensity rural–urban integration transition or a high-intensity rural–urban integration transition combined with a low-intensity rural–urban development transition cannot form a high-quality rural–urban transition.

**Figure 1.** A conceptual model of rural–urban transition. **Figure 1.** A conceptual model of rural–urban transition.

#### *2.2. Index System Construction*

*2.2. Index System Construction*  Some studies have explored the coordination and relationships between rural and urban regional systems by constructing indicator systems of urban or rural systems [31,36,42], as well as the individual characteristics of regional development and integration [31,36]. However, the components of the indicator system are rather mixed. It is challenging to present the specific traits of regional rural–urban development and integration. The relevant indicators are chosen following the principles of completeness, representativeness, and accessibility of data. The indicator layers of the URDI and URII systems are established from four dimensions: production, income, consumption, and livelihood (Table 1). Urban and rural residents' incomes and consumption levels among them play significant roles in their wealth accumulation. To some extent, this can reflect the local levels of urban and rural development [43]. In addition to income and consumption levels, other significant factors in integrated rural–urban development include rural–urban disparity Some studies have explored the coordination and relationships between rural and urban regional systems by constructing indicator systems of urban or rural systems [31,36,42], as well as the individual characteristics of regional development and integration [31,36]. However, the components of the indicator system are rather mixed. It is challenging to present the specific traits of regional rural–urban development and integration. The relevant indicators are chosen following the principles of completeness, representativeness, and accessibility of data. The indicator layers of the URDI and URII systems are established from four dimensions: production, income, consumption, and livelihood (Table 1). Urban and rural residents' incomes and consumption levels among them play significant roles in their wealth accumulation. To some extent, this can reflect the local levels of urban and rural development [43]. In addition to income and consumption levels, other significant factors in integrated rural–urban development include rural–urban disparity in living standards as well as coordinated growth of rural–urban production sectors [44]. The data of each indicator layer are processed by the extreme difference standardization method, which eliminates the influence of the data's dimensionality and allows for comparison of data from various indicators and years.


**Table 1.** The index system of rural–urban development and rural–urban integration.

#### 2.2.1. Weight Measurement

In this study, we employ the CRITICAL method to empower indicators. The CRITICAL method is an objective empowerment method that calculates the weight of indicators [45]. It is more objective than a traditional hierarchical analysis and entropy weight methods. The preliminary data are processed dimensionless to facilitate the comparison and weighting of indicators in different units or orders of magnitude.

#### 2.2.2. Index Calculation

The URDI represents the absolute level of rural–urban development, while the URII represents the relative gap between rural and urban development. The formula for calculating these indices is as follows:

$$\mathbf{Y}\_{\mathbf{i}} = \sum\_{j=1}^{n} \omega\_{j} \mathbf{X}\_{\mathbf{i}j} \tag{1}$$

$$Z\_{\rm i} = \sum\_{j=1}^{n} \omega\_{j} X\_{\rm ij} \cdot 100\% \tag{2}$$

where *<sup>Y</sup><sup>i</sup>* and *<sup>Z</sup><sup>i</sup>* represent the URDI and the URII for the *<sup>i</sup>* region, respectively; *Xij* is the dimensionless data for the indicator; *ω<sup>j</sup>* is the weight for the *j* indicator.

#### 2.2.3. Measurement of ∆URDI and ∆URII

Rural–urban transition refers to the process of changing the state of rural–urban development or integration relative to a certain stage, and the intensity of the transition is used to determine its magnitude. The intensity of the rural–urban transition is judged by comparing the development status at the end of the period (T2) and the beginning of the period (T1) with the formula below:

$$
\Delta IIRDI = Y\_{\bar{t}} \cdot \frac{1}{Y\_{\bar{t}-1}} \tag{3}
$$

$$
\Delta \text{URII} = Z\_t - Z\_{t-1} \tag{4}
$$

where ∆*URD I<sup>t</sup>* and ∆*URI I* denote the intensity of rural–urban development transition and the intensity of rural–urban integration transition from stage *t* − 1 to *t*, respectively; *Y<sup>t</sup>* and *Yt*−<sup>1</sup> are the URDI from stage *t* − 1 to *t*, respectively; *Z<sup>t</sup>* and *Zt*−<sup>1</sup> are URII at time points *t* and *t* − 1, respectively.

#### 2.2.4. Measurement of Rural–Urban Transition Coordination Degree

Rural–urban integration aims to drive high-quality rural–urban development as a whole through rural development. Therefore, in this study, we construct a rural–urban development-integration coordination degree model to quantitatively measure the coordination state of rural–urban transition [46], which is calculated as:

$$\mathcal{C}(YT\_{l}\cdot ZT\_{l}) = \left\{ \left(\frac{YT\_{l} + ZT\_{l}}{2}\right) \cdot \left[ (YT\_{l}\cdot ZT\_{l}) \cdot \frac{1}{\left(\frac{YT\_{l} + ZT\_{l}}{2}\right)^{2}}\right]^{\frac{1}{2}} \right\} \tag{5}$$

where *C*(*YT<sup>t</sup>* ·*ZTt*) denotes the coordination degree of rural–urban transition from stage *t* − 1 to *t*, *YT<sup>t</sup>* is ∆*URDI* from stage *t* − 1 to *t*, and *ZT<sup>t</sup>* is ∆*URII* from stage *t* − 1 to *t*. A high degree of coordination means coordinated rural–urban transition.

#### 2.2.5. Data Sources

For this study, to explore the rural–urban transition characteristics since the reform and opening-up, based on the availability of data, we selected 1980–2020 as the research period to largely correspond to the period of reform and opening-up. The relevant data were mainly obtained from the China Statistical Yearbook, China Population, and Employment Statistical Yearbook, China Rural Statistical Yearbook, China Compilation of Population Statistics 1949–1985, regional statistical yearbooks, etc. To reduce the impact of price changes during the inter-annual period on timing data, 1980 was taken as the base period. The Consumer Price Index (CPI) was used to correct the data of subsequent related years for urban and rural residents' incomes, consumption expenditures, and GDP. The statistics for some regions were lacking in 1980, and anomalies in the indicators were modified by data interpolation based on adjacent areas and years.

#### **3. Results and Analysis**

### *3.1. Characteristics of the URDI and the URII*

At the national level, the ∆*URDI* has generally shown an upward trend since 1980. The first fluctuation occurred from 1992 to 1996, and an upward trend resumed after 2001. Since globalization and economic liberalization, the URII reached its highest value in 1984, and then showed a wave of decline until it reached its lowest value in 2003 [47]. The URII changed little between 2003 and 2009, with an upward trend after 2009 (Figure 2). *Land* **2023**, *12*, x FOR PEER REVIEW 6 of 15

**Figure 2.** Changes in the URDI and URII of China during 1980–2020. **Figure 2.** Changes in the URDI and URII of China during 1980–2020.

**Figure 3.** The URDI values of different regions during 1980–2020.

**Figure 4.** The URII values of different regions during 1980–2020.

The provincial URDI is arranged in reverse order using the maximum URDI value for each year as the benchmark (Figure 5). In general, the inter-provincial differences have gradually widened over the past four decades. First, the gap between Shanghai, Beijing and other regions has been gradually increasing, and the ratio between their URDI and the third place has risen from 1.09 (in 1980) to 1.18 (in 2000), and further expanded to 1.36 (in 2020). Second, with respect to the URDI, the gap between the central regions, western regions, and the northeast has been completely smoothed over the 40 years. The URDI

At the regional level, the URDI has grown significantly in each region over the past forty years. The western region has experienced a larger growth rate than the northeastern region (Figure 3). It is noteworthy that the URDI in the northeastern region was surpassed by the central and western regions from 2010 to 2020, and the gap between the western region and the northeastern region was slightly decreased by 2020. In terms of the URII, from 1980 to 1990, the URII of the western region showed a slight decline (Figure 4). During 1990–2000, the URII of all regions showed a significant decline, among which the northeastern region dropped the most, i.e., from 0.72 to 0.41, but it was still the highest. From 2000 to 2010, the URII in the eastern region declined slightly, while the URII in other regions increased slightly. The URII increased significantly across all regions between 2010 and 2020, with the central and western regions outpacing other regions. **Figure 2.** Changes in the URDI and URII of China during 1980–2020. **Figure 2.** Changes in the URDI and URII of China during 1980–2020.

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**Figure 3.** The URDI values of different regions during 1980–2020. **Figure 3.** The URDI values of different regions during 1980–2020. **Figure 3.** The URDI values of different regions during 1980–2020.

**Figure 4.** The URII values of different regions during 1980–2020. **Figure 4.** The URII values of different regions during 1980–2020. **Figure 4.** The URII values of different regions during 1980–2020.

The provincial URDI is arranged in reverse order using the maximum URDI value for each year as the benchmark (Figure 5). In general, the inter-provincial differences have gradually widened over the past four decades. First, the gap between Shanghai, Beijing and other regions has been gradually increasing, and the ratio between their URDI and the third place has risen from 1.09 (in 1980) to 1.18 (in 2000), and further expanded to 1.36 (in 2020). Second, with respect to the URDI, the gap between the central regions, western The provincial URDI is arranged in reverse order using the maximum URDI value for each year as the benchmark (Figure 5). In general, the inter-provincial differences have gradually widened over the past four decades. First, the gap between Shanghai, Beijing and other regions has been gradually increasing, and the ratio between their URDI and the third place has risen from 1.09 (in 1980) to 1.18 (in 2000), and further expanded to 1.36 (in 2020). Second, with respect to the URDI, the gap between the central regions, western The provincial URDI is arranged in reverse order using the maximum URDI value for each year as the benchmark (Figure 5). In general, the inter-provincial differences have gradually widened over the past four decades. First, the gap between Shanghai, Beijing and other regions has been gradually increasing, and the ratio between their URDI and the third place has risen from 1.09 (in 1980) to 1.18 (in 2000), and further expanded to 1.36 (in 2020). Second, with respect to the URDI, the gap between the central regions, western regions, and the northeast has been completely smoothed over the 40 years. The URDI

regions, and the northeast has been completely smoothed over the 40 years. The URDI

regions, and the northeast has been completely smoothed over the 40 years. The URDI

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values of some provincial regions in the central and western regions exceed those of the northeast region. values of some provincial regions in the central and western regions exceed those of the northeast region. values of some provincial regions in the central and western regions exceed those of the northeast region.

**Figure 5.** The comparison of provincial URDI values during 1980–2020. **Figure 5.** The comparison of provincial URDI values during 1980–2020. **Figure 5.** The comparison of provincial URDI values during 1980–2020.

#### *3.2. Spatial Pattern of the URDI and the URII 3.2. Spatial Pattern of the URDI and the URII 3.2. Spatial Pattern of the URDI and the URII*

In terms of the spatial distribution of the URDI, high-value areas exhibit a pattern of migration from north to south and from east to west over the course of 40 years. The lowvalue areas vary slightly and are all concentrated in the western region (Figure 6). The URDI gradually evolves from a coastal distribution in 1980 to a "T-shaped" distribution pattern along the coast in 2020, while the center of gravity is transferred from the Bohai Rim region to the southeast coastal area. In terms of the URII, it shows a spatial distribution of high values in the east and low values in the west, in 1980 and in 2020, with highvalue areas in 1980 concentrated in the northeast and south. Furthermore, high-value areas of URII shift to coastal areas in east China in 2000 (Figure 7). While in 2020, the URII shows a scattered distribution with high- and low-value areas distributed across all regions, among which high-value areas show a continuous distribution in the central region. In terms of the spatial distribution of the URDI, high-value areas exhibit a pattern of migration from north to south and from east to west over the course of 40 years. The low-value areas vary slightly and are all concentrated in the western region (Figure 6). The URDI gradually evolves from a coastal distribution in 1980 to a "T-shaped" distribution pattern along the coast in 2020, while the center of gravity is transferred from the Bohai Rim region to the southeast coastal area. In terms of the URII, it shows a spatial distribution of high values in the east and low values in the west, in 1980 and in 2020, with high-value areas in 1980 concentrated in the northeast and south. Furthermore, high-value areas of URII shift to coastal areas in east China in 2000 (Figure 7). While in 2020, the URII shows a scattered distribution with high- and low-value areas distributed across all regions, among which high-value areas show a continuous distribution in the central region. In terms of the spatial distribution of the URDI, high-value areas exhibit a pattern of migration from north to south and from east to west over the course of 40 years. The lowvalue areas vary slightly and are all concentrated in the western region (Figure 6). The URDI gradually evolves from a coastal distribution in 1980 to a "T-shaped" distribution pattern along the coast in 2020, while the center of gravity is transferred from the Bohai Rim region to the southeast coastal area. In terms of the URII, it shows a spatial distribution of high values in the east and low values in the west, in 1980 and in 2020, with highvalue areas in 1980 concentrated in the northeast and south. Furthermore, high-value areas of URII shift to coastal areas in east China in 2000 (Figure 7). While in 2020, the URII shows a scattered distribution with high- and low-value areas distributed across all regions, among which high-value areas show a continuous distribution in the central region.

**Figure 6.** The spatial pattern of the URDI in China, during 1980–2020. **Figure 6.** The spatial pattern of the URDI in China, during 1980–2020. **Figure 6.** The spatial pattern of the URDI in China, during 1980–2020.

### *3.3. Coupling Relationships between the URDI and the URII*

The URDI and the URII have both undergone significant changes over the last four decades. Scatter charts of the URDI and URII were constructed for 1980, 2000, and 2020 (Figure 8). Taking the average values of the URDI and the URII as the boundary to divide the high- and low-value regions, it can be seen that the scatter distribution varies little between 1980 and 2000, with the scatter primarily concentrating in the first and third quadrants in 1980–2000, and the scatter concentrating in the fourth quadrant in 2020. Between 2000 and

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2020, the points in the high URDI—high URII decrease and in the low URDI—low URII increase. The positive correlation between URDI and the URII is gradually decoupled.

URDI—low URII increase. The positive correlation between URDI and the URII is gradu-

**Figure 7.** The spatial pattern of the URDI in China, during 1980–2020. **Figure 7.** The spatial pattern of the URDI in China, during 1980–2020. ally decoupled.

**Figure 8.** The scatter diagram of rural–urban development intensity during 1980–2020. **Figure 8.** The scatter diagram of rural–urban development intensity during 1980–2020.

#### *3.4. Spatial Pattern of Rural–Urban Transition 3.4. Spatial Pattern of Rural–Urban Transition*

**Figure 8.** The scatter diagram of rural–urban development intensity during 1980–2020. From 1980–2000, the Δ*URDI* showed a gradient difference from northwest to southeast (Figure 9). The intensity of the Δ*URDI* in the three southeastern coastal regions is significantly greater than that in the neighboring regions; the Δ*URDI* in the central and western regions is relatively low. From 2000 to 2020, the Δ*URDI* shows a balanced spatial pattern, with high-value areas are mainly concentrated in central and western China. Some of the low-value areas in the previous stage (Guizhou, Tibet, Sichuan, Shaanxi, Inner Mongolia, etc.) are transformed into high-value areas during this stage, while some highvalue areas during the previous stage (Shanghai, Guangdong, Zhejiang, and Tianjin) are transformed into low-value areas during this stage. The rate of growth in the eastern region, especially in the northeast, has slowed down significantly. From 1980–2000, the ∆*URDI* showed a gradient difference from northwest to southeast (Figure 9). The intensity of the ∆*URDI* in the three southeastern coastal regions is significantly greater than that in the neighboring regions; the ∆*URDI* in the central and western regions is relatively low. From 2000 to 2020, the ∆*URDI* shows a balanced spatial pattern, with high-value areas are mainly concentrated in central and western China. Some of the low-value areas in the previous stage (Guizhou, Tibet, Sichuan, Shaanxi, Inner Mongolia, etc.) are transformed into high-value areas during this stage, while some high-value areas during the previous stage (Shanghai, Guangdong, Zhejiang, and Tianjin) are transformed into low-value areas during this stage. The rate of growth in the eastern region, especially in the northeast, has slowed down significantly. *Land* **2023**, *12*, x FOR PEER REVIEW 9 of 15

**Figure 9.** The spatial pattern of rural–urban development intensity in China, during 1980–2020. **Figure 9.** The spatial pattern of rural–urban development intensity in China, during 1980–2020.

The distribution pattern of the Δ*URII* differs from that of the Δ*URDI*. From 1980 to 2000, the Δ*URDI* shows high spatial distribution characteristics of high in the east and low

tion characteristics of the Δ*URII* in 2000–2020 are opposite to those of the previous two decades, showing the distribution characteristics of high in the west and low in the east. Among them, Shanghai (−0.162) and Beijing(−0.136) have lower Δ*URII* values and they are the only two regions with negative Δ*URII* values. Guizhou has the highest Δ*URII* value (0.384) and Guangxi follows (0.356). The areas with negative Δ*URII* values are in the eastern and northeastern regions: Shanghai (−0.348) and Beijing (−0.292). Guangdong, Jilin, Liaoning, Tianjin, and Hainan also have relatively low Δ*URII* values. Hubei (0.218)

**Figure 10.** The spatial pattern of rural–urban integration transition intensity in China, during 1980–

Based on the above results, we explore the rural–urban coordination degree of rural– urban transition. The coordination degree is classified into five types based on the transition characteristics: severe incoordination (0.0–0.4), general incoordination (0.4–0.5), mild incoordination (0.4–0.5), general coordination, and high coordination. The results show that, from 1980 to 2020, the regions with high coordination are mainly concentrated in eastern coastal China, with Shanghai (0.829), Beijing (0.799), Zhejiang (0.7954), Fujian (0.7738), and Jiangsu (0.736) ranking in the top five. The regions with lower coordination show a two-tier distribution pattern: Guangdong (0.235) and Hebei (0.294), which have a high level of URDI in 1980, are at the bottom; Tibet (0.361) and Guizhou (0.356), which have a low level of URDI, also have a lower level of coordination. From 2000 to 2020, the national coordination degree has improved as compared with the previous two decades, having a higher coordination degree of more than one-third of provincial regions, and an even distribution in all regions except the northeastern region. There are only six regions

and Guangxi (0.194) have higher Δ*URII* values than other regions.

*3.5. Coordination Degree Analysis of Rural–Urban Transition* 

2020.

The distribution pattern of the ∆*URII* differs from that of the ∆*URDI*. From 1980 to 2000, the ∆*URDI* shows high spatial distribution characteristics of high in the east and low in the west (Figure 10). Specifically, Jiangsu and Fujian have ∆*URII* values of 0.015 and 0.023, respectively, while other regions have negative ∆*URII* values. The spatial distribution characteristics of the ∆*URII* in 2000–2020 are opposite to those of the previous two decades, showing the distribution characteristics of high in the west and low in the east. Among them, Shanghai (−0.162) and Beijing(−0.136) have lower ∆*URII* values and they are the only two regions with negative ∆*URII* values. Guizhou has the highest ∆*URII* value (0.384) and Guangxi follows (0.356). The areas with negative ∆*URII* values are in the eastern and northeastern regions: Shanghai (−0.348) and Beijing (−0.292). Guangdong, Jilin, Liaoning, Tianjin, and Hainan also have relatively low ∆*URII* values. Hubei (0.218) and Guangxi (0.194) have higher ∆*URII* values than other regions. The distribution pattern of the Δ*URII* differs from that of the Δ*URDI*. From 1980 to 2000, the Δ*URDI* shows high spatial distribution characteristics of high in the east and low in the west (Figure 10). Specifically, Jiangsu and Fujian have Δ*URII* values of 0.015 and 0.023, respectively, while other regions have negative Δ*URII* values. The spatial distribution characteristics of the Δ*URII* in 2000–2020 are opposite to those of the previous two decades, showing the distribution characteristics of high in the west and low in the east. Among them, Shanghai (−0.162) and Beijing(−0.136) have lower Δ*URII* values and they are the only two regions with negative Δ*URII* values. Guizhou has the highest Δ*URII* value (0.384) and Guangxi follows (0.356). The areas with negative Δ*URII* values are in the eastern and northeastern regions: Shanghai (−0.348) and Beijing (−0.292). Guangdong, Jilin, Liaoning, Tianjin, and Hainan also have relatively low Δ*URII* values. Hubei (0.218) and Guangxi (0.194) have higher Δ*URII* values than other regions.

**Figure 9.** The spatial pattern of rural–urban development intensity in China, during 1980–2020.

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**Figure 10.** The spatial pattern of rural–urban integration transition intensity in China, during 1980– 2020. **Figure 10.** The spatial pattern of rural–urban integration transition intensity in China, during 1980–2020.

#### *3.5. Coordination Degree Analysis of Rural–Urban Transition 3.5. Coordination Degree Analysis of Rural–Urban Transition*

Based on the above results, we explore the rural–urban coordination degree of rural– urban transition. The coordination degree is classified into five types based on the transition characteristics: severe incoordination (0.0–0.4), general incoordination (0.4–0.5), mild incoordination (0.4–0.5), general coordination, and high coordination. The results show that, from 1980 to 2020, the regions with high coordination are mainly concentrated in eastern coastal China, with Shanghai (0.829), Beijing (0.799), Zhejiang (0.7954), Fujian (0.7738), and Jiangsu (0.736) ranking in the top five. The regions with lower coordination show a two-tier distribution pattern: Guangdong (0.235) and Hebei (0.294), which have a high level of URDI in 1980, are at the bottom; Tibet (0.361) and Guizhou (0.356), which have a low level of URDI, also have a lower level of coordination. From 2000 to 2020, the national coordination degree has improved as compared with the previous two decades, having a higher coordination degree of more than one-third of provincial regions, and an even distribution in all regions except the northeastern region. There are only six regions Based on the above results, we explore the rural–urban coordination degree ofrural–urban transition. The coordination degree is classified into five types based on the transition characteristics: severe incoordination (0.0–0.4), general incoordination (0.4–0.5), mild incoordination (0.4–0.5), general coordination, and high coordination. The results show that, from 1980 to 2020, the regions with high coordination are mainly concentrated in eastern coastal China, with Shanghai (0.829), Beijing (0.799), Zhejiang (0.7954), Fujian (0.7738), and Jiangsu (0.736) ranking in the top five. The regions with lower coordination show a two-tier distribution pattern: Guangdong (0.235) and Hebei (0.294), which have a high level of URDI in 1980, are at the bottom; Tibet (0.361) and Guizhou (0.356), which have a low level of URDI, also have a lower level of coordination. From 2000 to 2020, the national coordination degree has improved as compared with the previous two decades, having a higher coordination degree of more than one-third of provincial regions, and an even distribution in all regions except the northeastern region. There are only six regions with lower coordination degrees, among which the coordination degrees of Gansu (0.275) and Shanghai (0.297) are lower than 0.3. Throughout the four decades, the high-value areas of rural–urban development/integration and transition coordination show a coastal and riverine "T-shaped" pattern, while Gansu, Shanghai, Jilin, and Hebei have lower coordination degrees (Figure 11).

Based on the URDI and URII in 2020, the state type is divided by the mean value. According to the types of rural–urban transition coordination in 2020, the transition types of various states are identified (Figure 12). In 31 provincial regions, five provinces are high-quality transition types (Zhejiang, Jiangsu, Tianjin, Fujian, and Hubei), and their transition types are all coordinated. This indicates that the URDI and the URII values are rising with a high level of coordination. The lagging integration transition type also includes five regions. The higher the level of rural–urban development, the less coordinated the rural–urban transition is, indicating that the rural–urban divide in developed regions is widening. Thirteen regions are lagging development transition types; nine provinces

and regions are double-lagging transition types. The lagging integration transition type regions show higher URDI values with lower coordination of rural–urban transition, while the double-lagging transition type regions show that the higher the URDI value, the higher the coordination of rural–urban transition. and Shanghai (0.297) are lower than 0.3. Throughout the four decades, the high-value areas of rural–urban development/integration and transition coordination show a coastal and riverine "T-shaped" pattern, while Gansu, Shanghai, Jilin, and Hebei have lower coordination degrees (Figure 11).

with lower coordination degrees, among which the coordination degrees of Gansu (0.275)

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**Figure 11.** Spatial pattern of rural–urban transition coordination degree in China, during 1980– **Figure 11.** Spatial pattern of rural–urban transition coordination degree in China, during 1980–2020.

**Figure 12.** The spatial distribution of rural–urban state and transition types, in China, since reform **Figure 12.** The spatial distribution of rural–urban state and transition types, in China, since reform and opening-up.

#### **4. Discussion**

ment potential of urban areas.

and opening-up.

**4. Discussion** 

*4.1. The Optimal Path of Rural–Urban Transition*

*4.1. The Optimal Path of Rural–Urban Transition*  The lagging development regions are further classified into three subtypes: lagging development with transition coordination, lagging development with general incoordination, and lagging development with uncoordinated transition. The rural–urban lagging/transition coordination type includes Jiangxi, Sichuan, Anhui, and Hunan provinces, The lagging development regions are further classified into three subtypes: lagging development with transition coordination, lagging development with general incoordination, and lagging development with uncoordinated transition. The rural–urban lagging/transition coordination type includes Jiangxi, Sichuan, Anhui, and Hunan provinces, where the rural–urban transition is more coordinated and the rural–urban gap is smaller. The optimization strategy for these regions is to enhance the growth pole effect of urban

where the rural–urban transition is more coordinated and the rural–urban gap is smaller. The optimization strategy for these regions is to enhance the growth pole effect of urban

includes four provinces, namely Heilongjiang, Hebei, Jilin, and Hainan. These provinces had high-level URDI in the early stage of reform and opening-up, but the growth rate declined in the later stage. In these regions, the infrastructure is concentrated in urban areas. The optimal path forward is to focus on the redevelopment and improvement of small towns and cities, revitalization of old industrial bases, and releasing the develop-

In lagging integration regions, Shanghai is in an uncoordinated transition, while Beijing and Guangdong are generally incoordination, and Chongqing and Shandong belong to the coordinated transition. To optimize these regions, recommendations include improving the growth pole effect of small towns for the countryside, encouraging capital flow to rural areas, accelerating the development of rural tourism such as leisure farms, and promoting the integrated development of rural industries. Furthermore, broadening the channels of farmers' property incomes, improving the income structure of rural residents, creating a unified construction land market, and promoting the market of collective business construction land are all urgently needed. Local governments can promote the equalization of basic public services and build a comprehensive public service system.

Most double-lagging regions are concentrated in the west. Due to a western development strategy, coordinated rural and urban transition in the western region is areas, especially metropolises. The lagging development/transition incoordination type includes four provinces, namely Heilongjiang, Hebei, Jilin, and Hainan. These provinces had high-level URDI in the early stage of reform and opening-up, but the growth rate declined in the later stage. In these regions, the infrastructure is concentrated in urban areas. The optimal path forward is to focus on the redevelopment and improvement of small towns and cities, revitalization of old industrial bases, and releasing the development potential of urban areas.

In lagging integration regions, Shanghai is in an uncoordinated transition, while Beijing and Guangdong are generally incoordination, and Chongqing and Shandong belong to the coordinated transition. To optimize these regions, recommendations include improving the growth pole effect of small towns for the countryside, encouraging capital flow to rural areas, accelerating the development of rural tourism such as leisure farms, and promoting the integrated development of rural industries. Furthermore, broadening the channels of farmers' property incomes, improving the income structure of rural residents, creating a unified construction land market, and promoting the market of collective business construction land are all urgently needed. Local governments can promote the equalization of basic public services and build a comprehensive public service system.

Most double-lagging regions are concentrated in the west. Due to a western development strategy, coordinated rural and urban transition in the western region is prioritized. For these regions, infrastructure construction in remote areas and hilly regions should be prioritized to enhance transportation of the countryside, in particular, connecting roads from central towns to various villages. Moreover, an innovative industrial system should be established and advantageous industries such as new energy, tourism services, and ICT industry should be developed.

In general, the essence of coordinated rural–urban transition is to narrow the livelihood level of rural–urban residents [48]. In terms of income, there is a need to expand the channels of rural residents' property incomes and give peasants more sufficient property rights and interests [49]. In terms of production, there is a need to liberate the productivity of rural areas and actively explore the development path of rural industrialization and local urbanization. In terms of policies, funds, talents, and technologies should be encouraged to flow and backflow to the countryside [50], and local advantages should be capitalized on to develop high-value-added industries.

#### *4.2. Policy Implications*

The urban-biased and coastal opening development strategies have caused discoordination of rural–urban transition [47]. During the process of urbanization, rural–urban transition should be gradually promoted to further improve the current situation of an uncoordinated state, thereby achieving high-quality development. Policies should be targeted at the support of rural development. It is necessary to stimulate the initiative of endogenous growth of rural areas, especially regions of lagging development, to achieve high-quality coordinated development of areas.

Specifically, state-led policies have led to an increase in rural–urban disparities [51,52]. In the last 20 years, land-based finance has made the most substantial contribution to urban development in China [53]. Cities have achieved rapid development and expansion; however, it has also exacerbated the rural–urban divide [54]. Furthermore, land-based finance has resulted in pockets of accumulation of wealth for the wealthy, with fewer services for the poor [55]. The land-based finance model should be strengthened to help rural areas instead of exploiting the rural poor. For highly urbanized regions, policies can increase the intensity of levying land and real estate taxes. Moreover, capturing land value in cities can supplement funds for rural revitalization [56]. Governments need to provide affordable housing for low-income households to minimize the impact of increased land and housing prices owing to land-based finance.

In terms of rural development, increasing the value of rural land can be realized by rent, circulation, and mortgage of rural homesteads [57]. It can also be realized through the construction of rental housing for rural collective-owned land, reform of real estate tax, and control of the bubble of urban housing price [53,58,59]. Comprehensive land consolidation can further promote rural multi-functional development [60], and it can coordinate rural regional demand and income and improve the quality of rural living.

#### *4.3. Limitations and Future Research*

Although this study focuses on the rural–urban transition in China, it has general value for the governance of rural–urban development in the Global South. Developing countries are globally confronted with widespread problems due to rapid urbanization. At the same time, there are similarities in the development status of different countries and regions. Therefore, exploring large-scale spatial classification and zoning methods not only provides development paths for promoting sustainable development in China, but also provides valuable lessons for other regions in the Global South.

The Chinese example has implications for low and medium development levels and unbalanced rural–urban development areas in the Global South. However, it is not unique but rather a microcosm of many regions in developing countries. Notably, social and cultural backgrounds differ between China and other countries. Therefore, it is essential to introduce China's experience according to local conditions. Additionally, exploring reciprocal feedback between rural–urban transition and land use transition, especially concerning construction land, can control the development of rural–urban transition paths more specifically. This study focuses on macro-level spatial and temporal changes at a larger scale and is insufficient for specific impact mechanisms, a fact that deserves more academic attention in future studies.

#### **5. Conclusions**

This study evaluates the coordination level of rural–urban transition in each region of China, from 1980 to 2020, by constructing indicator systems for rural–urban development and integration. The conclusions are as follows.


The implementation of urban-biased and unbalanced regional development strategies can lead to an uncoordinated rural–urban transition. In the context of rapid urbanization, it is essential to control rural–urban transition to improve rural–urban disparity and to achieve high-quality development. Policies should be targeted at supporting rural development, and the initiative of rural endogenous growth is an effective way to realize a positive rural–urban transition.

**Author Contributions:** S.Z. contributed to the idea, data curation, methodology, formal analysis, and the original draft of the manuscript; J.Z. contributed to project administration, review and editing, and funding acquisition; Y.J. contributed to the conceptualization, original draft of the manuscript, review and editing; A.C. contributed to review and editing; W.Z. contributed to review and editing. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was supported by the Start-up research funding from Zhejiang University (126000-540501) and Research Project-"Measurement and optimal regulation of the integrated urbanrural development level in the Yangtze River Delta region" funded by Institute of Spatial Planning, Yangtze Delta Region Institute of Tsinghua University, Jiaxing.

**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 with this work.
