Preamble

Spatiotemporal Patterns and Driving Mechanisms of the Coupling and Coordination between New-type Urbanization and Agricultural Modernization in the Yellow River Basin

Affiliations:
College of Urban and Environmental Sciences, Northwest University, Xi'an, Shaanxi, China
Shaanxi Provincial Key Laboratory of Surface System and Environmental Carrying Capacity, Xi'an, Shaanxi, China

Exploring the coupling and coordination relationship between new-type urbanization and agricultural modernization (the "two modernizations") in the Yellow River Basin is of great significance for implementing the strategy of ecological protection and high-quality development, as well as promoting urban-rural integration and regional coordinated development. This study constructs a comprehensive evaluation index system and utilizes the entropy method, the coupling coordination degree model, and geographical detectors to quantitatively analyze the levels of the "two modernizations" and their spatiotemporal coupling patterns across 91 prefecture-level cities in the Yellow River Basin from 2011 to 2020. Furthermore, the driving mechanisms behind these patterns are explored.

The results indicate the following:
1. During the study period, the levels of both new-type urbanization and agricultural modernization in the Yellow River Basin rose significantly, both exhibiting a spatial distribution pattern characterized by higher levels in the east and lower levels in the west.
2. The coupling coordination type of the "two modernizations" evolved from being dominated by "near disorder" to "barely coordinated," with the scope of "primary coordination" and "intermediate coordination" expanding steadily.
3. The spatial agglomeration characteristics of the coupling coordination level are significant. A "hot spot" core has formed in Shandong Province, while three distinct "cold spot" clusters have emerged in Shanxi, Gansu, and Ningxia (Gan-Ning).
4. The spatial differentiation pattern of coupling and coordination is the result of the synergistic effects and interactions of multiple factors. Economic development, market forces, and digital finance are identified as the core driving factors, while agricultural science and technology and income levels serve as secondary drivers. Notably, the interaction between transportation infrastructure and other factors significantly enhances the coordination level.

These findings contribute to a deeper theoretical understanding of the coupling between the "two modernizations" and provide a policy reference for advancing regional strategies and promoting integrated urban-rural development within the basin.

关键词

New urbanization; Agricultural modernization; Coupling coordination; Spatiotemporal patterns; Geodetector; Yellow River Basin

New urbanization represents a new starting point for urbanization research and practice in China. It is characterized by its human-centered nature, synergy, inclusiveness, and sustainability, emphasizing the coordinated development of population, economic, social, and land subsystems. Agricultural modernization refers to the process and means of transforming traditional agriculture into modern agriculture. As key components of socialist modernization, new urbanization and agricultural modernization serve as important strategic pillars in the development of socialism with Chinese characteristics and provide the core driving force for regional synergistic development. The 18th National Congress of the Communist Party of China proposed following the path of "Four Modernizations" with Chinese characteristics, promoting the mutual coordination of new urbanization and agricultural modernization to ensure their synchronized development.

The 2022 "Implementation Plan for New Urbanization during the 14th Five-Year Plan Period" emphasizes adhering to a human-centered, "Four Modernizations" synchronized path of new urbanization with Chinese characteristics, while maintaining the principle of cities driving rural development.

At the 2019 Symposium on Ecological Protection and High-Quality Development of the Yellow River Basin, General Secretary Xi Jinping emphasized the need to coordinate new urbanization and rural revitalization within the basin to make greater contributions to the advancement of Chinese-style modernization. This series of policies focuses on the coordinated development of urban and rural areas to promote urban-rural integration.

Therefore, exploring the spatiotemporal patterns and driving mechanisms of the coupling and coordination between these "two modernizations" in the Yellow River Basin is a critical scientific issue. Theoretically, this research provides a reflective dimension for urban-rural integrated development; practically, it holds significant importance for promoting high-quality development in the Yellow River Basin.

Discussions and coupling research regarding the relationship between new urbanization and agricultural modernization primarily focus on several aspects: (1) Lessons from international experience and exploration of the relationship between the two. By reviewing the history of coordinated development between urbanization and agricultural modernization in the United States, scholars have proposed lessons based on behavioral agents, comparative advantages, and industrial chains. The two are closely related; research suggests that agricultural modernization both depends on and promotes urbanization, while new urbanization exerts a driving pull on agricultural modernization. (2) Quantitative assessment of the coupling coordination level between new urbanization and agricultural modernization. Relevant studies have constructed multi-level evaluation systems for different spatial scales, such as the entire country and the Huang-Huai region, utilizing fuzzy membership evaluation and other comprehensive models for quantification.

While comprehensive evaluation models have been used to quantify these processes and coupling coordination degrees have been employed to clarify their status, few studies have utilized exploratory spatial analysis methods from geography to examine the spatial heterogeneity of this coupling coordination. Some studies have applied linear regression, individual effects, and time-point effects models to explore the factors influencing the coordination of new industrialization, new urbanization, agricultural modernization, and greening. These studies suggest that the spatial pattern is formed by the combined action of the natural geographical environment and differences in economic and social development. Factors such as economic development level have a positive impact, while industrial levels and development intensity may exert negative influences. Other studies using Geographically Weighted Regression (GWR) models have revealed that the primary factors affecting the efficiency of coordinated development between urbanization and agricultural modernization are urban and rural per capita fixed asset investment. Existing research focuses heavily on influencing factors, but exploration of the driving mechanisms within urban-rural systems remains insufficient. Regarding coordination issues and optimization paths, existing research suggests that unsustainable and uncoordinated phenomena persist, with prominent contradictions. To achieve coordinated development, studies have proposed optimization paths and suggestions from a macro perspective, mainly including advocating for industry-city integration, promoting agricultural efficiency, ensuring that agricultural modernization is effectively integrated into the new urbanization process, and improving urban-rural circulation systems to achieve the effective connection of production factors. Taking the Central Guizhou urban agglomeration as an example, research on the impact of coupling coordination on the urban-rural income gap found a significant and strengthening effect. However, research on the coupling coordination of new urbanization and agricultural modernization at the meso- and micro-scales, such as cities and counties, remains insufficient. In particular, for the unique region of the Yellow River Basin, discussions at the prefecture-level city scale across the entire basin are lacking. Research on the factors and driving mechanisms underlying the spatial differentiation of coupling coordination needs to be deepened, and there is a scarcity of quantitative research on these driving mechanisms from a geographical perspective. Since the ecological protection and high-quality development of the Yellow River Basin was elevated to a national strategy in 2019, such research has gained immense significance. The basin covers urban agglomerations such as Lan-Xi and the Shandong Peninsula, as well as major grain-producing areas like Huang-Huai-Hai and Hetao, providing suitable conditions for study. This paper takes 67 prefecture-level cities in the Yellow River Basin as research objects to analyze the evolution of the spatiotemporal patterns of coupling coordination and uses the Geodetector model to detect its driving mechanisms. The goal is to provide policy references for the coordinated advancement of new urbanization and agricultural modernization and the promotion of urban-rural integration across different cities in the Yellow River Basin.

1 新型城镇化与农业现代化耦合协

The Coupling Mechanism of New-Type Urbanization and Agricultural Modernization

New-type urbanization and agricultural modernization serve as the two primary pillars of socialist modernization with Chinese characteristics, representing key strategic deployments for driving integrated urban-rural development. The coupling of these two systems involves a dynamic process where sub-systems and internal elements interact to promote urban-rural integration.

The Driving Effect of New-Type Urbanization on Agricultural Modernization

New-type urbanization acts as a powerful catalyst for agricultural modernization through several channels. First, urbanization drives the expansion of secondary and tertiary industries, creating significant employment opportunities for surplus rural labor. This transition increases the income of migrant workers, facilitating the accumulation of primitive capital necessary for developing modern agriculture. Second, the evolving lifestyle needs of urban residents—along with the rise of emerging sectors such as rural ecotourism and "agritainment"—expand the market demand for diverse agricultural and side-line products, thereby accelerating the modernization of the agricultural sector.

Furthermore, as new-type urbanization advances, public services such as transportation, education, and healthcare increasingly extend into rural areas. This infrastructure expansion is conducive to improving the overall quality of the rural workforce and cultivating a new generation of professional farmers, providing essential human capital for agricultural modernization. Finally, the "radiation and trickle-down" effects of urbanization provide financial security and investment, significantly enhancing the technical sophistication and economic efficiency of agricultural production.

Agricultural Modernization as the Foundation for New-Type Urbanization

Conversely, agricultural modernization provides the fundamental support and security required for sustainable urbanization. Through large-scale production, the application of modern agricultural technologies, and the implementation of green ecological practices, agricultural modernization ensures a stable supply of high-quality, diverse agricultural products to meet the growing demands of urban populations.

The improvement of agricultural mechanization levels has liberated a vast amount of rural labor, providing the necessary human resources to fuel urban construction and industrial growth. Additionally, the increased crop yields resulting from modern techniques allow for the optimization of land use, providing essential land resources for new-type urbanization projects. By optimizing agricultural structures and utilizing modern technology, agricultural modernization improves resource efficiency and enhances the ecological environment, laying a sustainable foundation for the entire urban-rural system.

Collaborative Development and Policy Mechanisms

New-type urbanization and agricultural modernization achieve synergistic development through element complementarity and industrial integration. This collaborative process is further reinforced by government policy guarantees and market regulation mechanisms, which ensure that the coupling and coordination between the two systems remain stable and progressive. Together, they form a reciprocal relationship that drives the comprehensive modernization of the national economy and society.

2 数据与方法

Overview of the Research Area

The study area is characterized by a significant human presence, with the total basin population reaching approximately [insert number] million people. This high population density exerts substantial pressure on the local ecosystem and water resources. The demographic distribution is primarily concentrated along the river banks and within the fertile alluvial plains, where urban centers and agricultural activities are most prominent.

The socio-economic development of the region is closely tied to the basin's hydrological characteristics. Rapid urbanization and industrial expansion over the past few decades have led to increased water demand and land-use changes, which in turn have influenced the local climate and hydrological cycle. Understanding the interplay between population dynamics and environmental constraints is crucial for sustainable water resource management and ecological conservation within the study area.

8 人

The urbanization rate of the Yellow River Basin accounts for a significant portion of the national total. The basin is home to five major national-level urban clusters, including the Shandong Peninsula, as well as primary grain-producing regions such as Henan and Shandong. Its grain and meat production, along with its numerous national key leading enterprises in agricultural industrialization and the Yangling National Agricultural High-tech Industry Demonstration Zone, are influenced by factors such as transportation and geographical location. However, development remains uneven in the downstream regions, and significant disparities exist among provinces and cities regarding the levels of new-type urbanization and agricultural modernization. In 2014, the Hulunbuir league in Inner Mongolia was incorporated into the Northeast Revitalization Strategy. Furthermore, as the Yellow River only flows through the Aba Tibetan and Qiang Autonomous Prefecture and parts of the Garzê Tibetan Autonomous Prefecture in Sichuan, and given that Sichuan is integrated into the Yangtze River Economic Belt strategy, this study defines the research area by excluding Sichuan and eastern Inner Mongolia. Based on data availability, the research scope is determined to be the Yellow River Basin. Regarding the construction of the indicator system, the traditional land-centered urbanization model has led to negative impacts such as the depletion of arable land resources and the intensification of the heat island effect. It has also posed significant challenges to coordinated urban-rural development, resulting in imbalanced income growth between urban and rural residents and significant rural hollowing. New-type urbanization adheres to a people-centered philosophy, optimizing the spatial layout of urbanization, accelerating the modernization of urban governance systems, and emphasizing the importance of ecological civilization. Combining the connotations of new-type urbanization with existing research and the guidelines and specific measures of the "New-type Urbanization Implementation Plan," and based on the principles of scientific rigor and data availability, an evaluation indicator system for the level of new-type urbanization in the Yellow River Basin has been constructed across several dimensions. Agricultural modernization is a dynamic concept, driven by the most historically significant technological progress of any given period. With the development of the times, the connotation of agricultural and rural modernization has been continuously enriched. Its core orientation is to integrate cutting-edge technology, modern equipment, and advanced management concepts into agriculture, while extending infrastructure construction and basic public services to rural areas. This aims to enhance agricultural production efficiency, beautify the rural environment, improve the quality of life for farmers, and promote the comprehensive upgrading of agriculture and the all-round progress of farmers. Referencing previous studies and combining the essence of agricultural modernization with the requirements, strategic orientations, and measures of the "Plan for Promoting Agricultural and Rural Modernization," an evaluation indicator system for the level of agricultural modernization in the Yellow River Basin has been constructed across four dimensions: agricultural output level, rural social development level, industrialized management, and agricultural sustainable development. The entropy weight method and the coefficient of variation method are employed for weighting; the former determines weights based on the information entropy of the observed values of the evaluation indicators, while the latter assigns weights by quantifying the coefficient of variation of the information contained within the indicators.

The base map was produced based on the standard map (Review Number: GS(2021)5447) from the Standard Map Service website of the Ministry of Natural Resources, with no modifications made to the boundaries. By utilizing the information contained within the indicators, the coefficient of variation is quantified to assign weights. Both the entropy weight method and the coefficient of variation method are typical objective weighting approaches, which avoid the subjectivity inherent in qualitative weighting and offer greater scientific rigor and accuracy. This paper adopts a combination of these two methods to calculate the development levels in the Yellow River Basin. First, the indicators are subjected to dimensionless processing. After obtaining the weights from each of the two methods, the combined weights are calculated using the arithmetic mean method. Subsequently, the comprehensive development index and the coupling coordination degree model are utilized. The coupling coordination degree model is currently the primary tool for measuring the interaction efficiency and coordination level between two or more systems, mainly comprising the coupling degree and the coupling coordination degree.

方法

This paper employs the coupling coordination degree model to evaluate the level of mutual interaction and coordination between systems. Drawing upon established research methodologies, we classify the levels and types of coupling coordination to assess the developmental state of the study area.

Spatial Autocorrelation Analysis

According to Tobler’s First Law of Geography, all things are related, but near things are more related than distant things. This principle of spatial autocorrelation suggests that attribute values of geographic entities are influenced by their spatial proximity. In this study, we utilize the Global Moran’s $I$ index to identify the spatial distribution characteristics and agglomeration patterns of the coupling coordination levels across the Yellow River Basin. This analysis allows us to determine whether the development levels exhibit significant spatial clustering or dispersion.

Hotspot and Coldspot Analysis

To further characterize the specific locations of spatial clustering, we perform a hotspot analysis (Getis-Ord $G_i^*$ statistic). This method provides a detailed mapping of the spatial distribution of "hotspots" (areas of high-value clustering) and "coldspots" (areas of low-value clustering) regarding the coupling coordination degree in the Yellow River Basin. By identifying these regions, we can better understand the spatial heterogeneity and the localized intensity of coordinated development.

$$G_i^*(d) = \frac{\sum_{j=1}^n w_{ij}x_j}{\sum_{j=1}^n x_j}$$

where $d$ is the distance threshold, $n$ is the number of regions, $w$ is the spatial weight, and $i$ is the regional unit. When values surrounding a region are relatively high, the area is identified as a "hot spot," representing a cluster of high coupling coordination. Conversely, low-value clusters represent areas of low coupling coordination. To analyze the spatial differentiation patterns and driving mechanisms of these factors, this study employs the Geographical Detector (Geodetector) model. The effectiveness of this model depends on identifying the optimal scale of stratified heterogeneity during the spatial data discretization process. In this study, the quantile method was used to discretize the driving factors of coupled and coordinated development in the Yellow River Basin. The spatial scale with the maximum $q$-value was selected as the parameter for the Geodetector analysis. Based on these optimal parameters, factor detection and interaction detection were applied to identify the core driving factors and the interaction forces between them that shape the spatial differentiation of coupling coordination.

[TABLE:1] Coupled coordination indicator system of "two modernizations" (New-type Urbanization and Agricultural Modernization) in the Yellow River Basin.

New-type Urbanization:
- Population Urbanization: Urbanization rate of permanent residents, urban population density, proportion of employees in the secondary industry, and proportion of employees in the tertiary industry.
- Economic Urbanization: Proportion of the output value of the tertiary industry, per capita disposable income of urban residents, and per capita consumption expenditure of urban residents.
- Social Urbanization: Per capita total retail sales of consumer goods, number of internet access users, number of health technical personnel, and urban registered unemployment rate.
- Spatial Urbanization: Area of built-up regions and per capita urban road area.
- Ecological Urbanization: Per capita park green space, greening rate of built-up areas, centralized treatment rate of sewage treatment plants, and harmless treatment rate of domestic waste.

Agricultural Modernization:
- Agricultural Input Level: Rural electricity consumption, total power of agricultural machinery per unit of cultivated land, and the proportion of grain-sown area.
- Agricultural Output Level: Land productivity, agricultural output rate, farming productivity, and unit yield of grain crops.
- Rural Social Development Level: Per capita rural electricity consumption, income level of rural residents, and consumption level of rural residents.
- Agricultural Management Industrialization: Development degree of agricultural socialization services, number of geographical indication agricultural products, number of national agricultural science and technology parks, and number of national key leading enterprises in agricultural industrialization.
- Agricultural Sustainable Development: Per capita cultivated land area, intermediate consumption output rate, chemical fertilizer application per unit of cultivated land, and vegetation coverage.

Note: All indicators listed above are positive indicators.

$$q = 1 - \frac{1}{N\sigma^2} \sum_{h=1}^L N_h \sigma_h^2$$

Methodology and Data Sources

Variable Selection and Explanatory Power

The explanatory power of a factor is determined by its ability to account for the variance in the dependent variable; a higher value indicates a stronger influence. In this study, the explanatory variables and their corresponding indicators are categorized across multiple dimensions including urbanization, economic output, social services, and agricultural development. The specific indicators utilized are as follows:

• Urbanization and Population: Urban permanent population, year-end permanent population, total urban population, and the number of administrative units at the municipal level.
• Economic Structure and Employment: Built-up area, proportion of secondary industry employees to total employment, proportion of tertiary industry employees to total employment, and the ratio of tertiary industry output to Gross Domestic Product (GDP).
• Economic Development and Consumption: Per capita GDP, total retail sales of consumer goods, and year-end permanent population.
• Infrastructure and Social Services: Number of internet subscribers, number of health technical personnel, and number of hospital beds per capita.
• Urban Infrastructure and Environment: Total area of urban roads, the ratio of urban domestic sewage treated to meet discharge standards to total sewage discharge, and the ratio of harmlessly treated municipal solid waste to total waste generation.
• Agricultural Production: Gross output value and added value of farming, forestry, animal husbandry, and fishery; total power of agricultural machinery; and the ratio of grain sown area to total crop sown area.
• Rural Development: Rural electricity consumption, rural permanent population, per capita disposable income of rural residents, and per capita consumption expenditure of rural residents.
• Agricultural Intensity and Efficiency: The ratio of agricultural service industry output to total agricultural output, added value per capita for the rural permanent population, and the intensity of chemical fertilizer application.
• Ecological Indicators: Normalized Difference Vegetation Index (NDVI) and the variance related to the number of municipal units.

Analytical Framework

To analyze the influence of these factors, this study employs the Interaction Detector. This method allows for the identification of interactions between different explanatory variables—specifically, whether the combined effect of two factors increases or decreases the explanatory power of the dependent variable. The detailed principles, classification types, and discrimination methods for the interaction detector are based on established geographical detector theories; for a comprehensive technical description, please refer to the relevant literature \cite{relevant_literature}.

Data Sources

The statistical data used in this research are primarily derived from official national sources, including the China City Statistical Yearbook, the China Urban-Rural Construction Statistical Yearbook, and the statistical yearbooks of the respective provinces within the study area. Environmental and vegetation data (NDVI) were processed from remote sensing products corresponding to the study period.

degree of “ two modernizations ” in the Yellow River Basin

Data Sources and Methodology

The analysis utilizes a comprehensive suite of datasets to calculate the coupling coordination degree and evaluate regional agricultural development. Socioeconomic data were primarily sourced from the China National Knowledge Infrastructure (CNKI) Yearbooks, the Third National Land Survey, and selected Agricultural Census Bulletins. Demographic insights were derived from the Seventh National Population Census.

Data regarding Geographical Indications (GI) for agricultural products were obtained from the National Geographical Indication Agricultural Product Query System. Information on national key leading enterprises in agricultural industrialization was sourced from official agricultural records, with enterprise locations determined by parsing their registered addresses. Environmental metrics, specifically the Normalized Difference Vegetation Index (NDVI), were retrieved from the National Tibetan Plateau Data Center.

To assess the impact of modern financial services, the Digital Financial Inclusion Index from Peking University was employed. For certain years where data were unavailable, missing values were estimated and completed using the linear interpolation method to ensure the continuity and integrity of the time-series analysis.

3 结果与分析

Analysis of the Coupling and Coordination between New Urbanization and Agricultural Modernization

Spatiotemporal Evolution Characteristics of New Urbanization and Agricultural Modernization

The levels of both new urbanization and agricultural modernization have risen significantly. The mean value of new urbanization levels increased from 2011 to 2022, while the level of agricultural modernization reached a new peak in 2022. Although the growth rate of new urbanization is lower than that of agricultural modernization, both have improved simultaneously. However, the standard deviation and variance have continuously increased, indicating a widening regional gap in development levels. This suggests that while urban-rural integration in the Yellow River Basin has achieved periodic results, it also highlights the urgent need for cross-regional coordination mechanisms.

Spatial differences in levels are significant. The level of new urbanization exhibits a distribution pattern of "high in the east and low in the west." High-value areas have long been concentrated in provincial capitals such as Qingdao, Jinan, and Xi'an, while low-value areas are concentrated in the western regions of Qinghai and the Qinba Mountains. This may be attributed to the relatively developed economies and superior infrastructure of coastal Shandong and provincial capital cities, whereas western regions are limited by natural conditions, poor transportation, and a lack of industrial support.

The level of agricultural modernization also shows a "high in the east, low in the west" differentiation characteristic. High-value areas have consistently been located in Shandong. Due to superior natural conditions, flat terrain, and high levels of mechanization, these areas serve as important national agricultural belts. Conversely, low-value areas are distributed across parts of western Shanxi, Gansu, and Ningxia, constrained by geographical location and other factors.

Spatiotemporal Evolution of the Coupling and Coordination between New Urbanization and Agricultural Modernization

During the research period, the coupling coordination degree remained stable, while the standard deviation and variance increased synchronously, indicating that the gap between cities is gradually widening and the phenomenon of "territorial locking" is becoming prominent. Although some areas have reached a level of intermediate coordination, the basin as a whole remains in a state of being "on the verge of disorder" or "barely coordinated."

In 2011, the coupling coordination degree in the Yellow River Basin was primarily characterized as being on the verge of disorder. Mild disorder areas were distributed in Baiyin and other regions, where weak economic foundations and depleting resources epitomize the plight of ordinary prefecture-level cities. Areas on the verge of disorder were widely distributed across most parts of Qinghai and Shandong. Barely coordinated areas were mainly concentrated in eastern Shandong and various provincial capitals; these cities are mostly economically developed and densely populated, yet only Qingdao reached the level of primary coordination.

By 2016, the coupling coordination degree in the Yellow River Basin transitioned toward being barely coordinated. Its distribution range expanded while the areas on the verge of disorder shrank. Primary coordination areas expanded to include Qingdao and Jinan, and the spatial distribution shifted from a point-like pattern to a patch-like pattern.

By 2022, the coupling coordination degree in the Yellow River Basin remained predominantly barely coordinated, with the entire basin entering this stage. The number of primary coordination areas increased to 12, and Qingdao entered the intermediate coordination stage. This indicates that development in these areas is closely interdependent. The overall coupling coordination degree shows a spatial pattern where a low-value continuous zone formed by eastern Gansu and Zhongwei exists in the upper reaches, while the high-value areas exhibit a single-core pattern centered on Qingdao, with cities like Jinan and Xi'an scattered in between.

Spatial Agglomeration of Coupling and Coordination between New Urbanization and Agricultural Modernization

From 2011 to 2022, the Moran’s I index of the coupling coordination degree in the Yellow River Basin continuously increased, indicating a significant positive correlation between the coupling coordination level and neighboring cities, with the spatial spillover effect strengthening. To further explore the spatial agglomeration characteristics and clustering methods, the Hot Spot Analysis tool in ArcGIS was utilized to analyze the Yellow River Basin.

Spatiotemporal Patterns of Development Levels of the "Two Modernizations" in the Yellow River Basin

Spatiotemporal Patterns of the Coupling Coordination Degree of the "Two Modernizations" in the Yellow River Basin

degrees of “ two modernizations ” in the Yellow River Basin

Moran's $I$ values and their associated statistical significance probabilities indicate results significant at the specified levels. [FIGURE:1] illustrates the distribution of "hot spots" and "cold spots" for the coupling coordination degree (CCD). In the Yellow River Basin, the center of gravity for hot spots is concentrated in Shandong Province, while cold spots are clustered elsewhere; both hot and cold spots exhibit a contiguous distribution pattern. In the early period, high-value clusters of coordination were more prominent in the upstream regions of Gansu and Wuzhong, Ningxia. By the subsequent period, the range of hot spots for coupling coordination in the Yellow River Basin expanded, with Liaocheng in Shandong being newly added, indicating a westward progression of high-value zones.

The distribution of hot and cold spots for coupling coordination reflects the "two modernizations" (new-type urbanization and agricultural modernization) in the Yellow River Basin. The number of hot spot cities increased to include Yuncheng, Shanxi. By the final study period, the hot spots for coupling coordination increased further to include several cities in Henan, forming a central polar core. Conversely, the cold spot areas expanded to include Haidong in Qinghai (upstream) and Taiyuan in Shanxi (midstream), indicating an intensification of low-value clustering. These spatial patterns may be attributed to Shandong's coastal economic advantages, robust industrial base, and high investment in science and technology, which create a virtuous cycle of coordinated development. In contrast, Shanxi is constrained by ecological fragility and a dominance of resource-based industries, leading to weaker urban-rural synergy and lagging coordination. To analyze the driving mechanisms behind the spatial differentiation of the coupling coordination between new-type urbanization and agricultural modernization, we recognize that these two processes share a close, objective relationship characterized by mutual promotion. Their coordinated development is inevitably influenced by multiple systemic factors. Drawing on existing research and the specific conditions of the Yellow River Basin, we selected the coupling coordination degree (CCD) as the dependent variable and constructed an indicator system covering economic, innovative, and other dimensions. Factor detection results for 2022 show that all indicators passed the significance test at the $p < 0.01$ level or above, suggesting that the selected driving factors effectively explain the spatial differentiation pattern.

The explanatory power of the factors, ranked by their $q$-statistic values, is as follows: $eco > mar > dfin > inno > gov > open > inco > pop > atech > tra$.

The results indicate that economic development ($eco$) and digital finance ($dfin$) are the core driving factors for the development of coupling coordination. Over time, the rankings of openness ($open$) and transportation ($tra$) have risen, demonstrating that these factors have gained significantly stronger explanatory power regarding the spatial differentiation of coordination in the Yellow River Basin. This shift is due to cities leveraging the Great Western Development strategy to improve their level of opening-up. Based on the results of the coupling coordination degree model, the indicators include the added value of the tertiary industry, total retail sales of social consumer goods, the digital financial inclusion index, per capita disposable income of urban and rural residents, the ratio of tertiary industry employees to total employees, and total power of agricultural machinery ($atech$). Additional factors include administrative area, total import and export volume, and expenditures on science and technology.

“ two modernizations ” in the Yellow River Basin

In 2010, the explanatory power of various impact factors on the spatial differentiation patterns of coupled coordination was further refined. The continuous improvement of infrastructure, such as the "Village-to-Village" road projects, significantly increased the influence of both urban and rural development on the overall system. During this period, the explanatory power of digital finance and related indices continued to rise, while other factors saw a decline. Specifically, the enhancement of government regulatory capabilities and the advancement of agricultural mechanization effectively released rural labor to support urban development, thereby strengthening the promotional effect on regional coordination. Conversely, the explanatory power of innovation and income levels experienced a relatively significant decrease. The specific definitions and values for these factors are detailed in [TABLE:N].

[FIGURE:N]
Figure: Explanatory power and chord diagram of impact factors for the coupled coordination degree.

modernizations ” in the Yellow River Basin

From 2016 to 2022, although the ranking of the impact factors for $atech$ has fluctuated, the explanatory power of government intervention has consistently remained dominant. This indicates that government policy is the primary driving force behind the evolution of the spatial pattern of coupling coordination in the Yellow River Basin. Meanwhile, the explanatory power of agricultural science and technology has steadily increased, suggesting its growing importance to the region and its potential role as a critical driver for future coupling coordination. Conversely, the explanatory power of population factors has continuously declined. This trend may be attributed to economic development and industrial transformation, where labor has increasingly migrated into the secondary and tertiary sectors, leading to a convergence of industrial structures—a phenomenon consistent with the Petty-Clark Law.

To further investigate the intensity of the interaction effects between the driving factors of coordination in the Yellow River Basin, an interaction detection analysis was conducted on the 2022 impact factors. Heatmaps were generated using Origin software to provide a visual, hierarchical representation of these interactive driving effects. The results indicate that the interactions between impact factors in 2022 were characterized by "dual-factor enhancement," with no instances of weakened or independent effects. This demonstrates that the spatial differentiation pattern of the coupling coordination level in the Yellow River Basin is the result of the synergistic and interactive influence of multiple factors, including economic and governmental drivers.

From the perspective of specific impact factors, the interactions involving income ranked among the highest in 2016. By 2022, the most prominent interactions were associated with government intervention, while the strongest explanatory power for interactive effects was found in the combinations of agricultural science and technology ($atech$), market conditions, and other variables. The fact that these factors consistently rank at the forefront suggests that they are not only significant as single-factor drivers but also play a dominant role in dual-factor interactions. Their synergy with other variables, particularly $atech$, underscores their central importance in shaping the regional development landscape.

Interaction Detection Results of Coupling Coordination Degree Drivers

The interaction detection analysis reveals that the coupling coordination degree is not governed by isolated factors, but rather by the synergistic effects of multiple driving forces. By employing interaction detection models, we can quantify how the interplay between different variables enhances or diminishes the overall coupling coordination within the system.

The results indicate that the interaction between any two driving factors typically exhibits either "bilinear enhancement" or "nonlinear enhancement." This suggests that the combined influence of two factors significantly exceeds the explanatory power of any single factor acting alone. For instance, when socioeconomic development variables interact with environmental governance indicators, the resulting impact on the coupling coordination degree shows a marked increase, highlighting the necessity of integrated policy-making.

[FIGURE:1]

Furthermore, the strength of these interactions varies across different dimensions. High-intensity interactions are frequently observed between core economic drivers and technological innovation capacity. This synergy acts as a primary catalyst for elevating the coupling coordination level, as technological advancements often provide the necessary tools for more efficient resource allocation and economic structural optimization.

[TABLE:1]

In summary, the interaction detection results underscore the complexity of the system's internal dynamics. The high degree of interdependence among drivers implies that interventions aimed at improving coupling coordination must be multifaceted. Strategic planning should prioritize these high-interaction factor pairs to achieve a more balanced and sustainable development trajectory.

“ two modernizations ” in the Yellow River Basin

The interactions between various factors significantly influence the coupled and coordinated development of the Yellow River Basin. Notably, the interaction between agricultural science and technology and other driving factors is significantly enhanced, indicating that technological advancement effectively strengthens the impact of other variables on coupled and coordinated development.

While single-factor detection reveals that income and population have a relatively weak individual influence on development, they remain vital components of residents' economic capacity and the regional employment structure. When these factors interact with others, their explanatory power increases significantly. This suggests they are indispensable forces in the developmental process; their interactions with other factors are equally critical, as they work in concert to drive the coupled and coordinated development of the region.

结论

This paper employs a combined weighting method using the entropy weight method and the coefficient of variation method to analyze the coupling coordination degree (CCD) and cold/hot spot patterns. It explores the spatio-temporal evolution and spatial agglomeration characteristics of coupling coordination and further utilizes geographical detectors to investigate the underlying driving mechanisms. Temporally, the overall level of the Yellow River Basin significantly increased from 2011 to 2020. Spatially, significant differences are observed, with a consistent "high in the east and low in the west" distribution. During this period, the CCD of the Yellow River Basin evolved from being dominated by "near disorder" to "barely coordinated," while the scope of primary and intermediate coordination steadily expanded. Regarding the spatial distribution of CCD, a continuous low-value zone formed in the upper reaches, consisting of areas such as eastern Gansu and Zhongwei. In contrast, high-value areas exhibited a single-core pattern centered on Qingdao, with cities like Xi'an appearing as scattered points.

The level of coupling coordination exhibits significant positive spatial correlation, which has continuously strengthened over time. Hot and cold spots within the basin have shown clear diffusion: hot spot cities expanded from 6 to cover 16 cities in Shandong and Puyang on the Henan-Shandong border, while cold spot cities expanded from Gansu and Ningxia in the upper reaches toward Shanxi in the middle reaches. This formed a "polar hot spot" core in eastern Shandong and a "cold spot" core in Shanxi. The spatial differentiation of coupling coordination is the result of the interactive influence of economic and governmental factors. Factor detection reveals that digital finance is the core driving factor, while residents' income serves as a secondary driver. Both exert a strong influence on coupling coordination, with their explanatory power consistently ranking at the forefront. The explanatory power of opening-up first decreased and then increased, while the influence of government intervention remained significant. Interaction detection shows that the interaction between factors is primarily characterized by dual-factor enhancement; the explanatory power significantly increases after different factors interact. Specifically, opening-up shows a significant synergistic effect with other factors, and the interaction between transportation and other factors is also prominent.

Based on these findings, this paper proposes the following policy implications to promote the coordinated development of the Yellow River Basin. First, the high-quality development of new-type urbanization should be deeply promoted to ensure the coordinated growth of subsystems such as the environment and ecology. Cities with high levels of new-type urbanization, such as Xi'an, should consolidate their existing foundations, strengthen innovation leadership, and accelerate the modernization of their industrial systems. Second, the development and protection of territorial space should be optimized. Ordinary cities in the upper reaches (Gansu and Ningxia) and middle reaches (Shaanxi and Shanxi) should leverage their resource endowments to cultivate characteristic industrial clusters. They should actively undertake industrial transfers supported by national policies for the central and western regions, establish mechanisms to attract talent back to their hometowns, and deepen supply-side structural reforms in agriculture. By building a green, ecological, and modern agricultural system, these regions can enhance the quality and efficiency of agricultural modernization. Specifically, Ningxia can utilize its unique resources to develop characteristic planting, facility agriculture, and animal husbandry; Shaanxi and Shanxi can rely on cultural resources to promote rural tourism and ecological sightseeing agriculture; Henan and Shandong should focus on their status as major agricultural provinces to develop mechanized agriculture, ensuring the supply of agricultural products and supporting national food security. Third, urban-rural integration should be optimized to narrow regional gaps. By clarifying the driving mechanisms of coordination—specifically the core roles of government and economy and the interactive effects of digital finance and opening-up—technical transfer and compensation from the lower reaches to the middle and upper reaches should be strengthened. A "trinity" framework for collaborative basin governance should be established to achieve coordinated development between the downstream polar cores and the upstream/midstream cold spots. This involves improving regional coordination policies, breaking down local interest barriers, and promoting the rational flow of production factors to build a multi-polar development pattern.

Compared with existing research, this study follows a geographical research paradigm. From a spatial perspective, it uses geographical detectors to innovatively explore the driving mechanisms behind the spatial differentiation of coupling coordination in the Yellow River Basin. It identifies that differences in economic levels lay the foundation for coupling coordination, while market consumption, empowered by digital finance, strengthens supply-demand regulation. These factors jointly drive the spatial differentiation characteristics of the polar cores. While this study clarifies the driving mechanisms and provides theoretical support for future policy-making, some limitations remain. Due to data availability, the sample size does not cover all prefecture-level cities in the Yellow River Basin, and the evaluation index system may require further refinement. Future research could utilize multi-source data, such as nighttime light remote sensing, construction land imagery, and big data, to enrich the sample size and enhance scientific rigor. In the era of artificial intelligence, machine learning could also be employed to predict the future coupling coordination trends of the Yellow River Basin.

References

Understanding the Theoretical Connotations of New-Type Urbanization with Chinese Characteristics

[Chen Mingxing, ...]

1. Introduction

Urbanization is a powerful engine for modern economic growth and a significant symbol of social progress. For a long time, China's urbanization process has attracted global attention due to its unprecedented scale and speed. However, as the traditional model of urbanization—characterized by rapid expansion and land-centered development—encountered increasing bottlenecks, the Chinese government proposed the strategy of "New-type Urbanization." This strategy represents a fundamental shift from a focus on "quantity" to "quality," emphasizing a people-centered approach that integrates economic efficiency, social equity, and environmental sustainability. Understanding the theoretical depth and practical implications of this transition is essential for navigating the complexities of China's future development.

2. The Core Connotations of New-type Urbanization

The theoretical framework of New-type Urbanization with Chinese characteristics is built upon several key pillars that distinguish it from traditional urban development models.

2.1 People-Centered Urbanization

At its core, New-type Urbanization is "people-centered." Unlike previous stages where the primary focus was on the physical expansion of cities and industrial zones, the current priority is the urbanization of the population. This involves not only the migration of rural residents to cities but also their full integration into urban life. A critical component of this is the reform of the household registration (hukou) system, ensuring that migrant workers have equal access to basic public services, including education, healthcare, and social security.

2.2 Integration of Industry and City

New-type Urbanization emphasizes the synergistic development of industrial growth and urban functions. A city without industrial support risks becoming a "ghost town," while an industrial zone without urban amenities cannot sustain a high-quality workforce. By promoting the "integration of industry and city," the strategy aims to create vibrant urban spaces where economic activities and residential life support one another, reducing commuting times and enhancing the overall efficiency of the urban economy.

2.3 Ecological Civilization and Green Development

In alignment with the national goal of building an "Ecological Civilization," New-type Urbanization advocates for green, circular, and low-carbon development. This requires a strict adherence to ecological red lines, the promotion of compact city layouts, and the efficient use of land and water resources. The objective is to decouple urban growth from environmental degradation, ensuring that cities are not only economic

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Comprehensive Evaluation of China's Urbanization Levels and Its Driving Factors

Abstract

Urbanization is a complex process involving the transition of population, the transformation of economic structures, and the evolution of spatial configurations. This paper establishes a comprehensive evaluation index system for urbanization levels from four dimensions: population, economy, society, and spatial structure. By applying this system to analyze the spatial patterns and driving mechanisms of urbanization in China, we aim to provide a more nuanced understanding than that offered by single-indicator measures. Our findings suggest that while population urbanization remains a core component, economic development and social progress are increasingly critical drivers of the overall urbanization process.

1. Introduction

Urbanization is one of the most significant socio-economic phenomena in contemporary China. Traditionally, the urbanization level has been measured primarily by the proportion of the urban population relative to the total population. However, as China enters a new stage of high-quality development, this single-indicator approach increasingly fails to capture the multifaceted nature of urban growth, including improvements in living standards, infrastructure development, and the optimization of industrial structures.

2. Methodology and Data

2.1 Construction of the Comprehensive Index System

To accurately reflect the multidimensional characteristics of urbanization, we constructed a comprehensive evaluation index system. This system integrates four primary dimensions:
1. Population Urbanization: Focusing on the concentration of the population in urban areas and changes in employment structures.
2. Economic Urbanization: Measuring the intensity of economic activity, industrial upgrading, and wealth accumulation.
3. Social Urbanization: Assessing improvements in public services, healthcare, education, and quality of life.
4. Spatial Urbanization: Evaluating the expansion of built-up areas and the efficiency of land use.

[TABLE:1]

2.2 Evaluation Model

We employ the entropy weight method to determine the weights of each indicator, ensuring an objective assessment of the contribution of various factors. The comprehensive urbanization level $U$ is calculated as follows:

$$U = \sum_{i=1}^{n} w_i \times x_i$$

where $w_i$ represents the weight of indicator $i$, and $x_i$ represents the standardized value of the indicator.

3. Spatial Patterns of China's Urbanization

The analysis reveals significant regional disparities in China's urbanization levels. The eastern coastal regions exhibit the highest comprehensive urbanization scores, characterized by advanced economic structures

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Research on the Coordinated Development of Agricultural Modernization and Urbanization

1. Introduction

The relationship between agricultural modernization and urbanization is a core issue in the process of national economic development. As China enters a new stage of high-quality development, achieving the coordinated advancement of these two processes has become essential for bridging the urban-rural divide and promoting sustainable economic growth. Agricultural modernization provides the foundational material support and surplus labor necessary for urban expansion, while urbanization offers the technological innovation, capital investment, and market demand required to transform traditional agriculture.

2. Theoretical Framework

The interaction between agricultural modernization and urbanization can be understood through the lens of structural transformation. According to dual-sector models, the migration of labor from the primary sector to the secondary and tertiary sectors is a hallmark of development. However, this transition must be balanced. If urbanization proceeds too rapidly without corresponding improvements in agricultural productivity, it may lead to food security risks and the "hollowing out" of rural areas. Conversely, stagnant urbanization can limit the market for agricultural products and hinder the transfer of modern technology to the countryside.

3. Methodology and Data

To evaluate the degree of coordination between these two systems, this study employs a coupling coordination degree model. We define the level of agricultural modernization ($A$) and the level of urbanization ($U$) using a multi-dimensional indicator system.

[TABLE:1]

The coupling degree $C$ is calculated as follows:
$$C = 2 \times \left[ \frac{A \times U}{(A + U)^2} \right]^{1/2}$$

To better reflect the actual level of coordinated development, we further calculate the coordination degree $D$:
$$D = \sqrt{C \times T}$$
where $T = \alpha A + \beta U$, and $\alpha, \beta$ are weights representing the relative importance of each system (typically $\alpha = \beta = 0.5$).

4. Empirical Analysis

Based on the data collected from various provinces, the results indicate a steady upward trend in the coordination degree over the past decade. However, significant regional disparities remain.

[FIGURE:1]

As shown in [FIGURE:1], eastern coastal regions exhibit a "high-level coordination" pattern, characterized by advanced industrial structures and highly efficient, technology-driven agriculture. In contrast, several western provinces remain in a state of "lagging coordination," where urbanization is primarily driven by administrative expansion rather

ernization and urbanization[J]. Urban Development Studies, 2007

Measurement of the Coordinated Development of Urbanization and Agricultural Modernization in China

1. Introduction

The coordinated development of urbanization and agricultural modernization is a critical component of China's national strategy for sustainable economic growth and social transformation. Urbanization serves as a powerful engine for structural change, while agricultural modernization provides the essential foundation for food security and rural stability. Historically, the "dual-track" development model often led to a lag in rural progress compared to rapid urban expansion. Achieving a synergistic relationship between these two processes—often referred to as "coordinated development"—is essential for narrowing the urban-rural gap and promoting high-quality development. This study aims to measure the degree of coupling and coordination between urbanization and agricultural modernization across various regions in China to provide a scientific basis for policy optimization.

2. Research Methodology and Data Sources

2.1 Construction of the Indicator System

To accurately evaluate the level of urbanization and agricultural modernization, we established a comprehensive evaluation index system based on the principles of scientific rigor, data availability, and systematicity.

The urbanization subsystem is evaluated through four dimensions: population urbanization, economic urbanization, social urbanization, and spatial urbanization. Key indicators include the proportion of the urban population, GDP per capita, the number of hospital beds per 10,000 people, and the proportion of built-up areas.

The agricultural modernization subsystem is assessed through four dimensions: agricultural production conditions, agricultural production efficiency, agricultural management level, and rural sustainability. Key indicators include the total power of agricultural machinery, grain yield per unit area, the proportion of effective irrigation area, and the use of chemical fertilizers per unit of cropland.

2.2 Evaluation Models

We employ the entropy weight method to determine the weights of each indicator, ensuring an objective assessment by minimizing human bias. The comprehensive development level for urbanization ($U_1$) and agricultural modernization ($U_2$) is calculated as follows:

$$U_i = \sum_{j=1}^{n} w_j x_{ij}$$

where $w_j$ represents the weight of indicator $j$ and $x_{ij}$ represents the standardized value of the indicator.

To measure the interaction between the two systems, we utilize the Coupling Coordination Degree (CCD) model. The coupling degree ($C$) is calculated as:

$$C = 2 \times \left[ \frac{U_1 \times U_2}{(U_1 + U_2)^2} \right]^{1/2}$$

modernization in China[J]. Statistics & Decision, 2015 ( 8 ): 121 -

Evaluation of the Coupling Coordination Degree Between New Urbanization and Agricultural Modernization

The coordinated development of new urbanization and agricultural modernization is a critical component of national strategic planning. This study evaluates the coupling coordination degree between these two systems to understand their interactive relationship and spatial-temporal evolution.

1. Introduction

The relationship between urbanization and agricultural development has long been a focal point of economic research. New urbanization emphasizes a people-centered approach, focusing on quality and sustainability rather than mere physical expansion. Simultaneously, agricultural modernization involves the transition from traditional farming practices to a highly efficient, technology-driven, and sustainable agricultural sector. The synergy between these two processes is essential for narrowing the urban-rural gap and achieving comprehensive regional development.

2. Literature Review

Existing research has explored various dimensions of the urban-rural relationship. Chen Tao, Yang Jiayi, and Chen Chibo \cite{Chen201X} utilized statistical methods to evaluate the coupling coordination degree, providing a framework for understanding how urban growth and agricultural advancement reinforce one another. Furthermore, regional studies have highlighted the geographical disparities in this coordination. For instance, Chen Li and Min Xiaofei \cite{ChenMin201X} conducted a specialized study on the coordinated development of new urbanization and agricultural modernization in Xinjiang, emphasizing the unique challenges faced by arid regions. Their findings suggest that environmental constraints and resource availability play a significant role in determining the pace of synergy between urban and rural systems.

[TABLE:1]

3. Methodology

To assess the coupling coordination degree, this study constructs a comprehensive evaluation index system for both new urbanization and agricultural modernization.

3.1 Index System Construction

The new urbanization index includes dimensions such as population urbanization, economic urbanization, social urbanization, and spatial urbanization. The agricultural modernization index incorporates factors such as agricultural production levels, management efficiency, and sustainable development capacity.

3.2 Coupling Coordination Model

The coupling degree $C$ is calculated to represent the strength of the interaction between the two systems:

$$C = 2 \times \left[ \frac{U_1 \times U_2}{(U_1 + U_2)^2} \right]^{1/2}$$

Where $U_1$ represents the evaluation value of new urbanization and $U_2$ represents the evaluation value of agricultural modernization. To further reflect the level of coordinated development, the coupling coordination degree $D$ is defined as:

$$\begin{aligned} D = \sqrt{C \times T} \end{aligned}$$

agricultural modernization in Xinjiang under policy of “ Three

Coordination Evolution and Patterns of Urbanization and Agricultural Modernization in Chifeng City

1. Introduction

The coordinated development of urbanization and agricultural modernization is a critical component of regional sustainable development. In the context of China's rural revitalization strategy and the "new-type urbanization" initiative, understanding the coupling relationship between these two systems is essential for optimizing resource allocation and promoting integrated urban-rural growth. Chifeng City, located in the Inner Mongolia Autonomous Region, serves as a significant case study due to its unique geographical position in an arid to semi-arid transition zone, where the balance between urban expansion and agricultural preservation is particularly delicate.

2. Research Methodology and Data Sources

This study employs a comprehensive evaluation index system to measure the levels of urbanization and agricultural modernization. Urbanization is assessed through four dimensions: demographic, economic, spatial, and social urbanization. Agricultural modernization is evaluated based on production factors, management efficiency, and sustainable development indicators.

2.1 Coupling Coordination Degree Model

To analyze the interaction between urbanization and agricultural modernization, we utilize the coupling coordination degree model. The coupling degree $C$ is calculated as follows:

$$C = 2 \times \left[ \frac{U \times A}{(U + A)^2} \right]^{1/2}$$

Where $U$ represents the level of urbanization and $A$ represents the level of agricultural modernization. To further reflect the synergistic effect and the overall development level, the coordination degree $D$ is defined as:

$$D = \sqrt{C \times T}$$
$$T = \alpha U + \beta A$$

In this model, $T$ is the comprehensive coordination index, while $\alpha$ and $\beta$ are weights assigned to each system, typically set to $0.5$ assuming equal importance.

3. Evolution of Urbanization and Agricultural Modernization in Chifeng

The empirical analysis reveals that Chifeng City has experienced a steady increase in both urbanization and agricultural modernization over the past decade. However, the growth rates and spatial distributions vary significantly across different banners and districts.

[TABLE:1]

As shown in [TABLE:1], the demographic urbanization rate has seen a consistent upward trend, driven by the migration of rural populations to urban centers. Simultaneously, agricultural modernization has been bolstered by increased mechanization and the implementation of the "three rights separation" policy for agricultural land, which has facilitated land transfer and large-scale farming operations \cite{Liu

selection of urbanization and agricultural modernization[J]. Chi ⁃

Evaluation of the Coordinated Relationship Between New-Type Urbanization and Agricultural Modernization in Henan Province

1. Introduction

The coordinated development of new-type urbanization and agricultural modernization is a critical component of China's national strategy for high-quality regional development. As a major agricultural province in central China, Henan faces the dual challenge of accelerating urban expansion while ensuring food security and rural revitalization. Understanding the coupling and coordination between these two systems is essential for optimizing resource allocation and promoting sustainable regional growth.

2. Research Methodology and Data Sources

2.1 Index System Construction

To objectively evaluate the level of development in both systems, we constructed a comprehensive evaluation index system. The new-type urbanization system focuses on four dimensions: population urbanization, economic urbanization, social urbanization, and spatial urbanization. Conversely, the agricultural modernization system is evaluated based on agricultural production conditions, output levels, and sustainable development capacity.

2.2 Evaluation Models

We utilize the entropy weight method to determine the weights of each indicator, ensuring an objective assessment. The coordination level is measured using the Coupling Coordination Degree (CCD) model. The coupling degree $C$ is calculated as follows:

$$C = 2 \times \left[ \frac{U_1 \times U_2}{(U_1 + U_2)^2} \right]^{1/2}$$

Where $U_1$ represents the evaluation value of new-type urbanization and $U_2$ represents the evaluation value of agricultural modernization. To better reflect the overall development level and the interaction between the two systems, the coordination degree $D$ is defined as:

$$D = \sqrt{C \times T}$$
$$T = \alpha U_1 + \beta U_2$$

In this model, $T$ is the comprehensive coordination index, and $\alpha$ and $\beta$ are undetermined coefficients. Given the equal importance of both systems in Henan's development strategy, we set $\alpha = \beta = 0.5$.

3. Results and Analysis

[TABLE:1]

3.1 Temporal Evolution of Development Levels

The analysis of data from recent years indicates that both new-type urbanization and agricultural modernization in Henan Province have shown a steady upward trend. However, the growth rate of urbanization has slightly outpaced that of agricultural modernization, leading to a widening gap in some periods. This suggests that while urban centers are expanding rapidly

dination relationship of the new urbanization and agricultural mod ⁃

ernization in Henan Province[J]. Chinese Journal of Agricultural

Resources and Regional Planning, 2020 , 41 ( 4 ): 143 - 149 . ]

Measurement of the Coupling Coordination Degree Between Agricultural Modernization and New Urbanization in Major Grain-Producing Areas

1. Introduction

The coordinated development of agricultural modernization and new urbanization is a critical component of China's national strategy for integrated rural-urban development. In major grain-producing areas, this relationship is particularly significant, as these regions bear the dual responsibility of ensuring national food security and promoting regional economic transformation. Understanding the spatiotemporal evolution of the coupling coordination between these two systems is essential for formulating targeted policies that balance agricultural productivity with urban expansion.

2. Research Methodology and Data Sources

To evaluate the synergy between agricultural modernization and new urbanization, this study constructs a comprehensive evaluation index system. Agricultural modernization is assessed through dimensions such as production efficiency, technological input, and sustainability. New urbanization is measured via population dynamics, economic structure, infrastructure, and basic public services.

The coupling coordination degree model is employed to quantify the interaction between these two systems. The coupling degree $C$ is calculated as follows:

$$C = 2 \times \left[ \frac{U_1 \times U_2}{(U_1 + U_2)^2} \right]^{1/2}$$

Where $U_1$ represents the evaluation value of agricultural modernization and $U_2$ represents the evaluation value of new urbanization. To further reflect the level of coordinated development, the coupling coordination degree $D$ is defined as:

$$D = \sqrt{C \times T}$$

In this formula, $T$ is the comprehensive evaluation index of the two systems, expressed as $T = \alpha U_1 + \beta U_2$, where $\alpha$ and $\beta$ are weights assigned to each system (typically $\alpha = \beta = 0.5$).

[TABLE:1]

3. Spatiotemporal Patterns and Evolution

The empirical analysis reveals distinct spatiotemporal characteristics in the coupling coordination degree across major grain-producing areas. Over the study period, there has been a general upward trend in the coordination level, moving from "basic coordination" toward "moderate coordination." However, significant regional disparities persist.

[FIGURE:1]

The spatial distribution indicates a pattern of "high in the east and low in the west," with coastal grain-producing regions demonstrating higher synergy due to advanced industrial foundations and more efficient resource allocation. In contrast, inland regions often face challenges where urbanization outpaces agricultural modernization, or vice versa,

and influencing factors of the “ Five Modernizations ” coordinated

Pattern Evolution and Influencing Mechanisms of the "Five Modernizations" Coordinated Development in Northeast China

The coordinated development of the "Five Modernizations"—industrialization, informatization, urbanization, agricultural modernization, and green modernization—represents a critical pathway for regional revitalization and sustainable growth. This study examines the spatial-temporal evolution and the underlying influencing mechanisms of this coordination within the context of Northeast China, a region traditionally characterized by its heavy industrial base and unique socioeconomic challenges.

[FIGURE:1]

Spatial-Temporal Pattern Evolution

The measurement of spatial-temporal differentiation in development efficiency across Chinese cities at the prefecture level and above reveals significant regional disparities. In Northeast China, the coordination among the "Five Modernizations" has undergone a complex evolutionary process. Historically, the region's development was heavily skewed toward traditional industrialization. However, recent data indicates a gradual shift toward a more integrated model where informatization and green modernization play increasingly prominent roles.

The spatial distribution of development efficiency is not uniform. Higher levels of coordination are typically concentrated in provincial capitals and major industrial hubs, such as Shenyang, Changchun, and Harbin, which benefit from superior infrastructure and policy support. Conversely, peripheral cities and resource-depleted areas often exhibit lower coordination scores, reflecting the structural difficulties in transitioning away from legacy industrial frameworks.

[TABLE:1]

Influencing Mechanisms

The mechanisms driving the coordinated development of the "Five Modernizations" are multifaceted, involving a combination of internal structural factors and external policy drivers. Key factors include:

• Industrial Transformation: The transition from traditional heavy industry to high-tech manufacturing and service-oriented sectors is fundamental to improving overall development efficiency.
• Technological Innovation: The integration of informatization acts as a catalyst, enhancing the productivity of both the industrial and agricultural sectors while facilitating smarter urban management.
• Policy and Governance: Regional revitalization strategies and environmental regulations have been pivotal in promoting green modernization and ensuring that urban expansion does not come at the expense of ecological integrity.
• Resource Allocation: The efficiency of land, labor, and capital allocation across the "Five Modernizations" determines the degree of synergy achieved within the regional system.

[FIGURE:2]

Conclusion

The coordinated development of Northeast China is characterized by a distinct spatial-temporal pattern where core cities lead the transition toward a more balanced "Five Modernizations" framework. Addressing the lag in peripheral areas requires targeted policy interventions that focus on technological diffusion and the ecological restoration of resource-dependent regions

of the coordinated development efficiency of the ‘ Four Moderniza ⁃

tions of prefecture level cities or above in China[J]. Scientia Geo

graphica Sinica, 2016 , 36 ( 4 ): 512 - 520 . ]

Research on the Problems and Countermeasures of the Coordinated Development of New Urbanization and Agricultural Modernization

1. Introduction

The coordinated development of new urbanization and agricultural modernization is a critical component of China's modernization drive and a necessary requirement for achieving high-quality economic development. New urbanization emphasizes a people-centered approach, focusing on the integration of industry and cities, while agricultural modernization aims to transform traditional agriculture through technological innovation and institutional reform. The synergy between these two processes is essential for narrowing the urban-rural gap and promoting common prosperity.

2. The Relationship Between New Urbanization and Agricultural Modernization

New urbanization and agricultural modernization are mutually reinforcing and interdependent. On one hand, new urbanization provides the necessary market demand, technical support, and capital investment for agricultural modernization. As the urban population grows, the demand for high-quality agricultural products increases, driving the optimization of agricultural structures. Furthermore, the transfer of rural labor to urban areas facilitates the moderate-scale management of land, which is a prerequisite for modernizing agricultural production.

On the other hand, agricultural modernization serves as the foundation for stable urbanization. By increasing agricultural productivity and ensuring food security, agricultural modernization provides the basic material guarantee for urban residents. Moreover, the modernization of the agricultural sector releases surplus labor, providing a steady supply of human resources for urban industrial and service sectors. The coordinated development of these two systems creates a virtuous cycle of urban-rural integration.

3. Current Problems in Coordinated Development

Despite significant progress, several challenges hinder the deep integration of new urbanization and agricultural modernization:

3.1 Lagging Agricultural Modernization Relative to Urbanization
In many regions, the pace of urbanization has significantly outstripped the progress of agricultural modernization. While cities expand rapidly, the agricultural sector often suffers from aging infrastructure, low technological adoption, and a lack of professional talent. This imbalance threatens the sustainability of urban growth and limits the overall efficiency of the national economy.

3.2 Inefficient Resource Allocation and "Dual Structure" Constraints
The long-standing urban-rural dual structure remains a major obstacle. Constraints in the land system, household registration (hukou) system, and social security framework prevent the free flow of production factors between urban and rural areas. For instance, the difficulty in transferring rural land use rights often prevents the consolidation of land necessary for large-scale, mechanized farming.

3.3 Weak Industrial Linkages
The integration of primary, secondary, and tertiary industries

velopment of new urbanization and agricultural modernization [J].

Coordinated Development Between Urbanization and Agricultural Modernization: A Case Study in Kunshan

1. Introduction

The relationship between urbanization and agricultural modernization is a critical component of regional economic development. As urbanization accelerates, the traditional agricultural sector undergoes significant structural transformations. This study focuses on Kunshan, a region that has experienced rapid industrialization and urban expansion, to analyze the mechanisms of coordinated development between these two systems.

2. Theoretical Framework and Methodology

The coordination between urbanization and agricultural modernization is not a simple linear relationship but a complex interaction involving resource allocation, labor migration, and technological diffusion. To quantify this relationship, we employ a coupling coordination degree model.

2.1 Indicator System Construction

We established a comprehensive evaluation index system for both urbanization and agricultural modernization. The urbanization subsystem includes dimensions such as population density, non-agricultural employment ratios, and infrastructure investment. The agricultural modernization subsystem encompasses mechanical power, land productivity, and the application of modern agricultural technologies.

2.2 Coupling Coordination Model

The coupling degree $C$ is calculated to represent the strength of the interaction between the two systems:

$$C = \left{ \frac{U_1 \cdot U_2}{[(U_1 + U_2)/2]^2} \right}^{1/2}$$

where $U_1$ represents the evaluation value of urbanization and $U_2$ represents the evaluation value of agricultural modernization. To further reflect the level of coordinated development, we calculate the coordination degree $D$:

$$D = \sqrt{C \cdot T}$$

where $T$ is the comprehensive evaluation index of the two systems, defined as:

$$T = \alpha U_1 + \beta U_2$$

In this model, $\alpha$ and $\beta$ are weights representing the relative importance of each system, typically set such that $\alpha + \beta = 1$.

[TABLE:1]

3. Empirical Analysis of Kunshan

Kunshan serves as an exemplary case for studying the "Sunan Model" of development. Our analysis indicates that the region has transitioned through several stages of coordination.

3.1 Evolution of Urbanization and Agricultural Modernization

Over the past decade, Kunshan's urbanization rate has seen steady growth, driven by the expansion of high-tech industrial zones and the integration of rural communities into the urban fabric. Simultaneously, agricultural modernization has shifted from traditional labor-intensive practices to capital

City [J]. Research of Agricultural Modernization, 2015 , 36 ( 6 ): 921 -

On the Coupling Coordination of New Urbanization and Agricultural Modernization in Traditional Rural Areas

Introduction

The coordinated development of new urbanization and agricultural modernization is a critical component of China's modernization strategy. In traditional rural areas, where agriculture has historically been the dominant industry and rural populations are concentrated, the relationship between urban expansion and agricultural advancement is particularly complex. Achieving a high degree of coupling and coordination between these two systems is essential for narrowing the urban-rural gap and promoting sustainable regional development. This study explores the internal mechanisms and spatial-temporal evolution of this coupling coordination in traditional rural regions.

1. Theoretical Framework and Mechanism of Coupling

The interaction between new urbanization and agricultural modernization is characterized by a reciprocal relationship of mutual promotion and constraint. New urbanization provides the necessary impetus for agricultural modernization through the transfer of surplus labor, the provision of advanced technology, and the expansion of market demand for high-quality agricultural products. Conversely, agricultural modernization serves as the foundation for urbanization by ensuring food security, supplying raw materials for urban industries, and creating a stable social environment in the countryside.

The coupling coordination degree (CCD) serves as a vital metric to evaluate the level of synergy between these two systems. A high CCD indicates that urbanization and agricultural modernization are evolving in a synchronized and mutually reinforcing manner, while a low CCD suggests structural imbalances or developmental lags in one of the systems.

2. Research Methodology and Data Sources

2.1 Indicator System Construction

To quantitatively assess the coupling coordination, we established a comprehensive evaluation index system. The new urbanization subsystem includes dimensions such as population urbanization, economic urbanization, social urbanization, and spatial urbanization. The agricultural modernization subsystem encompasses agricultural production conditions, output levels, social efficiency, and ecological sustainability.

2.2 Calculation of Coupling Coordination Degree

We employ the entropy weight method to determine the weights of each indicator, ensuring an objective assessment. The coupling degree $C$ is calculated using the following formula:

$$C = 2 \times \left[ \frac{U_1 \times U_2}{(U_1 + U_2)^2} \right]^{1/2}$$

Where $U_1$ represents the evaluation value of new urbanization and $U_2$ represents the evaluation value of agricultural modernization. To better reflect the overall level and synergistic effect, the coupling coordination degree $D$ is defined as:

$$D = \sqrt{C \times T}$$

(Humanities and Social Science), 2017 , 49 ( 4 ): 123 - 129 . ]

Long-term Mechanism for the Mutual Promotion of Urbanization and Agricultural Modernization under the Background of Urban-Rural Integration

1. Introduction

Under the strategic framework of urban-rural integration, the coordinated development of urbanization and agricultural modernization has become a critical component of national economic transformation. Urbanization provides the necessary spatial carriers, market demand, and technological spillover for agricultural advancement, while agricultural modernization serves as the foundational support for stable urban expansion by ensuring food security and providing labor resources. Establishing a long-term mechanism where these two processes promote each other is essential for overcoming the traditional dual-structure dichotomy and achieving high-quality regional development.

2. Theoretical Framework of Mutual Promotion

The interaction between urbanization and agricultural modernization is characterized by a dynamic feedback loop. Urbanization drives agricultural modernization through several key channels: first, the concentration of population in urban areas creates a robust market for high-value agricultural products; second, urban industrial sectors provide the machinery, fertilizers, and digital technologies required for modern farming; and third, the transfer of rural labor to cities facilitates land consolidation and large-scale farming operations.

Conversely, agricultural modernization supports urbanization by increasing land productivity, which releases surplus labor for urban industries. Furthermore, the rising income of modern farmers expands the rural consumer market, providing a sustainable growth engine for urban-based manufacturing and service sectors. This reciprocal relationship forms the basis of the "mutual promotion" mechanism.

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3. Key Components of the Long-term Mechanism

To ensure the sustainability of this coordinated development, several core mechanisms must be established:

3.1 Resource Allocation Mechanism

A market-oriented system for the flow of production factors—such as land, labor, and capital—is fundamental. This includes the reform of the rural collective land system to allow for more flexible land transfer and the establishment of a unified urban-rural labor market that protects the rights of migrant workers.

3.2 Technological Innovation and Diffusion

Agricultural modernization relies heavily on the "trickle-down" effect of urban technological innovation. Establishing regional innovation centers that bridge the gap between urban R&D and rural application is vital. This involves the deployment of "Smart Agriculture" technologies, including IoT sensors and big data analytics, to enhance resource efficiency.

3.3 Infrastructure and Public Service Integration

The long-term mechanism requires the extension of urban infrastructure—such as transportation, electricity, and high-speed internet—to rural areas. Simultaneously, equal

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Towards Rural-Urban Integration: Key Issues and Trends in the Integration of New Urbanization and Rural Vitalization

The relationship between urban and rural areas is a fundamental structural issue in the process of modernization. As China enters a new stage of development, the coordinated promotion of "New Urbanization" and "Rural Vitalization" has become a critical national strategy for achieving high-quality development and common prosperity. This paper explores the theoretical logic, practical challenges, and future trends of rural-urban integration within the context of these dual strategies.

1. The Theoretical Logic of Rural-Urban Integration

The integration of New Urbanization and Rural Vitalization is not a simple additive process but a synergistic evolution of two major systems. Historically, the urban-rural relationship has transitioned from "urban-rural dualism" to "urban-rural coordination," and is now moving toward "comprehensive integration."

The core of this integration lies in the bidirectional flow of production factors—including land, labor, and capital. As noted by Long et al. \cite{Long2019}, policies such as the "increasing vs. decreasing balance" (zengjian gua'ou) for land use have played a pivotal role in restructuring rural spaces and addressing the phenomenon of "hollowed villages." By optimizing land resource allocation, these policies provide the spatial foundation for both urban expansion and rural industrial upgrading.

2. Key Issues in Current Rural Restructuring

The restructuring of rural China is accelerating under the influence of various policy instruments and market forces. Several key issues emerge in this process:

• Spatial Restructuring: The consolidation of fragmented rural settlements into more efficient configurations. This involves addressing the "hollowed village" problem where migration to cities leaves behind underutilized land and aging populations.
• Economic Restructuring: Shifting from traditional subsistence agriculture to diversified rural industries, including high-tech farming, rural tourism, and e-commerce.
• Social Restructuring: The transformation of rural social structures as "new professional farmers" emerge and migrant workers return to start businesses, necessitating improved social services and governance.

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3. Challenges in the "Increasing vs. Decreasing