Introduction

As one of the world’s largest develo** countries, China has seen significant advancements in economic and urban development in recent years, largely due to the continuous improvement of its transportation infrastructure, particularly in railway network construction (Li et al., 2022). On the other hand, high-speed rail new towns consume significant amounts of land, energy, and water resources, exacerbating the conflict between farmland protection and urban construction. This is not conducive to the development of resource-saving and environmentally friendly cities (Meng et al., 2018). Additionally, recent research indicates that the construction of high-speed rail new towns does not always achieve the anticipated positive outcomes. Particularly in inland areas, the development of these new towns can lead to regional hollowing, reflecting the complex impact of integrating high-speed rail with urbanization strategies (Balsa-Barreiro et al., 2019).

In 2018, the National Development and Reform Commission issued guidelines on the rational development and construction of areas surrounding high-speed rail stations. It pointed out that research on integrating high-speed rail construction and urbanization is still insufficient. Problems such as excessive scale, high functional positioning, and inadequate comprehensive supporting facilities in the development and construction of areas surrounding high-speed rail stations have not been properly addressed. Some high-speed rail new towns lack sufficient attractiveness to populations and industries, and their foundation for sustained and healthy development falls short of the overall planning goals.

Studying the impacts of high-speed rail new towns on urban economic, resource, and environmental systems can provide a scientific basis for planning decisions, promoting regional coordinated development, and ensuring urban sustainability (Sands, 1993). Evaluating the specific impacts of central and peripheral high-speed rail new towns on urban sustainability helps comprehend the variations in their effects. This, in turn, provides decision-makers with a scientific foundation for formulating appropriate development strategies, thereby facilitating efficient, coordinated, and sustainable urban development goals.

However, there is still a lack of relevant research literatures on the impacts of high-speed rail new towns. Most existing studies on high-speed rail new towns treat the opening of high-speed rail as a virtual variable and investigate its impact on regional socio-economic factors, urban spatial evolution, and development patterns around high-speed rail stations. There is a lack of quantitative research directly evaluating the impacts of high-speed rail new towns on the coordinated development of urban economy, resources, and environment.

Presently, China has planned and is in the process of constructing over 300 high-speed rail new towns, a strategic initiative with significant implications for promoting regional economic development and advancing urbanization. However, the construction of high-speed rail new towns is increasingly associated with prominent economic, social, and environmental challenges. Urban sustainable development has long been a focal point within academia, yet the impact of high-speed rail new towns on urban sustainability remains inadequately explored. Our study aims to assess the impacts of high-speed rail new town construction on urban sustainable development. It seeks to explore construction strategies for different types of high-speed rail new towns, providing feasibility and policy recommendations for the development of high-speed rail new towns in China.

Compared to existing research, this paper is of innovation in three key aspects. Firstly, it assesses urban sustainable development from the perspective of the coordinated development of urban economic, resource, and environmental systems. The study employs spatial econometric models to investigate the impacts of high-speed rail new towns on urban sustainable development, addressing a research gap in this field. Secondly, the study integrates long-term satellite remote sensing observations of nighttime lights and cumulative regional data around high-speed rail stations. It establishes a comprehensive index using the entropy method, creating an evaluation framework that encompasses the development scenarios of multiple urban high-speed rail new towns. Thirdly, the study compares and discusses the specific impacts of central and peripheral high-speed rail new towns on different cities, providing references for the development planning of subsequent high-speed rail new towns.

The remaining sections of this paper are organized as follows: Section 2 introduces the research methods, related models, variable selection, and data sources. Section 3 presents the main research findings. Section 4 discusses the research findings. Section 5 concludes with policy recommendations. The research framework is illustrated in Fig. 2.

Fig. 2
figure 2

Research framework.

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Methods and data sources

Spatial matrix construction

In determining the spatial weight matrix, it is important to consider the significant impact of economic interconnections between regions, which is often overlooked by neighbor-based matrices. However, the economic distance matrix also has certain limitations. For instance, when economic distances are equal, it does not necessarily imply the same level of spatial correlation. In reality, regions with higher levels of economic development tend to have a stronger radiating effect on surrounding areas compared to regions with lower levels of economic development (Zhao and Wang, 2022).

Therefore, this study combines a geographical distance matrix with an economic distance matrix to construct a nested matrix, referred to as W1, reflecting the specific impacts of high-speed rail new towns on urban sustainable development. Additionally, a geographical matrix, W2, is constructed to ensure the robustness of the estimation results.

The construction method for the economic-geographic nested matrix W1 is as follows:

$$\begin{array}{c}{W}_{ij}=\frac{1}{\sqrt{{({x}_{i}-{x}_{j})}^{2}+{({y}_{i}-{y}_{j})}^{2}}}\times diag({Y}_{1}/Y,{Y}_{2}/Y,\cdots {Y}_{n}/Y)\\ {Y}_{i}=\frac{1}{{t}_{n}-{t}_{0}+1}\mathop{\sum }\limits_{{t}_{0}}^{{t}_{n}}Y\end{array}$$
(1)

The construction method for the geographic distance matrix W2 is as follows:

$${W}_{ij}=\frac{1}{\sqrt{{({x}_{i}-{x}_{j})}^{2}+{({y}_{i}-{y}_{j})}^{2}}}$$
(2)

In this study, the variables xi and yi represent the latitude and longitude coordinates of provincial capital cities in various regions, respectively. The data for these coordinates were obtained from the National Basic Geographic Information Center.

The variable Yi represents the per capita GDP of each city during the observation period, while Y represents the per capita GDP of all cities during the observation period.

Spatial Durbin model

We established a dynamic spatial Durbin model with lagged terms to analyze the impact of HSRNT on urban sustainable development. In contrast to the static spatial Durbin model, the dynamic spatial Durbin model not only takes into account dynamic effects and spatial spillover effects but also helps alleviate endogeneity issues (Deng et al., 2022; Chen et al., 2023; Gu et al., 2022). The specific model is as follows:

$$\begin{array}{l}LnUS{D}_{it}=\alpha +\beta \ast {W}_{ij}\ast (LnUS{D}_{it}+LnUS{D}_{it-1}+LnHSRN{T}_{it}+Ln{X}_{it})\\\qquad\qquad\;\,+ {\beta }_{1}LnUS{D}_{it-1}+{\beta }_{2}LnHSRN{T}_{it}+\gamma \sum Ln{X}_{it}+{\mu }_{i}+{\lambda }_{t}+{\zeta }_{it}\end{array}$$
(3)

Where USDit represents the sustainable development of the city, USDit-1indicates the lag period, HSRNTit reflects the developmental status of the HSRNTs, and Wij signifies the spatial weight matrix. Xit comprises control variables, which encompass foreign direct investment (FDIit), the ratio of total social retail consumption to GDP (TRSCGit), urbanization rate (URBit), digital economic development level (DEit), and population density (PDit). To address potential heteroscedasticity and its impact on estimation results, we have logarithmically transformed the variables.

The LM test indicates that a spatial econometric model is more suitable than a non-spatial econometric model. The Wald_SDM/SAR and LR_SDM/SAR values pass the significance tests at the 1% level, rejecting the null hypothesis that the Spatial Durbin Model can degenerate into a spatial autoregressive model. Similarly, the Wald_SDM/SEM and LR_SDM/SEM values also pass the significance tests at the 1% level, rejecting the hypothesis that the spatial Durbin model can degenerate into a spatial error model. Therefore, this paper employs a spatial Durbin model that accounts for both fixed time and spatial aspects as the empirical model. The results are presented in Table 1.

Table 1 Spatial Durbin model suitability tests.
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Fixed effects model

Once spatial correlation is identified between the high-speed rail development indicators and urban sustainable development, it may be inappropriate to persist in using spatial econometric models to examine the impact of high-speed rail development on urban sustainability in different regions. This is because, in the presence of existing spatial correlation, investigating the impact of high-speed rail development on individual regional areas would disregard the effects of spillovers into other regions, potentially leading to biased estimation results. To address this issue, we employed a fixed effects model while controlling for time and studying individuals. The model is as follows:

$$LnUS{D}_{it}=\alpha +\beta LnHSRN{T}_{it}+\gamma \sum Ln{X}_{it}+{\mu }_{i}+{\lambda }_{t}+{\zeta }_{it}$$
(4)

In the equation above, u represents individual fixed effects, and r denotes time-fixed effects. All other variables are identical to those in Eq. (3).

Urban sustainable development

We concur with the viewpoint of Jegatheesan et al. (2009): the coordinated development among subsystems is crucial for achieving sustainable development. Building upon the research of ** high-speed rail new towns. This study, on the other hand, focuses on the impact of high-speed rail new towns on urban sustainable development. To the best of our knowledge, this is the first research literature examining the influence of high-speed rail new towns on urban sustainable development.

This study examines the impacts of high-speed rail new towns on urban sustainable development in China. The findings of the study indicate that high-speed rail new towns can have a positive impact on urban sustainable development, but the magnitude of the impact varies depending on the type of city and the location of the high-speed rail station.

The findings of this study underscore the positive contributions of HSR new towns to urban sustainable development. The establishment of HSR new towns has led to enhanced economic vitality, industrial upgrading, resource optimization, and environmental improvements, particularly in regions with robust industrial foundations, abundant human resources, and supportive policy environments. The central region, despite experiencing rapid development, has demonstrated potential for further economic restructuring, investment attraction, and talent mobility under the impetus of HSR new towns.

The construction of high-speed rail (HSR) new towns generates substantial spatial spillover effects on urban sustainable development. For local cities within the region, the short-term and long-term impacts of HSR new towns are generally consistent. However, for neighboring cities, the long-term effects of HSR new towns are significantly greater than the short-term effects. This phenomenon can be attributed to the fact that HSR new towns attract population and resources from surrounding cities, thereby accelerating their rapid development and economic growth. Neighboring cities may experience resource outflows and population reduction in the short term, resulting in relatively smaller short-term effects. Nevertheless, in the long-term development, HSR new towns can drive the development of neighboring cities.

Moreover, our study finds that the impact of high-speed rail new towns on urban sustainable development also exhibits distinct regional disparities. The construction of high-speed rail new towns in the eastern region has the most significant influence on urban sustainable development, as the region possesses a relatively complete industrial foundation, abundant human resources, a higher level of economic development, and policy support. Although the central region has experienced rapid development and has certain potential, its overall strength is relatively weak, the construction of high-speed rail new towns can drive economic structural adjustment, attract investment, and facilitate talent mobility. The western region has a relatively backward infrastructure, industrial development, and resource endowment, so the impact of high-speed rail new towns on its development is relatively small. However, it can still bring about a certain degree of economic growth and optimize resource utilization.

Furthermore, the study highlights the importance of considering the location of HSR stations when evaluating the impacts of HSR new towns. Central-type HSR stations, situated in the heart of urban areas, exert a stronger influence on urban sustainable development compared to peripheral-type HSR stations. This is attributed to their superior transportation accessibility, higher concentration of economic activities, and stronger interconnections among various urban subsystems.

The findings of this study have significant implications for urban planning and policymaking. To harness the full potential of HSR new towns and promote urban sustainable development, policymakers should prioritize balanced development strategies that foster harmonious growth across different city types. Additionally, encouraging cooperation and linkage between HSR new towns and neighboring cities can maximize the diffusion of development benefits and foster regional integration.

In conclusion, this study provides a comprehensive analysis of the impacts of HSR new towns on urban sustainable development, offering valuable guidance for urban planners and policymakers. By promoting balanced development, encouraging cooperation, and protecting the environment, cities can leverage HSR new towns as catalysts for sustainable and inclusive urban growth.

Conclusion and policy recommendations

Conclusion

We collected nighttime light and built-up area’s spatiotemporal data for 223 prefecture-level cities in China’s high-speed rail new towns from 2011 to 2021 using satellite remote sensing technology. Utilizing a spatial econometric model, the impact mechanisms of high-speed rail new towns on urban sustainable development were investigated. The study analyzed the impacts of high-speed rail new towns on different regions and cities with varying population sizes. Furthermore, the effects of different types of high-speed rail new towns on sustainable development were evaluated. The principal findings are as follows:

First, the built-up area and nighttime lights exhibited significant growth from 2011 to 2021. The growth rate of nighttime lights was notably higher than that of the built-up area. The development status of the built-up area and nighttime lights was correlated with geographic location, with the eastern region outperforming the central region and the western region lagging. The developmental disparities among high-speed rail new towns in different cities have gradually diminished.

Second, high-speed rail new town construction had significantly positive spatial spillover effects on sustainable development, regardless of whether it was under an economic-geographic nested matrix or a geographical distance matrix. Specifically, the impact of high-speed rail new towns on local cities exhibited consistent long-term and short-term effects, while the impact on neighboring cities showed a long-term effect greater than the short-term effect.

Third, high-speed rail new towns could significantly promote urban sustainable development, with the strongest promotional effect in economically developed areas and the weakest in the western region. Different types of high-speed rail stations also exhibited varying impacts on the three main regions, with the strongest influence on the eastern region and the weakest on the western region. The construction effectiveness of “central-type” high-speed rail new towns surpassed that of “peripheral-type” high-speed rail new towns.

Policy recommendations

Based on the conclusions drawn from this study, we propose the following policy recommendations:

Prioritize balanced regional development by strengthening intercity transportation connectivity. Despite the diminishing disparities in the development of high-speed rail new towns, it is still necessary to enhance intercity transportation connectivity to promote economic cooperation and exchanges between cities. While the government continues to expand the coverage of the high-speed rail network, improve the convenience and efficiency of high-speed rail transportation, and further facilitate intercity connectivity, considering the relatively inferior development status of the central and western regions, it should increase infrastructure investment, optimize industrial layout, and provide tax incentives to support their development.

Foster intercity cooperation and coordination through enhancing the planning and construction of high-speed rail new towns. The government should continue to invest in develo** high-speed rail new towns to facilitate the flow of personnel and goods. Strengthen communication and cooperation mechanisms between cities, promote resource sharing, and implement cooperative projects. At the same time, strengthen policy coordination and institutional integration between regions to provide a better institutional environment and policy support for the development of high-speed rail new towns.

Develop tailored planning and construction policies for different types of high-speed rail stations. Considering the differential impacts of different types of high-speed rail stations on the three major regions, the government should formulate planning and construction policies accordingly. For the eastern region, priority can be given to the development of central-type high-speed rail new towns and major hub stations to further enhance the agglomeration capacity and competitiveness of cities. For the western region, the government should strengthen the construction of peripheral-type high-speed rail stations.