Yangtze River Delta Urban Agglomeration Research Articles

The Impact Analysis of the Digital Economy on Green Total Factor Productivity in the Yangtze River Delta Urban Agglomeration

The deep integration of digitalization and greening is a driving force for promoting high-quality economic development. The rapid development of the digital economy empowers green innovation, and the Yangtze River Delta urban agglomeration, as the most developed region in China's economy, carries an important mission for the future economic and social development of China. Clarifying the differences and influencing factors of digital economy and green total factor productivity (GTFP) among different cities within the Yangtze River Delta urban agglomeration is of great significance for formulating regional and national green development policies, achieving regional coordinated development, and environmental sustainability. This paper takes the impact of digital economy development on changes in GTFP as the starting point. Through the analysis of innovation efficiency, a theoretical model is established to reveal the internal mechanism by which digital economy development promotes GTFP. The research results show that digital economy development significantly promotes the improvement of GTFP, with greater impacts on large and medium-sized cities, regions with higher productivity levels, and regions with a more advanced industrial structure. Additionally, the internal mechanism test results indicate that digital economy development enhances GTFP by improving regional innovation efficiency and resource allocation efficiency.

Regional carbon inequality and its impact in China: A new perspective from urban agglomerations

The principal urban agglomerations in China function as critical hubs for both economic advancement and the mitigation of carbon emissions. Given the disparate levels of development across various urban agglomerations, trade between these agglomerations may result in inequality between carbon transfers and value added transfers. Assessing carbon inequality among major urban agglomerations in China can help identify the identification of primary trade relationships and industrial sectors of carbon inequality, thereby fostering the coordinated development of urban agglomerations. This study constructs a carbon inequality index based on an environmentally extended input-output model. This study conducts a thorough evaluation of carbon inequality among various urban agglomerations and analyzes the industry characteristics of embodied carbon net transfers and value added net transfers in typical urban agglomerations. The research findings indicate that: The carbon inequality index for underdeveloped urban agglomerations, exemplified by the Central Plains urban agglomeration, is generally greater than 1. The carbon inequality index for developed urban agglomerations, exemplified by the Yangtze River Delta urban agglomeration, is generally less than 1 due to their higher levels of economic development. An analysis of the industry characteristics of carbon emissions net transfer and value added net transfer in typical urban agglomerations reveals that heavy industry is the main contributing sector to the net inflow of embodied carbon and net outflow of value added in the Central Plains urban agglomeration. The main contributing sector to the net outflow of embodied carbon and net inflow of value added in the Yangtze River Delta urban agglomeration is the service industry. This study ultimately proposes more refined recommendations aimed at fostering coordinated development among regions in China, establishing a win-win situation for economic growth and carbon reduction.

Coupling Coordination Relationship between Ecological Human Settlements and the Happiness Levels of Residents in the Yangtze River Delta Urban Agglomeration

Coupling Coordination Relationship between Ecological Human Settlements and the Happiness Levels of Residents in the Yangtze River Delta Urban Agglomeration

How Do Changes in Ecosystem Services Multifunctionality Influence Human Wellbeing? Evidence From the Yangtze River Delta Urban Agglomeration in China

ABSTRACTA proclaimed goal of landscape management is to improve the multifunctionality of ecosystem services (ESs) to sustain higher levels of human wellbeing (HWB). Although the enhancement of ES multifunctionality is often considered to lead to better HWB, empirical evidence directly supporting this claim remains scarce. This study investigates the relationship between ES multifunctionality and HWB in rapidly urbanizing regions, using the Yangtze River Delta Urban Agglomeration in China as a case study. We quantified ES multifunctionality with the Gini‐Simpson Diversity Index and identified ES multifunctional types using the bundle approach. We also calculated both the HWB mean score and HWB evenness score with the improved radar chart method, examining their relationships with ES multifunctionality through Spearman correlation analysis and the Kruskal–Wallis rank‐sum test. Results showed that (1) ES multifunctionality exhibited varied relationships with HWB indicators, but overall showed significant negative associations with both HWB mean score and HWB evenness score. (2) Each HWB indicator significantly differed across the detected ES bundles, but none of the bundles exhibited the highest values of all HWB indicators. (3) HWB mean score and HWB evenness score were generally higher in the peri‐urban bundle while lower in the agriculture and forest bundles. Our findings suggest that peri‐urban landscapes can provide relatively higher and more balanced levels of HWB in urban agglomerations. This also implies that a “land‐sharing” urban development model, which balances natural and built environments, may be more beneficial for enhancing ES multifunctionality and HWB compared with a “land‐sparing” model, where natural and built areas are separated.

Characterizing Ecological Sensitivity of Yangtze River Delta Urban Agglomeration in China

Ecological sensitivity, as one of the most important indicators to evaluate regional environmental issues, holds significant implications for ecological governance and management in the related area. This study utilized remote sensing imagery of Landsat Thematic Mapper (TM) from the Yangtze River Delta (YRD) in 2014 and 2018, combined with field surveys and socio-economic data. Considering the local ecological and environmental conditions in the region, nine factors related to seven aspects, soil erosion, topography, humidity, habitat, water environment, human interference, and climate, were selected to create an ecological sensitivity evaluation framework for the YRD urban agglomeration. The coefficient of variation method was applied to determine factor weights, while the zonal statistics and spatial overlay methods were used for a comprehensive analysis of ecological sensitivity in a geographic information system (GIS). The YRD urban agglomeration was categorized into five ecological sensitivity levels: extremely sensitive, highly sensitive, moderately sensitive, slightly sensitive, and insensitive. The analysis results revealed spatial variations in the distribution of ecological sensitivity across the YRD urban agglomeration, with the overall ecological sensitivity level being slightly sensitive. The proportions of the total area occupied by extremely sensitive, highly sensitive, moderately sensitive, slightly sensitive, and insensitive zones were 14.30%, 12.02%, 25.29%, 30.34%, and 18.05% in 2014, and 14.30%, 24.01%, 16.33%, 27.32%, and 18.05%, respectively, in 2018. Based on these results, relevant ecological vulnerabilities for the YRD urban agglomeration were discussed.

Urban Sprawl and Imbalance between Supply and Demand of Ecosystem Services: Evidence from China’s Yangtze River Delta Urban Agglomerations

The contradiction between ecological resource protection and urban sprawl in urban agglomeration areas is becoming more and more prominent, facing a serious imbalance between the supply and demand of ecosystem services. To analyze the impact of urban agglomeration expansion on regional ecosystem services, based on multi-source data, an assessment model of supply and demand of ecosystem services for water conservation, carbon sequestration, soil conservation and crop production was constructed. With the help of value transformation model and spatial analysis method, this paper explores the risk of ecosystem service supply and demand imbalance faced by the Yangtze River Delta urban agglomeration in the process of expansion. This study found that the supply capacity of ecosystem services in the YRDUA has continued to decline at the spatial pixel scale; ecosystem service value deficits are a common problem in the YRDUA, with cities around Taihu Lake, such as Shanghai and Suzhou, being the most serious; the value surplus areas are concentrated in the southern cities, such as Xuancheng and Chizhou, but the balance between the supply of and demand for ecosystem services in these cities is also facing a challenge as the cities are expanding. This study analyzed the spatial pattern changes in the Yangtze River Delta region in the context of urban sprawl from the perspective of ecosystem service supply and demand, which helps to clarify the changing ecosystem service dynamics of the region and guide the formulation of urban planning policies and to achieve a balance between ecological supply and demand as well as sustainable development.

Land ecological security evaluation and prediction based on SBM-BP model: a case study of Yangtze River Economic Belt, China

Land ecological security is the foundation for ecological environmental protection and regional sustainable development. Therefore, examining the land ecological security and spatial heterogeneity in the Yangtze River Economic Belt (YREB) in China can guide effective land ecological protection in this region. Using a driving force-pressure-state-impact-response (DPSIR) index system, a global super-efficiency slacks-based measure (SBM) model, and a backpropagation (BP) neural network model, this study evaluated the land ecological security in 126 YREB prefecture-level cities and then employed spatial correlation analysis to identify the spatial distribution characteristics. It was found that: (1) from 2012 to 2021, the land ecological security in the study area decreased and then increased, with the eastern and western regions being better than the central regions; (2) from 2015 to 2017, the high land ecological security was clustered in the Yangtze River Delta urban agglomeration and the low value was clustered in Yunnan Province, Hubei Province, and the Chongqing Municipality; (3) from 2022 to 2026, the land ecological security in the study area is expected to gradually increase, but in the southwest is expected to remain low. These research results provide a theoretical basis for the evaluation and prediction of land ecological security and practical guidance for land ecological protection in areas with similar natural conditions.

Comprehensive maps of material stock dynamics reveal increasingly coordinated urban development in the Yangtze River Delta of China

Sustainable urban development critically depends on effectively managing the interplay between material stock (MS) and economic growth. This study combined convolutional neural network model and nighttime lights data to map building MS of Yangtze River Delta (YRD) urban agglomeration in China from 2000 to 2020 across 1 km × 1 km pixel scale, then uncovered the spatiotemporal dynamics of MS and its correlation with economic development. Our findings indicate that the model performed robustly on the test set (R2 > 0.88). YRD's MS surged over tenfold, reaching 20,772 teragram, primarily expanding along northwest-southeast developmental axes. Most YRD cities exhibited synchronized growth in material stock and GDP, suggesting an emergent pattern of sustainable urban expansion. However, cities at the developmental extremes highlighted the need for optimizing urban development strategies. By categorizing YRD cities into four distinct development modes, our study offers deep insights into the dynamics of urban development, underpinning targeted strategies that could guide cities towards more sustainable and resource-efficient growth trajectories.

Driving the Evolution of Land Use Patterns: The Impact of Urban Agglomeration Construction Land in the Yangtze River Delta, China

The rapid increase in population and economic activities has greatly influenced land use and spatial development. In urban agglomerations where socioeconomic activities are densely concentrated, the clash between ecological protection and economic growth is becoming more evident. Therefore, a thorough quantitative assessment of spatial changes driven by land use dynamics, alongside an examination of temporal and spatial driving factors, is crucial in offering scientific backing for the long-term and sustainable growth of urban agglomerations. This paper focuses on the major urban agglomerations in China’s Yangtze River Delta region, examining the spatiotemporal evolution of land use and landscape patterns from 2000 to 2020. By employing the standard deviation ellipse technique, coupled with multiple linear regression and the geographical detector model, we conduct a quantitative assessment of the directional trends in urban construction land expansion as well as the diverse impacts of temporal and spatial factors on this expansion across various periods and regions. The findings indicate that over the past 20 years, construction land in the Yangtze River Delta Urban Agglomeration expanded in concentrated patches, showing significant scale effects with relatively intact farmland and forest land being increasingly encroached upon. Landscape-type transitions predominantly occurred in cities around Taihu Lake and Hangzhou Bay, with the most significant transition being farmland converted to construction land, resulting in a greater number of patches and more pronounced land fragmentation. Throughout the 20 years, the standard deviation ellipse of construction land in the Yangtze River Delta Urban Agglomeration expanded and shifted, with the predominant expansion trending from the northwest toward the southeast, and the EN orientation being the most intense expansion area, covering 1641.24 km2. The influence of temporal and spatial driving factors on the expansion of urban construction land differed across various periods and regions. This study thoroughly examines the driving factors that affect the evolution of urban construction land in the region, offering valuable scientific evidence and references for future planning and development of the Yangtze River Delta Urban Agglomeration, aiding in the formulation of more precise and efficient urban management and land use strategies.

Prediction of Market Share of Different Vehicle Powertrains on Interprovincial Highways amid the Development of Urban Agglomerations

In the coordinated development of urban agglomerations in China, inter-city connections within urban agglomerations have been gradually strengthened, with more interprovincial highways built. Given the complex geological conditions, interprovincial highways often require tunnels. The construction of tunnel ventilation facilities needs to take into account the types of vehicle, traffic flows, and the market share of different vehicle powertrains using the highways. This paper aims to develop a method to predict the future market share of the powertrains of different types of vehicle on the interprovincial highway. The paper builds a policy cluster by analyzing the regional policies for new energy vehicles and then builds a parameter cluster by summarizing industry reports, expert opinion, and policy clusters to predict the market share of different vehicle types categorized by powertrains. Finally, based on the historical vehicle stock data, and using vehicle sales and scrappage rate models, the paper builds a future stock cluster to estimate the annual stock share of different vehicle powertrains up to 2045. The paper applies the method to the interprovincial highway S7 in the Yangtze River Delta urban agglomeration. It obtains the future trend of the market share of the powertrains of different vehicle types on S7 in the target year, validating the model. The results show that the share of new energy vehicles on the S7 highway will increase gradually until 2025. Electric vehicles will dominate the growth, with light trucks forming the highest proportion, followed by cars, and finally buses and heavy trucks.

Retraction Note: Application of real-time data processing system of internet of things based on blockchain technology in the financial field of Yangtze River Delta urban agglomeration

Retraction Note: Application of real-time data processing system of internet of things based on blockchain technology in the financial field of Yangtze River Delta urban agglomeration

How to decipher the environmental resilience performance? A case study of Yangtze River Delta Urban Agglomeration

Improving environmental resilience performance (ERP) is a significant support for achieving sustainable development goals. This study introduces the three-dimensional analysis framework of "object-process-actor", capable of addressing multidimensional and multilevel issues. This framework systematically addresses the "three key questions" of what, how, and who to improve ERP. Results indicate that from 2011 to 2020, the ERP of the Yangtze River Delta Urban Agglomeration (YRDUA) was between 0.42 and 3.30. The violin plot and visualization analysis showed that its probability density and distribution status were stable, with significant regional differences. The ERP of economically developed cities such as Hangzhou and Shanghai is high, while the ERP of cities in the Yancheng-Chuzhou line is low, and the number of high-performing cities increases to 40.7% in 2020, which is a constantly improving development trend. Factors related to market actors have the greatest impact on ERP, with the explanatory power of FDI, green invention patents, and population concentration all exceeding 0.6, and the importance of government and social actors is also supported. The explanatory power of factor interactions was stronger than that of single factors, and land development degree ranked third in terms of its interaction power with other factors and was also a key factor influencing ERP. These findings provide new explanations and knowledge for improving ERP, which can provide references for policymakers and urban planners.

Spatiotemporal Evolution and Influencing Factors of Heat Island Intensity in the Yangtze River Delta Urban Agglomeration Based on GEE

Urban agglomerations significantly alter the regional thermal environment. It is urgent to investigate the evolution and influence mechanisms of urban agglomeration heat island intensity from a regional perspective. This study is supported by Google Earth Engine long-term MODIS data series. On the basis of estimating surface urban heat island intensity (SUHI) in the Yangtze River Delta urban agglomeration from 2001 to 2020 based on the suburban temperature difference method, the causes of heat islands in the urban agglomeration were analyzed by using geographical detector analysis. Additionally, the heat island proportion (PHI) and SUHI indicators were used to compare and analyze the changing characteristics of the urban heat island effect of ten representative cities. The research reveals the following: (1) The average SUHI of the study area increased from 0.11 °C in 2001 to 0.29 °C in 2020, with an average annual increase rate of 0.009 °C. (2) According to the results of the geographical detector analysis, SUHI was influenced by several driving factors exhibiting obvious seasonal variations. (3) SUHI difference between cities is significant in the summer (1.52 °C), but smallest in the winter; the PHI difference between cities is larger in the autumn (46.7%), while it is smaller in the summer. The research findings aim to effectively serve the formulation of collaborative development plans for the Yangtze River Delta urban agglomeration.

Research on the correlation network of carbon emissions and economic between Chinese urban agglomerations

Urban agglomerations are currently at the center of China's efforts to reduce carbon emission and sustainable economic development. It is critical to investigate the carbon emissions and economic correlation between urban agglomerations in order to assist their carbon emission reduction and economic coordinated development. This paper is based on an environmentally extended multi-regional input-output model, and studies the embodied carbon emissions and economic two-dimensional correlation network between major urban agglomerations in China from 2012 to 2017. The research results indicate that the production-based carbon emissions of the production and supply of electricity and heat industry in the Yangtze River Delta urban agglomeration were higher than the consumption-based carbon emissions, with a significant gap. However, the construction and service industries were the opposite. The Hohhot-Baotou-Ordos-Yulin urban agglomeration experienced carbon emission losses and economic benefits. The Yangtze River Delta urban agglomeration achieved a win-win situation for carbon emissions and economy. The Pearl River Delta urban agglomeration benefited from carbon emissions but suffered economic losses. The Central Plains urban agglomeration faced a loss-loss situation for carbon emissions and economy. Major urban agglomerations in China should implement differentiated emission reduction measures based on their own characteristics. For example, the Hohhot-Baotou-Ordos-Yulin urban agglomeration should utilize natural resources to develop green industries and high value added industries.

Comparison of Urban Heat Island Differences in the Yangtze River Delta Urban Agglomerations Based on Different Urban–Rural Dichotomies

Comparison of Urban Heat Island Differences in the Yangtze River Delta Urban Agglomerations Based on Different Urban–Rural Dichotomies

Mapping high-resolution XCO2 concentrations in China from 2015 to 2020 based on spatiotemporal ensemble learning model

High-resolution column-averaged dry air mole fraction of CO2 (XCO2) data is crucial for understanding the spatiotemporal patterns of XCO2 and for mitigating carbon emissions. Due to the limited scanning range of sensors and strict inversion conditions, satellite-retrieved XCO2 data are often significantly incomplete. Machine learning models are widely used to fill these gaps in satellite XCO2 data. However, the limitations of individual machine learning models and the complexity of the spatial distribution of XCO₂ mean that the accuracy of XCO2 predictions still needs improvement. In this study, a new spatiotemporal stacked ensemble learning model (STEL) was developed by combining random forest (RF), extremely randomized trees (ERT), extreme gradient boosting (XGBoost), optical gradient boosting (LightGBM), and categorical boosting (CatBoost) using the stacking ensemble learning methodology. Considering the spatiotemporal heterogeneity of XCO2, a novel spatiotemporal weighting feature was constructed as part of the model's input parameters. Finally, the XCO2 observed by Orbiting Carbon Observatory 2 (OCO-2) was reconstructed using STEL, and a monthly mean XCO2 dataset covering China from 2015 to 2020 was generated at a spatial resolution of 0.1°. The results show that STEL exhibits superior performance and generalization capabilities compared to individual machine-learning models. R2 RMSE and MAPE were 0.9624, 1.0023 ppm, and 0.1583 % on the test set, and 0.8970, 1.4213 ppm, and 0.2475 % for R2, RMSE, and MAPE in ground validation, respectively. In 10-fold cross-validation, STEL's RMSE was reduced by 9.52 % compared to the best-performing single model (RF). The spatiotemporal trend of CO2 in China from 2015 to 2020 was analyzed using STEL XCO2 data. The results indicate that this dataset accurately reflects the spatiotemporal heterogeneity of XCO2 distribution at a fine scale. Overall, XCO2 exhibited a spatiotemporal pattern of “high in the east and low in the west” and “high in spring and low in summer.” Except in summer, high XCO₂ values were mainly distributed in the North China Plain. XCO2 trends and hotspots showed considerable spatial variation. The Pearl River Delta and Yangtze River Delta urban agglomerations have the fastest XCO2 growth rates, and the distribution of XCO2 hotspots is consistent with the distribution of population and economic centers. In the sparsely populated northwest of China, XCO2 is growing rapidly due to increased thermal power generation and coal mining. XCO2 hotspots in Northwest China are mainly located in Xinjiang, Ningxia, and Inner Mongolia. The methodology and data presented are useful for further research on carbon emissions, carbon sinks, and climate change.

The mechanism and path of pollution reduction and carbon reduction affecting high quality economic development - taking the Yangtze River Delta urban agglomeration as an example

In the wake of the COVID19 pandemic, what is crucial for the continued promotion of ecological civilization construction and sustainable green development in China is to achieve the dynamic and balanced development between pollution reduction, carbon emission reduction, and economic growth. Therefore, the indexes of CO2 emissions, pollution reduction intensity, and high-quality economic development are quantified in this study by using the panel data related to 26 cities in the Yangtze River Delta urban agglomeration(YRDUA) from 2010 to 2020. Furthermore, kernel density analysis, GIS spatial analysis, and other methods are employed to demonstrate the spatial and temporal patterns of pollution reduction intensity, CO2 emission levels, and the characteristics of high-quality economic development in the YRDUA. In order to reveal the dynamic relationship between pollution reduction, carbon emission reduction, and high-quality economic development, a panel vector autoregressive model (PAVR) was established and the system generalized method of moments was used to estimate the model coefficients. Additionally, Granger causality tests, impulse response analysis, and variance decomposition were conducted. There is a fluctuating upward trend shown by the overall level of CO2 emissions in the YRDUA, with significant spatial nonuniformity exhibited in carbon emissions. Despite the self-promotion mechanism playing a more significant role in the high-quality economic development in the YRDUA and its three regions, the impact of pollutant and carbon emissions on high-quality economic development is quite limited. A significant promoting effect is exhibited in those high and moderately high-quality economic development regions, while nonlinear effects are observed in those high and moderately high-quality economic development regions. As for the interactive relationships, the three factors are correlated with each other to a more significant extent in those high and moderately high-quality economic development regions, which contributes to mutual influence and causal relationship. However, there is no effective interactive mechanism observed among the three factors in the whole area and low-quality economic development regions, with high-quality economic development playing a major role in environmental pollution and carbon emission reduction.

Coupling synergy level and interaction effect between the ecological environment and low-carbon development in the Yangtze River Delta urban agglomeration: Characteristics of spatial and temporal heterogeneity

Low-carbon development and the ecological environment are often assessed separately, but understanding their interaction effect and the coupled coordination development from a spatially heterogeneous perspective remains limited, particularly in the context of rapidly urbanizing urban agglomeration regions. To address this research gap, this study assessed the levels and variations in coupled coordinated development between low-carbon development and the ecological environment at the urban agglomeration level using a coupled coordination degree model. Key factors of the interaction effect for each system were initially identified by ordinary least squares, then a geographically and temporally weighted regression model was used to reveal the spatial and temporal heterogeneity of these factors. Our study showed that the comprehensive development level of low-carbon development system in all cities exceeded that of the ecological environment system from 2006 to 2021. However, the level of synergy between the two systems showed slight improvement, with most cities exhibiting a moderate balance from 2010 to 2020. Regional heterogeneity was apparent in the coordinated development types, with highly balanced cities located primarily in the west and north of the urban agglomeration. Furthermore, our findings illustrated the positive effect of the air and climate environment on low-carbon development, contrasted with the negative influence of the land environment. These results not only enrich our understanding of low-carbon development and ecological environment interrelations in the Yangtze River Delta urban agglomeration but also provide insights applicable to similar regions worldwide, thereby contributing to the global discourse on synergistic sustainable development of low-carbon and ecological environment.

Spatial dynamics of transport accessibility and regional efficiency in the Yangtze River Delta Urban Agglomeration

Transport accessibility is crucial for defining urban clusters and evaluating a region's centrality and connectivity. To foster equitable growth in urban conglomerates, it is crucial to understand the relationship between transport accessibility and regional development. This study introduces the concept of 'regional efficiency'—the effectiveness of converting regional inputs into outputs—determined via the super-efficiency Data Envelopment Analysis methodology, to assess the progression of regional development. Employing a combination of bivariate spatial autocorrelation and spatial regression analysis, this research elucidates the spatial dynamics between transport accessibility and regional efficiency, both at macro and micro levels. A binary Logit model identifies the factors affecting the Moran's I correlation between regional efficiency and transport accessibility. Based on the diverse urban characteristics within a single conglomerate, tailored development strategies are suggested. Focusing on the Yangtze River Delta Urban Agglomeration in China as a case study, four distinct spatial clusters—High–High (HH), Low–Low (LL), High–Low (HL), and Low–High (LH)—are identified, based on the local correlation between regional efficiency and transport accessibility. The findings reveal that regions with a High–High Moran's I correlation between road accessibility and regional efficiency predominantly located in the eastern sectors of the Yangtze River Delta, exhibiting effective regional efficiency. These regions are characterized by superior road accessibility, aligning well with their regional efficiency metrics. For air accessibility, cities classified under the HH category, including Shanghai and its neighboring cities, demonstrate a significant spatial correlation with regional efficiency. Population density and urban tier are key predictors of the significance of the Moran's I correlation between road accessibility and regional efficiency. In contrast, for air accessibility, these factors assume an inverse role. The identified cluster types (HH, LL, LH, and HL) are proposed as predictive indicators for the significance of the Moran's I relationship between air accessibility and regional efficiency.

Land price dynamics in response to high-speed rail network characteristics: An empirical analysis

High-speed railway (HSR) has become the backbone of China's rapid and comprehensive urban transportation network system. However, the impact of the network characteristics of HSR on urban land prices has not been studied in sufficient detail. To fill this gap, this study focuses on both the Yangtze River Delta urban agglomeration and the Beijing-Tianjin-Hebei urban agglomeration and explores the linkage relationship between the HSR network and urban land prices. For this analysis, social network analysis and fixed effects model are used. The results show that the overall HSR network density of these two urban agglomerations still has room for improvement. Affected by regional proximity and the direction of HSR lines, HSR presents a spatial pattern of a multi-center–multi-tier network. The “siphon effect” is the main effect of the HSR network characteristics on land prices. However, the weakening degree of spatial spillover effect on siphon effect of the HSR network in the Yangtze River Delta urban agglomeration is stronger than that in the Beijing-Tianjin-Hebei urban agglomeration. Local governments should fully utilize the spatial effects of HSR and enhance the level of coordinated development among urban agglomerations.