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  • Zhang Yanji, Huang Hongxiang, Lin Sheng
    SCIENTIA GEOGRAPHICA SINICA. https://doi.org/10.13249/j.cnki.sgs.20230320
    Accepted: 2024-05-20
    To compensate for the limitations of case fragmentation, inconsistent standards, misused methods of identifying city centers, and incomparable conclusions in the established Chinese polycentric spatial structure studies, this study aimed to identify all the city (sub) centers of 297 Chinese prefecture-level or above cities in 2019 by using fine-grained Landscan ambient population data and integrating spatial autocorrelation analysis with polycentric regression models. We also measured the degree of urban polycentricity using three indicators: the number of city centers, the relative distance between city centers, and the balance of center development. Then, we summarized ten types of urban spatial structure patterns based on the combination of the three polycentricity indicators mentioned above. The study identified a total of 863 centers in 297 prefecture-level or above cities in 2019, and learned the theoretical density and density gradient of each center in every city through the negative exponential function. These findings served as a comprehensive examination of the underlying base map of the polycentric structure of Chinese cities and formed the basis for subsequent longitudinal tracking analyses. Our study revealed that in 2019, monocentric, bicentric and polycentric cities accounted for approximately 29%, 20% and 45% of the total, while 5.7% of the cities remained in a dispersed pattern. We found that, except for a few cities with a dispersed pattern, the more centers, the fewer the corresponding cities. Developed, mountainous, provincial border cities, and small and medium-sized cities with an evenly distributed urban population were more likely to form sub-centers far from the main center. Larger cities with a cluster layout and smaller cities with strong counties but weak districts were more likely to develop multiple (or dual) centers with equal density and balanced influence, while the main center of circle-sprawling cities tended to dominate the population distribution in the whole region, and their spatial patterns showed a polarized trend. Our study demonstrated that the level of social and economic development was the primary factor in shaping the polycentric spatial structure of Chinese cities, and the fluctuation and variability of natural topography also objectively contributed to the growth of urban polycentricity. However, out-migration public policies such as government relocation and the construction of industrial development zones and new town did not have a significant effect on urban polycentricity. It was also difficult for road construction to effectively promote the growth of new sub-centers. Therefore, the polycentric spatial structure was the product of high-level socio-economic development rather than an artificial creation through leapfrogging planning.
  • Xiong Wei, Huang Meijiao, Zhong Shiyao, Luo Xiaowen
    SCIENTIA GEOGRAPHICA SINICA. https://doi.org/10.13249/j.cnki.sgs.20230250
    Accepted: 2024-05-20
    Chinese culture is centered on food. In the context of representation and non representation theory, food crosses communities, nations, and boundaries. The cognition of food comes from the mobile life practice. There are customarily such expressions as “the sweet flavor in the south, the salty flavor in the north” and “he rice in the south, the wheat in the north”, can this be seen as a metaphor for the existence of widespread food territorial stereotypes? Based on mobility, it is worth to explore whether the food regional stereotype evolves dynamically or statically. This study adopted a mixed approach to validate and measure food regional stereotypes. Applying the exploratory sequence design, this study consisted of three sub-studies. Study 1 used content analysis to initially examine the basic content of food regional stereotype. Data was crawled from Bilibili through Python, and used Rost CM6 software to analyze network text and construct semantic social network. Study 2 recruited subjects through convenience sampling and used the questionnaire survey to test the food regional stereotypes at the explicit level. Study 3 conducted Implicit Association Test to examine the existence of food implicit regional stereotype, and the experiment was designed with two within-subject variables (semantic consistency: consistency or inconsistency)×(objective area: south or north). Study 1 showed that the food regional stereotypes of the subjects were mainly reflected in the preferences of staple food and taste of the north and the south, which were specifically expressed as “ sour in east, hot in west, sweet in south and salty in north”, consistent with the people’s previous cognition of food regional differences. Study 2 showed that the subjects tended to choose food words that matched the region, and formed eight specific dimensions, including: northern staple food, northern flavor, northern portion, northern dish, southern staple food, southern flavor, southern portion, and southern dish. Study 3 showed that: when the priming words of staple food, flavor, portion, and dishes were consistent with the target region (such as “noodles and the north”), the responding time was significantly lower than the inconsistency (such as “noodles and the south”). Overall, this study showed that the subjects held the regional stereotype of food in implicit and explicit levels, and the specific contents could be divided into four dimensions: staple food preference, flavor preference, portion preference and specific dishes. This study has the following implications. At the theoretical level, this stable place perception represented by food reflects the dialectical relationship between representation and non representation theory, and expands the research content of immobility under the new mobility paradigm. From the perspective of practice, this study tries to interpret commonsense food regional stereotypes in a scientific way, so as to improve the public’s understanding of food regional stereotype and reduce food cultural conflicts.
  • Liu Tianbao, Zhu Zhangwei
    SCIENTIA GEOGRAPHICA SINICA. https://doi.org/10.13249/j.cnki.sgs.20230247
    Accepted: 2024-05-20
    With the implementation of the “double reduction” policy and the advent of the post-epidemic era, the status of family education has become increasingly important. Based on the data from the 2020 questionnaire survey, this paper uses factor analysis, hotspot analysis and other methods to interpret the socio-spatial differentiation of the family education environment at the compulsory education stage and its impact on the in-home learning experience. It is found that: 1) There is multi-scale spatial differentiation in the family education environment. First, the highest degree of differentiation is found among families, reflecting the dominant role and great differences between families in constructing the family education environment. Second, the differentiation between urban circles is obvious, and the family education environment in the urban core area is more advantageous than that in urban suburbs and urban new areas. Thirdly, the differentiation and decentralized clustering of family education environments among residential and school districts also requires attention. The differentiation of the family education environment is the result of a combination of different scale factors, such as the urban environment, school districts, and residential neighborhoods and families. 2) The characteristics and spatial distribution of family education environments differ significantly among different groups. High-socioeconomic-status families provide a high-quality family education environment with the highest comprehensive score and the highest scores on all dimensions, which are concentrated in the urban core areas. Ordinary socio-economic status families provide a next best comprehensive score but weaker cultural dimensions of the family education environment, which are mainly distributed in the inner suburbs and the core of new urban areas. Low-income families provide an overall worse but better social dimension of the family education environment, which are mainly distributed at the edges of each urban circles. Low-education families provide the worst family education environment with the lowest comprehensive score, which are also mainly distributed in the outer part of each urban circles. 3) There are many factors in the family education environment that have an impact on the in-home learning experience. Among all the factors, the five dominant factors are: ‘Noise impact degree at home’ ‘Parental expectation’ ‘Study partner is your parent’ ‘Parents are able to help you solve problems of learning at home’ and ‘Number of extracurricular books at home’, which reflect the importance of a quiet home environment, parental involvement, and a good family atmosphere for students learning at home. Urban circles had little effect on the in-home learning experience, and the dominant influencing factors were much the same across circles. The interaction of two factors significantly increased the explanatory power, indicating that in-home learning experience is influenced by a combination of factors.
  • Yang Chen, Wang Qiang, Jin Cheng, Li Haihong, Ren Hongrun
    SCIENTIA GEOGRAPHICA SINICA. https://doi.org/10.13249/j.cnki.sgs.20230103
    Accepted: 2024-05-20
    Refinement governance is the future governance direction of the city, and it is also an important challenge for Shanghai to build an outstanding global city. Most of the existing research is based on the innovative mode and management mechanism of urban grid management, but the analysis and mining of grid management event data are still insufficient, and there is a lack of regular analysis of meteorological conditions on the occurrence of events. From the meteorological perspective, this paper uses spatiotemporal feature analysis and natural language processing methods to analyze the features of grid management event data, and uses correlation analysis and frequent pattern mining algorithms to obtain the association rules between meteorological conditions and urban management events. On this basis, the typical meteorological conditions that trigger grid management events are obtained, and the typical event knowledge graph covering meteorological conditions is constructed. The results show that the events are highly correlated with the characteristics of residents’ activities, the occurrence time of events is highly consistent with the working time, and the occurrence area also coincides with the densely populated areas of the city. There is a phenomenon of “concentrated head and long tail distribution” in the category, and a clear clustering structure can be formed in the event word segmentation, forming a co-occurrence term relation network with citizen activities as the main body. Analysis with meteorological data, municipal facilities and sanitation categories have obvious correlations with air temperature, windvulnerable structures are greatly affected by wind, and some illegal behaviors are also highly correlated with meteorological conditions. In addition, under specific weather conditions, some events will show an obvious tendency to occur easily. For example, events such as foundation pits, disputes, high-altitude parabolas, and river greening occur under specific weather conditions such as precipitation, low temperature, high temperature and strong wind, and strong winds will also have an amplified effect on environmental problems such as river pollution, open burning and the distribution of leaflet. On this basis, the knowledge graph technology is used to summarize and express the relationship between meteorology and urban operation, so as to form a knowledge framework for urban operation signs triggered by meteorological conditions, which is beneficial for urban operation managers to respond and deal with specific weather conditions in advance, and provide certain decision-making references for Shanghai to improve refined management measures and optimize the urban governance system.
  • Yang Yi, Yang Fengyi
    SCIENTIA GEOGRAPHICA SINICA. https://doi.org/10.13249/j.cnki.sgs.20220937
    Accepted: 2024-05-20
    With the intensification of climate change and the rapid development of the economy and society, the uneven distribution of water resources in time and space and the contradiction between supply and demand in the urban agglomeration in the Yellow River Basin have become increasingly prominent, exposing the problem of interactive stress between the ecological environment in the basin and urban development. High-quality development in the Yellow River Basin represents an advanced stage of sustainable development, and sustainable utilization of water resources in urban agglomerations creates more room for improvement in high-quality development. To actively respond to the Sustainable Development Goals proposed by the United Nations, this study takes five national urban agglomerations in the Yellow River Basin as the research object and uses the water footprint and related evaluation indices to construct an evaluation framework of the water resource utilization level oriented to Sustainable Development Goal 6. This framework is used to evaluate the water resource utilization and protection level of urban agglomerations in the Yellow River Basin. The dynamic change characteristics of the water footprint of the Yellow River Basin urban agglomeration from 2010 to 2019 are described based on the total water footprint and the proportion of each account, per capita water footprint, water footprint intensity, and water planet boundary. Global and local Moreland indices are used to describe the spatial evolution characteristics of the water footprint of the Yellow River urban agglomeration from 2010 to 2019. Based on an analysis of the spatial and temporal evolution characteristics of the water footprint of urban agglomerations in different sections of the Yellow River Basin, spatial econometric models of urban agglomerations in the whole basin, the upper and middle reaches and the lower reaches are established. This paper discusses the similarities and differences in the driving effects of socioeconomic factors on the water footprint in different sections of the basin; these factors include gross regional product, permanent resident population at the end of the year, population density, total investment in fixed assets, foreign direct investment, built-up area, total import value and total export value. The results show that the total water footprint and mean value of urban agglomeration in the Yellow River Basin increase from the upper reaches to the lower reaches in a cascade distribution pattern, with significant regional differences. The water footprint and its related indicators show an overall downward trend, but there is still a certain gap in achieving Sustainable Development Goal 6. The water footprint of urban agglomerations in the upper and middle reaches and the lower reaches presents a polarization state of “low-low” agglomeration and “high-high” agglomeration, respectively, and transitions to “lowlow” agglomeration on the whole. The driving factors in different urban agglomerations have significant differences and spatial interaction effects. Therefore, countermeasures and suggestions are proposed to strengthen the radiative driving role of central cities, improve the resilience of urban water resource ecosystems, and implement differentiated water resource system management according to the comparative advantages of different urban clusters. These suggestions provide a scientific basis for strengthening watershed system governance.
  • Chen Tao, Gao Ge, Du Xiaohui, Chen Hua
    SCIENTIA GEOGRAPHICA SINICA. https://doi.org/10.13249/j.cnki.sgs.20220844
    Accepted: 2024-05-20
    Snow cover changes in the middle (2035—2064) and end (2070—2099) of 21st century are investigated over the Qinghai-Tibet Plateau based on the Historical data and ScenarioMIP data of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Compare with the reference period (1985—2014), the mean annual snow cover days and mean snow duration decrease during the middle and end of the 21st century over the Qinghai-Tibet Plateau, and the overall reduction are more pronounce with the increase of greenhouse gas emission concentration; the reduction in the late-21st century is more pronounced compare to the mid-21st century except for the low emission scenario; Spatially, the decrease in the southeast of the Qinghai-Tibet Plateau is more severe than that in the northwest. The snow onset date is delayed and the snow end date is advanced in the middle and late 21st century, the days of former is 1.5-2.0 times that of the latter; The more greenhouse gas emissions the more days the snow onset (end) date is delayed (advanced); The changes of the snow onset date and the snow end date are more pronounced in the late 21st century. Snowfall (temperature) is positively (negatively) correlated with the annual snow cover days; Generally,the relative contribution rate of snowfall to the annual snow cover days increases with the increase of greenhouse gas emission concentration; Spatially, snowfall (temperature) contributes more to the annual snow cover days in the southern and northern (east and west) parts of the Qinghai-Tibet Plateau. Decrease in snowfall from July to December is greater than from January to June, which may be the reason why the days of snow onset date is delayed more than the days of snow end date is advanced. There are great differences in the future snow cover changes over the Qinghai-Tibet Plateau under different scenarios, so controlling greenhouse gas emissions is crucial to slowing down the future snow cover reduction rate over Qinghai-Tibet Plateau.
  • Li Shuangshuang, He Jinping, Duan Keqin, Yan Junping
    SCIENTIA GEOGRAPHICA SINICA. https://doi.org/10.13249/j.cnki.sgs.20220438
    Accepted: 2024-05-20
    A striking warming trend has triggered extreme weather and events in the regions worldwide. Snowfall is an important indicator of climate change, changes in snowfall at different levels reflect the integrated response of global warming to the trends in key climate variables and extreme events, and significant geographical variation exists in the response pattern of snowfall in different levels across regions. Mountainous areas are highly sensitive to climate change. As an important geographical demarcation line between the north and south of China, the Qinling Mountains belongs to China’s snow-frequent belts, a sensitive area under climate change. Based on the daily data from the 72 meteorological stations, we analyzed the spatio-temporal variation of heavy snowfall and light snowfall during November-March of the following year in the south and north of Qinling Mountains from 1970 to 2018, using the method of the wet bulb temperature dynamic threshold and trend analysis. Moreover, we assessed the relationship between the snowfall and temperature in three sub-regions (Guanzhong Plain, south slope of Qinling Mountains and Hanjiang Valley). The results show that: 1) From 1970 to 2018, the number of rainless days increased, and the solid precipitation decreased obviously during November-March of the following year in the south and north of the Qinling Mountains. The number of snowfall days decreased from 8.5% to 5.2% in the previous period after 1998, and the proportion of sleet days decreased from 1.2% to 0.6%. 2) The response patterns of snowfall to climate change varies from snowfall in different levels. The snowfall amount and snowfall days of light snowfall decreased significantly, as well as intensity of light snowfall increased significantly. However, there was no clear linear increasing tendency in the snowfall amount, snowfall days and intensity of heavy snowfall, which indicates that the change of snowfall in the transition zone between north and south of China is dominated by the decrease of light snow. 3) In terms of the response to the temperature, the snowfall amount and days of light snowfall in the three sub-regions were significantly negatively correlated with temperature changes (P<0.05). Similar results were observed in the snowfall amount and days of heavy snowfall days in Guanzhong Plain and Hanjiang Valley. Meanwhile, three indexes of heavy snowfall were weakly correlated with the temperature of the south piedmont of the Qinling Mountains. Both Guanzhong Plain and Hanjiang Valley are the sensitive area the response of heavy snowfall to the temperature. The findings of this research can provide a theoretical basis for better understanding the winter climate response pattern in winter in the transitional zone between the north and south of China.
  • Wang Shengpeng, Teng Tangwei, Hu Senlin, Li Wei
    SCIENTIA GEOGRAPHICA SINICA. https://doi.org/10.13249/j.cnki.sgs.20230132
    Accepted: 2024-05-17
    In the era of digitalization, it is of great practical significance to explore the spatial network structure of digital economy and its driving factors for promoting the construction of “digital China”. The research applied the modified CRITIC evaluation method to measure the development level of digital economy of China from 2013 to 2020, and explored the evolution characteristics and causes of the spatial network structure of the digital economy by social network analysis. The results show that: 1) The overall level of digital economy development has shown a steady upward trend, and the spatial pattern is characterized by high in the east and low in the west. 2) During the study period, the spatial connection network of the provincial digital economy in China shows a complex situation of multi-threaded and dense networking. The network density is improved, and there is no hierarchical spatial structure as a whole. 3) The economically developed regions have a significant advantage in the spatial network structure, and the connections between the western and border regions and other regions needs to be improved; the condensed subgroup spatial distribution gradually forms an orderly agglomerated distribution. 4) The spatial correlation network of digital economy is affected by the joint action of multiple factors. The level of scientific and technological innovation, government support and geographical distance have always played a significant role, while the effects of economic development level, industrial structure level and urbanization level reflect the stage characteristics by strong first and weak later. The above factors together drive the optimization and restructuring of the provincial digital economy spatial network structure in China. Key words: digital economy; spatial network structure; social network analysis
  • Wang Wenqi, Liu Zhaode, Zhao Hu
    SCIENTIA GEOGRAPHICA SINICA. https://doi.org/10.13249/j.cnki.sgs.20221173
    Accepted: 2024-05-17
    Resource-based cities (RBCs) are a unique type of cities in China that have significantly contrib-uted to China’s national economy. However, the development of RBCs has encountered challenges, and their transformation and development require urgent attention due to the depletion of resources in RBCs and the need to comply with national ecological environment protection requirements in the 21st century. To explore the hotspots and frontiers of RBCs’ transformation and development, this paper analyzes 602 CSSCI journal papers published between 1999 and 2021. The research distribution was analyzed from 3 aspects: time, journal and author distribution, using software such as CiteSpace, VOSviewer, Data source, scientific knowledge graph. The paper explores the overall situation from evolution, hotspots and frontier. The conclusions are as follows: 1) The transformation and development of RBCs has gradually entered the Chinese government’s and academia’s vision since the 1980s, but substantive research only began in 2004. 2) From a time distribution perspect-ive, research on the transformation and development of RBCs in China can be roughly divided into 3 periods: slow exploration period (1980s—2003), high-speed growth period (2004—2013) and steady progress period (2014—); In terms of journal distribution, China Population, Resources and Environment, Economic Geography, Journal of Natural Resources, Geographical Research and Scientia Geographica Sinica are notable journals that signific-antly supported and led studies on RBCs. Regarding authorship, the study found that Yu Jianhui, Qiu Fangdao, Zhang Wenzhong and Jiao Huafu have had great influence and contribution in this field. 3) The study also identified 6 research frontier trends: green transformation and development of RBCs, population shrinkage of RBCs, carbon emissions of RBCs, spatial reconstruction of RBCs, innovation and transformation development of RBCs, comprehensive management of two special difficult areas of coal mining subsidence areas and inde-pendent industrial and mining areas. Finally, the study proposed future research directions in four aspects: high-quality development of RBCs, smart development of RBCs, carbon emission reduction of RBCs and spatial de-velopment of RBCs.
  • Sun Shuqi, Wang Bangjuan, Liu Chengliang, Liu Tong
    SCIENTIA GEOGRAPHICA SINICA. https://doi.org/10.13249/j.cnki.sgs.20230195
    Accepted: 2024-05-17
    The South China Sea Rim region is the anchor of China’s “21st Century Maritime Silk Road” initiative. It is of great significance to clarify the regional aviation connectivity and its development mechanism to promote economic and trade cooperation among countries. To this end, this paper attempts to describe the spatial evolution of the regional airline network around the South China Sea and reveal its self-organization development mechanism by constructing an aviation connectivity index, using the dominant flow and TERGM models. The results are as follows: First, the aviation hub hierarchy in the South China Sea Rim region maintains a basic stability and a certain degree of mutation. The capitals of ASEAN countries with Singapore, Kuala Lumpur, Jakarta, Bangkok, and Manila as the core, as well as Hong Kong, Guangzhou and other cities are the aviation hubs of the South China Sea Rim region. Second, the connection within the South China Sea Rim region is stable in the Indonesia-Malaysia-Thailand triangle, and it is spreading to the coastal cities of China and the Philippines in the east. The hub-and-spoke organization presents a multi-center evolution trend, following the law of regional agglomeration. Finally, the closed ternary structure has a positive effect on the air connection, the air connection of non-core cities expands rapidly, and the low-level nodes show a trend of active expansion in the process of network evolution. The urban economic development, city size, institution, culture and cooperation events all have positive impacts on air passenger transport enhancement, while geographical distance and the conflict events have a negative impact on air connections, and the overall network presents a gradual development trend.
  • Qi Qi, Ma Ruiguang, Yin Jiangbin, Wang Zixuan
    Accepted: 2023-12-19
    Return migration has become a notable socio-economic trend in the new stage of China's urbanization, and the analysis of its driving mechanism has received extensive academic attention. As a micro behavior, the return of migrants is not only affected by personal and family factors, but also closely related to external environment. However, existing studies have focused on the role of individual factors, but not enough research has been conducted on the relationship between regional contexts and return migration. We introduce a gradient boosting decision tree model in the field of machine learning, based on the data from the 2017 China Migrants Dynamic Survey, with the return intention as the response variable and the regional contexts—Both in the place of origin and destination—As well as migrants' personal and household factors as the explanatory variables, focusing on the non-linear influence of the regional contexts on the return migration intentions and the threshold effect. The results show that: 1) The total contribution of the local contexts of the place of place of the origin and destination to the intentions of the migrants to return is 44.1%, which is an important factor influencing the return intentions, and the contributions of the two places is roughly equal. Among these, medical and health resources and air pollution are extremely important in both places. In addition, economic growth in the place of origin is also important for the return intention of migrants, while the climatic condition in the place of destination is more important; 2) There are both non-linear and linear relationships between local contextual factors and migrants' intention to return. Among them, medical and health resources, basic education resources, air pollution have obvious non-linear effects on the return intention, while economic growth and temperature conditions have mainly linear effects; 3) The influence of individual factors on return intention is mainly nonlinear effect. There is an irregular U-shaped relationship between age, migration duration and return intention, and the non-linear influence of household income is more complex. There is an obvious threshold effect between household housing expenditure and return intention, and a negative correlation between migrant's education level and return intention. This study incorporates the local contexts of the place of origin and destination into the analytical framework for the mechanism of return migration, identifies the relative importance of the local context and individual characteristics of the two places on the return intention of the migrants, and reveals the specificity and complexity of internal return migration in China, which contributes to deepening the research on migration in the new era and provides scientific reference for policy makers.
  • Qiu Fangdao, Yin Pengxing, Tan Juntao, Chen Ran
    Accepted: 2023-11-01
    With the increase of uncertainty in the development environment at home and abroad, coastal cities are more exposed to various risk disturbances than other regions, and the evolution process of economic resilience is more complicated, however, there is a lack of coupling analysis from multiple scales such as regions, industries, and enterprises. Therefore, scientifically revealing the evolution characteristics and influence mechanism of economic resilience of coastal cities is an important support for promoting the scientific development of coastal cities and consolidating the leading position in the opening up of eastern coastal areas. By constructing the economic resilience analysis framework of coastal cities, taking Lianyungang as a case, the paper analyzes the economic resilience characteristics and influence mechanism of coastal cities with the economic resilience measurement model and the Esteban-Marquillas extended model from 1996 to 2020. The results show that: 1) The macro-economic resilience of coastal cities showed a periodic change of weakening-strengtheningweakening, and the secondary industry dominated the development of Lianyungang's economic resilience. 2) The resilience of traditional path industry in coastal cities was weaker than that of emerging path industry, and the strength of industrial mix effect, competitive advantage effect and allocation effect had a has a dynamic and staged feature. The evolution of the economic resilience of coastal cities was determined by the development of emerging industries. Emerging industries were not necessarily high-tech industries, but adapted to local conditions. 3) The resilience of enterprises in coastal cities tended to weaken, and the resilience of enterprises in emerging industries was stronger than that in traditional industries. The new enterprises of new path industries and chemical industry of the traditional path showed path dependence on specific spatial locations such as ports and high-tech zones, which indicated port location had a positive impact on enterprise survival. Therefore, guiding the agglomeration of industries in ports and development zones (high-tech zones) was the key path to improving the economic resilience of coastal cities.
  • Zhang Pei, Wang Jiaoe, Ma Li
    Accepted: 2023-10-20
    Based on the panel data of 31 provinces (cities and districts) in China from 2013 to 2020, this paper measures the level of new infrastructure development and the degree of coordinated regional economic development in each province and then uses the coupling coordination model to measure the coupling coordination degree of the two and analyzes their spatial and temporal evolution patterns and influencing factors. The results show that: 1) The level of development in China's new infrastructure and regional economic coordination degree has been improving each year, with increasing coupling and coordination between the two. Despite starting from a lower level, the growth rate of new infrastructure has been significant since 2018, reaching 29.96% in 2020. Similarly, there has been a noticeable upward trend in the degree of regional economic coordination and the coupling between new infrastructure and regional economic coordination degree. 2) The coupling and coordination between new infrastructure and regional economic coordination degree exhibit spatial heterogeneity, with the eastern region surpassing the central and northeastern regions, while the western region lags behind. This discrepancy can be attributed to the relatively higher levels of new infrastructure development and regional economic coordination degree in the eastern provinces, as well as the smaller internal differences within the central and northeastern provinces. On the other hand, the western provinces exhibit greater disparities. 3) The level of new infrastructure development demonstrates negative spatial spillover effects among provincial regions, whereas the degree of regional economic coordination and the coupling between new infrastructure and regional economic coordination degree exhibit positive spatial spillover effects among provincial regions. 4) The factors that primarily influence the coupling and coordination between new infrastructure and regional economic coordination degree are related to industrial structure and urbanization processes. Conversely, factors such as government management and population density have less discernible effects on this coupling and coordination. The article investigates the evolutionary characteristics and influencing factors of the level of new infrastructure development, the degree of coordinated regional economic development, and the degree of coupling and coordination of the two in China, and expects to provide a reference for decision-making on the benign interaction between new infrastructure and coordinated regional economic development in China.