While advancing urban digital transformation, smart city development exerts profound influences on the spatial configuration of cities. A nuanced understanding of its impacts on urban polycentric development is critical for formulating evidence-based urban spatial planning policies in the context of rapid digitalization. This study used a panel dataset of 269 prefecture-level cities in China covering the period 2003-2019 and employed multi-period spatial difference-in-differences (DID) models to systematically examine the direct effects and spillover impacts of national smart city pilot policies on urban polycentricity. The research further delved into the distance-decay thresholds of spillovers, city heterogeneity in policy responses, and the moderating roles of institutional factors in shaping these relationships. Key findings include: 1) Smart city construction had an inhibitory effect on the process of urban polycentric development. 2) Across three distinct spatial weight matrices—geographic proximity, economic similarity, and nested economic-geographic frameworks—smart city construction demonstrated negative spatial spillovers on neighboring cities' polycentric development. The geographic proximity matrix yields the most pronounced negative effects, indicating that geographic distance remains a key factor influencing resource flows between cities and the transmission of policy effects. 3) The spatial spillover effects of smart city construction exhibited characteristics of attenuation as geographic distance increased and spatial scale expanded, presenting a circular hierarchy of close-distance decay of pilot cities-provincial regions-urban agglomerations. The effects exhibited a trend of first strengthening and then weakening with increasing distance—indirect spillover effects were most pronounced in the 200-400 km distance range, reaching their peak at 400 km, and became insignificant beyond 600 km. This trend reflects the nonlinear transmission patterns of policy effects across different geographic distances and spatial scales. 4) Heterogeneity analysis revealed that, in terms of the division of economic zones, urban hierarchy, and dominant industry, the policy spillover effect was positively significant in cities in the western region, higher-level cities, and cities dominated by the tertiary industry. 5) Market integration levels and governmental governance efficiency played pivotal moderating roles. Lower market segmentation and higher governance capacity amplified the positive effects of smart city policies on polycentric development by facilitating resource flows and coordinated planning, while excessive administrative barriers weakened these impacts. The study underscored the need for spatially differentiated smart city development strategies that account for regional economic landscapes, urban hierarchies, and institutional contexts. Policymakers should adopt adaptive spatial planning approaches—such as promoting cross-city digital collaboration in urban agglomerations and enhancing governance coordination—to leverage smart city investments for optimizing urban internal structures and fostering balanced regional development in China's new-type urbanization process.

Since 2008, China's urban development model has undergone a financialized transformation, driven by a shift in the logic of land development from "commodification" to "assetization". Urban redevelopment processes epitomize such transformation. Existing research has primarily examined land financialization, focusing on land-collateralized borrowing, infrastructure construction, and the indebtedness of local governments, thereby elucidating the financing model of urban redevelopment. This study shifts the lens to the investment side, analyzing how mechanisms of commodification, assetization, and capitalization restructure property-led redevelopment and reconfigure the urban accumulation regime. Using Guangzhou City as a case study, the findings reveal that: 1) at the urban scale, redevelopment programs prioritize infrastructure investment, leveraging its capitalization effects to elevate the asset value of surrounding land and housing, thereby generating higher economic returns for local governments and developers; and 2) at the household scale, housing assetization reinforces middle-class families' property consciousness and investment motivations, with growing numbers of households engaging in property investment driven by optimism about urban development prospects. This asset-based urban accumulation regime, heavily reliant on real estate appreciation, fundamentally sustains the land-collateralized financing model and the land-driven fiscal regime. The article concludes by reflecting on the current housing market downturn and considers possible avenues for reframing the logic of assetization to guide new governance models of urban redevelopment.

In the context of urban renewal, it is of great value to understand the housing decision-making mechanism of residents in old urban communities to improve the suitability and effectiveness of old community regeneration. Based on the sampling data of Jiucheng District in the center of Chongqing Municipality in the 2023 Urban Physical Examination Social Survey of the Ministry of Housing and Urban-Rural Development, this study constructed a dual-model analysis framework of renovation intention and relocation intention, and used the random forest algorithm combined with explainable model to systematically explore the influencing factors and correlation effects of the two types of decision-making behaviors. The results indicate that residents in old urban communities showed a significant preference for in-situ improvement. Location is the primary factor that influenced housing decision making, renovation and relocation intentions formed completely different distribution patterns in urban space, and a key spatial threshold appeared at 10 km distance. In terms of housing characteristics, there was a positive correlation but with a decreasing margin between floors and relocation intentions, and a "U"-shaped relationship for relocation. The clarity of property rights strengthened the tendency to renovate and inhibited the relocation behavior; Housing quality was negatively correlated with both types of intentions. The length of residence had the opposite effect on the two. The social environment had a significant negative effect on the intention to renovate and the intention to relocate. In terms of individual characteristics, the middle-aged group rather than the elderly showed the strongest intention to renovate, and the elderly also had the most conservative tendency to relocate. Residents with higher income levels and education levels showed more positive attitudes in both renovation and relocation decisions, reflecting their decision-making flexibility. In addition, there was a significant substitution effect between renovation and relocation intentions. This study provides a theoretical support for targeted and differentiated urban renewal policies, and is helpful for realizing the urban renewal goal of "co-construction, co-governance, and sharing" of the people.

Research on the identification and evaluation of inefficient land use is the premise of revitalizing and reusing the stock land. Existing studies focused on the comprehensive evaluation of inefficient land use, but lack interactive analysis of a variety of inefficiency factors, and ignore the excavation of inefficient high potential parcels. In addition, existing inefficient land use identification models usually use linear methods such as entropy weight method, which do not consider the nonlinear relationships between the attribute characteristics and the degree of land use. Therefore, this study took land parcels as the spatial unit of research and proposed a dual dimensional interactive framework for identifying and evaluating inefficient land use. Specifically, BP neural network was used to identify the internal development intensity of land parcels, entropy weight method was used to evaluate the external locational conditions of land parcels, and the interaction between internal development intensity and external locational conditions was analyzed to identify low development intensity-favorable locational conditions land parcels with synergistic effects. An empirical research was conducted using Beijing as an example. The results show that the BP neural network model can better take into account the nonlinear relationships between the internal attribute characteristics and development intensity. Through the coupling analysis between inefficient land use and urban regeneration districts, we found that most relatively severe/severe low efficiency-superior/favorable locational conditions parcels are distributed in key urban renewal blocks, with a high degree of coincidence. In addition, there are also a few relatively severe/severe low inefficiency-superior/favorable locational conditions parcels outside the key blocks, mainly distributed in Yangfangdian and Qinghe Communities of Haidian District, Lugouqiao Community and Nanyuan Community of Fengtai District, and Jinsong Community and Shibalidian area of Chaoyang District. The research results can provide a reference for the fine-scale governance and dynamic improvement of urban renewal blocks.

In the context of urbanization transition from growth to stock retention, optimizing and enhancing land use functions to revitalize inefficient urban stock space is of significant theoretical and practical importance for urban ecological protection and livability improvement, high-quality sustainable development, and improving governance levels. However, current research on inefficient urban stock space mainly focuses on social, economic, and built environment dimensions, with few scholars addressing the issue of inefficient urban stock space from a functional perspective using detailed and quantitative research methods. Therefore, this study adopted a multifunctional land use perspective, integrating multi-source data such as statistics, surveys, remote sensing, and point-of-interest (POI), along with theories and methods from the systems theory, spatial governance theory, and GIS spatial analysis, to explain the formation mechanism of inefficient urban stock space. It also developed a precise identification method for urban inefficient stock space and governance optimization path, using Xi'an City as a case study for empirical research. The study found that: 1) The spatial efficiency of urban stock space of Xi'an showed a "high in the center-low at the periphery" distribution, gradually decreasing from the city center to the outer areas. 2) The production-living deficient function was the main obstructive function for one-third of the area in Xi'an City. 3) The dual-function improvement zone contained the largest number of towns, followed by the triple-function improvement zone, and the single-function improvement zone had the smallest number of towns. Enhancing and optimizing the structural functions at the overall urban level is the primary task to comprehensively improve the efficiency of inefficient urban stock space. Moving forward, Xi'an should adhere to the principles of planning guidance and regional optimization, focus on improving deficient functions, and optimize the entire inefficient urban space to promote the healthy development and protection of territorial space, thereby achieving the goal of high-quality development. This study provides theoretical, methodological, and empirical references for optimizing inefficient urban stock space in Xi'an and other megacities.

As an important instrument of high-density urban area micro-renewal, pocket parks significantly enhance green space accessibility, advance public welfare, and elevate residential environmental standards by repurposing underused urban spaces. During the strategic scaling phase of pocket parks, elucidating their spatial configuration mechanisms is essential for optimizing their site selection and spatial distribution. This study leveraged geospatial data from pocket parks in Shenyang City and integrated multi-source geographic datasets, employing a repeated random sampling-verification framework combined with interpretable machine learning algorithms to systematically decode the complex drivers of pocket park distribution through factor prioritization, nonlinear relationship analysis, and interaction effect quantification. The optimal algorithm modeling revealed that: 1) The repeated random sampling-verification model substantially mitigates subjectivity and stochastic bias in negative sample selection, thereby improving the reliability of machine learning outputs. 2) Compared to socioeconomic indicators such as GDP, spatial determinants including green space proximity and public transit accessibility exerted disproportionately stronger influences on distribution patterns, with housing costs demonstrating a slight negative marginal effect, land use diversity showing statistically negligible effects, and notable synergistic interactions emerging in park service overlap zones. 3) Threshold-dependent response dynamics (positive/negative/nonlinear) among key drivers establish quantitative guidelines for precision-oriented placement strategies. This research advances the theoretical foundations of pocket park planning while offering novel conceptual frameworks and practical implications for deciphering the spatial interplay between high-density urban configurations and micro-green infrastructure.

In the context of new mobility, spatial governance in rural tourism destinations faces complex challenges. Traditional governance models rely on administrative dominance and localized management, while the emergence of new mobility breaks the boundaries of physical space, promoting the cross-boundary integration of flow elements such as capital, people, information, and technology, thus forming dynamic social structures and power networks. This change makes traditional governance models ineffective in addressing the spatial governance needs of rural tourism destinations in the new mobility context, necessitating the exploration of adaptive governance strategies. Therefore, this study introduced the concept of "spatial good governance", and based on a clear understanding of the theoretical connotation of spatial good governance in rural tourism destinations under the context of new mobility, it constructed a multidimensional framework for spatial good governance around five key dimensions: goals, objects, subjects, scales, and methods. Based on this, the study further proposed directions for future research, emphasizing the importance of goal setting, object identification, subject coordination, scale transformation, and method transition. By transcending the binary opposition of mobility and locality, this study enriched the theoretical perspective on spatial governance in rural tourism destinations and provided some insights for the practical exploration of diverse governance models in rural tourism.

Globalization, climate change, population mobility, and technological transformation have brought multiple challenges to the transformation and upgrading of rural systems. Exploring the path and mechanism of the comprehensive revitalization of rural areas from the perspective of resilience has become the key to global sustainable development. International research has established the basic framework of rural resilience from the perspective of subject + space + system, which has become an enlightenment for researchers in China to explore the process of rural resilience from the perspectives of sociology, geography and management, and provides scientific references for finding adaptive transformation paths for rural areas in different regions of China. On this basis, this study deeply analyzed the relationship between the new quality productivity system and rural resilience, and used this framework to explore the paradigms that should be followed in future research on rural resilience in China. This research clarifies the path to enhance rural resilience and also provides a scientific basis for global rural development policies.

Accurately assessing the level of human development in cities is of critical importance for advancing people-centered urbanization and achieving the goal of common prosperity. This study extended the framework of the United Nations Human Development Index (HDI) by incorporating two additional dimensions-low-carbon development and social equity-to construct a Spatial Human Development Index (SHDI) that captures spatial dependencies. Using a Bayesian spatial factor model, the SHDI was estimated for 279 prefecture-level and above cities in China over the period 2010-2020, effectively addressing spatial endogeneity. Furthermore, the Theil index and its two-stage nested decomposition were employed to analyze the characteristics and sources of regional disparities. The results show that: 1) Although the SHDI shared a similar overall trend with the traditional HDI, it differed significantly in indicator weighting and city rankings, and demonstrated stronger sensitivity in distinguishing differences among cities with medium to low levels of development. 2) SHDI exhibited a phased pattern of spatial divergence, with regional disparities following a convergence-then-divergence trajectory, and intra-provincial differences emerging as the dominant source of imbalance. This study provides a methodological innovation for multidimensional, spatially-explicit measurement of urban human development and offers empirical tools and policy insights for promoting high-quality urban development and regional coordination.

Biomedical industrial parks are an important policy tool for the government to promote the high-quality development of the biomedical industry. Most existing studies on the layout of industrial parks focused on aspects such as global production networks at distance or resource allocation within local administrative boundaries, with insufficient attention to the impact of network externalities in regional integration. Borrowed size, as an important manifestation of network externalities, provides a new perspective to break through the limitations of existing research on industrial park layout that does not fully consider regional collaboration. Therefore, based on the theory of borrowed size for network externalities, this study selected biomedical industry function, medical financial services, biomedical talent supply, and medical facility services as core considerations for borrowed functions, and regional economic level and biomedical innovation environment as core considerations for borrowed performance, according to the two dimensions of borrowed function and borrowed performance. It constructed an analytical framework for the layout of biomedical industrial parks at the district (county) scale and empirically tested the framework within the Pearl River Delta urban agglomeration. First, this study divided biomedical enterprises into three types based on industry segmentation—pharmaceutical manufacturing, medical services, and medical devices. It further categorized biomedical industrial parks into four types based on the proportion of enterprise numbers: pharmaceutical manufacturing-led, medical services-led, medical devices-led, and comprehensive biomedical. Combining multi-source data, the weighted average travel time method and the standard deviation from the mean method were used to measure borrowed functions and test borrowed performance, respectively. Through linear fitting of enterprise numbers and borrowed size, the core factors of enterprise location choice were evaluated, thereby identifying the saturation state of enterprises in districts and counties. Finally, this study proposed layout optimization suggestions and policy recommendations for different types of biomedical industrial parks. The study found that: 1) The spatial distribution of biomedical industrial parks in the Pearl River Delta presented a core-periphery structure with Guangzhou and Shenzhen as the dual cores. 2) The local foundation and spatial distribution of borrowed size for various factors exhibited heterogeneity. The local industrial foundation was the primary driving force for attracting enterprises to settle in, while borrowed size served as a supplementary development impetus, evident in some economically developed core urban areas but not fully utilized in some non-core regions. 3) Based on the classification of industrial parks, layout optimization strategies and policy recommendations were proposed for the four types of biomedical industrial parks at four levels: priority recommendation, general recommendation, relatively not recommended, and not recommended. This study incorporated borrowed size into the consideration framework of industrial park layout, enabling a more comprehensive evaluation of the development potential of industrial parks. It provides optimization suggestions for the government's layout of biomedical industrial parks in the Pearl River Delta and offers methodological references for the layout of other high-tech industrial parks in China.

The development of today's new energy system has prompted resource-rich regions abundant in both traditional and new energy sources to prioritize technological innovation as the key to upgrading and transforming their regional energy industries, but the existing research lacks a comparison of the spatial and temporal change of technological innovation between traditional energy and emerging energy industries. In this study, taking western Jilin Province, which has developed both the traditional petroleum industry and emerging wind power industry, as an example, we analyzed the technological innovation output, agglomeration pattern, and spatial linkage characteristics of the two types of energy industries from the perspective of industrial chain division, and explored the spatial and temporal change paths of technological innovation and their differences. The study found that: 1) The technological innovation activities of the petroleum industry are concentrated in the upstream exploration and exploitation links, the innovation density is decreasing, and the spatial agglomeration shows a mono-core polarization at the crude oil producing areas. The proportion of technical cooperation shows an inverted "U" shape, and the center of gravity of cooperation alternates between intra- and interterritorial, with intraterritorial cooperation centering around the oil resource-intensive Ningjiang District, and interterritorial cooperation gradually expanding from the three eastern provinces to the south. 2) Technological innovation activities in the wind power industry break through a single industry chain link, innovation density continues to grow, and the agglomeration pattern evolves towards multiple cores in wind energy rich areas. Technological cooperation is dominated by interterritorial links and steadily enhanced, the interterritorial cooperation mainly involves Changchun City in Northeast China and the Beijing-Tianjin-Hebei region, the Yangtze River Delta, and the Chengdu-Chongqing area, and the intraterritorial links between Songyuan City and Baicheng City have always been competitive than cooperative. 3) The spatial and temporal change paths of technological innovation in the petroleum and wind power industries are subject to the joint action of multiple factors, and their performances are different. The petroleum industry tends to be "endogenously driven", while the wind power industry is "exogenously supported". Based on the research findings, this paper offers differentiated guidance recommendations for technological innovation in two types of industries in western Jilin Province, aiming to provide reference and insights for the green transformation of the energy sector in such resource-based regions.

The protection of traditional villages is a topic of common interest to all sectors of society today, and it has been highly valued by the communist party and the government of China. However, due to the late start of the protection of traditional Chinese villages, relevant theories in the context of Western culture are often used for reference. The current practice of traditional village protection is based on the theory of heritage protection and landscape genes, which fails to fully grasp the multi-dimensional characteristics of traditional villages, and leads to the emergence of contradictions and conflicts in the protection and utilization of traditional villages. On the other hand, the place theory as an assemblage can provide a new perspective for the theoretical and practical research of traditional village protection. Taking Chengkan Village in Huizhou District of Anhui Province as an example, this study used literature research and field investigation methods to show that traditional villages, as a multiple assembly of rural settlements, cultural heritage, and tourism resources, are generated by the interaction of heterogeneous elements such as material components, expression components, and territorial forms. In this process, the vertical connection of the place is as important as the horizontal connection, especially the existence of the geographical environment, location conditions, and history and culture of the village itself is still meaningful from the perspective of traditional village assembly. Our case analysis further showed that the protection of traditional villages is a protection of the dotted history of specific periods, focusing on the physical landscape and visual appearance, while relatively ignoring the reconstruction and inheritance of the "invisible landscape". This study effectively expanded the case study of the place assemblage theory in rural areas, and demonstrated the insightfulness of the theory for the analysis of the interaction mechanism of heterogeneous elements in different time and space of traditional villages, which is helpful for deepening the theoretical interpretation and mechanism analysis of traditional village protection, and highlights the relational, holistic, and dynamic nature of traditional village protection practices. The analysis of the case of Chengkan Village showed that the application of the place assemblage theory should be carried out with a relatively clear non-human subject, which is helpful for clarifying the process from the relevance of non-human subjects, and the process refers to when, where, and how the elements are added to the assemblage.

The sense of belonging to a place and its influencing factors are important topics in urban and social geography research. The sense of belonging to a place has spatial scale characteristics. Although existing studies have revealed differences across scales, but the comparison of belongingness at the community and city levels remains insufficient. For migrant populations, the sense of belonging at both the community and city levels represents a key psychological marker of social integration and is an indicator of their incorporation into the host city. Nevertheless, migrant populations face the problem of residence and relocation in big cities, which makes it difficult for them to establish a sense of psychological belonging to their residential communities and cities. Investigating the sense of belonging from the perspective of residential mobility offers valuable insights that can contribute to promoting social integration and achieving the goal of people-oriented urbanization. This study examined the impact of residential relocation on community and city belongingness among various household registration groups, drawing on a survey of suburban residents' travel and behavior in Shanghai. The study found that: 1) Residents generally rate their sense of belonging to the city higher than their immediate community. However, notably, both community and city belongingness are significantly lower among the migrant population than among local residents. 2) Housing ownership, residential location change, and the reason for relocation impacted the community and city belongingness and were significantly different. Continuous renting decreases city belongingness. Relocating from other regions correlates with high community belongingness, but this does not necessarily enhance city belongingness. Furthermore, relocation due to convenience is not necessarily conducive to community belongingness. 3) The effects of residential relocation on community and city belongingness vary by household registration groups. Local residents tended to exhibit a "positive accumulation" characteristic in residential relocations, where meeting their relocation needs leads to an increased sense of belonging. In contrast, the migrant population requires "compensatory" factors (such as social networks and low-cost housing) to gain a sense of belonging. It is more susceptible to negative impacts brought about by demolition and resettlement. 4) Community belongingness is more heavily influenced by the quality of the community environment, while city belongingness is more strongly affected by personal and family socioeconomic attributes.