Urban–rural integration (URI) is essential to achieving sustainable development. However, the rural areas surrounding large cities typically have a large scale and significant differences in development conditions. It is necessary to formulate rural development policies by category to better promote the integrated development between urban and rural areas, stimulate rural vitality, and create more significant opportunities for rural development. This study constructs an evaluation system for rural areas under URI, using the Xi’an metropolitan area as a case study. A clustering algorithm enhanced by the random forest (RF)–principal component analysis (PCA)–partitioning around medoids (PAM) method is applied to evaluate rural integration comprehensively. Key findings in this study include the following: (i) URI should be decoupled from administrative divisions, considering the complex impacts of multi-town functional spillover; (ii) ecological environment, economic development, public service allocation, and construction land supply are key factors influencing URI; (iii) the overall URI index in the Xi’an metropolitan area presents a “high in the center, low in the east and west” pattern. The rural areas with high URI index are around Xi’an and Xianyang, while other cities show insufficient communication with neighboring villages; (iv) rural areas can be categorized into four types of integration: ecological, ecological–economic, ecological–social–spatial, and ecological–economic–social–spatial, which exhibit an outward expansion of layers and extension along the east–west axis in the spatial structure of integration. Finally, differential development policies and suggestions for promoting urban–rural integration are put forward because of the different types of rural villages. This paper provides a framework for formulating rural development policies, significantly deepening urban–rural integration.

The occurrence and spread of infectious diseases pose considerable challenges to public health. While the relationship between the built environment and the spread of infectious diseases is well-documented, there is a dearth of urban planning tools specifically designed for conducting Health Impact Assessments (HIAs) targeted at infectious diseases. To bridge this gap, this paper develops a comprehensive framework of an HIA for Urban Planning and Epidemic (HIA4UPE), formulated by considering the progression of public health incidents and the distinct transmission patterns of infectious diseases. This framework is designed to provide a comprehensive assessment by including a health risk-overlay assessment, health resource-quality assessment, health resource-equality assessment, and health outcome-impact prediction, enabling a multidimensional evaluation of the potential impacts of current environmental conditions or planning proposals on the incidence of infectious diseases. Furthermore, this paper advances the application of spatial analysis and computation, comprehensive assessment methodologies, and predictive analytics to conduct specific assessments. The theoretical framework and analytical tools presented in this paper contribute to the academic discourse and offer practical utility in urban planning and policymaking on epidemic prevention and control.

At present, the practice of national spatial planning in China is progressing actively. Provincial and autonomous regional spatial plans (public notice drafts), which are pivotal policy instruments for managing the development, utilization, and conservation of national territorial spaces, have been formulated and passed approval procedures across 27 provinces and autonomous regions. Systematically analyzing spatial planning documents can help clarify provincial objectives, visions, and policy details, identify planning innovations and trends, and uncover potential oversights, providing a scientific basis for developing lower-level spatial plans, special plans, and policy frameworks. This study employed the Nvivo qualitative analysis software for policy text coding and executed text mining and spatial distribution characterization of pivotal planning elements. The research constructed a three-tier coding system including 4 parent codes, 14 first-level codes and 33 second-level codes. The result shows: (i) Provincial territorial spatial planning primarily focuses on macro-programmatic content, with attention to spatial strategies, positioning and objectives, and major regional infrastructure, while some provinces emphasize inter-provincial collaboration under the guidance of regional strategic development. (ii) There is a high degree of similarity in the specific content of concern across provinces, with a pervasive emphasis on sustainable development models, overall developmental goals and strategies, ecological conservation, agriculture, infrastructure and its guarantees. (iii) The content of provincial territorial spatial plans in certain regions exhibits a marked interrelation, indicative of a pronounced regional spatial correlation. Overall, this study offers new perspectives for understanding provincial policy intentions and characteristics, establishing a link between planning content and Sustainable Development Goals, and furnishing valuable insights and references for the refinement of future planning policies.

The impact of the built environment on urban vitality is multifaceted, yet a holistic understanding that simultaneously considers its scale dependence, spatial heterogeneity, and interactive mechanisms remains limited. To unravel these multi-scalar mechanisms, this study develops an integrated analytical framework. Taking Xi’an, China, as a case study, we first construct a multidimensional built environment indicator system grounded in Jane Jacobs’ theory of vitality. Empirically, we employ the Optimal Parameters-based GeoDetector (OPGD) to objectively identify the optimal spatial scale and detect non-linear and interaction effects. Meanwhile, the Multiscale Geographically Weighted Regression (MGWR) model is used to delineate spatial heterogeneity. Our findings systematically unravel the complex mechanisms: (1) The optimal analysis scale is identified as a 2 km grid; (2) All elements significantly influence vitality, but through distinct linear or non-linear pathways; (3) The effects of attraction density, road network structure, and bus stop density exhibit significant spatial heterogeneity; and (4) Third place density and population density act as key catalysts, non-linearly enhancing the effects of other elements. This research presents a synthesized perspective and nuanced evidence for precision urban regeneration, demonstrating the necessity of integrating scale, heterogeneity, and interaction to understand the drivers of urban vitality.

Composite indicators support policy comparison by compressing multidimensional information, but different indicator configurations can appear similar in aggregate. This study develops and applies a contribution-structure audit to China’s 86 county-level urban-rural integration pilot units. Using 2019–2023 multi-source spatial data, we apply principal component analysis (PCA) to indicators of economic-activity change, built-up expansion, public-service facility nodes, and transport-service nodes. Along the dominant axis, built-up and economic-activity changes oppose facility- and transport-node changes, enabling different indicator configurations to occupy nearby composite positions through compensation. Across all 3655 pairs among the 86 units, composite-position and contribution-structure distances constructed from the same standardized indicators and PCA weights are positively associated (Pearson $r=0.543$), reflecting their internal alignment. The baseline Q25/Q75 same-zone strict screen identifies 11 pairs in which close composite positions coexist with divergent contribution structures. Such pairs also appear in alternative checks that vary screening thresholds, regional composition, POI variables, and distance definitions. Their counts and identities change across specifications. This finding supports inspecting contribution structures when selecting apparently similar cases. For comparative learning among pilot units, the audit identifies cases requiring contextual evidence on institutions, implementation, and outcomes before their experiences are assessed for replication.