To design a more suitable scheme under different conditions so that subway stations can play their role better, this study investigated the construction elements of subway stations in residential areas. Metro stations in residential areas are generally located at the intersection of urban roads. As the “handover space” of the city, the construction principle should be based on people’s experience. As the core basis for traffic planning and future operation management, construction of subways in residential areas should take into consideration factors such as trip volume, distribution, and mode selection of residents, and be determined based on such mathematical models as the unit factor method, gravity model, and disaggregated analysis method. Station site selection is based on the point, line, and surface elements, and the importance of a station in the line network is judged by degree and betweenness centrality; the accessibility of the line network is determined by connectivity. In this study, the influencing factors of residential area subway station construction are divided into construction elements and site selection. Internal construction elements of stations include station entrances and exits, escalators, ticket machines, and transfer routes, and the conclusion of the mathematical model is used to select or give opinions about the internal construction elements of the subway. The point, line, and surface elements and the connection relationship between the subway and buses are used to determine the site selection of the subway. Furthermore, this paper discusses the three elements that affect the construction of the subway, comprehensively considers the functional requirements of the subway, and makes reasonable adjustments to each element. Finally, the requirements for the elements of the subway construction are determined.

Adapting to climate change and controlling carbon emissions have emerged as significant challenges faced by the international community. The high-quality pedestrian space system of TOD blocks, as an important means for carbon reduction and carbon sink increase in cities, showcases the effect of green intensification and low-carbon sustainable urban space development. In this study, by combining the research on low-carbon block creation and urban microclimate, focusing on the technical process of the three stages of pre-treatment, core calculation, and post-treatment, comprehensively considering the three elements of microclimate, namely wind, heat, and carbon, and their influencing parameters, and introducing a CFD simulation method for porous media, a CFD simulation technology framework for microclimate improvement in urban design is constructed. Through the spatial visualization of the software solution calculation results and the correlation and comparative analysis of the measured data, we quantitatively analyze the coupling relationship between the block morphology and the comprehensive environment of wind, heat, and carbon. The research results indicate that by rationally adjusting indicator elements such as the height-to-width ratio of streets and entrance forms, it is possible to effectively facilitate cooling, ventilation, and air circulation within blocks and dilute the CO₂ concentration. Finally, from the urban design element systems at the micro, meso, and macro levels, the adaptive planning strategies in the three dimensions of the spatial form, constituent elements, and planning guidelines of TOD blocks are summarized and refined, with the aim of achieving the low-carbon transformation of cities through the creation of a healthy microclimate environment.

Urban sprawl and excessive reliance on motorization have led to many urban problems. The balance of supply and demand in the real estate market, as well as price fluctuations, also face many challenges. Urban rail transit not only alleviates traffic congestion and air pollution, but also significantly reduces residents’ commuting time, broadens urban accessibility, and reshapes the decision-making basis for residents when choosing residential locations. This study takes the 1st, 2nd, 3rd, 4th, 8th, 11th, and 13th metro lines that have been opened in Qingdao City as examples. It selects 12,924 residential samples within a 2 km radius along the rail transit lines. By using GIS spatial analysis tools and the multi-scale geographically weighted regression (MGWR) model, it analyzes the spatial differentiation characteristics of housing prices along the rail transit lines and the reasons and mechanisms behind them. The empirical results show that housing prices decrease to varying degrees with the increase in the distance from the rail transit. For every additional 1 km from the rail transit station, the housing price increases by 0.246%. Through model comparison, it was found that MGWR has a better fitting degree than the traditional ordinary least squares method (OLS) and the previous geographically weighted regression model (GWR), and reveals the spatial heterogeneity of the influence of urban rail transit on housing prices. Different indicator elements have different effects on housing prices along these lines. The urban rail transit factor in the location characteristics has a positive impact on housing prices, and has a significant negative correlation in some areas. The significant influence range of the distance to the nearest metro station on housing prices is concentrated within a radius of 373 m, and the effect decays beyond this range. The total floors, building area, green coverage rate, property management fee, and the distance to hospitals and parks in the neighborhood and structural characteristics have spatial heterogeneity. Analyzing the areas affected by the urban rail transit factor, it was found that the double location superposition effect, the networked transportation system, and the agglomeration of urban functional axes are important reasons for the significant phenomena in some local areas. This research provides a scientific basis for optimizing the sustainable development of rail transit in Qingdao and formulating differentiated housing policies. Meanwhile, it expands the application of the MGWR model in sustainable urban spatial governance and has practical significance for other cities to achieve sustainable urban development.

Urban vitality serves as an important indicator for evaluating the level of urban quality development and sustainability. In response to a series of urban challenges arising from rapid urban expansion, enhancing urban quality and fostering urban vitality have become key objectives in contemporary urban planning and development. This study summarizes the spatial distribution patterns of urban vitality at the street and neighborhood levels in the central area of Qingdao, and analyzes their spatial characteristics. A 5D built environment indicator system is constructed, and the effects of the built environment on urban vitality are explored using the Optimal Parameter Geographic Detector (OPGD) and the Multi-Scale Geographically Weighted Regression (MGWR) model. The aim is to propose strategies for enhancing spatial vitality at the street and neighborhood scales in central Qingdao, thereby providing references for the optimal allocation of urban spatial elements in urban regeneration and promoting sustainable urban development. The findings indicate the following: (1) At both the subdistrict and block levels, urban vitality in Qingdao exhibits significant spatial clustering, characterized by a pattern of “weak east-west, strong central, multi-center, cluster-structured,” with vitality cores closely aligned with urban commercial districts; (2) The interaction between the three factors of functional density, commercial facilities accessibility and public facilities accessibility and other factors constitutes the primary determinant influencing urban vitality intensity at both scales; (3) Commercial facilities accessibility and cultural and leisure facilities accessibility and building height exert a positive influence on urban vitality, whereas the resident population density appears to have an inhibitory effect. Additionally, factors such as building height, functional mixing degree and public facilities accessibility contribute positively to enhancing urban vitality at the block scale. (4) Future spatial planning should leverage the spillover effects of high-vitality areas, optimize population distribution, strengthen functional diversity, increase the density of metro stations and promote the coordinated development of the economy and culture.

As indispensable elements of public space in the city, metro stations and parks have the dual characteristics of “node” and “place”. Based on the “node–place” theoretical framework, the spatial evaluation and detailed classification of Qingdao metro station is carried out by integrating ArcGIS technology and diversified data sources. On this basis, an innovative metro station spatial coupling evaluation model is constructed, which takes into account the station carrying capacity, park accessibility, land use degree, and other factors, while evaluating the economic and environmental benefits. This study deeply explores the complex coupling relationship between the surrounding metro stations and park space in Qingdao. According to the results of the evaluation model, corresponding strategies for different types of station space are proposed. By taking measures, such as focusing on fine development strategies, stimulating the vitality of stations and implementing guided renewal, and enhancing the mutual suitability of rail transit and surrounding park space, the great potential of combining green ecology with urban space optimization is demonstrated.

As an important indicator of the level of urban economic development and the quality of the residents’ lives, housing prices are affected by various factors, such as the spatial distribution of the housing market, the housing characteristics of neighborhoods, and the location conditions. This paper summarizes the spatial distribution of housing prices in Qingdao using GIS, analyzing spatial distribution characteristics, and combines these with the Geographically Weighted Regression (GWR) model to explore the influence of various factors, such as community attributes, location, transportation, and peripheral facilities on residential prices. The results show that from 2003 to 2023, residential housing prices in Qingdao exhibited a significant, continuous upward trend, with rapid growth in the early period and more stable growth in the later period; the spatial structure of residential prices evolved from a “single core” in Shinan District to a “double core + fan” structure involving both Shinan and Laoshan Districts, eventually forming a “double core + fan + mosaic” spatial layout; the green environment, congestion, leisure facilities, service management, and other community factors not only reflect the economic strengths and lifestyles of the residents, but also serve as key drivers of residential price differentiation.