As core public spaces in cities, urban commercial pedestrian streets are important destinations for local residents and foreign tourists, and confusion regarding the visual space of a commercial pedestrian street sends direct environmental warning signals to pedestrians, affecting their visiting decisions. In this paper, through an investigation consisting of the artificial field simulation of the visual perception of pedestrians, we collect the corresponding street images and extract visual elements using the full convolutional network. Semantic segmentation is performed to obtain the visual parameters of the street. According to the quantitative model, the visual elements are matched with geographic elements, and a geographic information database is established to evaluate the spatial visual quality of commercial pedestrian streets. (1) There is obvious spatial heterogeneity in the spatial visual quality of different streets in commercial pedestrian streets. (2) The building heights, street widths, as well as the street vegetation, facilities, and landscape vignettes are spatial elements that shape the spatial visual quality of commercial pedestrian streets. (3) The main distribution of commercial facilities and the distribution of active businesses have an important impact on the degree of crowd gathering in a street space and the visual spatial quality of a street. This paper provides comparable data collection methods and research methods for the visual spatial quality of commercial pedestrian streets. This paper can also provide valuable data for the design, planning, and sustainable renewal management and regulation of the visual perception of commercial pedestrian streets.

During the transition of culture-featured district planning from static conservation to innovation-driven models, existing research remains constrained by mechanistic paradigms, reducing districts to functional containers and neglecting human perceptual interactions and meaning-production mechanisms. This study explores and quantifies the generative mechanisms of spatial communicability and cultural dissemination efficacy within human-centered frameworks. Grounded in humanistic urbanism, we analyze Harbin Central Street as a case study integrating historical heritage with contemporary vitality, developing a tripartite communicability assessment framework comprising perceptual experience, infrastructure utility, and behavioral dynamics. Machine learning-based threshold analysis reveals that spatial encoding elements govern communicability through significant nonlinear mechanisms. The conclusion shows synergies between street view-quantified greenery visibility and pedestrian accessibility establish critical human-centered design thresholds. Spatial data analysis integrating physiologically sensed emotional experiences and topologically analyzed spatial morphology resolves metric fragmentation while examining spatial encoding’s impact on interaction efficacy. This research provides data-driven decision support for sustainable urban renewal and enhanced cultural dissemination, advancing heritage sustainability.

As urban–rural integration deepens, the growth of suburban integrated villages, as the key link between urban–rural factor flow and coordinated development, is affected by the asymmetric reciprocal symbiosis between urban and rural areas. Utilizing urban–rural integration and sustainable development theories, this study selected twenty-four suburban integrated villages in the Daoli District of Harbin as its research object. It concentrates on the township–village micro-symbiotic unit, formulates a two-dimensional evaluation framework of “village endogenous + township linkage,” and utilizes quantitative methodologies, including the coupling coordination degree model, the obstacle degree model, and sensitivity analysis, to identify the factors hindering the expansion of these villages and propose targeted strategies according to villages’ coordination levels. The results show that 79% of samples exhibit imbalanced coordination; although spatial constraints are the primary hindrances to village systemic coordination, balanced development of spatial, economic, social and ecological subsystems remains essential; the developmental constraints of the samples stem from weak village developmental foundations and insufficient township–village radiation linkages. This study enhances the township–village symbiosis micro-research framework and functions as a reference for the classification planning of suburban integrated villages and the sustainable amalgamation of urban and rural development.

Effective governance of informal commercial spaces is a common challenge faced by cities globally. To break through the superficial governance mindset of traditional spatial regulation, this study focuses on clarifying the spatial distribution characteristics and influencing factors of such spaces. By integrating the theory of “The right to the city” with the “7D” principles of New Urbanism, and focusing on the Jinxiang Street area in Harbin, a representative zone combining traditional industrial and modern residential communities, this study constructed a multidimensional indicator framework including population factors, functional diversity of facilities, accessibility of the built environment, spatial suitability, and intensity of community management, extracting 17 significant variables. Through spatial autocorrelation analysis (Moran’s I), multiscale geographically weighted regression (MGWR), and geographic detector analysis, the results show that informal commercial spaces exhibit clustered yet uneven characteristics between aging and upscale communities; the MGWR model reveals significant spatial heterogeneity in influencing factors; and geographic detector analysis shows that the interaction between public service facilities’ proximity to main roads and enhanced community management has the most significant explanatory power for heterogeneity (q = 0.85). These findings inform differentiated governance strategies and provide scientific support for sustainable governance of informal commercial spaces.

Resource-based cities in Northwest China face increasing ecological, geotechnical, and socio-economic challenges caused by long-term mining, including subsidence, slope instability, waste rock accumulation, soil erosion, industrial decline, and settlement deterioration. Post-mining land reuse is constrained by geological safety, foundation stability, slope safety, drainage capacity, erosion risk, and waste rock dump stability, yet existing restoration studies often separate engineering remediation from landscape reuse, industrial pathway selection, and long-term governance. Taking a mining area in City A, Gansu Province, as a case study, this paper develops a geotechnical constraint-based ecology–landscape–economy framework for post-mining land reuse and sustainable human settlement improvement. Unlike conventional reclamation approaches that mainly emphasize engineering remediation, vegetation recovery, or single-function land reuse, this study integrates geotechnical constraints, land-unit classification, pathway-specific compatibility assessment, and capital–space coupling into a planning-scale decision-support framework. Post-mining land was classified into five units, and their compatibility with three restoration plus industrial pathways was assessed using five indicators: geological safety, ecological sensitivity, land-use availability, landscape and cultural value, and industrial operation potential. The results indicate that backfilled mining voids and reclaimed platforms are most suitable for modern agriculture, tailings ponds and subsidence waterbodies for cultural tourism and wellness, and waste rock dump platforms and other stable, low-sensitivity open land for new energy development. A capital–space coupling mechanism is further proposed to link restoration, support, and development zones with government funds, corporate capital, social capital, green finance, and industrial income. This framework provides a planning-scale engineering-suitability screening tool for sustainable post-mining land transformation.

Promoting public transport use in leisure contexts is important for extending sustainable mobility policy beyond commuting. However, the role of car ownership in realized leisure-oriented bus use remains insufficiently understood, especially among residents who already have bus use experience. This study examines how car ownership and perceived public transport barriers are associated with leisure-oriented bus use intensity in Harbin, China. Based on 688 questionnaire responses from residents with leisure-oriented bus use experience, this study combines group-difference tests, threshold-based binary logit models, and XGBoost-SHAP exploratory analysis. The results show that, within this bus user sample, car owners and non-car owners do not differ significantly in realized leisure-oriented bus use intensity. However, car owners report significantly higher perceived spatial constraints, temporal constraints, bus use resistance, and overall perceived barriers than non-car owners. The binary logit models did not provide robust statistical evidence that car ownership-related heterogeneity differed across bus use intensity thresholds, although the interaction results should be interpreted as suggestive rather than conclusive. Because the XGBoost model showed limited discriminatory performance, the SHAP results are retained only as exploratory and descriptive information rather than confirmatory evidence. The findings suggest that sustainable leisure mobility policies should distinguish between car owners and non-car owners among existing bus users, while avoiding generalization to all urban residents or complete non users.