Serving as the direct interface for interaction between the waterfront and urban dwellers, the street space environment significantly influences people’s living experiences and social interactions. Despite progress in the renovation and development of waterfront streets, these areas remain underutilized and lack the vitality expected of such locations. Using the Hunhe Waterfront Streets in Shenyang as a case study, this research employed Baidu heatmap data and the Semantic Differential method to assess both the behavioral and perceived vitality of the area. Subsequently, the study explored the main factors influencing behavioral vitality in waterfront streets from three aspects: street accessibility, facility configuration and environmental construction. It also examined the key environmental features of waterfront streets that affect perceived vitality under visual perception. Additionally, the study performed a coupling analysis to explore the relationship between behavioral and perceived vitality within the waterfront streets. The results indicated that the density of infrastructure and commercial facilities, as well as the continuity of pedestrian paths, were key environmental features influencing behavioral vitality. The degree of motorization, green visual index and building enclosure ratio were the main environmental features affecting perceived vitality. Moreover, the vitality coordination of the Hunhe Waterfront Streets was relatively poor, leaving considerable room for improvement. By integrating behavior and their perceptions of the environment, the study explored the coordination of waterfront street vitality and its intrinsic connection with street environmental features. This work aids in developing more effective and user-centric design strategies for waterfront streets, offering practical guidance for their revitalization and redevelopment.

Currently, coordinated development in terms of perceived urban quality and function has become a key problem. However, there is an imbalance between the street environment and urban amenities. It is necessary to explore the current status and propose optimization strategies to promote the coordinated development of urban spaces. Dalian, China, was selected as the study area. Based on space syntax, high-accessibility and low-accessibility streets were selected as study sites. An evaluation system was constructed as part of the study. It included the urban function and perceived street quality. Data on the density and diversity of urban amenities were obtained by establishing points of interest (POIs). The subjective and psychological perception of quality was calculated using street view images (SVIs). Then, a coupling analysis based on the urban function and perceived quality was conducted as part of the study. The results indicated that there were differences in the development levels of urban amenities and in regard to spatial quality in Dalian. Specifically, high-accessibility streets and urban amenities were mainly concentrated in the central urban area. The perceived quality of high-accessibility streets was higher than low-accessibility streets. The coupling analysis found that high-accessibility and low-accessibility streets had the highest proportions of advantage streets and opportunity streets. The urban amenities and subjective perception of quality were the highest in regard to advantage streets. The perception of beauty was the lowest in regard to maintenance streets. The psychological perception was the highest among improvement streets. Openness was the highest in regard to opportunity streets. As a result of the coupling analysis, this study not only helps to optimize the layout of urban amenities and improve the quality of the street environment, but also provides practical guidance for future urban design. Additionally, the results of this study will help to promote the coordinated development of street environments and urban amenities and enhance the overall livability and spatial quality of the urban environment.

With the advancement of high-quality urban development, the assessment of urban visual quality (VQ) based on public perception is of great significance for enhancing the liveability of coastal cities. However, there is still a lack of systematic quantitative analysis regarding the complex nonlinear relationship between visual quality and the built environment. This study takes Shinan District, Qingdao, as a case study to construct a data-driven visual quality assessment framework. By collecting a large-scale dataset of street-view images and using semantic segmentation techniques. This study extracts five physical features—walkability, openness, greenness, enclosure, and the visual building density—to represent key streetscape dimensions related to spatial openness, naturalness, walking experience, and building interface intensity. It shows that the visual quality of Shinan District presents obvious spatial heterogeneity. Areas with relatively high visual quality are mainly concentrated in newly developed urban districts and coastal areas, while areas with lower visual quality are mostly distributed in old urban districts and inland areas. Newly developed urban areas have higher sky openness and continuous green interfaces, thereby bringing a good visual experience. The lower visual quality of old urban districts and some inland streets is more related to the superposition of factors such as a high proportion of visible buildings, excessive spatial enclosure, disordered street interfaces, and insufficient greenness. The further finds that the nonlinear relationship between sky openness and enclosure indicates that street visual quality does not depend on simply increasing open space, but on the coordination between visual permeability and interface order: excessive openness weakens the sense of street boundary, while excessive enclosure strengthens the sense of oppression, both of which reduce the quality of visual perception. Greenness, the building visibility index, and walkability also show obvious model-estimated turning points: after greenness exceeds approximately 0.14, continuous green interfaces begin to improve visual quality more stably; the building visibility index within the range of approximately 0–0.28 helps form street structure and visual order, but when it exceeds approximately 0.28, it may shift toward visual pressure; after walkability exceeds approximately 0.2, its effect on visual quality changes from negative to positive. This study not only quantifies the spatial variation in visual quality but, more importantly, reveals the underlying mechanisms of key environmental factors, providing a scientific basis for refined urban design interventions and the optimization of coastal spaces.