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Streets are important spaces for transportation and life. It is important to clarify the economic effects of street quality on the real estate industry to create high-quality street spaces and meet the environmental needs of residents. Based on factors influencing traditional housing prices, such as street quality, this study used the random forest model and an accumulated local effects plot to explore the nonlinear relationship between street quality and housing prices, with its threshold effect in Guangzhou. The results show that the random forest model's fitting accuracy is 0.145 times higher than that of traditional linear methods and that the random forest model effectively captures the nonlinear relationship and threshold effect between street quality characteristics and housing prices. Commercial location, global betweenness, and the years of community construction significantly impact housing prices. The total contribution of green vision rate, sky openness, and enclosure to housing prices reached 5.68%, and residents' preferences for a comfortable environment drew attention. When distance increased, the negative influence of the commercial and economic location on housing prices gradually decreased. When global betweenness is less than 1,715, it has an exponential positive correlation with housing prices. When local proximity exceeds 117, it has little impact on housing prices, revealing the alternative effects of transportation hubs at different levels. Positive externalities, such as convenient transportation and negative externalities, such as traffic congestion and environmental pollution, affect housing prices equally. Road construction should consider traffic efficiency and environmental livability. When the degree of road motorization is less than 23% and more than 26%, the construction ratio of protective isolation facilities is more than 4.27%, and the night light brightness is higher than 0.0037 W/(m2·sr·μm), they have a lesser impact on housing prices. The over-construction of safety facilities reduces the economic benefits of street quality. Moreover, to ensure fair street usage, the green vision rate of the living environment should not be less than 15%. The spatial distribution trends of sky openness and enclosures are opposite, but both negatively impact housing prices. In urban development and construction, the development intensity should be reasonably controlled to avoid psychological depression caused by space cramping. For future street-stock renewal, it is necessary to accurately understand the current situation of street quality and the needs of residents, specifically improving street quality. Avoiding street quality creates property premiums and strives to ensure the fairness of residents' access to and use of street spaces. It guides real estate developers to participate in street construction. This study compensates for the limitations of traditional characteristic price models and the lack of explanatory properties in traditional linear methods, thereby providing a scientific basis for improving residents' living environments and building a livable city.

Transit-oriented development (TOD) is a crucial way to achieve compact, livable, and sustainable urban development. The integration of shared bikes and rail transit significantly expands the service scope of public transportation and promotes the implementation of TOD planning strategies. Based on TOD planning concepts, this paper identifies the transfer flow patterns of shared bikes. Considering the semantic functions of metro stations, an interpretable machine learning model is used to explore the tidal flow patterns of shared bikes and their nonlinear correlations with the built environment in the main urban area of Wuhan. The conclusions are as follows. (1) Based on the tidal balance index of shared bikes during morning and evening peak periods, two types of tidal flow patterns are identified in the main urban area of Wuhan, namely "convergence in the morning and divergence in the evening" and "divergence in the morning and convergence in the evening". The "convergence in the morning and divergence in the evening" tidal pattern mainly occurs in residential areas at a moderate distance from the urban center and employment areas on the edge of the Hankou central activity zone, while the "divergence in the morning and convergence in the evening" tidal pattern mainly occurs in employment-dense areas near the Second Ring Road. (2) Four types of semantic functional themes and two mixed functional clusters of metro stations are identified through POI semantic information modeling and hierarchical clustering. The semantic functional types of metro stations are strongly correlated with the flow patterns of shared bikes. (3) The nonlinear effects of built environment factors are significant. The moderate supporting living facilities and road density, and the large residential scale can effectively promote the occurrence of stable connection pattern of shared bikes with high riding flow. This study can provide a basis for alleviating the tidal flow problem of shared bikes from the aspects of optimizing shared bikes scheduling and adjusting the urban built environment. [ABSTRACT FROM AUTHOR]