The built environment, as perceived and felt by human beings, can shape and affect residential satisfaction. From the perspective of municipal administrators, understanding the building environment and its relationship with people’s residential satisfaction is crucial to improving people’s living environment. This study examines the correlation between built environment elements and residential satisfaction using the consideration of spatial heterogeneity of such a correlation. Machine vision technology is introduced to quantify the design dimension of the built environment. The method of multiscale geographically weighted regression is used to evaluate the relationship between built environment and residential satisfaction and to analyze the spatial heterogeneity in the influencing effects. This empirical study draws on 399 collected samples from the residents of Zhengzhou, China. The results show that elements of the built environment, including street space design features, have a significant effect on people’s residential satisfaction in Zhengzhou City. The factors of functional diversity and distance to the city center show spatial heterogeneity in influencing effects on residential satisfaction. The results of this study could help municipal managers to improve people’s residential satisfaction in Zhengzhou City through the development of urban renewal policies.

Given the accelerating speed and scale of urbanization in China, a rational formulation of a composite development plan to increase the vitality and value of various areas is required. Thus, this study proposes a method for evaluating the spatial relationship among facilities around bus terminals by combining urban points-of-interest data and street view image data from two perspectives: the current level of development and potential of the terminals, and an evaluation of the surrounding pedestrian environment. This is in response to the lack of quantitative descriptions of the composite development of existing bus terminals. The validity and applicability of the methods are verified using the samples of five planned composite development bus terminals in the city of Zhengzhou. These results offer strategic suggestions for the composite development of the Zhengzhou bus terminals. This study demonstrates innovation in integrating geographic information data and street view image data. It reflects the spatial characteristics of the built environment using geographic information data and the visual characteristics of the built environment using street view images.

Given the lack of quantitative descriptions on the interaction between psychological factors and the built environment in existing urban bus travel behavior, this study examines the simultaneous influences of the objective-built environment and subjective psychological factors on bus travel intentions. An empirical study on the influence path of bus travel intention was conducted using structural equation modeling. Then, personal attribute factors were introduced, and a linear regression model was used to explore the influence of behavioral intentions. This study uses 410 investigated samples from the residents in Zhengzhou, China. The findings proved that psychological factors play mediating roles between the travel environment and its impact on travel behaviors and confirms the validity of the description of the measurement variable with respect to the bus travel intentions proposed in the study. We also found that the retirement factor among the personal attribute factors could significantly affect bus travel intentions, which means that the retired group prefers to use buses for traveling. This study shows innovations in catching the intermediary effect of psychological factors between the built environment and travel behavior while also quantifying the effects of both subjective and objective factors when choosing bus travel.

As an important component of bike-sharing (BS) users, the travel behavior of college students and office workers is important to the promotion of BS within Chinese cities. To explore the influencing factors for the behavioral intentions of BS, this paper makes a different analysis between the two groups. Based on the theory of planned behavior, and using environmental awareness as an extended variable, a BS travel intention model was developed. A total of 676 valid questionnaires were collected and analyzed from college students and office workers in Zhengzhou. The results indicate that attitude, subjective norms, perceived behavior control, and environmental awareness have a positive impact on the behavioral intentions of BS. However, the influence degree of each variable is different between the two groups. Perceived behavior control, including travel time, travel cost, and cycling difficulty, has the greatest impact on BS behavioral intention for college students. Meanwhile, subjective norms, including policy and media publicity, has the most significant impact on BS behavioral intention for office workers. The impact of environmental awareness on college students’ use of BS is higher than that of office workers. We also found that undergraduates use BS more frequently than postgraduates. The findings provide the clear influence factors on behavioral intentions of BS between college students and office workers, that can help policy optimization in terms of bike-sharing systems, giving some suggestion for an approach devoted to deepen the individual-context interactions

People’s perceptions and understanding of the built environment can shape and regulate travel intention and behavior. From the perspective of urban design, improving the built urban environment is an important way to encourage green travel. This study determined the impact path from the built environment to subway travel behavior, considering the intermediate effect of psychological factors. The impact path could provide feedback for optimizing the built environment, thereby improving the ratio of subway travel. In this study, the impact path hypothesis of “objective environment—subjective psychological—travel behavior” was first proposed, taking travelers’ psychological perceptions as the intermediary variable. Second, questionnaires and geographic information were used to measure the objective environment and subjective psychological perceptions. Third, a structural equation model was constructed to verify the proposed path hypothesis. Finally, multiscale geographically weighted regression was used to analyze the influence of subjective and objective factors on travel behavior and its spatial differences. The empirical case sampled 405 residents of Zhengzhou, China. The results verified the proposed impact path hypothesis and revealed spatial heterogeneity in its impact on travel behavior. The research explains how travel behavior is generated and could support the optimization of the urban built environment.