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The issues of housing and traffic in China's mega cities have become increasingly pressing problems, particularly for middle/low-income tenant workers. These tenants are from less advantaged socioeconomic backgrounds, which has resulted in a significant geographical separation between their workplace and their residence. Although a large number of studies have confirmed that built environment factors have a solid impact on residents' commuting distance, few studies have investigated the mechanism underlying the nonlinear influence on middle/low-income tenants. This paper aims to provide an in-depth analysis of the key factors and nonlinear influencing mechanism of the built environment on middle/low-income tenant workers' commuting distance by establishing a gradient-boosting decision tree model, using Beijing as an empirical case. The paper reveals three primary findings: (1) An important nonlinear relationship between the surrounding built environment and peoples' jobs–housing spatial proximity can be observed for those middle/low-income tenant workers who use slow and public modes of commuting. Specifically, the density of public transport stations, road networks, and workplaces, and the land use mix play a dominant role. (2) A limited effect of built environment factors can be found for the same group of tenant workers who choose cars as their mode of commuting. (3) The differences in self-selected commuting modes have a significant mediating effect on the relationship between the built environment and jobs–housing situation among middle/low-income tenant workers. Given this, effective policy guidance for residents' travel modes is necessary to optimize the built environment indicators to achieve the best effect. In addition, we should consider giving priority to the matching indicators such as land use mix and resident population density. Another possibility is to strengthen the connection to the public transport stations, which in turn can optimize the walkability in residential environments. [ABSTRACT FROM AUTHOR]

The last mile between metro stations and commuters' homes or workplaces has become one of key topics in relation to metro ridership in megacities where more than 10 million people live. Although the public bicycle is widely believed to be one of new ways to solve the last-mile problem, the determinants of the use of public bicycles by commuters as a feeder mode have been scarcely discussed in the literature. This paper aims to contribute to this topic by using Beijing as a case study. Based on a travel survey among public bike users in Beijing, this study applied the binary logit model and cluster analysis to explore the determinants of public bike use around metro stations. The paper focused on three independent variables: route environment, socioeconomic factors, and travel distance. The results showed that middle-aged and medium-income commuters are more likely to use public bicycles as a feeder mode for metro transport. The built environment had significant effects on public bike use. Most of the cyclists preferred cycling routes with high directness, while high-income and high-education cyclists viewed comfort and safety of the trip as priority factors. Most trips were within 2 km, and a longer travel distance was significantly related to a higher possibility of public bicycle use. The findings and conclusions can enhance our existing understanding of public bike use as a feeder mode to solve the last mile problem and provide new evidence for policymaking on promoting public bikes in megacities. [ABSTRACT FROM AUTHOR]

Concerns over traffic congestion and environmental pollution have prompted more studies into the impacts of built environment on commuters' mode choice behavior. This paper aims to make a comprehensive analysis of commuters' mode choice behavior with the 5th Household Travel Survey in Beijing. A mixed nested logit model was employed to jointly explore the impacts of mode attributes and built environment variables on commuters' mode choice. The results show that the proposed mixed nested logit model outperforms the contrastive models, i.e., standard multinomial logit model and nested logit model. Estimated results indicate that non-motorized mode commuters pay more attention to OD distance. Land-use mix and density have significant influence on reducing car preference, and only show significant effect in working zone. Furthermore, public modes including bus and subway are regarded as one group that the convenient of either one of them changes will influence commuters' preference on the whole public transportation system. [ABSTRACT FROM AUTHOR]

This paper investigates the life experiences of creative expats and the associated impact of, and on, the built environment of their host localities. Grounded on participants' testimonies, we develop the concept of transient mentality as a potential mediating factor in-between such reciprocal relations. Employing an interview and survey-based research approach and drawing on grounded theory for data collection and analysis in Beijing, China, we found that the prevalence of a transient mentality among creative expats is influenced by the nature of their occupations, the fluidity of their social relationships, and the rapid transformations in the built environment. This transient mentality, in turn, affects the production of the cityscape through the consumption preferences of these expats. We argue that understanding such a transient mentality is crucial for urban planning and cultural policy, particularly in (emerging) global cities that work to brand themselves as international creative hubs. [ABSTRACT FROM AUTHOR]

In recent years, the development of China's megacities has entered the stage of stock renewal. Research and practice concerning old city renewal in cities with a long history, represented by Beijing, has also become a hot spot for researchers and designers in the fields of urban planning, architecture and landscape architecture. As one of the main spatial components of the old city, Beijing's traditional quadrangles are closely related to the spatial perception and emotional experience of citizens and tourists due to their near-human scale characteristics. However, current research focuses more on the evaluation of the historical value of the quadrangles in the early stage of renovation and the specific design and construction methods in the process of renovation, and few studies pay attention to the characteristics of the built environment that promote the emotional experience of users after renovation is completed. Under these circumstances, the study focuses on the emotional attachment between people and the spatial composition and built environment characteristics of the renovated traditional Beijing quadrangles; the avant garde small-scale quadrangle renovation type, which has a wider coverage, more types of user, and pays more attention to people's emotional experience in the renovated space, was selected as the research object. Four typical quadrangle cases were selected for in-depth discussion. Based on the theory of emotional attachment from a multidisciplinary perspective, this study constructed a series of scales that can measure the degree and dimension of emotional attachment between people and the built environment, coupled with local observation and interviews, to obtain multi-dimensional data reflecting attachment, and used SPSS to conduct correlation analysis and exploratory factor analysis to quantitatively explore the effects of different built environment characteristics on attachment. The results show that: (1) As for the material characteristics, the organic integration of traditional and modern materials, structures and colors can effectively enhance people's positive emotional experience and promote the establishment of emotional attachment. The combination of these characteristics and the process of people's three-dimensional spatial experience can further enhance the degree of attachment. In addition, the consistency of materials and technologies, the organic integration of the old and the new, and the carrying capacity of the renovation method for traditional history and culture are the basis for promoting this kind of emotional attachment, which needs to be further explored and considered. (2) As for the non-material characteristics, the diverse, variable, recognizable, unique, and digital spatial function settings that respond to changes in people's need and current developments can significantly promote the establishment of emotional attachment between people and the environment. This further emphasizes the importance of positioning the space in the early stage of the renovation and the operation of the space in the later stage. (3) The results further support the validity and rationality of the series of scales constructed in this study in quantitatively measuring the attachment characteristics between people and the built environment. As a result, the study provides a reference for emotion-oriented design means, research logic and quantitative evaluation methods in the practice and research of urban renovation and renewal in the future. [ABSTRACT FROM AUTHOR]

There is a consensus toward quantitative environmental design in the information age, but the content and specific practices of its quantification have yet to be systematically studied. To enhance residents' subjective well-being through environmental design, this study includes 847 valid questionnaires across four types of communities and identifies different types of resident groups using correspondence analysis. Then, this study compares the differences in the built environment and subjective well-being using one-way ANOVA and analyzes their impact via regression analysis. The results indicate that residents in old communities have the highest subjective well-being (3.93/5) and built environment assessments, and residents in policy housing communities have the lowest subjective well-being (3.37/5) and built environment assessments. A resident's subjective well-being is more influenced by two types of built environment factors: architecture and landscape and the human–land relationship. Age, education level, public place usage, and the community's overall evaluation also significantly affect residents' subjective well-being. In the information age, quantitative design is the inevitable direction of future design. Through quantitative research, targeted design strategies can be proposed to serve community residents better in their communities and provide references for communities in other developing countries. [ABSTRACT FROM AUTHOR]

Transit-oriented development (TOD) has become a dominant form of spatial planning and land use in large cities internationally. As the intersections of urban space and rail transportation, metro station areas play a key public service function in the lives of city residents. Based on the "5D" index and Node-Place theory in the metro station area, current research on the built environment in metro station areas focuses on improving the economic and transportation efficiency while neglecting public perception of the construction of station space. Sentiments, as an important part of the individual's perception, are closely related to the built environment. Therefore, this study takes 187 metro stations within the fifth ring road of Beijing, China, as an example and extracts public sentiment information from social media data using a wide range of natural language processing techniques to quantitatively analyze the distribution of the public's sentiment characteristics (including intensity, polarity, and category) in the metro station area and deeply explores the spatial correlation with the distribution of the objective built environment elements. The study shows that influenced by the spatial design of the metro station, density, land use functions, etc., the sentiment intensity of the station area within the Fifth Ring Road of Beijing is "strong in the east and weak in the west, strong in the north and weak in the south", and the sentiment polarity has the characteristic of gradually negative from inside to outside in a circular pattern. Synthesizing the sentiment perception in the metro station area, our study further divided the Beijing metro station area into four major categories and eight specific subtypes. [ABSTRACT FROM AUTHOR]

Exploring the built environment factor's impact on metro ridership can help develop metro station area planning strategies. This is in order to compensate for the shortcomings of previous studies, which mostly used all uniform pedestrian catchment areas (PCA) around metro stations. Beijing was divided into two zones and 12 built environment explanatory variables were selected as independent variables based on the "7D" dimension of the built environment. The boarding ridership during the morning peak hours was used as the dependent variable. Nineteen PCA radii from 200 to 2000 m were assumed. The optimal PCA of metro stations for each zone was determined by using the eXtreme Gradient Boosting (XGBoost) model with the objective of minimizing the Mean Absolute Percentage Error (MAPE). The nonlinear impact of the built environment factor of each zone on metro ridership is analyzed under the optimal PCA of metro stations. The study results show that (1) the optimal PCAs of metro stations inside the 4th Ring Road and outside the 4th Ring Road are the circular buffer zones with a radius of 800 m and 1300 m, respectively. (2) There is a nonlinear influence of the built environment factor on metro ridership, with strong threshold effects and spatial heterogeneity. The PCA results can be used for the built environment's zoning of metro stations. The XGBoost model and the nonlinear impact results provide significant implications for the practice of station-level ridership forecasting and integrating TOD development and built environment renewal. [ABSTRACT FROM AUTHOR]

Revealing the characteristics of the spatial and temporal evolution of regional tourism-related ecological security and exploring its driving factors are of great theoretical and practical value to promoting the coordinated and sustainable development of the tourism economy and the ecological environment. Taking the Beijing–Tianjin–Hebei region as a case study, this study constructed a tourism-related ecological security evaluation index system based on the DPSIR theoretical framework. The tourism-related ecological security index was measured from 2011 to 2022 and its spatiotemporal characteristics and dynamic evolutionary process were analyzed. Finally, the panel quantile regression model was used to analyze its driving factors. The results show that: (1) in time, the average value of tourism-related ecological security fluctuates and rises, and the differences between the units show a convergent trend, which is mainly manifested in the catching-up effect from low-value cities to higher-value cities; (2) in space, Beijing and its southeastern cities have a high level of tourism-related ecological security, and although the study area is mainly at the less secure level, it is developing continuously and progressively; (3) in terms of the dynamic evolution characteristics, the type transfer of tourism-related ecological security has certain "path dependence" and "self-locking" effects, often occurring between neighboring levels, and the type transfer under the influence of different neighborhoods has significant differences; (4) in terms of driving factors, environmental pollution has a significant inhibitory effect on the level of tourism-related ecological security, and the level of economic development has the largest positive marginal effect on tourism-related ecological security, while other influencing factors such as the level of tourism development have certain differences in terms of their positive role in the promotion of the level of tourism-related ecological security. This study can provide a reference for decisionmakers to promote ecological protection and high-quality tourism development in the Beijing–Tianjin–Hebei region. [ABSTRACT FROM AUTHOR]

Built environment (BE) planning and parking policy are two major strategies for restricting car use. However, researchers usually explore the independent associations of BE and parking policy with the use of the car in commuting, and most earlier studies are limited to investigating the benefits of integrating them. This study adopts a machine learning approach to explore the associations of home and workplace BE features and parking policy with the use of the car in commuting and whether the associations of BE features are moderated by parking policy. Results suggest that workplace BE features have larger collective contributions to the use of the car in commuting than home BE features. All BE features have nonlinear associations with the use of the car in commuting, and the nonlinear patterns differ across home and workplace neighborhoods. Moreover, free parking and parking convenience have significant moderating effects on the connection between BE and the use of the car in commuting. Thus, planning practitioners and policy makers should highlight the importance of coordinating BE planning and policy making to restrict the use of the car in commuting. [ABSTRACT FROM AUTHOR]

Travel mode and distance choices are not independent decisions, and individual choices are usually made in the knowledge of the preference and needs of other household members. To represent the dependency between mode choice and travel distance and the role of intra-household interactions in travel behavior, we develop a joint discrete–continuous model with intra-household interactions. In this model, we use joint household tour as the unit of analysis and characterize the dependency between mode choice and travel distance using flexible copula functions. Then, we apply the proposed model to analyze tour-based mode choice and travel distance in Beijing, China. The results indicate that unobserved factors contribute to positive dependency between mode choice and travel distance. The choice of walk is more dependent on travel distance than other travel modes, and the choice of travel modes except public transit shows a higher correlation with travel distance in complex individual tours than in simple individual and joint household tours. Further, a comparison between the proposed model, the independent model, and the model without intra-household interactions reveals that ignoring the dependency between mode choice and travel distance, or not considering intra-household interactions, could lead to over- or under-estimation of the effects of changes in exogenous variables. [ABSTRACT FROM AUTHOR]

Urban rail transit has been commonly regarded as an efficient transportation mode for alleviating the negative impacts of rapid urbanization. However, the complex and comprehensive built environment caused by rapid urbanization prevents policymakers and planners from understanding the performance of urban rail transit, particularly around transit stations. Developing station area typologies plays an important role in describing the characteristics of station areas. Numerous studies have developed typologies of station areas over the past decades; however, few have attempted to estimate the distribution of station types per station. To fill this gap, this paper first proposed the importance of a land use type (ILUT) index based on the term frequency-inverse document frequency method. This method avoids mutual concealment among land use types, to extract key built environment features based on built area datasets of the buffer areas of 337 selected urban rail stations in Beijing. Subsequently, the ILUT index was used to estimate the distribution of the station types per station using the latent Dirichlet allocation model. The 12 identified types of urban rail station areas in Beijing demonstrated that land use types consist of station types and presented the distribution of the station types with their probabilities, revealing the current performance of station areas. This paper proposes a description approach that will help policymakers and planners to effectively and efficiently identify and analyze built environment features. • Probability-based typology approach is proposed to describe built environments. • Index for extracting relatively important built environment features is developed. • Twelve types of station areas are identified using built area datasets in Beijing. • Distribution of 12 station types per station is estimated and visualized. [ABSTRACT FROM AUTHOR]

The built environment reshapes various scenes that can be perceived, experienced, and interpreted, which are known as city images. City images emerge as the complex composite of various imagery elements. Previous studies demonstrated the coincide between the city images produced by experts with prior knowledge and that are extracted from the high-frequency photo contents generated by citizens. The realistic city images hidden behind the volunteered geo-tagged photos, however, are more complex than assumed. The dominating elements are only one side of the city image; more importantly, the interactions between elements are also crucial for understanding how city images are structured in people's minds. This paper focuses on the composition of city image–the various interactions between imagery elements and areas of a city. These interactions are identified as four aspects: co-presence, hierarchy, heterogeneity, and differentiation, which are quantified and visualized respectively as correlation network, dendrogram, spatial clusters, and scattergrams in a framework using scene recognition with volunteered and georeferenced photos. The outputs are interdependent elements, typologies of elements, imagery areas, and preferences for groups, which are essential for urban design processes. In the application in Central Beijing, the significant interdependency between two elements is complex and is not necessarily an interaction between the elements with higher frequency only. The main typologies and the principal imagery elements are different from what were prefixed in the image recognition model. The detected imagery areas with adaptive thresholds suggest the spatially varying spill over effects of named areas and their typologies can be well annotated by the detected principal imagery elements. The aggregation of the data from different social media platforms is proven as a necessity of calibrating the unbiased scope of the city image. Any specific data can hardly capture the whole sample. The differentiation across the local and non-local is found to be related to their preference and activity space. The results provide more comprehensive insights on the complex composition of city images and its effects on placemaking. [ABSTRACT FROM AUTHOR]

Household size and its spatial distributions reflect not only the socioeconomic development in a city but also the rationality of urban resource allocation. Most existing studies rely heavily on census data to explore the potentially influential factors using methods such as macro-statistical analysis and socioeconomic analysis, of which the spatial resolutions and geographic scales are constrained. More importantly, the association between the household size distribution and the built environment is oversimplified or even neglected to some extent. In this work, we use massive mobile phone data combined with travel surveys of Beijing inhabitants' data (TSBI) to infer the household size and analyze the effect of spatial heterogeneity in a finer spatial resolution in Beijing, China. First, the machine learning method (i.e., support vector machine (SVM)) is applied to identify the household relationships of mobile users, and there are around 3.44 million households (families) with different sizes are obtained. Second, we analyze the spatial distribution patterns of household size and its association with built environmental indicators (e.g., public service density, public transportation density, etc.). The results exhibit a heterogeneous effect of the regional built environment on average household size (AHS). For instance, "commercial density" and "administrative density" show a negative impact on household size, while "public service density" and "public transportation density" show positive correlations with household size. As a complement to census data, mobile phone data can be used to obtain the household size in real-time. This paper provides quantified evidence for government departments to allocate facilities in a more targeted, balanced, and reasonable way according to the regional differences in household size, which would potentially support the sustainable urban development. • Using phone call characteristics between family members to infer family relationships • Family relationship was determined using SVM algorithm. • MGWR is applied to explore the effects of built environment factors on family size. • House prices and distance to city center have significant effects on household size. • Potential decision-making support is provided for the facility allocation for government. [ABSTRACT FROM AUTHOR]

As an essential material carrier of cultural heritage, the accurate identification and effective monitoring of buildings in traditional Chinese villages are of great significance to the sustainable development of villages. However, along with rapid urbanization in recent years, many towns have experienced problems such as private construction, hollowing out, and land abuse, destroying the traditional appearance of villages. This study combines deep learning technology and UAV remote sensing to propose a high-precision extraction method for conventional village architecture. Firstly, this study constructs the first sample database of traditional village architecture based on UAV remote sensing orthophotos of eight representative villages in Beijing, combined with fine classification; secondly, in the face of the diversity and complexity of the built environment in traditional villages, we use the Mask R-CNN instance segmentation model as the basis and Path Aggregate Feature Pyramid Network (PAFPN) and Atlas Space Pyramid Pool (ASPP) as the main strategies to enhance the backbone model for multi-scale feature extraction and fusion, using data increment and migration learning as auxiliary means to overcome the shortage of labeled data. The results showed that some categories could achieve more than 91% accuracy, with average precision, recall, F1-score, and Intersection over Union (IoU) values reaching 71.3% (+7.8%), 81.9% (+4.6%), 75.7% (+6.0%), and 69.4% (+8.5%), respectively. The application practice in Hexi village shows that the method has good generalization ability and robustness, and has good application prospects for future traditional village conservation. [ABSTRACT FROM AUTHOR]

Women-friendliness is an important content of inclusive city, while it has received rare attention during the regeneration of old cities. This study constructed women-friendliness indicators in three dimensions, i.e., security, equity, and specialization, and combined the quantitative calculations of coupling coordination with the qualitative analysis of in-depth interview. 25 subdistricts in old Beijing city were selected as case studies to analyze the spatial variation pattern of women-friendliness at the subdistrict level, and the characteristics of supply and demand relationships in three scenarios, namely “living,” “working,” and “traveling,” were summarized. It was found that the spatial variation in terms of women’s security and equity indicators among each subdistrict of the old Beijing city was large, while specialized facilities, which are still at an early development stage, were more evenly distributed but fewer in number. And the facilities in old Beijing city were more inclusive for both female residents and female tourists, while less inclusive for female employees. Finally, specific suggestions for the women-friendly development of old Beijing city were proposed in perspectives of mixed use of function, facility optimization, supply and demand adjustment, etc., hoping to provide references for other cities to increase inclusiveness in the process of urban regeneration. [ABSTRACT FROM AUTHOR]

The urban built environment has been extensively studied as a means to reduce car use, but most of the built environment features that have been examined mostly include so-called 'D-variables', namely, density, (functional) diversity, (road network) design, etc. The influence of the three-dimensional street space, which cannot be directly understood from maps, is much less studied. However, characteristics of the street space are considered to influence people's travel behavior according to urban design and walkability theories. A major reason for this gap is the lack of data providing relevant information. This paper aims to fill the gap by harnessing new urban data to measure these characteristics of the urban environment and analyze their impact on travel behavior, as indicated by the amount of car use. Among the many characteristics of street space, we chose the quality of street buildings, continuity of street walls, and height-width ratio of the street valley as three key characteristics to study. Using Beijing as a case study, we found that the three street space characteristics had a statistically significant relationship with residents' car use, mainly by influencing travel mode choice. The continuity of street walls is the most influential factor in reducing car use. • We expanded existing research by examining the influence of the street space on urban car use. • The streetscape is measured using street view images, deep learning models and building footprint data. • The continuity of street walls is the most influential streetscape feature in reducing car use. [ABSTRACT FROM AUTHOR]

It is believed that having urban parks that residents are keen to visit will promote walking and daily exercise, thereby impacting the general health of the population. We conducted studies on three historical parks in Beijing (the Summer Palace, Beihai Park, and the Temple of Heaven) with the aim of exploring the influence of urban historical parks on the physical activity and public health of local residents and to develop recommendations for the management and revitalization of urban historical parks. We investigated the physical activity of residents in the parks, the characteristics of the parks, and the general health of the public. We applied statistical methods for correlation analysis and found that, (1) in famous historical parks, the frequency of physical activity of residents is positively related to the time cost to travel to the park, quietness, attractiveness of the scenery, and ancient trees; (2) physical health is positively correlated with air quality and usual companion; (3) mental health is positively correlated with education, frequency of physical activity, space size, and aesthetic landscape; (4) the influence of historical parks on physical activity and public health can vary from park to park because of specific features; and (5) the impact of the typical characteristics of historical parks on promoting physical activities and health is not obvious, except in a quiet atmosphere, which causes a higher frequency of physical activity in historical parks. The most important functions of an urban historical park are to spread cultural connotations, create a cohesive society, and promote the conservation and revitalization of historical sites instead of merely a place to encourage physical activity. [ABSTRACT FROM AUTHOR]

The creative industries and the digital economy have become the drivers for the metropolises of China. Despite the rapid transformation towards knowledge production in China, the understanding of the role of informalities (like urban villages) in creative cities is still lacking. This paper examines the following interrelated questions: a) why have urban villages become the cluster/assemblages for a circuit of knowledge production (e.g. , digital work, media, and arts); and b) how is the assemblage of creative communities created by the growing rent-gap seeking regimes with different agency and everyday practices as shown in Beijing's artist and IT worker villages? Our investigations of the Heiqiao and Shigezhuang Villages in Beijing reveal that the Chinese rural land system has shaped the porous and interstitial spaces (e.g. , urban villages as the " semi-commons " for landowners and migrant tenants) in the regime-specific community-making and is distinctive from Western models of creative cluster formation. This study refines Florida's elitist-oriented analysis where the "creative class" prefers the "quality of place," and the city thus needs to enhance the quality of life to attract creative workers. The artist and IT worker villages, as a microcosm of the like-minded creative worker assemblage, are also sites for establishing contacts and fostering interaction in creative production. It is the quality of the public realm and networking (beyond the quality of the built environment) that shapes the assemblage of creative communities in urban villages. The networking and grass-roots alliance (as " semi-commons ") can help cope with the appropriation and provision problems facing " commons." • Urban village as semi-commons is a floating oasis for low-wage creative workers. • We need a relational and negotiated view on temporary land use in semi-commons. • Creative workers can unleash creativity in the Rent Gap Seeking Stage II . • Artist and IT worker villages take varied spatial forms and neighborhood activity. • Urban planning can become "softer" to allow for temporary uses of space. [ABSTRACT FROM AUTHOR]

To develop an age-friendly society, it is a basic task to deeply understand what and how factors would affect elderly people's daily multiple-activity time-use patterns. In the literature, the impacts of built environments as the physical aspects of living environments have been widely studied. However, the impacts of social environments as the social aspects of living environments on multiple activity participation and duration constrained by time budgets have not been found. To fill this gap, this paper makes efforts to propose various social environmental indicators and incorporate them into a multiple discrete-continuous extreme value (MDCEV) model to test the significance of each variable and to explore the impacts of living environments on elderly people's daily multiple-activity time-use behaviours. In addition to socio-economic compositions, the social environmental indicators are extended to social ties of people, living pressure, social resources distribution, social safety and policy. Then a joint elasticity analysis for multiple activity participation and duration with constraints is proposed for deriving policy and practice implications. The specifications and joint elasticity analysis in Beijing of China which is a representative city affected by Confucian culture and faced with aging problem in Eastern and South-eastern Asia help find out significant factors and their impacts on elderly people's multiple-activity time-use patterns. Policy and practice implications are suggested to improve elderly people's out-of-home activity participation and duration so that an age-friendly society is expected. • Propose social environments indicators. • Integrate living environments into a MDCEV model. • Integrate living environments into a MDCEV model. [ABSTRACT FROM AUTHOR]

• Characterizing Electric Vehicle (EV) users' mobility patterns using trajectory data. • Exploring the association between mobility patterns and the built environment. • Private EV users tended to have regular travel and activity patterns. • EV users performed activities at a small number of places and within a small area. • Gymnasia tended to be more statistically associated with the mobility patterns. Human mobility pattern analysis has received rising attention. However, little is known about the mobility patterns of private Electric Vehicle (EV) users. In response, this paper characterized mobility patterns of private EV users using a unique one-month dataset containing moving trajectories of 76,774 actual private EVs in January 2018 in Beijing. Specifically, we first explored the diversity, regularity, spatial extent, and uniqueness of EV users' mobility patterns. The results suggested that most EV users had both regular travel and activity patterns (the mean travel and activity entropies were 2.17 and 1.83, respectively) with special preferences towards some specific activity locations relative to all the locations they visited (the mean number of activity locations visited was 13.57 in one month). Furthermore, they tended to perform activities within a small geographical area (the mean radius of gyration was 7.60 km) and have a short daily travel distance (the mean value was 37.35 km) relative to their electric driving range. Further, we associated EV users' mobility patterns with the built environment through ordinary least squares and geographically weighted regression models, particularly considering the so-called modifiable areal unit problem (MAUP). Due to the MAUP, most of the statistically significant built environment variables varied across spatial analysis units (SAUs). Gymnasia was the only variable statistically associated with the mobility patterns for all SAUs; while the variables related to residence and workplace were not statistically associated. [ABSTRACT FROM AUTHOR]

Due to rapid informatization and increasing urban sprawl, currently, metropolitan residents are facing challenges regarding spatial imbalance between their home, workplace, and activity locations, which seriously affects the quality of life and subjective well-being of urban residents. However, only a few existing studies have analyzed the relationship between home, workplace, and other activity spaces of urban residents and the influence mechanism of spatial separation of the three locations. In this study, we used the mobile phone signaling data of the residents of Beijing for May 2019 to explore the degree of mutual separation of the three locations, based on the identification of the homes, workplaces, and main activity spaces of over 2.3 million residents in Beijing. Leveraging these data, we discussed the influence mechanism of activity separation, in terms of the built environment and socioeconomic factors. The results indicated that the degree of the home-workplace separation was the highest, followed by the home-workplace-activity space separation, and the home-activity space separation was the lowest. Notably, the three types of spatial separations had significant spatial disparities. Attribution analysis indicated housing price as the dominant factor affecting the spatial separation of the residents, while the accessibility and location also having important effects. Moreover, the interaction of these factors had a stronger explanatory power for the spatial separation of the daily activity spaces of the urban residents. This study is the first to estimate the degree of spatial separation among the homes, workplaces, and other activity spaces of urban residents and analyzed their correlation using geographic context factors. Our results can provide useful scientific insights to explore the spatial characteristics of the home-work-activity relationship with respect to metropolitan residents and optimize the spatial distribution of urban functions. • 2.3 million Beijing residents' homes, workplaces, and major activity spaces were identified based on mobile phone data. • This study is the first paper to estimate the spatial separation among the homes, workplaces, and activity spaces. • The separations of homes, workplaces, and activity spaces had significant spatial heterogeneity at the subdistrict scale. • Housing price is the dominant factor for the spatial separation, and accessibility and location also had important effects. [ABSTRACT FROM AUTHOR]

In urban transportation systems, taxis are regarded as flexible, convenient, and time-saving. Taxi demand is affected by various built-environment factors and by the time of the day. Although many studies have investigated correlations between taxi demand and the built environment, the direct and spillover effects of built environment factors on taxi demand have not been examined at a fine spatial scale. To address this gap in the literature, this paper employs spatial econometric models using GPS-tracked taxi trips, mobile signaling data, and points of interest (POIs) to study taxi demand in Beijing at a 1-kilometer square grid resolution. The results show that, in the morning and evening peak hours, road network density has the strongest (positive) direct and indirect impact on taxi ridership. A relationship is also found between public transportation and taxi ridership: bus coverage has positive direct effects and insignificant indirect effects on taxi pick-ups and drop-offs, while subway coverage has negative indirect effects, suggesting that it may absorb taxi demand from surrounding grids. Results also indicate that various built-environment factors affect taxi demand differently at morning and evening peak times. This study reveals the complex nature of taxi ridership and has important implications for policymakers, transport planners, and other stakeholders in megacities around the world. • Use spatial autoregressive models to investigate the relation between built environment, socioeconomics and taxi ridership. • Conduct the analysis for morning and evening peak hours. • Built environment characteristics and socioeconomics influence taxi ridership via both local and spillover effects. • Offer a framework to incorporate various types of big data, including taxi data, mobile signaling data, points of interest. [ABSTRACT FROM AUTHOR]

In order to accurately analyze the building energy consumption and identify the problem of building energy consumption in advance, this study carries out the energy consumption analysis based on BIM (Building Information Modeling). The research object is a four-story college student dormitory in Beijing, and this set of BIM-based energy consumption simulation data was obtained using standard operating procedures (SOP). This operating procedure can start energy consumption analysis in the conceptual design stage, and developers can participate in real-time through the use of a three-dimensional information model, without additional design required. Then, comparing this study with the traditional energy consumption analysis, we see that the SOP of this research result has the following advantages: SOP function analysis is more professional, and the visual display method is more popular and intuitive; due to the flexible file format of the SOP, when data exchange is required between different software, the SOP can realize more convenient operation, and users can identify problems in the early stage of design through the SOP, correcting the scheme according to the simulation results, which is conducive to the development of the construction process. Finally, this study puts forward the analysis and estimation of energy consumption in different stages of the building life cycle, so as to provide researchers with ideas for improvement. [ABSTRACT FROM AUTHOR]

• Trips by dockless bike-sharing show the highest travel satisfaction. • The longer assess time is related to lower satisfaction with dockless bike-sharing. • Travelers have higher satisfaction with dockless bike-sharing as the primary mode. • Pro-public transit attitude relates to higher satisfaction of dockless bike-sharing. • Residential road network has no effect on satisfaction with dockless bike-sharinga. Using survey data collected among residents in Beijing, this paper presents an investigation of the difference in travel satisfaction between dockless bike-sharing and other travel modes. The effects of individual, spatial and trip attributes on travel satisfaction with dockless bike-sharing are also identified. Our analysis adds to the empirical support for higher satisfaction with trips by dockless bike-sharing than trips by private bicycles. The assess time for shared bicycles is negatively associated with travel satisfaction with dockless bike-sharing. In addition, travelers have higher satisfaction with dockless bike-sharing when used as the primary mode than as the first-mile/last-mile solution. Travel-related attitudes tend to play a more significant role in travel satisfaction with dockless bike-sharing than residential built environment. Travelers with a preference for bicycles and public transport and those who value the health or environmental influence of travel tend to evaluate dockless bike-sharing travel as more satisfying. [ABSTRACT FROM AUTHOR]

Numerous studies have investigated the travel effects of online purchases. However, compared to tangible goods (e.g., books, electronics, and clothes), very limited attention has been paid to online purchases of intangible services (e.g., hairdressing, dining out, and visits to movie theatres, zoos, and local theme parks). Utilizing data obtained from 733 structured interviews in Beijing, China, this paper aims to examine the influence of buying intangible services online on trip frequency. The results indicate that – because of buying intangible services online – 52% of respondents indicated an increase in travel frequency to use these services, while only 7% indicated a decrease in the frequency. More importantly, those who indicate an increase in travel frequency are inclined to travel longer distances to use these services. Therefore, purchasing intangible services online may impose additional pressure on transportation systems. Applying a multinomial logistic regression method, we additionally reveal the influential factors of changes in travel frequency. The results show that – due to buying intangible services online – people with lower accessibility to shopping centers and bus stops are less likely to increase and even more likely to decrease the frequency of travel to use these services. • Purchasing intangible services online makes consumers travel more frequently to use these services. • The built environment plays a role in travel frequency changes caused by buying intangible services online. • Physical retailers for intangible services can benefit from online purchases. • Purchasing intangible services online seems to be a challenge for transportation systems. [ABSTRACT FROM AUTHOR]

As one of the methods of urban environmental assessment, sensitivity assessment of urban climatic environment can accurately reflect the problem areas of current urban climate and built environment through visual means, and help cities to carry out sustainable transformation and renewal in the stock era to optimize the living environment. Taking the central urban area of Beijing as the research object, the sensitivity of climatic environment was evaluated by meteorological data and built environment element data. The results showed that the distribution of sensitive units showed a centrifugal radiation pattern of "high in the center and low in the periphery". Block units with high climate sensitivity were mostly concentrated in Xicheng District and Dongcheng District, accounting for 93% of the total number of units. Further research showed that complex built environment and lack of elements to regulate climatic environment were the main reasons for the poor local climatic environment in the region with high climate sensitivity. Finally, a comprehensive evaluation of the remolding capacity, renewal potential and future development intensity of different grades of climate sensitive units was given. The results will provide scientific reference for urban renewal and reconstruction under climatic and environmental changes, so as to promote urban sustainable development and improvement of living environment. [ABSTRACT FROM AUTHOR]

• Rail accessibility is measured by the market access approach. • Non-linear association between travel satisfaction and accessibility is observed. • Residential self-selection and social group strata differentiation play a moderating role. Rail stations located in residential environments provide significant amenities to the travel-related satisfaction of residents. Using an individual survey conducted in Beijing in 2013, this paper applies multilevel models to explore the association between travel satisfaction and rail accessibility, controlling for residential self-selection, socio-demographics, and neighborhood characteristics. We differentiate between station adjacent and non-adjacent residential locations to reveal non-linear association over space. We consider the effect of rail accessibility changes on travel satisfaction. The results suggest that rail accessibility improvements generate significant impacts on residents' satisfaction with commuting convenience. The findings suggest the important role of the spatial placement of rail transit infrastructure on people's subjective wellbeing with travel. [ABSTRACT FROM AUTHOR]

App-based, dockless bicycle-sharing systems (DBSSs) have proliferated across cities in China since their inception in 2016, managed by the major Internet service providers and with central government support, in an effort to help grow nonmotorized transport. Although offering more generalized use and extended range, DBSS exhibits great variability in local use rate, suggesting that control of certain local environmental attributes could be instrumental in supporting more widespread bicycle use. This article is concerned with the relationship between street morphology defined at the street segment level and related shared bicycle use rate. Mobike trip data for a 10-day period in May, 2017 – 3.09-m trip records with origins and destinations – were accessed. Multilevel regression analysis shows that generated trips and travel distance are positively related to both betweenness and maximum convex hull radius but are negatively related to diversion ratio. All street morphological metrics show significant effects across spatial scales. Number of shared bicycle trips is positively associated with floor area ratio but negatively associated with intersection density. Land use mix is positively related to generated trips but negatively related to biking distance, while destination accessibility shows the inverse relationship. The results provide insight into where trips using DBSS are likely to be found, given the street pattern, but also how their wider and more generalized use could be promoted using urban planning. [ABSTRACT FROM AUTHOR]

In recent years, more and more researches focus on the self characteristics and spatial location of housing, and explore the influencing factors of urban housing price from the micro perspective. As representative of big cities, spatial distribution pattern of housing price in national central cities has attracted much attention. In order to return the spatial distribution pattern of housing price to the research on influencing factors of housing price, the reasons behind the spatial distribution pattern of housing price in three national central cities: Beijing, Wuhan and Chongqing are explored. The results show that urban housing price is affected by many factors. Due to different social and economic conditions in each city, there are differences in the influence direction of the proximity to expressways, city squares, universities and living facilities, characteristics of companies and enterprises on Beijing, Wuhan and Chongqing. Various factors have different value-added effects on housing price in different cities. The location of ring line in Beijing and Wuhan has the greatest increase effect on housing price, while metro station of Chongqing has the greatest increase effect on housing price. [ABSTRACT FROM AUTHOR]

City service demand fluctuates across space and time. Although various data, such as 311 hotline data and social media data, have been used to explore the spatiotemporal patterns of city services, data uncertainty and the uneven distribution of service demand are overlooked to some extent and thus could result in bias. To overcome these shortcomings, top‐down collected city service data that fully cover urban areas are used as an emerging data source in this article. A visual analytical approach that employs a three‐dimensional model based on a space‐time cube combined with the Mann–Kendall algorithm is developed and applied in Xicheng District, Beijing, China. The results show that in comparison to other methods, the emerging data and visualization methods have more power to explain city services in terms of overall trends and micro‐scale details. For instance, city service cases demonstrate a significant downward trend. Meanwhile, the distribution of hotspots/coldspots is found to be related to the built environment and population density. For example, high‐incidence cases are located in some communities that are the key governance areas, indicating a demand to increase the staffing of grid administrators. The findings of this work can potentially benefit other cities in China and worldwide. [ABSTRACT FROM AUTHOR]