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• Outdoor thermal comfort is evaluated in an urban park in a hot-summer and cold-winter region of China (Chengdu). • Machine learning techniques are applied to determine the (nonlinear) relationship between thermal sensation vote and meteorological factors. • The effect of landscape spaces on human thermal comfort varies across the season. • NTR of PET is 6.79 °C to 19.90 °C, and NTR of UTCI is 13.27 °C to 27.25 °C. TAR of PET is 2.8 °C to 21.9 °C, and TAR of UTCI is 8.1 °C to 28.3 °C. Global warming and rapid urbanization have exacerbated the urban heat island effect. Urban parks contribute to alleviating such an effect and achieving the "carbon emission peak before 2030" and "carbon neutrality before 2060" goals of China. Their popularity is considerably influenced by human thermal comfort. However, limited thermal comfort studies have been conducted in the hot-summer and cold-winter region of China. This study examines human thermal comfort in different landscapes of an urban park in Chengdu and determines the thermal benchmarks. A machine learning (random forest) analysis shows that human thermal sensation is affected by different meteorological factors in different seasons. In addition, the influences of landscape space on human thermal comfort have considerable differences in different seasons. Residents prefer strong solar radiation in winter but fast wind speed in summer. UTCI (universal thermal climate index) is better than PET (physiological equivalent temperature) for outdoor thermal comfort assessment in the study area. This study serves as a valuable baseline and technical reference, contributing to sustainable urban park design. [ABSTRACT FROM AUTHOR]

• We explored the moderation effect of urban density on changes in physical activity during the COVID-2019 pandemic. • The results were based on a longitudinal study. • Urban density mitigated the decrease in physical activity caused by the pandemic. • The duration of physical activity performed in country parks increased during the pandemic. • A flexible and porous urban development strategy could enhance the resilience of a city during the pandemic and beyond. Various social distancing measures were carried out in many cities worldwide during the coronavirus disease 2019 pandemic (COVID-19). These measures have led to decreased physical activity levels and higher health risks among urban populations. Strong evidence has been established that built environment characteristics can stimulate physical activity and thus improve public health during non-pandemic periods. Urban density was arguably one of the most important built environment characteristics. However, little is known about whether high urban density amplifies or attenuates the decline in physical activity during the pandemic. Based on two-wave physical activity data collected before and during the pandemic (in January and May 2020, respectively), we used moderation analysis to compare the changes in physical activity levels between people living in low- and high-density neighborhoods. Our results showed that people living in low-density areas have a smaller decrease in physical activity conducted in neighborhood, compared to those living in high-density areas. Our findings suggest that a flexible and porous urban development strategy could enhance the resilience of a city during the coronavirus pandemic and beyond. [ABSTRACT FROM AUTHOR]

• We explored the effect of urban greenery on physical activity during COVID-19. • The results were based on a natural experimental study. • Urban greenery mitigated the decrease in leisure time physical activity during the pandemic. • People lived in greener neighbourhood visited country parks more often. • The protective and refuge effect of urban green space should be valued. The coronavirus disease 2019 (COVID-19) pandemic and related social distancing measures have altered the daily lifestyles of people worldwide. Although studies on this disease are emerging rapidly, less is known about the impacts of COVID-19 and urban greenery on leisure-time physical activity, which is critical to maintain health for urban residents during the pandemic. In this study, we used a natural experimental research design to identify whether urban greenery cushions the decrease in leisure-time physical activity caused by the pandemic and related social distancing measures in a high-density city. The two-wave physical activity data (before and during the pandemic) were collected for urban residents in neighborhoods with high or low levels of greenery. The results of difference-in-differences model suggest that urban greenery mitigated the decrease in physical activity during the pandemic. People who lived in greener neighborhoods experienced a lesser decrease in the leisure-time physical activity level than those who lived in less green neighborhoods. Additionally, people who lived in greener neighborhoods experienced increased levels of physical activity related to visits to country parks during the pandemic. These findings suggest that urban green spaces play a significant role in shaping physical activity and providing a refuge for the public during crises. Our study is among the first to investigate the impact of urban greenery on pandemic-induced changes in leisure-time physical activity in densely populated Asian cities, and our findings shed light on the potential protective role of urban greenery on public health during the COVID-19 pandemic and beyond. [ABSTRACT FROM AUTHOR]

Understanding the associations between demographic groups' metro travel behaviors and the built environment is crucial for addressing automobile dependence and promoting transportation equity and reasonable urban construction. This study examines the nonlinear relationships and threshold effects of the built environment on the metro travel patterns of three groups (i.e., commuters, seniors, and students) by applying smart card data in Kunming, China. We select the optimal machine learning model—gradient boosting decision trees (GBDTs)—and consider various built environment attributes. Our findings indicate that: 1) built environment attributes universally have nonlinear and threshold effects on metro travel for all groups; 2) the collective contributions of density and diversity differ greatly across groups compared to other attributes; and 3) only a few built environment attributes have similar effect directions and degrees across all three groups, while most have unique effects on each group. The findings suggest metro station area planning strategies to promote metro use and transportation equity for different groups. • Analyze the relationship between the built environment and different metro travelers. • Apply machine learning methods to evaluate nonlinearity. • Built environment attributes universally have nonlinear effects on all groups' metro travel. • A few built environment variables have similar effect directions and degrees for all three groups. • The effects of most variables vary across groups. [ABSTRACT FROM AUTHOR]

Population aging is a conspicuous demographic trend shaping the world profoundly. Walking is a critical travel mode and physical activity for older adults. As such, there is a need to determine the factors influencing the walking behavior of older people in the era of population aging. Streetscape greenery is an easily perceived built-environment attribute and can promote walking behavior, but it has received insufficient attention. More importantly, the non-linear effects of streetscape greenery on the walking behavior of older adults have not been examined. We therefore use readily available Google Street View imagery and a fully convolutional neural network to evaluate human-scale, eye-level streetscape greenery. Using data from the Hong Kong Travel Characteristic Survey, we adopt a machine learning technique, namely random forest modeling, to scrutinize the non-linear effects of streetscape greenery on the walking propensity of older adults. The results show that streetscape greenery has a positive effect on walking propensity within a certain range, but outside the range, the positive association no longer holds. The non-linear associations of other built-environment attributes are also examined. [ABSTRACT FROM AUTHOR]

Rental and vacancy dynamics in real estate markets have elicited substantial scholarly attention. Previous studies primarily focused on offices and paid much less emphasis on retail properties. Moreover, nearly all research fails to explore the causes of differences in rental and vacancy adjustment speeds. To this end, retail property rental and vacancy dynamics (1991–2017) in tourist- and local-dominant areas in Hong Kong are examined using error correction models. This study is the first to use information asymmetry theory to explain rent/vacancy adjustment speed differentials in the retail property market and investigate the change of the adjustment speeds accruing to a policy shock. The results show that both supply and demand factors influence retail property rentals. Rental adjustment is quicker in tourist-dominant areas than in local-dominant counterparts, which agrees with information asymmetry theory. The implementation of the Individual Visit Scheme hastens the rental adjustment process of tourist-dominant areas but not that of local-dominant counterparts. Finally, policy implications (e.g., adjusting the one-size-fits-all maximum loan-to-value ratio policy and enhancing tourists' accessibility to non-tourist-dominant areas) are discussed. [ABSTRACT FROM AUTHOR]

Urban parks have well-documented health benefits for urban residents. To increase the use of parks and enhance the physical activity level of city-dwellers, recent studies have explored the link between the amount of greenery in parks and the level of park usage. However, the results have been inconsistent, partly due to different measurements of park greenery. In this study, we developed a novel method to assess both the quantity and quality of park greenery from eye-level photographs taken along major paths in parks. The quantity of greenery in these photographs was objectively assessed with advanced machine learning techniques (PSPNet), and the quality of greenery was assessed by virtual audit. The associations between greenery and usage of 43 urban parks were further explored with regression models. The results showed that the quality of greenery has stronger association with total number of park visitors than the quantity. Both the quantity and quality of greenery had stronger associations with the number of elderly visitors (apparent aged 65 or above) than with the numbers of children or adults. Our results bring new insights into how park greenery can encourage park usage and contribute to healthy cities. [ABSTRACT FROM AUTHOR]

• While BIL supply became increasingly agglomerated, TIL supply was gradually dispersed. • A TIL supply corridor could be identified in the central part of the BTH region. • Contribution of TIL supply to local economic growth was much greater than that of BIL supply. • There existed a 'zero-sum inter-regional linkage effect' among neighboring counties. Industrial land supply, as an important governmental tool in China, has both economic and political connotations. Using the Beijing-Tianjin-Hebei (BTH) region as a study area, this paper examines local governments' behavior in supplying industrial land at different technological intensities and its contribution to economic growth from 2007 to 2018. The results are as follows: (1) As time passed, basic industrial land (BIL) supply became increasingly agglomerated, while technology-intensive industrial land (TIL) supply gradually dispersed. (2) A TIL supply corridor could be identified in the central part of the BTH region. (3) The contribution of TIL supply to local economic growth was significantly greater than that of BIL supply. (4) There existed a 'zero-sum inter-regional linkage effect' among neighboring counties, and TIL supply made a greater contribution than BIL supply in the zero-sum game. Finally, important implications for industrial land supply and regional development policies in the BTH region are proposed. [ABSTRACT FROM AUTHOR]

• Propose a people – metro – bike – route – urban space framework to describe the built environment. • Introduce the multilevel modeling framework to the studied problem. • Compare the integrated usage of dockless bike-sharing and the metro in different scenarios. • Investigate built environment effects on using dockless bike-sharing to connect the metro. • Discuss practical implications drawn from the empirical findings. The newly prevailing dockless bike-sharing system offers a decent solution to the first- and last-mile problem and connects trip origins/destinations and transit (mostly metro) stations. Few studies, however, have explored the effects of built environment characteristics on the integrated usage of dockless bike-sharing and the metro, especially in different conditions (e.g., access versus egress and morning peak versus evening peak) and using panel data. To fill the gap, this study proposes a people – metro – bike – route – urban space framework to describe the feeder-related built environment from the perspective of the feeder process. Using 3-day data of ofo bikes in Shenzhen, China, this study then develops multilevel negative binomial models that incorporate random effects and address the intracluster correlation attributed to repeated measures to scrutinize the feeder-related built environment effects on the integrated usage. The findings are listed as follows: (1) The majority of access and egress integrated trips have a distance range of 500–2000 m and a duration range of 2.5–10 min; (2) Popular metro stations (with a large ridership) are positively related to the access integrated usage; (3) The number of available shared bikes and the length of bikeway in the catchment areas of the metro are positively related to the integrated usage; and (4) Mixed land use increases the integrated usage, whereas urban villages are places with few demands for the integrated usage. These findings are beneficial in developing a bike-friendly built environment that facilitates the seamless connection between dockless bike-sharing and the metro. [ABSTRACT FROM AUTHOR]

Transit offers stop-to-stop services rather than door-to-door services. The trip from a transit hub to the final destination is often entitled as the "last-mile" trip. This study innovatively proposes a hybrid approach by combining the data mining technique and multiple attribute decision making to identify the optimal travel mode for last-mile, in which the data mining technique is applied in order to objectively determine the weights. Four last-mile travel modes, including walking, bike-sharing, community bus, and on-demand ride-sharing service, are ranked based upon three evaluation criteria: travel time, monetary cost, and environmental performance. The selection of last-mile trip modes in Chengdu, China, is taken as a typical case example, to demonstrate the application of the proposed approach. Results show that the optimal travel mode highly varies by the distance of the "last-mile" and that bike-sharing serves as the optimal travel mode if the last-mile distance is no more than 3 km, whilst the community bus becomes the optimal mode if the distance equals 4 and 5 km. It is expected that this study offers an evidence-based approach to help select the reasonable last-mile travel mode and provides insights into developing a sustainable urban transport system. [ABSTRACT FROM AUTHOR]

This study examined the longitudinal relationships among self-concept clarity (SCC), hope, and subjective well-being (i.e., emotional well-being and cognitive well-being). Specifically, we tested both the between-person and within-person associations of SCC with subjective well-being among 2,001 Chinese adolescents (age range 11–24 years, 42.9% males) during the first year. In addition, we examined the longitudinal mediating role of hope. Results showed that SCC had positive correlations with hope and subjective well-being both at one time point and over time. Multilevel mediation analysis indicated that hope could serve as a mediator in the association between SCC and subjective well-being, at both the between-person and within-person levels. Moreover, the model of longitudinal multilevel mediation was found to be moderated by gender and age. Our results indicated that hope could be an underlying mechanism for the longitudinal relationship between SCC and subjective well-being among Chinese adolescents, which provides a potential intervention target for improving adolescents' well-being. [ABSTRACT FROM AUTHOR]

Understanding differentiated services is pivotal for enhancing the appeal and diversity of the metro system, yet this facet has received relatively scant attention in existing literature. To bridge this research gap, our analysis delves into the business-class services offered by the metro and compares them with the common-class offerings. First, we illustrate the spatial and temporal patterns of business- and common-class ridership across stations and hours. Second, we construct two-stage geographically weighted regression models to identify key determinants and their spatiotemporally heterogeneous effects, focusing on land-use patterns, demographic considerations, and intermodal transfer modes. Leveraging one-week smart card data collected in Shenzhen from May 13th to 17th, 2019, our findings underscore the following aspects: (1) Spatial and temporal variations in business-class ridership across stations are linked to diverse land-use configurations. (2) Bus-metro transfers, business establishments, medical facilities, and the proportion of young commuters contribute significantly to the business-class ridership. (3) The emergence of business-class trip is weakly associated with bike-sharing activities but has a strong correlation with bus transfers. (4) Business establishments and medical facilities exhibit nuanced impacts on business-class travel, with excessive aggregation leading to unintended consequences. These insights offer valuable policy implications for fostering the development of business-class services in the metro systems of other Chinese cities. [ABSTRACT FROM AUTHOR]

High-density planting is a vital cultivation measure to improve crop yield. In the semi-arid region, insufficient precipitation and high variability are the primary factors that restrict agricultural development. Matching planting density and fertilizer application with precipitation is a promising technical strategy to ensure yield stability and enhance nitrogen (N) use efficiency (NUE). To achieve this objective, we conducted a continuous field experiment in the Loess Plateau region of Northwest China between 2015 and 2020. Under conventional (CF) and reduced fertilization (RF, 20 % CF) conditions, we investigated the response characteristics of dry matter accumulation, yield, yield components, NUE, N surplus, and net income of maize as the density increased from 5.25 (D1) to 6.75 (D2), 8.25 (D3), and 9.75 (D4) × 104 plants ha−1. The results indicated that reduced fertilizer application led to a decrease in grain yield by 6.2–8.7 %, whereas increasing the density by at least 1.50 × 104 plants ha−1 (D2) could compensate for the yield reduction caused by reduced fertilization (N 55 + P 2 O 5 27 kg ha−1) in normal and wet years. The compensatory effect initially increased and then decreased as the density increased, with the highest yield observed at planting density D3. By increasing the rapid growth rate of maize (6.3–17.1 %) and extending the rapid growth duration (0.9–2.5 days) through high planting density, reduced fertilization combined with high-density planting (RF·D3) significantly increased the cumulative yield, yield stability, net income, and NUE was by 9.4 %, 18.9 %, 10.6 %, and 37.0 %, respectively, over six years, compared with CF·D1 treatment. Additionally, the N surplus was reduced by 44.6 %. In conclusion, using reduced fertilization with high planting density measures can achieve yield stability and sustainable maize production in semi-arid areas. [Display omitted] • High density planting saved fertilizer without yield reduction. • Rainfall and its distribution affected the variability of planting density. • Increasing planting density in normal and wet years had compensatory effects. [ABSTRACT FROM AUTHOR]

In tandem with the urbanisation process, China's transport sector is currently experiencing rapid development and was ranked third out of all the industrial sectors in terms of generating CO 2 emissions in 2020, which poses a huge challenge to achieving carbon neutrality. Primarily using the energy consumption data from China's transport, storage and postal sectors (TSPS) and input and output data between 2007 and 2020, this study first uses the Tapio decoupling model to evaluate the decoupling effect in the TSPS. Structural decomposition analysis is then applied to explore sectoral linkages and decompose the forces driving CO 2 emissions. Additionally, we explore the main determinants of the energy structure effect and final demand in terms of energy consumption and industrial sector demand. Our results show that the target sector experienced a weak decoupling, which implies that the low-carbon transformation of this sector became increasingly apparent. Factor decomposition shows that improvements in energy intensity, energy structure and the production input and output structure have contributed significantly to reducing CO 2 emissions, but these gains have been largely offset by final demand, resulting in a net reduction of 27.97 million tons from 2007 to 2020. The increased usage of low carbon forms of energy, such as natural gas, is the key driver behind the emissions reduction effect in terms of the energy structure. However, the higher final demand from the construction sector and the wholesale and retail trades are the main factors that have increased CO 2 emissions. By adopting a sectoral and energy structure decomposition perspective, our study can be used to provide guidance to governments seeking to pursue carbon-reduction policies to achieve carbon peak and carbon neutrality, in the TSPS in particular. • Structural decomposition analysis is used to quantify the driving forces behind increasing CO2 emissions. • A decrease in energy intensity is vital to achieve carbon neutrality. • Natural gas is the main driver of reducing emissions in terms of energy structure. • Demand from specific industrial sectors is the main barrier to achieving carbon neutrality. • A pathway for achieving carbon neutrality in the transport sector is proposed. [ABSTRACT FROM AUTHOR]

Air pollution, an unexpected event, poses a significant threat to public health and affects human mobility. Ride-hailing provides an effective way to understand how human mobility adapts to air pollution. This study examines a week-long ride-hailing demand dataset from Chengdu, China, to evaluate the resilience of ride-hailing services (or ride-hailing resilience) in the face of poor air quality. A gradient boosting decision tree model is developed to explore the non-linear and interaction effects of air pollution, the built environment, and socioeconomic characteristics on ride-hailing demand and resilience. The results show that the relative importance and impact of independent factors on ride-hailing demand and resilience vary. Specifically, the density of residence facilities and air pollution are the most important predictors of ride-hailing demand and resilience, respectively. The non-linear and interaction effects of air pollution and selected built-environment and socioeconomic characteristics on ride-hailing resilience are presented. We recommend that urban planners and policymakers address the vulnerability of regions to air pollution, optimize the allocation of ride-hailing resources, and develop strategies to improve regional resilience. [ABSTRACT FROM AUTHOR]

Neighborhood compactness has been identified as a sustainable approach for fostering social relationships. However, existing studies have not clearly demonstrated whether neighborhood compactness in high-density cities directly influences the mental distress of community-dwelling older adults, or whether it indirectly influences mental distress through perceived accessibility to urban amenities (PA). Using a composite score of three dimensions (depressive symptoms, loneliness, and social isolation) to measure mental distress, and applying a mediation model within a cross-sectional design involving 947 older adults (aged ≥ 60) with at least mild symptoms in Hong Kong, our findings suggest an indirect pathway between neighborhood compactness, PA, and mental distress. Neighborhood compactness was positively associated with PA (B = 7.791, p < 0.001), and PA was negatively associated with mental distress (B = −0.12, p = 0.017). However, no direct impact of neighborhood compactness on mental distress was found. Moderated mediation analysis further indicated that neighborhood compactness and PA supported older females but not males. These results align with our hypothesis that (1) neighborhood compactness may not always be beneficial for older adults with mental distress in high-density cities unless compactness itself enhances PA and facility usage to support community-dwelling individuals, and (2) gender differences may result in varying interactions and perceptions of urban amenities and the built environment. To support the concept of "aging in place" in the future, urban plans aimed at enhancing neighborhood compactness and its social impacts should focus on addressing social inequality, including strategies to improve urban design, social participation, and gender-specific protocols, so that older adults can achieve better community awareness, environmental satisfaction, and facility usage, ultimately reducing mental distress. • An indirect pathway between neighborhood compactness, PA, and mental distress of older adults is found. • A mediation model is applied to a cross-sectional design of a high-density city. • Higher neighborhood compactness correlating with higher PA leads to alleviated mental distress. • Neighborhood compactness is associated with improved mental conditions among female older adults. • PA is associated with alleviated mental distress among females but not males. [ABSTRACT FROM AUTHOR]

• Study the alternative mode choice of ride-sourcing users based on survey data. • 54.71% of respondents choose public transit when the ride-sourcing is suspended. • Age, gender, income, car ownership, and trip purpose are significant determinants. • More metro stations around the trip origin could reduce private vehicle use. • Suspension of ride-sourcing services would lead to lower vehicle emissions. Despite the popularity of ride-sourcing services among the public, some cities consider suspending ride-sourcing services because of repeated safety failures and protests from taxi drivers. The impact of such a policy on the transportation system and environment is rarely studied. To fill this gap, we performed a stated preference survey in Chengdu, China, to investigate the alternative mode choice (AMC) of ride-sourcing users. We collected data of 435 trips from 340 respondents. The analysis results show that with suspension, 53.71%, 27.36%, 10.80%, and 7.13% of ride-sourcing trips would shift to public transit, taxi, active mode (walking and cycling), and private car trips, respectively. The mixed logit modeling results show that age, gender, household income, number of cars per person, trip purpose, and transit accessibility significantly influence AMC. Results of Monte-Carlo Markov Chain simulations indicate that vehicle emissions related to ride-sourcing trips will decrease by more than 50% after the suspension. [ABSTRACT FROM AUTHOR]

The combined use of non-negotiable (N-NDOs) and negotiable developer obligations (NDOs) has become a principal instrument for land value capture in most countries. In this circumstance, this study seeks to examine how the combined use of NDOs and N-NDOs affects the practical results of land value capture within the context of market-oriented urban redevelopment in China. The ordinary least squares (OLS) estimation and two spatial regression models (SLM and SEM) are applied to parcel-level data samples of all redevelopment projects in Shenzhen, China, for evaluating the practical results of DOs. The outcomes suggest that, in some ways, the combined use of NDOs and N-NDOs leaves room for market players/applicants and the local government to negotiate DOs and other development possibilities. Compared with old factory owners as the applicant, the portion of DOs is higher if developers are the applicant. The applicants who contribute more DOs will strive for a higher floor area ratio bonus, especially when developers act as the applicant. In addition, redevelopment projects located in less developed regions are required to contribute more DOs than those in highly urbanized areas. Our research findings also demonstrate that, in other ways, negotiation disappears, and obligations are charged through non-negotiable statutory urban redevelopment planning. Specifically, projects redeveloped for residential use contribute more DOs than those for industrial use. Moreover, redevelopment projects in higher density zones must contribute more portions of DOs than those in lower density zones. This study provides valuable guidance for policy makers and practitioners to pursue well-designed and properly regulated DOs in urban redevelopment and ultimately achieve sustainable public infrastructure financing. • The combined use of non-negotiable (N-NDOs) and negotiable developer obligations (NDOs) in bottom-up urban redevelopment of Shenzhen brings about varying practical results of contributed obligations. • Compared with the old factory owner as the applicant, the portion of DOs is higher if the developer is the applicant. • The applicant who contributes more DOs will strive for a higher FAR bonus, especially when the developer acts as the applicant. • Redevelopment projects located in less developed regions are required to contribute more DOs than those in highly urbanized areas. [ABSTRACT FROM AUTHOR]

Background: With the rapid escalation of global urbanization, the role of blue-green spaces in urban ecology, public health, and planning has become increasingly prominent. Although their contributions to ecological preservation, public health, and urban design are widely acknowledged, research into public engagement and willingness to participate in the management and planning of these spaces is still in its early stages. Objective: This study aims to identify key factors influencing public willingness to participate in blue-green space management, focusing specifically on people's perceptions of blue-green spaces (including perceived quality and accessibility), their usage behaviors (i.e., frequency of usage of blue-green spaces), and their self-assessed physical and mental health. Methods: We interviewed local residents through random sampling to obtain sample data, and used a representative sample (n = 815, 510 women; 305 men, age 18–85 years, lived in Chengdu for an extensive time) of residents living in Chengdu City, China. Employing a quantitative approach, we examined the relationships between factors such as gender, regular occupation, income, behavior, and health status in relation to the willingness to participate. Additionally, we explored how perceptions and behaviors impacted health statuses and, consequently, inclinations to participate. Results: The findings indicate that individuals with steady occupations and higher incomes are more inclined to engage in the management and planning of blue-green spaces. Notably, men exhibited a greater tendency to participate than women. Furthermore, access to blue-green spaces emerged as a crucial mechanism for addressing health disparities, offering significant implications for urban planning and public health. Conclusion: Successful blue-green space planning and understanding of willingness to participate necessitates the holistic consideration of people's perceptions of blue-green spaces, their usage behaviour and their self-rate health. For a tangible impact on health equity and global urban development, it's essential to prioritize blue-green spaces in planning, especially in lower-income regions. This not only promotes environmental perception but can also be a strategic approach to address health disparities. Our findings offer vital insights for tailoring international urban planning and management practices towards these goals. • Key factors affecting public engagement in urban blue-green space initiatives are perception, income, and health status. • Perception, behavior, and health level can directly affect residents' willingness to participate. • Individuals with higher incomes are more inclined to participate in blue-green space management. • Enhancing blue-green spaces contribute to bridging the gap in health inequalities. • Enhanced blue-green spaces address health disparities, benefiting lower-income communities. [ABSTRACT FROM AUTHOR]

Developing urban underground space for transportation and commercial purposes has become a vital strategy for sustainable urban growth, especially in dense urban contexts. The vitality of underground space has received wide attention as a key indicator of its efficiency and performance. The spatial vitality of underground space is affected by many factors, including function, spatial configuration, transport environment, and pedestrian-oriented design features. This study takes the underground space of Shanghai Hongqiao Business District (Phase I), one of the most successful integrated railway station-city development projects, as a case to explore the spatial and temporal distribution characteristics of spatial vitality and its influencing factors. Multilevel linear models were used to analyze the relationship between pedestrian flow and its influencing factors. Random forest models were used to investigate the relative importance of influencing factors on spatial vitality. This study verified that the distance to the transportation hub and spatial configurations calculated by space syntax are the two most essential factors for vitality. The number of retail stores and walkway width impact the vitality on weekends. The results shed light on our understanding of the urban vitality in the underground space and provide some tentative suggestions for the planning and design of underground space in high-density cities. [ABSTRACT FROM AUTHOR]

Urban resilience studies often prioritize the investigation of sudden and short-lived natural disasters, while overlooking the gradual emergence and enduring nature of pandemics. The COVID-19 crisis, a quintessential example of such a challenge, has elicited significant but underexplored shifts in the landscape of urban public events. This research, drawing on social sensing geospatial datasets, aims to examine the changes in public events prior to, during, and after the fifth wave of COVID-19 in Hong Kong. Employing a dynamic time warping-based clustering algorithm alongside multiple linear regression analysis, we endeavor to address two pivotal questions: (1) How have the patterns of public events transformed in response to the pandemic? (2) What factors significantly influence these changes? The findings reveal that: Temporally, the implementation of social distancing measures is correlated with a marked reduction in public event frequency, reflecting the extensive impact of the COVID-19 crisis. Spatial analysis reveals that while public events are concentrated in Hong Kong's central areas, the spread of confirmed COVID-19 cases is more evenly distributed, with only a weak correlation observed between event hotspots and case distributions. Furthermore, our analysis identifies three distinct temporal patterns of public event changes, underscoring a higher resilience of events in urban centers against pandemic-induced disruptions. Additionally, built environment factors are found to be positively correlated with the decline in events as per the impact ratio, while socio-demographic factors more significantly affect the recovery ratio of events post-pandemic. This study not only pioneers in providing a comprehensive framework for monitoring urban events during a pandemic but also offers crucial insights into urban dynamics and vitality. These findings are invaluable for shaping more effective public health policies and crisis management strategies, enhancing urban resilience in face of future pandemics. • This study addresses resilience from a slow-onset and long-standing pandemic perspective. • Social sensing geospatial datasets enhance fine-grained tracking of public activities. • Activity resilience is defined by COVID-19's impact and the recovery extent after COVID-19. • The driving mechanism of activity resilience is explored from the built environment and socio-demographic aspects. • The research framework provides insights into urban dynamics and allows policymakers to introduce better policies. [ABSTRACT FROM AUTHOR]

Despite many prior studies about the determinants of city-level private car ownership in China, limited studies investigate the effects of vehicle regulation policies and relative price (the ratio of the average car price to GDP per capita) on city-level private car ownership simultaneously. Thus, panel data of 212 cities in China from 2006 to 2015 were collected to explore these effects. The potential explanatory variables include relative price, vehicle regulation policies, socio-economic factors, urban characteristics of the city, and transportation-related factors. The pooled model, fixed-effects model, and random effects model are constructed to analyze the panel data. With the fixed effect on the temporal trend, the fixed-effects model turns out to be the best. Variables including relative price, license plate lottery, vehicle use restriction based on the last digit of the license plate, the average salary of employed workers, and the number of taxis per 10,000 population are all found significant. Supportive policies for alternative fuel cars do not significantly affect private car ownership. One percent increase in the relative price is associated with a 0.08% decrease in private car ownership. The license plate lottery and vehicle use restriction policies would reduce private car ownership by 18.94% and 7.7%, respectively. The finding of this study could provide a helpful reference for policymakers to develop appropriate measures to control the growth of private car ownership of a city. • Determinants of city-level car ownership are revealed based on data of 2006–2015. • Pooled OLS model, fixed-effects model, and random-effects model are compared. • Supportive policies for alternative fuel vehicles do not influence car ownership. • 1% increase in relative car price is related to 0.08% decrease in car ownership. • Implementation of vehicle use restriction leads to 7.7% decrease in car ownership. [ABSTRACT FROM AUTHOR]

• The impact of e-scooter sharing on the usage of bike sharing is explored using Chicago data. • The weekly usage of bike sharing in e-scooter sharing operation area declined by 10.2% due to the impact. • Usage of bike sharing by members and non-members declined by 4% and 34% respectively. • Bike sharing usage during workday peak hours and other times did not change and declined. As a new type of shared micromobility, e-scooter sharing first appeared in the United States and became popular worldwide. Considering e-scooter sharing and bike sharing have similar service attributes, the ridership of bike sharing may be affected by the introduction of e-scooter sharing. To date, studies exploring this impact are limited. In this study, we seek to analyze the impact of e-scooter sharing on the usage of bike sharing from trip data of e-scooter sharing and bike sharing in Chicago for a total of 30 weeks. We rely on a difference-in-differences modeling approach based on the propensity score matching method. We found that the average duration of e-scooter trips is shorter than that of bike trips. The introduction of e-scooter sharing reduced the overall bike sharing usage by 23.4 trips per week per station (10.2%). bike sharing usage of non-members and members decreased by 18.0 (34.1%) and 5.4 (4.0%) trips, and that of male and female members decreased by 3.3 (3.1%) and 2.0 (7.3%) trips, respectively. Furthermore, the volume of short-, medium-, and long-duration trips of bike sharing decreased by 10.9 (7.5%), 5.4 (9.6%), and 3.4 trips (20.5%), respectively. Finally, bike sharing use during non-peak hours decreased but was not affected during peak hours. [ABSTRACT FROM AUTHOR]

• Waiting time (WT) is used as an indicator of equity of ridesouricng service. • Trip, socioeconomic and built environment factors influence WT in Austin, TX. • WT is positively related to traffic condition, surge multiplier, and rainy weather. • WT is negatively related to road density, transit stop density, and land-use entropy. • WT is higher in areas with high fraction of Hispanic/Latino and Black residents. Waiting time (WT) is an important measure that can reflect accessibility to ridesourcing service. Previous studies explored the effects of built environment factors on WT based on estimated WT but did not control for trip-level characteristics, which may lead to biased parameter estimation. Thus, we further study this topic by using the actual WT recorded by the RideAustrin platform and considering trip-level variables. The single-level and multilevel proportional hazards models are constructed, and model comparison shows that the multilevel model performs better. We find that waiting time is positively correlated with trip-level characteristics such as traffic conditions, surge multiplier, and rainy weather. Regarding built environment factors, WT is positively related to distance to CBD and negatively related to road density, transit stop density, and land-use entropy. WT is also higher in areas with a high fraction of Hispanic/Latino and Black residents but lower in areas of low income. [ABSTRACT FROM AUTHOR]

• Relationship between the built environment (BE) and metro ridership (MR) is explored. • Four calendar events are considered during the modeling of the BE-MR relationship. • Global (OLS) and local (GWR) regression approaches are adopted. • BE factors that significantly affect MR are unlike between workdays and non-workdays. This study examines the associations between the built environment (BE) and metro ridership (MR) during different calendar events (workdays, weekends, Spring Festival, and Valentine's Day) in Shenzhen. Utilizing 18-day metro smart card and points of interest (POIs) data, we employ ordinary least squares (OLS) and geographically weighted regression (GWR) models to compare the BE-MR relationship across different calendar events. The findings show that MR during different calendar events follows the pattern: unofficial holiday (Valentine's Day) > workdays > weekends > public holidays (Spring Festival). Moreover, BE factors significantly affecting MR differ between workdays and non-workdays, with slight differences observed among non-workdays (i.e., weekends and holidays). Specifically, during non-workdays, especially Spring Festival, metro trips related to leisure and tourism activities are more prevalent in the southwest area of Shenzhen, while potential cross-city travel is more active in the north. On workdays, metro trips associated with hotel check-in activities concentrate in central urban areas (e.g., Luohu and Futian districts), whereas they are more active in the northeast suburbs during the Spring Festival. These findings can aid in predicting metro usage, enabling more efficient and productive resource allocation. [ABSTRACT FROM AUTHOR]

Dockless bike-sharing (DBS) has proliferated worldwide. Despite DBS's great potential to reduce air pollution, air pollution may also reduce the usage of DBS. However, not much research attention has been paid to the effects of air pollution on DBS usage. Existing attempts have mostly relied on traditional data sources and intended to establish associations, not causalities. To address this research gap, we compile a panel data set with more than 50 million DBS trip records and high-frequency air quality and weather monitoring readings over a 92-day period in Chengdu, China. We then estimate the causal effects of air pollution on DBS usage using an instrumental variable approach. We find that a 10 μg/m3 increase in PM 2.5 concentrations leads to a 2.5% reduction in DBS usage. Furthermore, such adverse effects are particularly pronounced among young DBS users, during non-peak hours, for long-distance trips, and in census tracts with low housing prices. [ABSTRACT FROM AUTHOR]

Ridesourcing is popular in many cities. Despite its theoretical benefits, a large body of studies have claimed that ridesourcing also brings negative externalities (e.g., inducing trips and aggravating traffic congestion). Therefore, many cities are planning to enact or have already enacted policies to regulate its use. However, these policies' effectiveness or impact on ridesourcing demand and traffic congestion is uncertain. To this end, this study applies difference-in-differences (i.e., a regression-based causal inference approach) to empirically evaluate the effects of the congestion tax policy on ridesourcing demand and traffic congestion in Chicago. It shows that this congestion tax policy significantly curtails overall ridesourcing demand but marginally alleviates traffic congestion. The results are robust to the choice of time windows and data sets, additional control variables, alternative model specifications, alternative control groups, and alternative modeling approaches (i.e., regression discontinuity in time). Moreover, considerable heterogeneity exists. For example, the policy notably reduces ridesourcing demand with short travel distances, but such an impact is gradually attenuated as the distance increases. [ABSTRACT FROM AUTHOR]

It has been well established that the infrastructural development for rail transit stimulates rail transit use. However, there is little agreement about the source of the increased rail transit use. Using data from two repeated cross-sectional surveys, we examine changes in individual travel behavior resulting from the introduction of a rail transit line in Hong Kong. To address some methodological limitations inherent to repeated cross-sectional research design (e.g., selection bias and longitudinal incomparability), a two-dimensional propensity score matching method (2DPSM) is adopted to pair samples between the treatment and control groups in both cross-sectional and longitudinal dimensions. Paired t -tests are used to compare the longitudinal changes in travel behavior between the treatment and control groups of the matched samples. To get a more comprehensive understanding of the net treatment effects of the new rail line on travel behavior, we examined its impacts on both home-based trips (trips originating or terminating at home) and all trips for both treatment and control group. For home-based trips, the opening of the new rail line increased the rail mode share by 10.4%, and rail trip number by 0.126 (in terms of net effect, i.e., difference in the change between treatment and control group). It reduced the bus mode share by 17.1% and bus trip number by 0.208, showing a significant bus-to-rail modal shift. For all trips, the new rail line increased rail mode share by 9.5% and total trip number by 0.189. It also decreased bus mode share by 13.2%, and bus trip number by 0.191. Hence, the source of the increased rail transit use came from both the modal shift from bus and the increased travel demand induced by the new transit infrastructure. For both home-based trip and all trips, there was no significant influence on car use and total trip distance. Our findings provide new evidence that the development of rail transit in a high-density urban setting encourages a modal shift from bus to rail transit and stimulates flexible travel behaviors, but fails to control private vehicle use. • We applied a 2DPSM approach combined with paired t -tests to identify the influence of a rail transit line on travel behavior (including both home-based trips and all trips) by using data from repeated cross-sectional surveys in Hong Kong. • For both home-based trip and all trips, the new rail line had a positive effect on rail transit use, and had a negative influence on bus use. • There was a positive relationship with the total number of all trips, but non-significant association with that of home-base trips, which indicated that the increase in rail transit ridership may partly come from increased non-home-based travel demand created by the new rail line. • The development of rail transit in a high-density urban setting encourages a modal shift from bus to rail transit and stimulates flexible travel behavior, but fails to control private vehicle use. [ABSTRACT FROM AUTHOR]

The adjustment of urban spatial structure in the process of urbanization and suburbanization leads to the separation of work and residence, which further leads to long-distance commuting. While there has been a lot of research on long-distance commuting in Western countries, the relevant studies in China are not enough. In the Chinese context, some factors deserve special attention, namely the hukou system and occupation. However, few studies have focused on the individual and interaction effects of these two factors on long-distance commuting. This paper explores the commuting behavior of different socioeconomic groups in Xiamen, China. Heckman's sample selection model was applied to data from the 2015 Xiamen household travel survey to separate the effect of socioeconomic factors and that of residential selection. Results show that the continued suburbanization of the industry attracted substantial numbers of blue-collar workers to live in the outer districts (Haicang, Jimei, Tong'an, and Xiang'an), and thus blue-collar workers are less likely than pink- and white-collar workers to be long-distance commuters in the outer districts. Among residents of the outer district, pink-collar migrants and white-collar migrants are more likely to be long-distance commuters than their local counterparts, while blue-collar migrants (a coefficient of −0.153) are less likely to be long-distance commuters than blue-collar locals (a coefficient of −0.046). For people who live in the inner districts, blue-collar locals (a coefficient of 0.256) are more likely to be long-distance commuters than blue-collar migrants (a coefficient of −0.029). These results have practical significance for providing alternative housing for migrants in urban renewal. [ABSTRACT FROM AUTHOR]

Urban redevelopment has been widely acknowledged as a cure for the urban diseases relevant to urban deterioration, decayed environment, and limited land supply in the process of rapid urbanization and economic development in Chinese megacities. Given the slow and inefficient progress of traditionally state-dominated redevelopment because of high transaction costs, Shenzhen has been authorized to pioneer market-oriented urban redevelopment. Our study aims to assess how institutional innovations in urban redevelopment affect the market value of redevelopment projects. In line with this goal, major institutional innovations in market-oriented urban redevelopment are identified and analyzed. Furthermore, a number of hypotheses on whether these innovative rules affect the market value of redevelopment projects are developed. Two-stage regression models are employed, and all existing 183 urban redevelopment projects are used as samples to test these hypotheses. Our empirical findings indicate that the market premium (MP) of redevelopment projects is higher if the developer is the applicant compared with old factory owners, village committees, or the local government department as the applicants. Redevelopment projects from old residential properties gain a higher MP than those from old factory buildings. The MP of redevelopment projects from old factories on state-owned land is higher than that on collective-owned land. MP is higher for projects sited in larger urban redevelopment areas and for projects constructed with the public school as the developer obligation. These MP performances incurred by different institutional arrangements in market-oriented urban redevelopments have barely been revealed in previous studies. This study serves as a valuable reference for the government to make tailor-made land value capture schemes so as not to lose public value increases or kill redevelopment projects. • Institutional arrangements play an important role in shaping price premium performance of urban redevelopment projects. • Institutional arrangements are differed by the nature of the applicants who have different sets of property rights and apply for land redevelopment rights. • The market premium (MP) of a redevelopment project is highest if the developer is the applicant. • The MP of the redevelopment projects arising from old urban villages or old urban residential communities is higher than that of the projects from old factories on state-owned or collective-owned land. • The MP is higher for projects sited in larger redevelopment areas and for projects contributing public schools as developer obligations. [ABSTRACT FROM AUTHOR]

Understanding the relationship between the built environment and e-scooter sharing (ESS) usage is important because it could help planners determine the high-demand area and design an effective investment plan to promote the use of micromobility. Previous studies usually assume that the relationship is linear, which may lead to inaccurate ridership prediction and ineffective policy. Thus, this study explores the nonlinear and threshold effects of the built environment on ESS ridership in Los Angeles using the gradient boosting decision tree. Fourteen built environment and ten demographic variables are selected as independent variables. We find that the built environment accounts for 91.66% of the total relative importance. The ten most important variables are intersection density, road density, public transit station density, restaurant density, employment density, distance to the center, population density, proportion of park area, parking density, and bike lane density. The nonlinear and threshold effects of the built environment on ESS ridership are determined. By using two spatial analysis units (census tract and census block group) and four temporal analysis units (spring, summer, autumn, and winter), the modifiable areal unit problem and the modifiable temporal unit problem are revealed. [ABSTRACT FROM AUTHOR]

Many studies have confirmed that the characteristics of the built environment affect individual walking behaviors. However, scant attention has been paid to population-level walking behaviors, such as pedestrian volume, because of the difficulty of collecting such data. We propose a new approach to extract citywide pedestrian volume using readily available street view images and machine learning technique. This innovative method has superior efficiency and geographic reach. In addition, we explore the associations between the extracted pedestrian volume and both macro- and micro-scale built environment characteristics. The results show that micro-scale characteristics, such as the street-level greenery, open sky, and sidewalk, are positively associated with pedestrian volume. Macro-scale characteristics, operationalized using the 5Ds framework including density, diversity, design, destination accessibility, and distance to transit, are also associated with pedestrian volume. Hence, to stimulate population-level walking behaviors, policymakers and urban planners should focus on the built environment intervetions at both the micro and macroscale. • Population-level walking behaviors were represented by street-level pedestrian volume at a large scale in Shanghai, China. • Pedestrian volume and street-level built environment were extracted from street view images using machine learning. • Both macro- and micro-scale built environment were simultaneously considered including 5D variables and street-level characteristics at a large scale. • Macro-scale built environment measured by 5Ds framework were associated with pedestrian volume. • Micro-scale built environment such as street-level greenery, open sky, and sidewalk were associated with pedestrian volume. [ABSTRACT FROM AUTHOR]

Bicycle-metro integration is an efficient method of solving the "last mile" issue around metro stations. Built environment is believed to have a significant effect on cycling behavior. However, transfer cycling around metro stations, as a specific type of cycling behavior, has often been overlooked in transport research. In addition, static contextual units such as circular or street-network buffers are typically used to delineate metro catchment areas of transfer cycling trips. These methods are inaccurate to represent the actual geographic contexts of cycling trips, according to the uncertain geographic context problem (UGCoP). Thus, in this study, bicycle-metro catchment areas are delineated based on aggregating the end points of over three million transfer cycling trips. The impact of the built environment on transfer cycling behavior is also explored. First, we find that the aggregate-points buffer outperforms traditional static buffers in predicting transfer cycling trips. Second, we also identify a high level of spatial heterogeneity in catchment area and transfer cycling density between urban and suburban areas. Third, residential and working population density, bus stop density, and metro stations accessibility have a significant effect on bicycle-metro transfer cycling. [ABSTRACT FROM AUTHOR]

Electric scooter (e-scooter) sharing systems (ESSs) have been widely adopted by many cities around the world and have attracted a growing number of users. Although some studies have explored the usage characteristics and effects of the built environment on ESS ridership using one city as an example, few studies have considered multiple cities to obtain generalizable and robust results. To fill this research gap, we collect the ESS trip data of five cities in the U.S., namely Austin, Minneapolis, Kansas City, Louisville, and Portland, and explore the effects of the built environment on ESS ridership after controlling for socioeconomic factors. The temporal distributions of e-scooter ridership of different cities are similar, having a single peak period on weekdays and weekends between 11:30 and 17:30. In terms of spatial distribution, the ESS ridership is higher in universities and urban centers compared to other areas. Multilevel negative binomial model results show that ESS trips are positively correlated with population density, employment density, intersection density, land use mixed entropy, and bus stop density in the census block group. E -scooter ridership is negatively correlated with the median age of the population in the census block group and distance to the city center. The findings in this article can help operators understand the factors that affect the ridership of shared e-scooters, determine the changes in ridership when the built environment changes, and identify high-ridership areas when ESS is implemented in new cities. • The effect of built environment on e-scooter ridership (ER) is studied. • Trip data of five cities are analyzed to obtain more generalizable and robust result. • Temporal variation of ER of different cities exhibits similar pattern. • ER increases with population, employment, intersection density, and mixed land use. • ER decreases with median age of the population and distance to the city center. [ABSTRACT FROM AUTHOR]

Background: The growth of urban dwelling populations globally has led to rapid increases of research and policy initiatives addressing associations between the built environment and physical activity (PA). Given this rapid proliferation, it is important to identify priority areas and research questions for moving the field forward. The objective of this study was to identify and compare research priorities on the built environment and PA among researchers and knowledge users (e.g., policy makers, practitioners)., Methods: Between September 2022 and April 2023, a three-round, modified Delphi survey was conducted among two independent panels of international researchers (n = 38) and knowledge users (n = 23) to identify similarities and differences in perceived research priorities on the built environment and PA and generate twin 'top 10' lists of the most important research needs., Results: From a broad range of self-identified issues, both panels ranked in common the most pressing research priorities including stronger study designs such as natural experiments, research that examines inequalities and inequities, establishing the cost effectiveness of interventions, safety and injuries related to engagement in active transportation (AT), and considerations for climate change and climate adaptation. Additional priorities identified by researchers included: implementation science, research that incorporates Indigenous perspectives, land-use policies, built environments that support active aging, and participatory research. Additional priorities identified by knowledge users included: built environments and PA among people living with disabilities and a need for national data on trip chaining, multi-modal travel, and non-work or school-related AT., Conclusions: Five common research priorities between the two groups emerged, including (1) to better understand causality, (2) interactions with the natural environment, (3) economic evaluations, (4) social disparities, and (5) preventable AT-related injuries. The findings may help set directions for future research, interdisciplinary and intersectoral collaborations, and funding opportunities., (© 2023. Crown.)

Urban heat challenges are increasingly severe, along with climate change and urbanisation. Despite significant environmental, economic, and social consequences, limited actions have been conducted to address urban heat challenges. To support the formulation of heat-health plans and guidelines at the city and community scale, this study presented results, through a questionnaire survey among 584 respondents in Shanghai, China, on heat-induced physiological and psychological impacts and analysed the variability of them with demographic characteristics. The results indicate that psychological impacts were more severe than physiological impacts in severity and susceptible people. Skin heat damage and digestive system diseases were ignored in previous studies, compared with fatal cardiovascular and respiratory diseases. Emotional irritability and difficulty in controlling temper were the two most prominent psychological symptoms. The elderly and health-vulnerable groups were more susceptible to heat-induced physiological and psychological impacts than other groups. Among different demographic groups, the most critical physiological and psychological symptoms could vary significantly. Afterwards, suggestions for heat-health plans or guidelines have been proposed. Overall, this study provides a reference for the understanding of heat-induced impacts and enhancing the capacity to cope with urban heat challenges., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)