Search

The UNESCO label of World Heritage can attract a high number of tourists to heritage properties for their Outstanding Universal Values (OUV). Although international studies have demonstrated the World Heritage system can contribute to stimulating cultural tourism and boosting the local economy, how this heritage-led development process promotes urban conservation and morphological changes in cities is yet to be explored adequately. This paper aims to explore the urban morphology of a historic Chinese city after its inscription on the UNESCO World Heritage List, taking the Old Town of Lijiang as case. The methods of spatial plan analysis and discourse analysis are used to analyse the data. The research findings have demonstrated that, theoretically, the Conzenian approach of urban morphology can be an effective framework for World Heritage OUV -monitoring. Methodologically, the analysis of spatial plans and multi-stakeholder interviews can reveal local urban morphology from macro to micro levels. Case-specifically in Lijiang, urban physical characteristics and building structures have been well maintained while traditional social fabric and neighbourhood networks have almost vanished. This research has incorporated the urban morphology approach into (world) heritage management in China, as well as worldwide, in order to maintain the balance between urban conservation and economic growth. [ABSTRACT FROM AUTHOR]

Loneliness may contribute to chronic diseases, while neighbourhood green space is increasingly understood to benefit health. However, whether green space is associated with loneliness is less understood, especially for an ageing population. This study aims to explore the relationship between different measures of green space and loneliness among middle-aged and older adults (N = 8383) based on a national cohort. Loneliness was measured with a yes-or-no (binary) self-reported question, while the availability of residential green space was assessed with the normalised difference vegetation index (NDVI) and proportion of neighbourhood public parks. Multilevel logistic regression models, stratified and mediation analysis were used to test whether green space availability was associated with loneliness. The results showed that both forms of residential green space were negatively associated with the risk of loneliness, even after adjustments for covariates. These associations were partially mediated by social cohesion and modified by socioeconomic status and age; residents who were males, at least 60 years old, had lower incomes, or had no high school degree showed protective associations of residential green space on loneliness in some stratified models. These findings indicate that residential green space plays an important role in loneliness risk reduction in middle-aged and older adults, so policymakers can consider urban greening as part of their comprehensive plans to support the mental health of ageing adults. [ABSTRACT FROM AUTHOR]

• Enhance the CA-Markov model by incorporating additional parameters to predict land use change around railway stations. • Validate the enhanced model by simulating land use changes around Dujiangyan station. • Put forward the optimization strategy for the coordinated development of transport and land use. Predicting land use change around railway stations is crucial for facilitating the coordinated development of transport and land use. Previous studies have seldom focused on simulating and predicting small-scale land use changes at a railway station. Therefore, this study employs an enhanced Cellular Automata-Markov (CA-Markov) model, aiming to achieve simulations and predictions with heightened precision. Firstly, two additional driving factors, namely accessibility to railway stations and the kernel density of points of interest (POIs), are incorporated into the CA-Markov model. Secondly, the validation of the enhanced model is achieved through simulating land use changes around Dujiangyan Station. Finally, this model is applied to predict land use around Mianzhu South Station in 2026, and optimization strategies for railway station areas are proposed. The results indicate an 83.43-hectare reduction in farmland area, accompanied by a moderate increase in 35.8 hectares of forest land and 41.52 hectares of residential land. This enhanced model provides valuable technical support for strategic planning in railway station areas. [ABSTRACT FROM AUTHOR]

Abstract Understanding the underlying behavioral mechanism of tourist destination choices is the first and foremost step in establishing effective and appropriate management measures for a scenic area. Few studies have used high-resolution and fine-grained spatio-temporal data to develop sophisticated statistical models for uncovering micro-scale tourist movements. This study combined Global Positioning Systems (GPS) and conventional questionnaire survey data of 312 respondents from Gulangyu, China, a small island with a total area of 1.87 km2, to develop multinomial logit (MNL) models for identifying factors that affect tourists' destination choices. A market segmentation analysis for different ticket purchasers was then performed. The Watson and Westin pooling test demonstrated that destination choices vary significantly between joint- and single-ticket purchasers. Joint-ticket purchasers are shown to be a more regular group whose mobility behavior can be better predicted and modeled compared with single-ticket purchasers. Several policy implication are discussed based on the modeling results. The proposed modeling, findings, and discussions provide the basis for policy instruments and will be useful for the enhanced planning of on-site movement, improved regulation of tourist flows, and rationalized design and management of tourist destinations. Highlights • Develop discrete choice models to depict tourist destination preference. • Identify significant factors that affect tourists' intra-destination choices. • Perform a market segmentation analysis for different ticket purchasers. • Observe that joint-ticket purchasers' behaviors are easier to be modeled. • Combine GPS technologies and statistical models to understand tourist behavior. [ABSTRACT FROM AUTHOR]

Highlights • Propose a transit accessibility measure that considers transfer. • Enrich existing land use plan evaluation methods by incorporating a transit accessibility measure. • Evaluate the performance of urban land use plan in a transit-dominated and car-lite context using the presented approach. Abstract This study proposes a measure to evaluate the urban land use plan with transit accessibility, more specifically, the spatial accessibility of transit stations. The spatial accessibility of transit stations is measured with the number of effective reachable grids, and the influence of transfer on reduction in spatial accessibility is considered. A geographically weighted regression model is used to determine the correlation between transit accessibility and urban land use characteristics. Moreover, the methodology is applied to Xiamen, China and the corresponding results demonstrate the usefulness and effectiveness of the proposed methodology. Researchers can adopt the proposed approach to evaluate urban land use plan, particularly in transit-dominated and car-lite contexts. [ABSTRACT FROM AUTHOR]

The escalating prevalence of extreme heat events has intensified scholarly interest in understanding the nexus between urban built environments and extreme heat. This study focuses on the central urban areas of Chengdu and Chongqing, sizable Chinese cities that share a common building climate zone but are divergent in topography and landform (i.e., plain versus mountainous). Leveraging spatial regression, XGBoost, and Shapley additive explanation techniques, we scrutinize the spatial effects, relative importance, and interactive impacts of two-dimensional and three-dimensional (2D/3D) built environments on land surface temperature (LST). The results indicate that: (1) 2D/3D variables exert significant effects on LST, with the cooling effect of the 3D green view index outweighing that of the 2D normalized difference vegetation index (NDVI). (2) The overall relative importance of 3D variables on LST is greater than that of 2D variables in both Chengdu and Chongqing. (3) The 3D variables have particularly strong impacts on LST in mountainous cities, which are 6.21 % higher than those in plain cities. (4) 2D/3D variables interactively influence LST. For instance, LST drops in Chengdu when floor area ratio (FAR) is above 1.5 and NDVI is below 0.53, as well as when FAR is less than 1 and NDVI is greater than 0.53. Our findings provide support and recommendations for location-specific sustainable urban development and effective heat adaptation strategies. • Leverage machine learning and Shapley additive explanation (SHAP). • The most powerful cooling is delivered by FAR. • The overall importance of 3D variables is greater than that of 2D. • The impact of 3D variables is higher in mountain cities compared to plain cities. • There are interactive effects between 2D and 3D built environment variables. [ABSTRACT FROM AUTHOR]

An easily applied and efficiently exploited approach was proposed for the prediction of inter- and intra-annual land surface temperature (LST) in a city's central zone. Chengdu is chosen as the study area to demonstrate the applicability of the novel approach. Built-up areas were extracted using Landsat images in 2008, 2013, and 2019 and projected for 2030 using the cellular automata-Markov chain model, indicating that built-up areas grew nearly 109% during 2008–2019 in Chengdu and will continue to grow up to 2030. Employing the multiple linear regression, the LST of built-up areas in 2019 was predicted using the normalized difference built-up index (NDBI) and the mean LST of its surrounding pixels (LST-R3) in 2013 (R2 = 0.981). The model's intra-annual application for 2019 showed a mean LST deviation of 0.93 °C. According to the model's inter-annual application, the projected LST of the built-up areas in 2030 will increase to 36.5 ± 2.0 °C. The results can contribute to achieving a thermally comfortable urban environment by providing insights into the impact of urban expansion on the urban heat island (UHI) phenomenon under the limited availability of continuous LST data. • High cloud coverage in Chengdu City limits continuous satellite-based monitoring of land surface temperature (LST). • To overcome this constraint, an integrated urban growth and LST prediction approach is proposed. • The training of the LST model involves the utilization of NDBI and LST of surrounding pixels. • The performance of the model in predicting inter- and intra-annual LST is satisfactory. • The model contributes toward creating a thermally comfortable urban environment. [ABSTRACT FROM AUTHOR]

Ecosystem services (ES) concepts and approaches have become more appealing to practice, such as municipal/urban planning, environmental policies and governance to address sustainable development. Inclusion of this concept in the planning or policy discourses is the first step for further implementation on the ground. Using China's capital, Beijing, as the case study, this article analyzes how ES (or similar concepts) have permeated China's urban development history since 1949 when the New China was established and how this has to be with China's urban green space development. The results show: (1) There were no explicit references to "ecosystem services" per se, but overlapping concepts such as "functions", "values" and "benefits" can be found in planning documents and, importantly, the lack of the concept per se has not affected the detailed services that emerged in all plans. (2) Among the three ES sections, only cultural services run from the beginning to end although the included services kept changing. Other sections show considerable variation and less continuity – the focal services of each stage changed over time. (3) Through the ES lens, some general patterns regarding China's urban development can be found such as regulation services gradually become valued for their own sake. The patterns found in Chinese planning documents are then compared with some western regions. This study reveals limitations of the past and opportunities for the future to inform urban development decision-making. Adaptation of old and incorporating new ES concepts can improve the quality of plans and foster cities' ability to learn from past patterns for future sustainability. • Analyzing how ecosystem services (ES) have permeated China's urban development. • The study is based on coding and analyzing discourse and document contents. • Through ES lens, general patterns can be found in China. • Cultural services play a pivotal role in urban development history. • Opportunities exist in the "non-mainstream" ES to incorporate more ES into plans. [ABSTRACT FROM AUTHOR]

• Effects of future climatic uncertainties on building retrofit decisions are estimated. • Life-cycle economics and carbon emissions are selected as the multiple objectives. • Future climatic uncertainties alter optimal values of some building retrofit measures. • Optimal infiltration standard and insulation options are susceptible to future climate. • Optimal glazing materials and shading options are not susceptible to future climate. Energy consumption of and carbon emissions from buildings, which substantially depend on outdoor climate conditions, may be susceptible to future climate change. However, how future climatic uncertainties affect decision-making regarding building energy retrofits is unclear from the life-cycle analysis perspective. This study used typical high-rise public rental housing buildings in subtropical Hong Kong as a case study to consider future climatic uncertainties under representative concentration pathway scenarios and in different general circulation models to estimate their effect on multi-objective building retrofit decisions considering trade-offs among different objectives, namely, life-cycle economics, life-cycle carbon emissions, and operational energy use impacts. The results indicate the significant influence of future climatic uncertainties on the optimal values of building energy retrofit measures. The passive house infiltration standard and thick (0.06–0.1 m) polyurethane foam insulation can be recommended for long-term future climatic conditions (RCP8.5–2065s). By contrast, optimal values of glazing materials, horizontal shading projection factors, and window-to-wall ratio are not susceptible to future climatic uncertainties. Uncertainties from different general circulation models are another notable factor affecting optimal values and retrofit options. This study reveals the importance of considering future climatic uncertainties when deciding optimal values and selecting building energy retrofit options. [ABSTRACT FROM AUTHOR]

• Use mobile phone signaling data to assess urban vitality. • Call for temporally and spatially varying policies for urban vitality enhancement. • The spatial distribution of urban vitality is clustered and polycentric. • Urban vitality varies considerably throughout the day. • The effects of metro accessibility are more evenly distributed on weekends. Urban vitality has long been a focus of urban planners and designers. This study portrays the spatiotemporal patterns of urban vitality in Chengdu, China, on weekdays and weekends and examines their relationship with a set of factors using spatial regression and geographically weighted regression models. The results reveal that the spatial distribution of urban vitality displays a clustered and polycentric pattern, which can be attributed to urban spatial structure. Urban vitality varies considerably throughout the day on weekdays and weekends, and it consistently decreases as the distance to the city center increases. Furthermore, weekday vitality is much more predictable (less random) than weekend vitality, indicating that human activity patterns present higher regularity on weekdays than on weekends. The normalized difference vegetation index (NDVI), road density, the number of residential facilities, and land-use mix have positive influences on urban vitality on weekdays and weekends, while the distance to the metro station has negative influences. The influences of NDVI on urban vitality in the city center are negative on weekdays but become positive on weekends. The influences of the distance to the metro station are more homogeneously distributed on weekends than on weekdays. Finally, this study calls for temporally and spatially varying policies for urban vitality enhancement. [ABSTRACT FROM AUTHOR]

Optimizing the built environment helps alleviate the adverse impact of extreme heat on public health and sustainable urban development. To this end, this study measured the daily land surface temperature (LST) in August 2022 (when extreme heat occurred) in Chengdu and introduced the 3D street view characteristics extracted from street view images. By employing OLS and spatial regression models, we probed the combined effects of 2D and 3D built environments on LST and their relationships under disparate circle spaces. The results show that: (1) compared with the 2D built environment, the 3D built environment presents a superior impact on LST. (2) urban land use that is 3D, compact, and has a high-floor area ratio diminishes LST, as evidenced by the finding that floor area ratio (FAR) reduces LST, but building density enhances it. (3) the green view index exhibits a stronger cooling effect than green space areas. (4) the built environment beneath distinct circle spaces displays a spatially varying impact on LST. For example, FAR is positively correlated with LST in the urban center, while in the urban periphery, it is prominently negative. Our empirical findings are conducive to formulating strategies from both 2D and 3D built environments for the formation and implementation of healthy urban design and development. • In 2022, extreme heat has risked public health and urban sustainable development. • 3D, rather than 2D, environment has superior impacts on LST. • FAR reduces—whereas building density increases—LST. • The green view index shows a stronger cooling effect than that of green space area. • Built environment and LST have spatially varying impacts in distinct circle spaces. [ABSTRACT FROM AUTHOR]

• Short EBSS trips mainly substitute walking and the BSS. • Long EBSS trips mostly substitute cars, buses, and the subway. • The integration of the EBSS and transit has reduced carbon emissions. • The CO 2 emissions per km are 19.47 g. • The EBSS has saved 75.52% of CO 2 emissions. This paper presents a quantitative analysis of the mode substitution and usage-phase carbon emission impacts of the electric bike-sharing system (EBSS) on urban transportation using self-administrated survey data and EBSS operating data. The substitution probabilities of a given EBSS trip for different transport modes is determined using the Bayesian inference method. Emission impact is measured by comparing the current emissions to those generated by other transport modes without the EBSS. Remarkably, the partial-trip substitution impact of the EBSS on car travel is investigated, where the EBSS serves as a connection to public transit. The results show that the EBSS barely generates new trips; most short-distance EBSS trips were transferred from walking and conventional bike-sharing, and most long-distance trips were shifted from cars, buses, and the subway. Around 5% of EBSS trips less than 2 km were transferred from the car by integrating with public transit while accounting for over half of the emission reduction. Based on our method, the CO 2 emissions per km of EBSS are 19.47 g, with 6.91 g generated by e-bikes due to electricity consumption and 12.56 g by trucks for battery swapping and bike relocation. The studied EBSS has saved 75.52% of CO 2 emissions that other transport modes could have generated. [ABSTRACT FROM AUTHOR]

In recent years, cardiovascular diseases (CVDs) have become the primary cause of death in the world. Existing studies have found that greenspace is important for the prevention of CVDs and stroke. However, since they only focus on large green infrastructure (e.g., urban parks) or the general greenspace (usually being evaluated through normalized difference vegetation index), little information exists regarding the association between street-level greenspace and CVDs (stroke). In this study, the CVDs and stroke data of participants were retrieved from the 33 Chinese Community Health Study. We measured participants' exposure to street-level greenspace exposure using street view images and machine learning technique. Multilevel logistic regressions were applied. While controlling for confounders, we found that higher level of street-level greenspace exposure was associated with lower CVDs prevalence. However, street-level greenspace exposure was associated with stroke prevalence only for females. The associations were stronger among females, younger adults, participants with educational attainment above high school, physically active participants and participants who were not overweight. None of the mediators (air pollution, physical exercise, and BMI) can explain the associations between street-level greenspace exposure and CVDs (stroke) prevalence. Our findings suggest that street-level vegetation should be increased to cope with the rapid growth of the CVDs burdens. Also, the differences between the effect of street-level trees and grasses should be noted before formulating specific urban planning policies. • Deep learning and street view images were used to measure tree and grass exposure. • Street-level greenspace exposure was negatively associated with CVDs prevalence. • Street-level greenspace exposure was associated with stroke prevalence for female. [ABSTRACT FROM AUTHOR]

Urban redevelopment is a crucial prescription in response to the problems associated with limited land, urban decay, and fading buildings, especially for China's megacities. Given that state-dominated urban redevelopment is slow and limited, the Chinese government has proposed a pioneering market-oriented approach to drive urban redevelopment in Shenzhen. This study seeks to examine the impacts of market-oriented institutional arrangements on land redevelopment approval duration (LRAD) in China from the perspective of public and private interests. Various institutional arrangements are observed under the institutional change of urban redevelopment in Shenzhen, and they are differed by the nature of the applicants, including the original property owners (old factory owner (OFO)), their representatives (e.g., village committees (VC) and the government agency involved in redevelopment (URB)), and developers (DP , second-hand property owner). A number of hypotheses are developed, and empirical tests are conducted to verify or dismiss our hypotheses with the data in Shenzhen. The empirical findings indicate that (1) The LRAD is the shortest when the applicant is the OFO and the longest if the applicant is the local government officials such as URB. (2) Compared with the URB , the LRAD is shorter if the VC is the applicant. (3) The LRAD is longer for the projects with a larger redevelopment scale and the projects with more dedicated public facilities. The findings shed new insights into the design and practical effects of market-oriented institutional arrangements on the progress performance of urban redevelopment, which can give the local government a timely reminder that they should examine and approve urban redevelopment schemes in a soundly planned and socially sustainable fashion. • Under bottom up urban redevelopment, property owners are endowed with land redevelopment right and allowed to apply for redevelopment directly. • Institutional arrangements are differed by the nature of the applicant who owns different sets of property/land rights. • Land redevelopment approval duration (LRAD) is the shortest when the applicant is the sole private property owners. • LRAD is the longest if the applicant is the local government officials. • Compared with the local government, LRAD is shorter if village committee (VC) is the applicant due to lower agency cost. • LRAD is longer for the projects with a larger-scale redevelopment site and the projects with more developer obligations. [ABSTRACT FROM AUTHOR]

• 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]

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]

A significant increase in the older population has been observed in numerous cities. Understanding the correlates of older adults' mobility is, therefore, of critical importance to meet their needs and preferences. Based on multisource data, including Google Street View street images and Hong Kong Travel Characteristics Survey 2011 data, we developed a series of multilevel and geographically weighted logistic regression models to scrutinize the global and local associations between urban greenery (eye-level street greenery, the number of parks, and the normalized difference vegetation index (NDVI)) and the travel propensity of older adults. Notably, eye-level street greenery was assessed by using readily available street images and machine learning techniques. The modeling results reveal that eye-level street greenery has a positive effect on older adults' mobility, but the number of parks and the NDVI do not significantly affect the mobility. Robustness checks verified the plausibility of these findings. Furthermore, the effect of street greenery varies over space, larger in suburban areas than in urban areas. This study advances the understanding of relationships between urban greenery and travel behavior. [ABSTRACT FROM AUTHOR]

• URT has a positive effect on nearby housing prices. • Transfer stations have a larger effect on nearby property prices than regular stations. • The price effects of URT accessibility are stronger in the suburban area than in the urban. • Practical implications, such as differential, location-specific value capture schemes, are discussed. Urban rail transit (URT) is shown to mitigate numerous contemporary urban problems (e.g., traffic congestion and environmental degradation). To reap such gains, many Chinese cities have actively constructed URT and/or have been on their way of doing so. However, these URT projects often encumber local governments with debt. Value capture schemes can be used to finance URT development. To implement such schemes, we need to understand the relationship between URT and property prices. Despite numerous studies on this topic in other countries, limited empirical studies in urban China have been conducted. Moreover, most previous studies are silent on two issues that are important to value capture, namely: (1) whether transfer stations provide a larger housing price premiums than regular stations, and (2) whether the price effect of URT accessibility is more perceptible in the suburban area than that in the urban. This study contributes to our understanding of these issues by constructing a set of hedonic pricing models using price data from 722 residential complexes in the vicinity of a URT line in Shenzhen, China. Our empirical results show that (1) URT has a positive impact on nearby property prices; (2) the positive impact diminishes quickly as the distance to URT station increases; (3) transfer stations have a larger positive effect on nearby property prices than regular stations; and (4) the price effects of URT accessibility are stronger in the suburban area than in the urban. The first two findings are in line with most previous studies, but the last two findings are seldom reported in existing literature. Practical implications of our findings, such as differential, location-specific value capture schemes, are further discussed. [ABSTRACT FROM AUTHOR]

• Combine the use of Geodetector analysis, PCA, and the GWR model. • Present a novel approach to analyze complex spatially non-stationary relationships. • Assess the spatial variation of PM 2.5 concentrations in the Pearl River Delta region by using the proposed methodology. This study develops an augmented geographically weighted regression (GWR) model to analyze the spatial distribution of PM 2.5 concentrations through the incorporation of Geodetector analysis and principal component analysis (PCA). The modeling approach we propose allows an effective identification of important PM 2.5 drivers and their spatial variation. Geodetector analysis is used to select predictor variables that truly affect the dependent variable, and PCA is adopted to eliminate multicollinearity among the variables. The spatial distribution of PM 2.5 concentrations within the Pearl River Delta region, China, is analyzed using the augmented GWR model. The augmented GWR model has an obvious advantage of parsimony. Moreover, it significantly outperforms the traditional regression model. [ABSTRACT FROM AUTHOR]

Previous studies suggest that generally, access to public services has a positive impact on housing price. However, most of them are silent on whether the impact varies across different housing submarkets. In some contexts like China, compared with high-end counterparts, low-end housing purchasers, generally, have lower income and thus lower car availability (and transportation mobility). As such, they may prefer and attach a higher value to living in the proximity of basic public services (which are essential to life, such as transit). This is likely to be applicable to contexts where purchasing and/or using cars are not fully affordable for low-income households. We use 22,586 second-hand housing data in Xiamen (China) to assess the differential price impacts of access to basic public services in low and high-end submarkets. Results from two-sample two-tailed t -tests and F -tests and hedonic modeling confirm several findings: (1) there are systematic differences between access to basic public services in low- and high-end properties; (2) the two housing submarkets do not follow the same pricing mechanism; (3) access to transit, commercial centers, shopping centers, and sports and cultural centers has positive and significant price impacts in the low-end housing submarket. Yet, this is not the case in the high-end counterpart; (4) the effect of access to basic public services on housing price varies across the two submarkets: typically, access to basic public services has a larger positive price impact on low-end properties than on high-end ones; (5) interestingly, access to shopping centers has a larger price impact in the high-end housing submarket than in the low-end. The findings of this study basically support our hypothesis and also benefit policy prescription. As such, practical implications of the findings are discussed finally. Notably, our argument is that low-end properties buyers are more willing to pay for access to "basic" public services rather than that to premium/high-quality services. By contrast, based on scattered evidence from this study and existing literature, we suspect, though definitely cannot conclude, that high-end properties buyers have a predilection for premium/high-quality amenities, such as natural beauty and prestigious schools. [ABSTRACT FROM AUTHOR]

• Effects of accessibility to BRT stations and proximity to the BRT corridor on property prices in a Chinese city are simultaneously evaluated. • Accessibility to BRT stations is positively related to property prices, while proximity to the BRT corridor is negatively associated with the prices. • BRT provides higher accessibility benefits in peripheral areas, compared with central areas. • Many policy implications, such as value capture and reducing the negative externality of BRT corridor, are discussed. Bus rapid transit (BRT) is popular worldwide because it provides high-quality transit services at low costs. China is not an exception in this regard, and it tops the world rankings in BRT network expansion rate. Many studies conducted in the West have shown that BRT accessibility has a positive impact on nearby property prices (accessibility effect). Comparatively, few studies have been conducted in urban China. Moreover, there are even fewer empirical studies on the undesirable factors associated with proximity to the BRT corridor, such as noise, air pollution, and unpleasant visual scenes (proximity effect). Based on 16,165 housing samples in Xiamen (China), we estimated a set of, non-spatial and spatial, hedonic pricing models to simultaneously investigate the accessibility and proximity effects of BRT and tested whether or not accessibility-based premiums and proximity-induced discounts coexist in the housing market. Empirical results of this study suggest that: (1) accessibility to BRT positively affects nearby property prices; (2) proximity to the BRT corridor negatively affects property prices; and (3) accessibility to BRT has a stronger positive impact on property prices in peripheral areas than in central areas. Though the first outcome has been well recognized, the other two have rarely been studied in existing literature, thereby representing the potential contributions of this study. Finally, we proposed policy implications from these results. [ABSTRACT FROM AUTHOR]