PUBLICATIONS LIST
*Corresponding author
40. Chen, L., Zhao, L., Xiao, Y., & Lu, Y.* (2022). Investigating the spatiotemporal pattern between the built environment and urban vibrancy using big data in Shenzhen, China. Computers, Environment and Urban Systems, 95, 101827. (Click for full text of PDF)
Promoting urban vibrancy is one of the major objectives of urban planners and government officials, and it is linked to various benefits, such as urban prosperity and human well-being. There is ample evidence that built environment characteristics are associated with urban vibrancy; however, the spatiotemporal associations between built environment and urban vibrancy have not been fully investigated owing to the inherent limitations of traditional data. To address this gap, we measured spatiotemporal urban vibrancy in Shenzhen, China, using Tencent location-based big data, which is characterized by fine-grained population-level spatiotemporal granularity. Built environment characteristics were systematically measured using the 5D framework (density, diversity, design, destination accessibility, and distance to transit) with multi-source datasets. We investigated the spatiotemporal non-stationary associations using a geographically and temporally weighted regression (GTWR) model. The results indicated that the GTWR models achieved better goodness-of-fit than linear regression models. Built environment factors such as population density; point of interest (POI) mix; residential, commercial, company, and public service POI; and metro station were significantly associated with urban vibrancy. Time series clustering revealed spatiotemporal clustered patterns of the associations between built environment factors and urban vibrancy. To promote urban vibrancy with urban planning and design strategies, both the spatial and temporal associations between the built environment and urban vibrancy should be considered.
39. Chen, L., Lu, Y.*, Liu, Y., Yang, L., Peng, M., & Liu, Y. (2022). Association between built environment characteristics and metro usage at station level with a big data approach. Travel Behaviour and Society, 28, 38-49. (Click for full text of PDF)
Transit-oriented development (TOD) planning strategy has been widely implemented worldwide to formulate dense, mixed-use built environment in the past three decades. The primary goal of TOD is to promote public transit usage including both transit mode share and ridership. Research supports that built environment characteristics around metro stations affect residents' travel behaviors and metro usage. However, the evidence remains inconsistent in different urban contexts. Furthermore, research focusing on mode share such as commuting trips at station level is still scarce. In this study, a rule-based model was used to identify commuting trips using metro service with smart card data (SCD), covering more than 90 percent of all metro passengers in Wuhan, China. Built environment characteristics around metro stations were measured with a 3Ds framework (density, diversity, and design). Results suggest that population density is negatively associated with metro commuting mode share, while street intersection shows a positive relationship. Office-oriented urban function and street intersection are positively correlated with metro ridership. Hence, exploring the fine-grained relationship of metro usage and built environment factors around transit stations in different urban and social contexts warrants further research attention.
38. Jiang, Y., Wang, S.*, Ren, L., Yang, L., & Lu, Y.* (2022). Effects of built environment factors on obesity risk across three types of residential community in Beijing. Journal of Transport & Health, 25, 101382. (Click for full text of PDF)
Introduction
There is strong evidence in Western cities that neighborhood-level characteristics of the built environment are linked with a higher risk of overweight or obesity among residents. Due to the rapid urbanization during the last several decades, many types of residential community have formed and coexisted in the major cities of China. These communities provide residents with different built-environment features and lifestyles. However, it remains unclear whether the community type affects the risk of overweight and obesity among residents.
Methods
The present study investigated the associations of built-environment characteristics and the bodyweight status (normal vs. overweight or obese) of 4,440 residents from three main types of community (i.e., commercial, work-unit, and traditional communities) in Shijingshan district, Beijing. Multilevel logistic regression and the random forest approach were adopted to investigate both the significance and relative importance of neighborhood-level factors of the built environment.
Results
The results of multilevel logistic regression suggest that the community type has a significant association with the obesity risk. In addition, the land-use mix, the number of water features, the number of supermarkets and groceries, street intersections, and the normalized difference vegetation index are negatively related to the odds of obesity. The number of transit stops is positively associated with the odds of obesity. Random forest analysis reveals significant disparities in the relative importance of population structure and the built environment factors among the three types of community. Furthermore, we find a notable difference between the results of the multilevel logistic model and random forest model. Hence, both the significance and relative importance of neighborhood-level factors of the built environment should be considered.
Conclusions
The findings indicate that the community type has a significant association with the risk of overweight. Tailored policies and urban renewal interventions should be developed for different community types.
37. Chen, L., Lu, Y.*, Ye, Y., Xiao, Y., & Yang, L. (2022). Examining the association between the built environment and pedestrian volume using street view images. Cities, 127, 103734. (Click for full text of PDF)
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.
36. Xie, H., He, Y., Wu, X.*, & Lu, Y.* (2022). Interplay between auditory and visual environments in historic districts: A big data approach based on social media. Environment and Planning B: Urban Analytics and City Science, 49(4), 1245-1265. (Click for full text of PDF)
Historic districts play a vital role in stimulating urban economic development, conserving regional culture, and enhancing public participation. Both auditory and visual environments, and the interplay between them, are critical to visitors’ perception and evaluation of historic districts. However, most studies have explored either the auditory or visual environments separately. The handful of existing studies on audiovisual interaction were confined to laboratory environments, leading to limited external validity. Here, we performed a data-driven study of the features of auditory and visual environments and the interaction between them in 17 historic towns in China using posts containing soundscape-related keywords and streetscape photos from a popular Chinese social media platform. First, we found that the auditory environments in historic districts mainly consist of man-made sounds from folkloric activities, the sounds of street shop vendors, and natural sounds from running water and birds. Second, street greenery, spatial enclosure, and presence of pedestrian in visual environment are positively associated with emotional feedback of the soundscape. This study and others support the importance of studying the auditory and visual environments of historic districts in conjunction. The innovative methods used in this study can be used in further studies in the field.
35. Xie, B., Lu, Y.*, & Zheng, Y. (2022). Casual evaluation of the effects of a large-scale greenway intervention on physical and mental health: A natural experimental study in China. Urban Forestry & Urban Greening, 67, 127419. (Click for full text of PDF)
Many cross-sectional studies have supported the health benefits of urban greenways. However, the causal relationship between urban greenway intervention and residents’ physical and mental health remains unclear. Furthermore, the potential dose-response effect by distance to a greenway intervention remains unknown. This study explored the impact of a large-scale urban greenway intervention (construction of a 102-km-long East Lake Greenway in Wuhan, China) on the health outcomes of residents by using a natural experimental research design. We collected data before and after the intervention (in 2016 and 2019, respectively) from 1,020 participants living within a 5-km street-network distance from the entrances of this greenway. The average age of the participants was approximately 50, and most of them were married. More than half of the participants were female, currently employed, and had received a college education or above. Mixed-effects difference-in-difference (DID) models were used while controlling for individual and neighbourhood covariates. The results showed that the East Lake Greenway had a positive effect on the self-reported mental health of residents who lived within 2 km, and these benefits decreased with distance. The physical health benefit was insignificant. To increase the health benefits of urban greenways, more effort should be made to improve the accessibility of greenways and the surrounding environment. We also advocate that future natural experiments should explore the distance-varying dose-response effect of green space interventions on health outcomes.
34. Wang, R., Grekousis, G., & Lu, Y.* (2022). Rethinking the link between the availability of neighborhood PA facilities and PA behavior: a comparison between private and public housing. Building and Environment, 207, 108401. (Click for full text of PDF)
To examine whether residential self-selection bias influence the associations between neighborhood physical activity (PA) facilities and respondents' PA behavior. This study uses a natural experimental research design. Three waves of China Family Panel Studies data were used. The outcome variables were the weekly duration and frequency of PA. The availability of neighborhood PA facilities was measured using the presence of PA facilities and the number of PA facilities within residential neighborhoods. Multilevel regression models were used to examine the relationships between the availability of neighborhood PA facilities and respondents' PA behavior, adjusted for covariates. Associations were stratified by two groups (those living in private housing vs. public housing). Residents of private housing can choose their residential location, whereas those in public housing have little freedom to do so. Therefore, comparing these two groups can help us determine whether residential self-selection bias exists. The results show that both the presence and number of neighborhood PA facilities are positively associated with the frequency and duration of PA among residents of private housing. However, the evidence does not support an association between the availability of neighborhood PA facilities and PA behavior among residents of public housing. Residential self-selection bias may have a pronounced effect on the findings of studies of the association between neighborhood PA facilities and individuals’ PA behavior. Therefore, it is important to control for residential self-selection bias when examining built environment–PA associations.
33. Jiang, Y., Chen, L., Grekousis, G., Xiao, Y., Ye, Y., & Lu, Y.* (2021). Spatial disparity of individual and collective walking behaviors: A new theoretical framework. Transportation research part D: transport and environment, 101, 103096. (Click for full text of PDF)
The creation of walkable environments, and the promotion of walkability for health and environmental benefits have been widely advocated. However, the term “walkability” is often associated with two related but distinct walking behaviors: individual and collective walking behaviors. It is unclear whether spatial disparity exists between them, and whether built environment characteristics have distinctive effects on them.
This research was the first to explore the spatial disparity between the two types of walking behaviors. Collective walking behaviors were measured using the citywide pedestrian volume, extracted from 219,248 street view images. Individual walking behaviors were measured form a population-level survey. Spatial mismatches were found between the two types of walking behaviors and built environment elements had stronger associations with collective walking behaviors. Therefore, it is prudent to theoretically differentiate collective and individual walking behaviors, and targeted planning policies must be developed to promote one or both types of walking behaviors.
32. Wu, X., Lu, Y.*, Gong, Y., Kang, Y., Yang, L., & Gou, Z. (2021). The impacts of the built environment on bicycle-metro transfer trips: A new method to delineate metro catchment area based on people's actual cycling space. Journal of transport geography, 97, 103215. (Click for full text of PDF)
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.
31. He, D., Lu, Y.*, Xie, B.*, & Helbich, M. (2021). Large-scale greenway intervention promotes walking behaviors: A natural experiment in China. Transportation research part D: transport and environment, 101, 103095. (Click for full text of PDF)
Extensive evidence from cross-sectional studies has revealed a positive link between greenspace access and walking behaviors. However, the inherent weaknesses of the cross-sectional research design have provided little causal inference. In this natural experimental study, we assessed the effects of a large-scale greenway intervention (i.e., the opening of East Lake greenway) on walking behaviors in Wuhan, China. Longitudinal survey data on 1,020 participants were collected before and after the intervention in 2016 and 2019, respectively. The results of the mixed-effect difference-in-difference (DID) models showed that the greenway intervention had a significantly positive effect on the walking time, especially for residents living within two kilometers from the greenway. Furthermore, women and socio-economically disadvantaged people benefited most from the greenway implementation regarding walking time. Our findings provided compelling evidence that public investment in transportation infrastructure (e.g., greenway) effectively promotes walking behaviors and mitigates social inequities in physical activity.