PUBLICATIONS LIST
*Corresponding author
10. Lu, Y.*, & Ye, Y. (2019). Can people memorize multilevel building as volumetric map? A study of multilevel atrium building. Environment and Planning B: Urban Analytics and City Science, 46(2), 225-242. (Click for full text of PDF)
The question of whether multilevel buildings are memorized as volumetric map or collection of floors is central to spatial cognition and wayfinding studies about multilevel buildings. The stacked-floor buildings used in previous studies may limit people’s ability to integrate floors into a volumetric mental map. In this study, we assessed wayfinding and cognitive performances of 31 participants in a multilevel shopping mall with five atriums which provided adequate visual access and smooth floor transitions. (1) In the wayfinding task, we observed path choice for 31 participants in this mall. The participants’ choice for all path segments, also vertical path segments, clearly gravitated toward the most accessible spaces in the whole building, rather than most accessible space within individual floors. (2) Participants were also asked to identify the locations where they can see maximum number of stores. The identified locations can be reliably predicted by objectively measured three-dimensional visibility information, but not two-dimensional visibility information. (3) In the pointing task, participants can accurately point to out-of-sight targets in the same floor and in the different floor, in both azimuth and elevation direction. In sum, those findings suggest that people can memorize a multilevel atrium building as a volumetric map. This study also demonstrates the usefulness of developing three-dimensional configurational variables to explain human spatial behavior and spatial cognition.
9. Wu, X., Lu, Y.*, Lin, Y., & Yang, Y. (2019). Measuring the destination accessibility of cycling transfer trips in metro station areas: A big data approach. International journal of environmental research and public health, 16(15), 2641. (Click for full text of PDF)
Many studies have established that urban greenness is associated with better health outcomes. Yet most studies assess urban greenness with overhead-view measures, such as park area or tree count, which often differs from the amount of greenness perceived by a person at eye-level on the ground. Furthermore, those studies are often criticized for the limitation of residential self-selection bias. In this study, urban greenness was extracted and assessed from profile view of streetscape images by Google Street View (GSV), in conjunction with deep learning techniques. We also explored a unique research opportunity arising in a citywide residential reallocation scheme of Hong Kong to reduce residential self-selection bias. Two multilevel regression analyses were conducted to examine the relationships between urban greenness and (1) the odds of walking for 24,773 public housing residents in Hong Kong, (2) total walking time of 1994 residents, while controlling for potential confounders. The results suggested that eye-level greenness was significantly related to higher odds of walking and longer walking time in both 400 m and 800 m buffers. Distance to the closest Mass Transit Rail (MTR) station was also associated with higher odds of walking. Number of shops was related to higher odds of walking in the 800 m buffer, but not in 400 m. Eye-level greenness, assessed by GSV images and deep learning techniques, can effectively estimate residents’ daily exposure to urban greenness, which is in turn associated with their walking behavior. Our findings apply to the entire public housing residents in Hong Kong, because of the large sample size.
8. Lu, Y*. (2019). Using Google Street View to investigate the association between street greenery and physical activity. Landscape and Urban Planning, 191, 103435. (Click for full text of PDF)
Urban greenspaces have been demonstrated to have associations with physical activity and health. Yet empirical studies have almost exclusively focused on parks rather than street, although streets are among the most popular venues for physical activity and street greenery is an indispensable component of urban greenspaces. Even fewer greenspace-physical activity studies have objectively assessed eye-level street greenery. By using free Google Street View images, this study assessed both the quantity and quality of street greenery and associated them with the recreational physical activity occurring in green outdoor environments of 1390 participants in 24 housing estates in Hong Kong. After controlling for socio-demographic characteristics and other built environment factors, multilevel regression models revealed that the quality and quantity of street greenery were positively linked to recreational physical activity. Our finding is important for interpretations of the operational mechanisms between street greenery and health benefits because it demonstrates that physical activity is an intermediate health-related outcome. The findings also reveal the influences of eye-level street greenery on residents’ physical activity levels and hence contribute to the development and implementation of healthy cities to stimulate physical activity.
7. Lu, Y.*, Chen, L., Yang, Y., & Gou, Z. (2018). The association of built environment and physical activity in older adults: Using a citywide public housing scheme to reduce residential self-selection bias. International journal of environmental research and public health, 15(9), 1973. (Click for full text of PDF)
Many studies have established that urban greenness is associated with better health outcomes. Yet most studies assess urban greenness with overhead-view measures, such as park area or tree count, which often differs from the amount of greenness perceived by a person at eye-level on the ground. Furthermore, those studies are often criticized for the limitation of residential self-selection bias. In this study, urban greenness was extracted and assessed from profile view of streetscape images by Google Street View (GSV), in conjunction with deep learning techniques. We also explored a unique research opportunity arising in a citywide residential reallocation scheme of Hong Kong to reduce residential self-selection bias. Two multilevel regression analyses were conducted to examine the relationships between urban greenness and (1) the odds of walking for 24,773 public housing residents in Hong Kong, (2) total walking time of 1994 residents, while controlling for potential confounders. The results suggested that eye-level greenness was significantly related to higher odds of walking and longer walking time in both 400 m and 800 m buffers. Distance to the closest Mass Transit Rail (MTR) station was also associated with higher odds of walking. Number of shops was related to higher odds of walking in the 800 m buffer, but not in 400 m. Eye-level greenness, assessed by GSV images and deep learning techniques, can effectively estimate residents’ daily exposure to urban greenness, which is in turn associated with their walking behavior. Our findings apply to the entire public housing residents in Hong Kong, because of the large sample size.
6. Lu, Y*. (2018). The association of urban greenness and walking behavior: Using google street view and deep learning techniques to estimate residents’ exposure to urban greenness. International journal of environmental research and public health, 15(8), 1576. (Click for full text of PDF)
Many studies have established that urban greenness is associated with better health outcomes. Yet most studies assess urban greenness with overhead-view measures, such as park area or tree count, which often differs from the amount of greenness perceived by a person at eye-level on the ground. Furthermore, those studies are often criticized for the limitation of residential self-selection bias. In this study, urban greenness was extracted and assessed from profile view of streetscape images by Google Street View (GSV), in conjunction with deep learning techniques. We also explored a unique research opportunity arising in a citywide residential reallocation scheme of Hong Kong to reduce residential self-selection bias. Two multilevel regression analyses were conducted to examine the relationships between urban greenness and (1) the odds of walking for 24,773 public housing residents in Hong Kong, (2) total walking time of 1994 residents, while controlling for potential confounders. The results suggested that eye-level greenness was significantly related to higher odds of walking and longer walking time in both 400 m and 800 m buffers. Distance to the closest Mass Transit Rail (MTR) station was also associated with higher odds of walking. Number of shops was related to higher odds of walking in the 800 m buffer, but not in 400 m. Eye-level greenness, assessed by GSV images and deep learning techniques, can effectively estimate residents’ daily exposure to urban greenness, which is in turn associated with their walking behavior. Our findings apply to the entire public housing residents in Hong Kong, because of the large sample size.
5. Lu, Y.*, Sarkar, C., & Xiao, Y. (2018). The effect of street-level greenery on walking behavior: Evidence from Hong Kong. Social Science & Medicine, 208, 41-49. (Click for full text of PDF)
Accumulating evidence shows that urban greenspaces have great health benefits, but establishing a causal relationship is difficult. It is often hypothesized that walking and physical activity are mediators in the relationship between urban greenspaces and health outcomes. Furthermore, most urban greenspace–physical activity studies have focused on parks rather than on landscaped streets, even though the latter are the most popular places for physical activity. The lack of research attention for landscaped streets is largely due to the fact that street greenery is difficult to measure, especially at eye level.
Using readily available Google Street View images, we developed methods and tools to assess the availability of eye-level street greenery. A two-layered study was developed that 1) examined the association between urban greenspaces and the odds of walking (versus not walking) for 90,445 participants in the Hong Kong Travel Characteristics Survey and 2) carried out sensitivity analysis of the association between urban greenspaces and total walking time for a subset of 6770 participants. Multilevel regression models were developed to reveal the associations between street greenery and walking behaviors while controlling for sociodemographic characteristics and other activity-influencing built environment factors, taking into account the inherent clustering within the data.
The results showed that both street greenery and the number of parks were associated with higher odds of walking; street greenery but not parks was associated with total walking time. Our results suggest that walking behavior is at least as strongly affected by eye-level street greenery as by parks. They also implicitly support the health benefits of urban greenspaces via walking and physical activity. With the large sample size, our findings pertain to the entire population of Hong Kong. Furthermore, the use of Google Street View is a sound and effective way to assess eye-level greenery, which may benefit further health studies.
4. Lu, Y.*, Sun, G., Sarkar, C., Gou, Z., & Xiao, Y. (2018). Commuting mode choice in a high-density city: Do land-use density and diversity matter in Hong Kong?. International journal of environmental research and public health, 15(5), 920. (Click for full text of PDF)
Hong Kong is a densely populated and transit-oriented Chinese city, which provides an ideal urban environment with which to study the various successful facets of land use policy as a model for potential replication to curb increasing car use in other Chinese cities. We examine the commuting mode choice of 203,900 households living in 4768 street blocks in Hong Kong from 2011 census. A street block is the smallest planning unit, made up of one or more housing estates with a homogenous built environment and socioeconomic status. The built environment is measured using the five Ds framework, an international dimensioning framework for classifying and measuring attributes of the built environment for physical activity and travel behaviors. Generalized, multi-level mixed models were applied to detect the associations between travel choice and built environment characteristics, while adjusting for socioeconomic status. Design and destination accessibility had greater effects on the choices to walk and take public transport than on the choice to drive. Density and diversity had only marginal effects on mode choice. Unexpectedly, distance to the urban center had the opposite effect on automobile use to that found in Western studies. Hong Kong residents living close to the urban center were more likely to drive for commuting trips. The contrasting findings between our study and Western studies suggest that the associations between a high-density built environment and travel choice vary with urban context.
3. Lu, Y.*, Gou, Z., Xiao, Y., Sarkar, C., & Zacharias, J. (2018). Do transit-oriented developments (TODs) and established urban neighborhoods have similar walking levels in Hong Kong?. International journal of environmental research and public health, 15(3), 555. (Click for full text of PDF)
A sharp drop in physical activity and skyrocketing obesity rate has accompanied rapid urbanization in China. The urban planning concept of transit-oriented development (TOD) has been widely advocated in China to promote physical activity, especially walking. Indeed, many design features thought to promote walking—e.g., mixed land use, densification, and well-connected street network—often characterize both TODs and established urban neighborhoods. Thus, it is often assumed that TODs have similar physical activity benefits as established urban neighborhoods. To verify this assumption, this study compared walking behaviors in established urban neighborhoods and transit-oriented new towns in Hong Kong. To address the limitation of self-selection bias, we conducted a study using Hong Kong citywide public housing scheme, which assigns residents to different housing estates by flat availability and family size rather than personal preference. The results show new town residents walked less for transportation purpose than urban residents. New town residents far from the transit station (800–1200 m) walked less for recreational purpose than TOD residents close to a rail transit station (<400 m) or urban residents. The observed disparity in walking behaviors challenges the common assumption that TOD and established urban neighborhoods have similar impact on walking behavior. The results suggest the necessity for more nuanced planning strategies, taking local-level factors into account to promote walking of TOD residents who live far from transit stations.
2. Lu, Y.*, Sarkar, C., Ye, Y., & Xiao, Y. (2017). Using the Online Walking Journal to explore the relationship between campus environment and walking behaviour. Journal of Transport & Health, 5, 123-132. (Click for full text of PDF)
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An online mapping questionnaire was developed to collect walking route and intention.
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Physical environmental characteristics associate with walking on a corporate campus.
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Street networks supporting campus-to-surrounding continuity impact walking.
1. Lu, Y.*, Xiao, Y., & Ye, Y. (2017). Urban density, diversity and design: Is more always better for walking? A study from Hong Kong. Preventive Medicine, 103, S99-S103. (Click for full text of PDF)
Many cities in China have undergone rapid urbanization and are experiencing a decline in residents' physical activity levels. Previous studies have reported inconsistent findings on the association between 3D's (density, diversity, design) and walking behavior, and few studies have been conducted in China. The aim of this study was to identify the association between objectively measured 3D's and different domains of walking (transport vs. leisure) in Hong Kong, China. A survey was conducted in 2014 to collect walking data and relevant individual data from 1078 participants aged 18–65. The participants were randomly selected from 36 Hong Kong housing estates with different built environment and neighborhood socioeconomic status (SES). Built environment factors—population design, land-use mix and street intersection density—were assessed using a geographic information system. Multi-level regression was used to explore the associations between walking behavior and built environment factors, while adjusting for covariates. Two out the three D's—land-use mix and street connectivity—are not significantly related to any domains of walking. Furthermore, the third D, population density, is only positively related to walking for transport and walking for leisure in the lower range of density, while is negatively related to walking for leisure in the higher range of density. The findings suggest that the association between original 3D's and walking may vary in different urban contexts. The policy or planning strategy—using three D's to promote physical activity—may be ineffective or even counterproductive in large and already dense cities in China.