Urban greenery has been recognized as a potential influential factor in shaping people’s travel behavior and promoting physical activity and health among citizens. However, its effectiveness has been inconclusive due to the various methods to assess urban greenery and ambiguous causal inference between urban greenery and travel behaviors.

This thesis aims to provide robust evidence on the impact of urban greenery on daily travel behavior by assessing multiple dimensions of urban greenery (overhead view and eye-level greenery) and multiple research design (cross-sectional and quasi-natural experimental design). Four case studies were conducted to identify the impact on active travel and travel mode choice.

The first case study explored the association between urban greenery and odds of cycling. Urban greenery was measured objectively by using two methods: overhead view greenery by normalized difference vegetation index (NDVI) and eye-level street greenery by Google Street View (GSV) images. Results from multilevel logistic regression models suggest that the odds of cycling are positively associated with eye-level street greenery but not with overhead view greenery across three buffer zones: 400, 800, and 1600 m.

The second case study focused on the association between eye-level street greenery and walking behavior, including the odds of walking and total walking time for older adults. A two-step multilevel analysis strategy was adopted. Findings from this study indicate that street greenery assessed by GSV is positively associated with the odds of engaging in walking and total walking time of older adults.

The third case study examined the complex relationships among urban greenery, active school travel, and body weight status of primary school students. Urban greenery was assessed in different dimensions by three measures: number of parks, NDVI based on satellite imagery, and street greenery based on GSV. Results from multilevel regression analysis suggest that children attending schools in greener surrounding areas are likely to engage in active school travel and have lower body mass index (BMI). Findings from structural equation modeling support that active school travel partially mediates the impact of urban greenery on BMI.

The last case study targeted the causal inference between urban greenery improvement and change in travel mode choice. A unique two-dimensional propensity score matching (2DPSM) method was applied to establish a panel dataset on the basis of two large-scale repeated cross-sectional surveys of travel characteristics. Such quasi-natural experimental study design addresses the selection bias and longitudinal incomparability between the datasets. The improvement of urban greenery was used as an intervention to investigate the change in individual travel mode choice. Results demonstrate that an increase in overall greenery level is positively associated with an upward trend in the share of bus mode choice.

This thesis addresses the debate on measurement and lack of understanding about causal inference of urban greenery in travel behavior in high dense city. Findings from current thesis support that street greenery provides better estimates of daily greenery exposure and serves as a reliable and superior predictor of active travel behavior. In addition, evidence supports that greenery improvement encourages the ground public transportation use. This thesis contributes to the existing literature by providing an innovation measuring approach for urban greenery and relatively robust evidence on the causal inference of urban greenery on individual daily travel behavior in high dense city. The findings provide important practical implications of sustainable urban planning for high dense cities facing pressures related to prevalence of physical inactivity and increased private automobile usage.