Urban greenness, mixed land-use, and life satisfaction: Evidence from residential locations and workplace settings in Beijing

Abstract

<p>China's unprecedented urbanisation in the last several decades has significantly transformed its urban built environment. On the one hand, such an urbanisation has brought about improvement in infrastructure, access to various public facilities, and opportunities for social connectivity, all of which would benefit citizen's wellbeing. On the other hand, rapid, unplanned, and unregulated urbanisation may lead to air pollution and water pollution, compact neighbourhoods, traffic noise and congestion, and lack of natural amenity, which pose various threats to urban dwellers’ wellbeing and life satisfaction. Therefore, how to build liveable cities has become one of the key goals and top priorities of urban planning in China and other developing countries. This study investigates the effect of urban greenness and mixed land-use, two key dimensions defining urban liveability, on residents’ life satisfaction at both residence and workplace settings in Beijing. Three big geo-coded datasets are combined, including a social survey about residents’ subjective life satisfaction and demographic characteristics, eye-sensored street greenness data extracted from online platform through machine learning, and fine-grain land-use data based on point-of-interest entropy, and then taken into a Bayesian multilevel ordered logit model. The empirical results reveal that (1) street view greenness could enhance life satisfaction at residence, but depress life satisfaction at workplace; (2) mixed land-use could positively contribute to life satisfaction at both residence and workplace; and (3) there exist positive interactions between greenness and mixed land-use. These empirical findings provide practical implications for planning and constructing liveable cities in China and other countries where both urban greening and mixed land-use are promoted and embraced as core elements of the compact city and smart city ideal.</p>