Context (archaeology)

Gentrification

Demography

Inequality

Ecology

Biology

Statistics

Bivariate analysis

Archaeology

Operating system

Socioeconomic status

Economics

Computer science

Mathematics

Geography

Environmental resource management

Population

Urban green space

Sustainable development

Sociology

Mathematical analysis

Economic growth

Space (punctuation)

Machine learning

Landscape and Urban Planning

Green space accessibility is widely acknowledged as a crucial aspect of a livable environment and human well-being. Whether green space accessibility is equitable among communities is increasingly considered as an issue of environmental justice. Therefore, this study focuses on the possible environmental inequality of green space accessibility that can be found among residential communities in the context of Chinese booming housing market. The case study of Shanghai, China was conducted with the use of big data. A real-time navigation route measurement based on Amap application programming interface (AAPI) was developed to calculate green space accessibility, and housing price was used to indicate dwellers’ socioeconomic status. Bivariate Moran’s I, multiple regression, and spatial lag regression were adopted to explore inequality of green space accessibility among residential communities. The results reveal a spatial inequality of green space accessibility between communities in central portion of the city and those in peri-urban areas. We further found a spatial mismatch between green space accessibility and housing price. Environmental inequality is evident within the inner and middle ring road wherein wealthier communities benefit more from green space accessibility than disadvantaged communities. We attribute these findings to spatial restructuring and green gentrification process in Shanghai. The findings can inform planners and policymakers to determine where and how to implement greening strategies and to gain awareness to prevent environmental inequality.

Which communities have better accessibility to green space? An investigation into environmental inequality using big data