Enclave-reinforced inequality during the COVID-19 pandemic: Evidence from university campus lockdowns in Wuhan, China

The COVID-19 pandemic has impacted urban life and created spatial and social inequalities in cities. The impacts of lifting full lockdown restrictions once fast-spreading and community-acquired infection waves were under control are still not fully understood.

Two phases shape the new inequality during the pandemic.

This study aims to explore spatial inequality reinforced in the intervals between the waves of infection during the COVID-19 pandemic. Enclave-reinforced inequality resulting from enclave-based lockdown policies in Chinese cities was investigated through an analysis of the impacts of university campus enclave closures on the accessibility and crowdedness of urban green spaces. Using a modified two-step floating catchment area (2SFCA) and inversed 2SFCA (i2SFCA) method, accessibility and crowdedness were calculated and compared under two different scenarios. Additionally, the Lorenz curve, Gini coefficient, and Theil index were used to measure and compare intra-city global and local inequalities under each scenario.

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Gated university campus and its implications for socio-spatial inequality: evidence from students’ accessibility to local public transport

Rapid urbanization has led to a massive transformation of urban space in China, spatially and socially. Its higher education has been growing much faster than ever before, along with an explosive increase of university students’ population. Different from the Western universities, a majority of Chinese university students are required to reside in gated campuses. Their accessibilities to public transport and subsequent spatial and social implications have been neglected in the literature.

Taking Wuhan city as a case study, this paper aims to examine the public transport service to gated university campuses and its impacts on spatial and social inequalities. The spatial accessibility is measured by four methods: proximity-based, gravity-based, population-weighted average, and competition-based, using population data at residential building level.

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The analysis of low-income people’s park green space accessibility based on 2SFCA in Wuhan

City park green space provide a free stage for low-income people who have low shopping and entertainment facilities consumption ability to rest, communicate and play, satisfying people’s spiritual and cultural needs.

Treating Wuhan city park green space as the research object, the paper uses the 2-Step Floating Catchment Area (2SFCA) to calculate the park green space accessibility based on walking, bicycle, and public transport. The Pearson correlation coefficient and Lorenz curve and the method of location entropy are used to analyze the matching degree and spatial matching pattern between park green space and low-income population spatial distribution.

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