Re-assess Meaningful Urban Spaces: Sensing Auckland social 'hotspots' with mobile location data under the COVID-19 impact

Abstract

The global COVID-19 outbreak has deeply affected everyone’s daily life and constrained human mobility behaviors by the preventive measures put in place to mitigate the transmission. Different mass media channels and live location data streaming techniques have contributed to tracking the spread and predicting the trajectory of the pandemic developments. Moreover, the human mobility patterns hidden in these digital datasets – if properly interpreted- can document and reflect how people cope with the ‘paradoxical’ daily activities when public life and social encounter are prohibited. In this research, we utilize the mobile location data collected from January 2019 to date within Auckland city, New Zealand, to explore the social impacts on urban ‘hotspots’ concerning the transformation of social behaviors. The urban ‘hotspots’ here refer to user-defined urban spaces with crowded human mobility and intensive social and economic activities regardless of their designated urban programs. We first construct the human-geographical networks and compare the pre- and post-COVID-19 pandemic human mobility patterns with respect to visitors' density and diversity. By mapping the density and diversity patterns, we can capture and derive insights from urban ‘hotspots’ spatial distribution changes to identify the adoptable urban space typologies that are quintessential places during the disruptive crisis. The research findings provoke rethinking on our urban spaces design and planning strategies and contribute to better-informed decisions towards resilient urban life environment while countries worldwide are slowly resuming normalcy.

Qingqing Chen

PhD Candidate | Data Scientist

Ph.D. candidate focuses on critically understanding urban space by leveraging big data, combined with data science and machine learning techniques.