A Systematic Literature Review of Big Data in Urban Studies

Abstract

The paper aims to explore the use of big data in urban studies by analyzing selected state-of-the-art studies in urban informatics that utilize big data to support urban decision-making. The study conducts exploratory research to gain insight into the association patterns of big data-related concepts. The researchers use the VOSviewer tool to analyze 30 selected references based on keyword occurrences, abstracts, and titles. The study also focuses on how the references handle decision support and examines the relationship network of decision support with other terms. The qualitative and quantitative analysis results are presented to show the association and numeric distribution of the terms. The paper finds that decision support in the selected studies is mainly provided through data-driven computational methods, spatial statistical methods, and mapping of the spatiotemporal pattern of urban phenomena. The reference studies mainly support decisions related to urban activities and functioning, user activities and movement, visiting, and urban perception. The study contributes to presenting the trend in big data studies for urban planning and decision-making.