Profile and theoretical advances in urban big data studies: A systematic review of 57 representative journals (2013–2023)

As big data becomes increasingly integral to urban studies, the evolving profile of its applications, including the trends in data, methodologies, and contributions to urban theories, remains unclear. This study systematically reviewed literature from 57 representative journals in the fields of Urban Studies, Geography, and Environmental Studies (JCR Q1) over the past decade (2013–2023), with a focus on quantitative research involving urban spatial big data. A total of 1,425 articles were identified through automated keyword filtering and manual screening, of which 82 were selected for further analysis due to their theoretical contributions. The results revealed key thematic areas, including urban transportation, spatial quality, vitality, and structure, with a predominant focus on developed countries and large cities. The applications of big data and novel methodologies in urban studies have increased from 2013 to 2023, with increasingly higher levels of spatiotemporal resolution. However, studies linking big data to urban theories remained limited, with most quantitative research centered on applying or proposing new methods or uncovering new phenomena. Theoretical contributions primarily explored the mechanisms underlying urban environment formation and their impacts on human activities and behaviors. This study provides a comprehensive understanding of big data applications and advances in theories in urban spatial studies and highlights key directions for future research.