The Synergy Between Remote Sensing and Social Sensing in Urban Studies: Review and perspectives

Xiaoyue Xing, Bailang Yu, Chaogui Kang, Bo Huang, Jianya Gong, Yu Liu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

Urban studies require a rich set of information sources and techniques that enable a comprehensive depiction of urban environments. Remote sensing captures physical characteristics of urban landscapes, while social sensing collects data from social media and digital devices to reflect human activities. The combination of remote sensing and social sensing has been employed to investigate urban environments, urban dynamics, and the well-being of city residents. This review explores leading ideas and methodologies of the synergy between remote sensing and social sensing in a broad context of urban studies. The synergy involves leveraging the benefits of remote sensing and social sensing to gain a deeper understanding of urban characteristics than can be acquired through any single sensing approach. Two types of synergy are identified, namely, 'transfer-based synergy' and 'integration-based synergy.' The former transfers ideas and techniques between remote sensing and social sensing based on their similarity. The latter integrates these sensing ways based on their complementary advantages. The motivations and methods are summarized to show how such synergy is suited for investigating the complex nature of urban systems. Typical applications of the synergy include land use and functional zone mapping, special land use identification, estimation of natural and socioeconomic elements, and emergency response. We also identify data quality issues, refinement of methodologies, and expansion of applications that still pose challenges and are worth future research. This review lays a foundation for synergizing remote sensing and social sensing, offering researchers guidance to reexamine and reconceptualize the city from multiple sensing perspectives.

Original languageEnglish
Pages (from-to)108-137
Number of pages30
JournalIEEE Geoscience and Remote Sensing Magazine
Volume12
Issue number1
DOIs
StatePublished - 1 Mar 2024

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