Hosted by the Program on Chinese Cities （PCC）
02/06/2025 3:00 PM-4:00 PM EST
Presenter: Peijin Sun
Lecturer, Department of Urban and Rural Planning, Dalian University of Technology
Visiting scholar, University of North Carolina at Chapel Hill
Supervisor: Prof. Yan Song
Abstract:
Urban environments have a profound impact on residents’ health behaviors, including physical activity, mobility patterns, and mental well-being. However, traditional research methods are often constrained by the limited coverage and accuracy of data, making it difficult to fully capture these complex relationships. In recent years, the emergence of multimodal data—such as images, text, location information, and trajectory data—has provided broader spatial-temporal perspectives and finer analytical granularity. Meanwhile, the rapid advancement of large models and machine learning techniques has enabled more efficient integration and analysis of multisource data, thereby enhancing the depth and precision of research. This presentation, based on recent research findings, will focus on the impact of urban built and natural environments on residents’ physical activity. It will explore the potential applications of multimodal data and large models, demonstrating how data-driven approaches can help uncover the mechanisms through which urban environments influence health behaviors. Ultimately, this discussion aims to reflect on the significance of data and technology and how emerging technologies can genuinely enhance our understanding and optimization of urban environments.