Meeting ID: 948 3891 9361
The interaction between urban environment and human activity is one of the most important issues in healthy city science. Remote sensing and social sensing big data have greatly facilitated mapping, monitoring, and modeling changes of human-environment system. This talk will first introduce data-model fusion approaches in quantifying a range of fine-resolution urban environment components including urban land use categories, air pollution, and green space. The second part of this talk will introduce a dynamic human-environment interaction framework by integrating real-time human mobility with the urban environment. Based on the proposed framework, this talk will use air pollution and green space exposure for an example to uncover the realistic human-urban environment interaction. The audience may receive insights about how to leverage multi-source data and interdisciplinary approaches in the field of urban environmental health science.
Dr. Bin Chen is currently an Assistant Professor in the Division of Landscape Architecture, Faculty of Architecture, at the University of Hong Kong. Before joining HKU, he worked as a Postdoc researcher at the University of California Davis. He received a B.S. degree in Geographic Information System from Wuhan University in 2013, and a Ph.D. degree in Global Environmental Change from Beijing Normal University in 2017. His research interests include most aspects of geoscience and remote sensing, specifically multi-source data-model fusion and geospatial big data analysis in the field of urban and environmental health science. He has published more than 40 journal articles, including Science, PNAS, Remote Sensing of Environment, ISPRS Journal of Photogrammetry and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, etc. He received the 2021 AAG Early Career Award in Remote Sensing, ISPRS Best Young Author Award, and Li Xiaowen Remote Sensing Excellent Youth Award.