Presentation by Dr. Xiaojiang Li.  View the presentation slides | Request to view the presentation video recording

Abstract: The increasingly frequent and intense extreme heat events in large U.S. cities cause more climate-related mortalities than any other hazardous weather event. In the context of global warming, heat waves are supposed to be more frequent and intense in many cities. In addition, the urban heat island effect is believed to further exacerbate the mortality increase caused by heat stress in cities. The summer heatwaves would also increase the deaths and illnesses caused by infectious disease and air pollution. While a lot of attention has been paid on the urban-rural temperature gradients, the heat intensity also varies from neighborhood to neighborhood and street by street within the city. Understanding the fine level spatial distribution of the human heat stress level would be helpful for developing strategies to minimize the negative impacts of extreme heat in cities and building more equitable and resilient cities in terms of thermal comfort. In this talk, I will talk about my recent work on urban microclimate modeling based on high resolution 3D urban models to map the finest ever (1 meter) urban outdoor heat exposure in US cities.

Speaker Bio: Xiaojiang is a tenure-track Assistant Professor at Department of Geography and Urban Studies, Temple University. He was a Postdoctoral Fellow at Department of Urban Studies and Planning, Massachusetts Institute of Technology. He has been selected as the 50 Rising Stars in Geospatial World. His research focuses on Urban Analytics for Sustainability, Spatial Data Science, Urban Resilience to Climate Change, High Performance Urban Computing, and Geovisualization. He has proposed to use Google Street View and machine learning for urban environmental studies and developed the Treepedia project (http://senseable.mit.edu/treepedia), which aims to map and quantify street greenery for cities around the world. He is also working on using artificial intelligence, remote sensing, urban microclimate modeling, and urban analytics with the support of Microsoft AI for Earth Grant to investigate the different vulnerabilities to climate change across different neighborhoods in the U.S, especially for under-represented communities (https://xiaojianggis.github.io/heatexpo/). Before that, he received his Ph.D. in Geographic Information Science from Department of Geography, University of Connecticut, USA. His research aims to provide a better understanding of urban socio-environmental systems and explore how computation helps us to tackle socio-environmental challenges. His work has been featured in popular media outlets, including TIME, Scientific American, Wall Street Journal, Forbes, The Guardian, Wired, CBC News, Fox News, The Atlantic, Associated Press, and MIT News.

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