Xiaojiang Li

Background & Research

Xiaojiang is an Assistant Professor of Urban Spatial Analytics at Department of City and Regional Planning, University of Pennsylvania. Xiaojiang was an Assistant Professor at Department of Geography and Urban Studies, Temple University. He was a Postdoctoral Fellow at Senseable City Lab, MIT. His research focuses on Urban Analytics, Geospatial Data Science, Urban Resilience to Climate Change, Landscape and Environmental Planning, and Urban Environmental Health. He has proposed to use Google Street View and machine learning for urban landscape studies and developed the Treepedia project, which aims to map and quantify streetscape for cities around the world. He also works on using GeoAI, urban analytics, and urban microclimate modeling with the support of NSF, NASA, Alfred P. Sloan Foundation, and Microsoft AI for Earth Grant to investigate the impacts of extreme heat on pedestrians and heat vulnerability across different neighborhoods and racial/ethnic groups. His research aims to provide a better understanding of urban socio-environmental systems and explore how data, science, design, and planning help us to tackle socio-environmental challenges. He has been selected as the 50 Rising Stars in Geospatial World. He has been awarded the NSF CAREER Award, Global Young Scientist Award, World Geospatial Developers Conference in 2021. His work has been featured in popular media outlets, including TIME, Scientific American, Wall Street Journal, Forbes, The Guardian, Wired, etc.

Website: https://www.urbanspatial.info/

Courses Taught at the Weitzman School

MUSA 6950: AI for Urban Sustainability

MUSA-5500-Geospatial Data Science Python
MUSA 8010: MUSA/Smart Cities Practicum

Education

B.S. Environmental Science, Henan University
M.A. Cartography and GIS, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences.
Ph.D. Geographic Information Science, University of Connecticut

Selected Publications

Li, X. (2024). Mapping pedestrian network level outdoor heat hazard distributions in Philadelphia. Environment and Planning B: Urban Analytics and City Science, 23998083241274391.

Li, X., Chakraborty, T. C., & Wang, G. (2023). Comparing land surface temperature and mean radiant temperature for urban heat mapping in Philadelphia. Urban Climate, 51, 101615.

Li, X., & Wang, G. (2021). GPU parallel computing for mapping urban outdoor heat exposure. Theoretical and Applied Climatology, 145(3), 1101-1111.

Li, X. (2021). Investigating the spatial distribution of resident’s outdoor heat exposure across neighborhoods of Philadelphia, Pennsylvania using urban microclimate modeling. Sustainable Cities and Society, 72, 103066.

Li, X., & Ratti, C. (2019). Mapping the spatio-temporal distribution of solar radiation within street canyons of Boston using Google Street View panoramas and building height model. Landscape and urban planning, 191, 103387.

Li, X., Zhang, C., Li, W., Ricard, R., Meng, Q., & Zhang, W. (2015). Assessing street-level urban greenery using Google Street View and a modified green view index. Urban Forestry & Urban Greening, 14(3), 675-685.