Urban Analytics, Spatial Data Science, Urban Science, Urban Sustainability
Xiaojiang is a Tenure-track Assistant Professor at Department of Geography and Urban Studies, Temple University. He was a Postdoctoral Fellow at MIT Senseable City Lab. His current research focuses on developing and applying geospatial analyses and data-driven approaches in the domain of urban studies. He has proposed to use Google Street View for urban environmental studies and developed the Treepedia project, which aims to map street greenery for cities around the world. He is also working on using human trace data to study human activities and investigate the connection between urban environments and human activities. Before that, he did his Ph.D. in the Department of Geography, University of Connecticut.
His research interests include GIScience, data-driven urban environment modeling, mobility and travel behavior profiling, urban computing and spatial analyses, and remote sensing. His research aims to provide a better understanding of human and urban environment systems and explore using digital technologies to benefit human society. His work has been featured in popular media outlets, including TIME, Wall Street Journal, The Guardian, Forbes, Atlantic-Citylab, Associated Press, and MIT News.
Xiaojiang Li, Bill Cai, Waishan Qiu, Jinhua Zhao, Carlo Ratti, (2019), A novel method to estimate and map the occurance of sunglare using Google Street View, Transporation Research C, Emerging Technologies (Accepted)
Xiaojiang Li, Fabio Duarte, Carlo Ratti, (2019), Analyzing the obstruction effects of the obstacles on light pollution cased by lighting system in Cambridge, Massachusetts, Environment and Planning B, Urban Analytics and City Science (In press).
Xiaojiang Li, Carlo Ratti, (2019). Using Google Street View for street-level urban form analysis, The Mathematics of Urban Morphology (In press).
Xiaojiang Li, Debarchana Ghosh, (2018). Associations between body mass index and urban “green” streetscape in Cleveland, Ohio. International Journal of Environmental Research and Public Health. (Accepted).
Xiaojiang Li, Carlo Ratti, (2018). Mapping the spatial-temporal distribution of solar radiation in street canyons of Boston using Google Street View panoramas, Landscape and Urban Planning (Accepted).
Villeneuve, P, Ysseldyk, R, Root, R, Ambrose, S, DiMuzio, J, Kumar, N, Shehata, M, Xi, M, Seed, E, Shooshtari, M, Xiaojiang Li , Daniel Rainham, (2018). Are greener and more walkable neighbourhoods associated with recreational physical activity and self-rated health in Ottawa, Canada? International Journal of Environmental Research and Public Health. (Accepted).
Xiaojiang Li, Paolo Santi, ..., Carlo Ratti. (2018). Investigating the association between streetscapes and human walking activities using Google Street View and human trajectory data. Transactions in GIS. (Accepted).
W Zhang, C Witharana, W Li, C Zhang, Xiaojiang Li, J Parent. (2018). Using Deep Learning to Identify Utility Poles with Crossarms and Estimate Their Locations from Google Street View Images. Sensors. (Accepted).
Xiaojiang Li, Bill Yang Cai, Carlo Ratti. (2018). Using Street-level Images and Deep Learning for Urban Landscape Analysis, Landscape Architecture Frontier, (Accepted).
Fangying Gong, Zhaocheng Zeng, Fan Zhang, Xiaojiang Li, Edward Ng, Les Norford. (2018). Mapping sky, tree, and building view factors of street canyons in a high-density urban environment, Building and Environment. 134, 155-167.
Xiaojiang Li, et al. (2018), Mapping the spatial distribution of shade provision of street trees in Boston using Google Street View panoramas, Urban Forestry and Urban Greening, 31, 109-119.
Xiaojiang Li, Carlo Ratti, Ian Seiferling. (2018). Quantifying the shade provision of street trees in urban landscape: A case study in Boston, USA, using Google Street View, Landscape and Urban Planning, 169, 81-91. (One of most downloaded papers).
Xiaojiang Li, et al. (2017). Building block level urban land use information retrieval based on Google Street View images, GIScience and Remote Sensing, 2017, 1-17.
Zhang W., W. Li, C. Zhang. D. Hanink, Xiaojiang Li, and W. Wang. (2017). Parcel-based urban land use classification in megacity using airborne LiDAR, high resolution orthoimagery, and Google Street View. Computers, Environment and Urban Systems, 64, (215-268).
Zhang, W., Li, W., Zhang, C., Hanink, D. M., Xiaojiang Li., & Wang, W. (2017). Parcel feature data derived from Google Street View images for urban land use classification in Brooklyn, New York City for urban land use classification in Brooklyn, New York City. Data in brief, 12, 175-179.
Zhang W., W. Li, C. Zhang, and Xiaojiang Li. (2017). Incorporating Spectral Similarity into Markov Chain Geostatistical Cosimulation for Reducing Smoothing Effect in Land Cover Post-Classification". IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, doi: doi: 10.1109/JSTARS.2016.2596040.
Xiaojiang Li, Chuanrong Zhang, Weidong Li, (2016). Modelling building proximity to greenery in a three-dimensional perspective using multi-source remotely sensed data, Journal of Spatial Science, (2016): 1-15.
Xiaojiang Li, Zhang, C., & Li, W. (2015). Does the Visibility of Greenery Increase Perceived Safety in Urban Areas? Evidence from the Place Pulse 1.0 Dataset. ISPRS International Journal of Geo-Information, 4(3), 1166-1183.
Xiaojiang Li, 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 and Urban Greening, 2015, 14(3) (PDF). (One of most cited and downloaded papers).
Xiaojiang Li, Q. Meng, W. Li, C. Zhang, T. Jansco, and S. Mavromatis. (2014). "An explorative study on the proximity of buildings to green spaces in urban areas using remotely sensed imagery." Annals of GIS 20, 3 (2014): 193-203.
Xiaojiang Li, Qingyan Meng, Xingfa Gu, Tamas Jasco. (2013). A hybrid method combining pixel based and object based methods and its applications in Hungary using Chinese HJ-1 Satellite image, International Journal of Remote Sensing, 2013, 34(13), 4655-4667.
Xiaojiang Li, Qingyan Meng, Chunmei Wang, Miao Liu. (2013). A hybrid model of object- and pixel based classification of Remotely sensed data, Geo-spatial Information Science, 2013, 15(5) (In Chinese).
Ke Wang, Xingfa Gu, Tao Yu, Jintang Lin, Guiping Wu and Xiaojiang Li, Segmentation of high resolution remotely sensed imagery combining spectral similarity with phase congruency, J. of Infrared Millim. Waves, 2013, 32(1):73-79 (In Chinese).
Chunzhu Wei, Qingyan Meng, Wenfeng Zheng, Xiaojiang Li, Xi Wei, Liang Wang, The study of Quantitative relationship between Land surface temperature and land cover of Guangzhou, Remote Sensing Technology and Application, 2013, 28(6): 955-963 (In Chinese).
Daniele Santucci, Umberto Fugiglando, Xiaojiang Li, Thomas Auer, Carlo Ratti. Methodological framework for evaluating liveability of urban spaces through human centred approach, 10th Windsor Conference 2018 – Rethinking Comfort – Proceedings.
Bill Yang Cai, Xiaojiang Li, Ian Seiferling, Carlo Ratti, Treepedia 2.0: Applying Deep Learning for Large-scale Quantification of Urban Tree Cover, IEEE BigData Congress (Accepted).
Xiaojiang Li, Chuanrong Zhang, Urban land use information retrieval based on scene classification of Google Street View images, GIScience 2016, Montreal, Canada.
Xiaojiang Li, Qingyan Meng. 2013, Using multi-source remotely sensed data to analyze green space at 3D perspective, Symposium of Remote Sensing Cross Taiwan Strait, National Central University, Taiwan.