Jonathan Li

Jonathan joined the Department in 2007 having spent 5 years as an associate professor at Ryerson University and one year as an assistant professor at the University of Regina. His research interests are in urban remote sensing and geospatial data science, especially in intelligent extraction of geometric and semantic information for earth observation images and LiDAR point clouds using machine learning and deep learning algorithms. His recent research focuses on use of the inhomogeneous and unstructured point clouds acquired by LiDAR and photogrammetry to generate HD maps and digital terrain models to support the development in smart cities and autonomous vehicles.

Key Areas of Graduate Supervision

Urban remote sensing using images acquired by multispectral, hyperspectral, and SAR sensors and point clouds acquired by LiDAR and photogrammetry; machine learning and deep learning algorithms and software tools for extraction of geometric and semantic information from images and point clouds; applied research in geospatial data science for environmental monitoring, infrastructure inspection, green space inventory, and disaster management

Recent Courses Taught

• GEOG 215: China: Diverse and Dynamic
• GEOG 310: Geodesy and Surveying
• GEOG 316: Multivariate Statistics
• GEOG 484 Machine Learning in Geospatial Science
• GEOG 608: Urban Remote Sensing

Research Interests

My research interests lie mainly in the areas of remote sensing and geospatial data science. The focus is placed on use of the-state-of-art Earth observation and mobile mapping systems to derive spatial and attribute information to support effective urban-suburban planning and environmental management activities; to extract geometric information of urban structures for developing theories and models of urban morphology; to detect land use and land cover changes to study spatiotemporal dynamics and consequences of urbanization as a major form of global changes.

My recent research projects are about the development of innovative methods and software tools, including GeoAI for multi-scale geospatial mapping and change detection, LiDAR point cloud processing for 3D urban modeling, mobile mapping solutions for outdoor and indoor mapping and 3D object detection, machine learning for intelligent processing of earth observation data, as well as novel remote sensing applications in transportation, utility, agriculture, resources and disaster management.