Welcome to Mobile Sensing and Geodata Science Lab
Who we are
The University of Waterloo Mobile Sensing and Geodata Science Lab consists of a multidisciplinary team of individuals, including faculty, students, postdoc fellows, and visiting scholars trained in geomatics, geography and geoscience, computer science and engineering, mathematics and statistics, environmental science and engineering. Our group is led by Dr. Jonathan Li, Professor of Geomatics with the Department of Geography and Environmental Management and cross-appointed at the Department of Systems Design Engineering, University of Waterloo. Our multidisciplinary backgrounds are reflected in the diverse research projects publications. Learn more about each member in the section of our people.
What we do
Mobile sensing may be defined as the science and technology of acquiring, processing, analyzing, visualizing, and applying geospatial data from a mobile vehicle, on which typically mounted with a range of passive and active remote sensors. Our research relies on theories and methods of photogrammetry, computer vision, machine learning, geospatial intelligence (geospatial big data and artificial intelligence), and geographic information science. In general, our research focuses on the following three broad themes:
Developing mobile mapping technologies
Our research in this area focuses on the development of innovative algorithms and software tools for intelligent processing of geospatial data acquired by optical cameras, synthetic aperture radar (SAR), laser scanners and other imaging and ranging sensors onboard mobile vehicles, including satellites, aircrafts, unmanned aerial vehicles, boats, trains, vans and cars as well as by backpack and handheld sensors, to derive geometric and semantic information.
Measuring and modeling built environments
Our research in this area is focused on the development of methodologies and sustainable solutions using multi-sensor and multi-temporal remotely sensed data in applications of intelligent transportation systems, autonomous vehicles, smart cities, green energy, environmental heath, precision farming, emergency and disaster management sectors.
Monitoring and understanding urban dynamics
Our research in this area focuses on adopting spatial analysis, artificial intelligence and big data analytic techniques to understand how land-use and land-cover (LULC) patterns changing at the local and regional scales to better support the evaluation of environmental impacts of urban growth for informed environmental management and policy.
Who supports us
Our projects have been funded by:
- Natural Sciences and Engineering Research Council of Canada (NSERC),
- Canadian Foundation for Innovation (CFI),
- Ontario Innovation Trust (OIT),
- Agriculture and Agri-Food Canada (AAFC),
- Environment Canada (EC),
- Canadian Space Agency (CSA),
- Natural Resources Canada (NRCan),
- Ontario Ministry of Transportation (MTO),
- Networks of Centres of Excellence of Canada (e.g., ArcticNet),
- Geomatics industrial partners (e.g., PCI Geomatics, Tulloch Engineering, RIEGL, Trimble, Leica Geosystems, Ecopia Tech and WatXtract.ai),
- International agencies (e.g., NSFC, CSC, XMU), and
- The University of Waterloo.
- Dec. 5, 2017
Congratulations to Saeid Pirasteh who successfully defended his PhD thesis on Dec 5, 2017.