Wide Area Monitoring System (WAMS)
Ground displacement caused by groundwater extraction, mining, oil & gas, urban development and other phenomena is a global problem, but is extremely costly and inefficient to monitor using ground instruments over wide areas. Using satellite radar data, Interferometric Synthetic Aperture Radar (InSAR) provides the most cost efficient method for ground displacement monitoring on a province-, state-, or nation-wide scale; however, existing InSAR technology lacks the speed and scalability for wide area operational monitoring. The Wide Area Monitoring System (WAMS) aims to eliminate these technological gaps and develop superior tools for InSAR as a wide area operational monitoring tool. Computer vision, computer acceleration, and machine learning are combined together for the first time for InSAR processing. Among others, the primary test site used for this project is California, since the entire state is subject to local and widespread ground displacement from all of the aforementioned causes. The resulting technological advances will be capable of leveraging multiple satellite data sources (TerraSAR-X, ALOS and Sentinel) for accurately mapping sites on a regional scale, anywhere in the world. WAMS will support monitoring of known displacement areas as well as identification of new risks.
This project is sponsored by Consortium for Aerospace Research and Innovation in Canada (CARIC) and Mitacs ($1.4 million for 18 months). The project is led by 3vG; UVic, UofA, and Sightline Innovation are project partners.
Date and Time
Location
Hosts
Registration
- Date: 09 Oct 2018
- Time: 11:00 AM to 12:00 PM
- All times are (GMT-08:00) Canada/Pacific
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- University of Victoria
- Engineering Office Wing
- Victoria, BC , British Columbia
- Canada
- Building: EOW 430, Engineering Office Wing
- Room Number: EOW 430
- Click here for Map
Speakers
Parwant Ghuman of 3vGeomatics
Wide Area Monitoring System (WAMS)
Ground displacement caused by groundwater extraction, mining, oil & gas, urban development and other phenomena is a global problem, but is extremely costly and inefficient to monitor using ground instruments over wide areas. Using satellite radar data, Interferometric Synthetic Aperture Radar (InSAR) provides the most cost efficient method for ground displacement monitoring on a province-, state-, or nation-wide scale; however, existing InSAR technology lacks the speed and scalability for wide area operational monitoring. The Wide Area Monitoring System (WAMS) aims to eliminate these technological gaps and develop superior tools for InSAR as a wide area operational monitoring tool. Computer vision, computer acceleration, and machine learning are combined together for the first time for InSAR processing. Among others, the primary test site used for this project is California, since the entire state is subject to local and widespread ground displacement from all of the aforementioned causes. The resulting technological advances will be capable of leveraging multiple satellite data sources (TerraSAR-X, ALOS and Sentinel) for accurately mapping sites on a regional scale, anywhere in the world. WAMS will support monitoring of known displacement areas as well as identification of new risks.
This project is sponsored by Consortium for Aerospace Research and Innovation in Canada (CARIC) and Mitacs ($1.4 million for 18 months). The project is led by 3vG; UVic, UofA, and Sightline Innovation are project partners.
Biography:
Parwant Ghuman studied Electrical Engineering at the University of British Columbia. He is currently Chief Technology Officer at 3v Geomatics, where he focuses on developing image processing technology for maximizing information extraction from SAR data stacks. His research focuses on automated monitoring solutions for difficult datasets exhibiting noise and undersampling across diverse applications including resource extraction, civil infrastructure, and permafrost. He is also interested in scalability challenges associated with efficient processing of large volumes of SAR data.