We are seeking a motivated student for a Ph.D. thesis project starting in spring/summer or fall 2021 to develop satellite-derived methods to detect sea ice break-up events in the Canadian Arctic.
Extreme weather events such as storms in the Arctic Ocean during the winter season and accelerated sea ice thinning during spring/summer season impacts sea ice stability and strength, leading to break up events. Winter break up events critically impact the migration activities and subsistence livelihoods of Canadian Arctic communities reliant on sea ice for navigation in coastal zones. Break up events also increase open water areas by amplifying the ice-albedo feedback, facilitating faster marine navigability through ice infested waters. As coastal ice conditions continue to change, web platforms and mobile apps sharing information about dangerous conditions resulting from sea ice break up events are becoming increasingly needed. SIKU, the Indigenous Knowledge social network, currently allows users to share information about dangerous conditions caused by the formation of sea ice cracks and ridges. The addition of break-up events to SIKU’s alert system would increase user access to information pertinent to their safety and well-being.
Presently operational SAR satellite missions such as Canada's Radarsat Constellation Mission (RCM) and the European Space Agency's Sentinel-1 offers high spatial and temporal baseline imagery, delivering high-resolution Interferometric SAR products capable of detecting sea ice movements and break-up events, which can be then be integrated into the SIKU app, as user-friendly risk and hazard avoidance maps, impactful towards the safety and livelihood of indigenous communities.
The proposed Ph.D. project will focus on developing InSAR techniques and machine learning methods to automatically detect sea ice break up events in various Canadian Arctic communities, from SAR data (e.g. RCM, Sentinel-1, RADASAT-2), and validated using cloud-free optical satellite imagery (e.g. Sentinel-2, Worldview etc) and crowdsourcing. The final SAR-derived sea ice break-up product will be further integrated into the SIKU app, and delivered as user-friendly sea ice hazard maps.
The Ph.D. student will be supervised by Prof. Julienne Stroeve and mentored by Drs. Vishnu Nandan and David Jensen. The student will also work with the SIKU app research and technical team. The student's research will be conducted within the Centre for Earth Observation Science (), Department of Environment & Geography at the University of Manitoba, Winnipeg.
The successful candidate will have an M.Sc. (or equivalent) degree in remote sensing, or related field, with demonstrated experience in working with SAR data, Geographic Information Systems, and strong python/R programming skills. Knowledge/Experience in InSAR techniques and machine learning methods will be considered an asset. The studentship is fully funded over a 4-year period as part of Prof. Stroeve's Canada 150 Chair program.
Initial applications should be sent directly to Prof. Julienne Stroeve ([hidden email]) and include: two letters of academic reference; a copy of your University transcripts; a letter of intent (1-2 pages) briefly describing your previous research or experience and a short research proposal fitting the above thesis topic, touching on objectives/hypotheses, preferred methods, and scientific significance; and an English Language test score, such as TOEFL or IELTS, if you are an international student with English as a second language. For further information, please contact Dr. Stroeve.
Application deadline: Open until filled
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