Skip to main content

PhD STUDENT – SAR Remote Sensing of Sea Ice to Detect Ice Break-up Events in the Canadian Arctic University of Manitoba. Fellowship and Scholarship.





PhD STUDENT – SAR Remote Sensing of Sea Ice to Detect Ice Break-up Events in the Canadian Arctic University of Manitoba

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 (umanitoba.ca/ceos), 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 (Julienne.Stroeve@umanitoba.ca) 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


....

Vineesh V
Assistant Professor of Geography,
Directorate of Education,
Government of Kerala.
https://www.facebook.com/Applied.Geography
http://geogisgeo.blogspot.com
🌏🌎
🌐🌍

Comments

Popular posts from this blog

Natural Disasters

A natural disaster is a catastrophic event caused by natural processes of the Earth that results in significant loss of life, property, and environmental resources. It occurs when a hazard (potentially damaging physical event) interacts with a vulnerable population and leads to disruption of normal life . Key terms: Hazard → A potential natural event (e.g., cyclone, earthquake). Disaster → When the hazard causes widespread damage due to vulnerability. Risk → Probability of harmful consequences from interaction of hazard and vulnerability. Vulnerability → Degree to which a community or system is exposed and unable to cope with the hazard. Resilience → Ability of a system or society to recover from the disaster impact. 👉 Example: An earthquake in an uninhabited desert is a hazard , but not a disaster unless people or infrastructure are affected. Types Natural disasters can be classified into geophysical, hydrological, meteorological, clim...

Linear Arrays Along-Track Scanners or Pushbroom Scanners

Multispectral Imaging Using Linear Arrays (Along-Track Scanners or Pushbroom Scanners) Multispectral Imaging: As previously defined, this involves capturing images using multiple sensors that are sensitive to different wavelengths of electromagnetic radiation. Linear Array of Detectors (A): This refers to a row of discrete detectors arranged in a straight line. Each detector is responsible for measuring the radiation within a specific wavelength band. Focal Plane (B): This is the plane where the image is formed by the lens system. It is the location where the detectors are placed to capture the focused image. Formed by Lens Systems (C): The lens system is responsible for collecting and focusing the incoming radiation onto the focal plane. It acts like a camera lens, creating a sharp image of the scene. Ground Resolution Cell (D): As previously defined, this is the smallest area on the ground that can be resolved by a remote sensing sensor. In the case of linear array scanne...

Discrete Detectors and Scanning mirrors Across the track scanner Whisk broom scanner.

Multispectral Imaging Using Discrete Detectors and Scanning Mirrors (Across-Track Scanner or Whisk Broom Scanner) Multispectral Imaging:  This technique involves capturing images of the Earth's surface using multiple sensors that are sensitive to different wavelengths of electromagnetic radiation.  This allows for the identification of various features and materials based on their spectral signatures. Discrete Detectors:  These are individual sensors that are arranged in a linear or array configuration.  Each detector is responsible for measuring the radiation within a specific wavelength band. Scanning Mirrors:  These are optical components that are used to deflect the incoming radiation onto the discrete detectors.  By moving the mirrors,  the sensor can scan across the scene,  capturing data from different points. Across-Track Scanner or Whisk Broom Scanner:  This refers to the scanning mechanism where the mirror moves perpendicular to the direction of flight.  This allows for t...

Trans-Himalayas

  1. Location and Extent The Trans-Himalayas , also known as the Tibetan Himalayas , form the northernmost mountain system of India . Stretching in an east–west alignment , they run parallel to the Greater Himalayas , covering: Ladakh (Jammu & Kashmir, UT) Himachal Pradesh (north parts) Tibet (China) They mark the southern boundary of the Tibetan Plateau and act as a transition zone between the Indian Subcontinent and Central Asia . 2. Major Ranges within the Trans-Himalayas Karakoram Range World's second highest peak: K2 (8,611 m) . Contains Siachen Glacier and Baltoro Glacier . Geopolitical importance: forms part of India–Pakistan–China border. Ladakh Range Separates the Indus Valley from the Tibetan Plateau . Known for rugged barren mountains and cold desert conditions. Zanskar Range Lies south of the Ladakh Range, cut deeply by the Zanskar River . Famous for trekking and frozen river expeditions...

Disaster Management

1. Disaster Risk Analysis → Disaster Risk Reduction → Disaster Management Cycle Disaster Risk Analysis is the first step in managing disasters. It involves assessing potential hazards, identifying vulnerable populations, and estimating possible impacts. Once risks are identified, Disaster Risk Reduction (DRR) strategies come into play. DRR aims to reduce risk and enhance resilience through planning, infrastructure development, and policy enforcement. The Disaster Management Cycle then ensures a structured approach by dividing actions into pre-disaster, during-disaster, and post-disaster phases . Example Connection: Imagine a coastal city prone to cyclones: Risk Analysis identifies low-lying areas and weak infrastructure. Risk Reduction includes building seawalls, enforcing strict building codes, and training residents for emergency situations. The Disaster Management Cycle ensures ongoing preparedness, immediate response during a cyclone, and long-term recovery afterw...