Oceanviewer Banner

Safer Shipping through Summer Sea Ice: New Synthetic Aperture Radar (SAR) Based Tools for Monitoring and Predicting Sea Ice Conditions

  • Headshot

    Randy Scharien

The goal of this research is to improve the observation and assimilation of summer sea ice conditions, using satellite synthetic aperture radar (SAR) data, so that stakeholders can make informed and timely decisions when operating in ice-prone waters.

The goal of this research is to improve the observation and assimilation of summer sea ice conditions, using the leading-edge capabilities of satellite synthetic aperture radar (SAR) data, so that stakeholders can make informed and timely decisions when operating in ice-prone waters. 

Government, industry, and residents of coastal Arctic communities are often required to delay or suspend marine-based activities during the summer due to a lack of tools for assessing risks associated with transient summer ice conditions, and inadequate safety guidelines. Demands for accurate summer sea ice information are expected to increase as vessel traffic increases, vessel technology improves, climate change causes Arctic transit routes to remain open for longer, and new industrial projects are developed.

Achievements of this project include the development of a research and application strategy for northern sea ice hazard assessments using satellite remote sensing, 5 publications in peer-reviewed literature, and 4 academic conference presentations. This project has resulted in the creation of a network of researchers from five Canadian Universities and two agencies of the Environment and Climate Change Canada department of the Canadian government (Meteorological Service and Canadian Ice Service). Four HQP have been trained through this project and three more recruited. Technology exchange achievements include the trial adoption of published results into Canadian Ice Service operational ice-charting workflows. 

This project is one of nine research projects funded through MEOPAR's partnership with Irving Shipbuilding Inc.  Read More


  • Environment Canada - Canadian Ice Service
  • C-CORE
  • Natural Sciences and Engineering Research Council of Canada (NSERC)
  • Environment Canada - Climate Research Division


  • Christian Haas
  • Andrea Scott University of Waterloo
  • John Yackel


  • Sasha Nasonova


  • Arkett,Matt,Scharien,Randy,Yackel,John ,Geldsetzer, T., T. Zagon, F. Charbonneau,. 2015, All season compact-polarimetry SAR observations of sea ice. Canadian Journal of Remote Sensing, Canadian Journal of Remote Sensing, 41(5), 485-504,10.1080/07038992.2015.1120661.
  • Howell,Stephen,Yackel,John ,Mahmud, M., Geldsetzer, T.. 2016, Detection of melt onset over the northern Canadian Arctic Archipelago sea ice from RADARSAT, Remote Sensing of Environment, 178, 59-69,10.1016/j.rse.2016.03.003.
  • Yackel,John ,Gill, J.P.S., Geldsetzer, T., Fuller, M.C., and Nandan, V.. 2017, Diurnal Scale Controls on C-Band Microwave Backscatter from Snow-covered First-Year Sea Ice during the Transition from Late Winter to Early Melt, IEEE,
  • Haas,Christian,Howell,Stephen,. 2015, Ice thickness in the Northwest Passage, Geophyical Research Letters, 42, 10.1002/2015GL065704.
  • Yackel,John ,Nandan, V., Geldsetzer, T., Mahmud, M., Gill, J.P.S., Fuller, M.C., and Ramjan, S.. 2017, Multi-Frequency Microwave Backscatter Indices from Saline Snow Covers on Smooth First Year Sea Ice, IEEE,
  • Yackel,John ,Nandan, V., Geldsetzer, T., Islam, T., Gill, J.P.S., and Mahmud, M.. 2017, Multifrequency Microwave Backscatter From a Highly Saline Snow Cover on Smooth First-Year Sea Ice: First-Order Theoretical Modeling, IEEE, 55(4), 2177-2190, 10.1109/TGRS.2016.2638323.
  • Haas,Christian,Kaleschke, L., X. Tian-Kunze, N. Maaß, A. Beitsch, A. Wernecke, M. Miernecki, G. Müller, B.H. Fock, A.MU Gierisch, K.H. Schlünzen, T. Pohlmann, M. Dobrynin, S. Hendricks, J. Asseng, R. Gerdes, P. Jochmann, N. Reimer, J. Holfort, C. Melsheimer, G. Heygster. 2016, SMOS sea ice product: Operational application and validation in the Barents Sea marginal ice zone, Remote Sensing of Environment, 10.1016/j.rse.2016.03.009.
  • Azetsu-Scott,Kumiko,Xu, Y.. 0, Sea ice and open water classification of SAR imagery using CNN-based transfer learning, IEEE Geoscience and Remote Sensing Symposium,
  • Haas,Christian,Beckers, J.F., A.H.H. Renner, G. Spreen, S. Gerland. 2015, Sea ice surface roughness estimates from airborne laser scanner and laser altimeter observations in Fram Strait and north of Svalbard, Annals of Glaciology, 56(69), 10.3189/2015AoG69A717.
  • Casey,Alec,Haas,Christian,Howell,Stephen,A. Tivy. 2015, Separability of sea ice types from wide swath C- and L-band synthetic aperture radar imagery acquired during summer melt, Remote Sensing of Environment, 174, 314–328,10.1016/j.rse.2015.12.021.
  • Yackel,John ,Nandan, V., Geldsetzer, T., Islam, T., Gill, J.P.S., Fuller, M.C., Gunn, G. and Duguay, C.. 2016, X-and C-band measured and modeled microwave backscatter from a highly saline snow cover on first-year sea ice, Remote Sensing of Environment, 187, 62-75,10.1016/j.rse.2016.10.004.

Project outcomes include:

  • Training of 6 Highly Qualified Personnel (HQP)
  • End-users who are engaged and informed about sea ice conditions
  • A competitive advantage for Canadian companies using leading-edge SAR technology for development of information products and decision-making services

Project outputs include:

  • Optimized SAR-based summer sea ice information
  • Reduced costs associated with image acquisitions and processing time
  • Improved sea ice predictions
  • Tools to support safe navigation and usage of sea ice

Follow Randy Scharien on Twitter: @PolarFronts