Katharine Scott

Andrea Scott is an Assistant Professor in the Systems Design Engineering department at the University of Waterloo.

Her research focuses on data to improve model predictions. One of Professor Scott’s projects involve the assimilation of remote sensing data to improve knowledge of the state of sea ice in the Arctic. More specifically, she conducts research on the assimilation of sea ice thickness and/or sea ice temperatures from visual/infrared sensors, and uses Synthetic Aperture Radar (SAR) data to estimate sea ice concentration. Other projects of Professor Scott’s include the use of data assimilation to estimate parameters in turbulence models and the development of scale aware/scale adaptive parameterizations.

Before working as a professor at UWaterloo, Professor Scott was a postdoctoral researcher at Environment Canada, where she was part of a team working on the assimilation of data to improve forecasts of sea ice conditions.

• Assimilation of remote sensing data to improve our knowledge of the state of sea ice in the Arctic
• The assimilation of sea ice thickness and/or sea ice temperature from visual/infrared sensors.
• The information content of passive microwave and visual infrared sensors as it pertains to sea ice concentration and thickness
• The assimilation of SAR (Synthetic Aperture Radar) data
• Using data assimilation to estimate parameters in turbulence models
• The development of scale aware/scale adaptive parameterizations
• Water

• 2008, Doctorate, Mechanical Engineering, University of Waterloo
• 2001, Master of Applied Science, Mechanical Engineering, McMaster University
• 1999, Bachelor of Applied Science, Mechanical Engineering, University of Waterloo

• Kheyrollah Pour, H., Duguay, C., Scott, K.A. and Kang, K-K, Improvement of Lake Ice Thickness Retrieval From MODIS Satellite Data Using a Thermodynamic Model, IEEE Transactions on Geoscience and Remote Sensing, 2017
• Mozaffari, Ahmad and Scott, K Andrea and Azad, Nasser L and others, A hierarchical selective ensemble randomized neural network hybridized with heuristic feature selection for estimation of sea-ice thickness, Applied Intelligence, 46(1), 2017, 16 - 33
• Pogson, Lynn and Geldsetzer, Torsten and Buehner, Mark and Carrieres, Tom and Ross, Michael and Scott, K Andrea, Collecting Empirically Derived SAR Characteristic Values over One Year of Sea Ice Environments for Use in Data Assimilation, Monthly Weather Review, 145(1), 2017, 323 - 334
• Wang, Lei and Scott, K Andrea and Clausi, David A, Sea Ice Concentration Estimation during Freeze-Up from SAR Imagery Using a Convolutional Neural Network, Remote Sensing, 9(5), 2017
• Mozaffari, Ahmad and Scott, K Andrea and Chenouri, Shojaeddin and Azad, Nasser L, A modular ridge randomized neural network with differential evolutionary distributor applied to the estimation of sea ice thickness, Soft Computing, 21(16), 2017, 4635 - 4659
• Liu, Jiange and Scott, K Andrea and Gawish, Ahmed and Fieguth, Paul, Automatic detection of the ice edge in SAR imagery using curvelet transform and active contour, Remote Sensing, 8(6), 2016
• Wang, Lei and Scott, K Andrea and Xu, Linlin and Clausi, David A, Sea ice concentration estimation during melt from dual-pol SAR scenes using deep convolutional neural networks: A case study, IEEE Transactions on Geoscience and Remote Sensing, 54(8), 2016, 4524 - 4533
• Wang, Lei and Scott, K Andrea and Clausi, David A, Improved sea ice concentration estimation through fusing classified SAR imagery and AMSR-E data, Canadian Journal of Remote Sensing, 42(1), 2016, 41 - 52
• Scott, K Andrea and Ashouri, Zahra and Buehner, Mark and Pogson, Lynn and Carrieres, Tom, Assimilation of ice and water observations from SAR imagery to improve estimates of sea ice concentration, Tellus A: Dynamic Meteorology and Oceanography, 67(1), 2015
• Scott, K Andrea and Li, Edward and Wong, Alexander, Sea ice surface temperature estimation using MODIS and AMSR-E data within a guided variational model along the Labrador Coast, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(9), 2014, 3685 - 3694