Cameron Fitzpatrick Email & Phone Number

Calgary, Ab, Ca

Calgary, Alberta, Canada

Currently employed with the Hydrometry, Hydraulics and Innovation group at the National Hydrological Service. My role is dynamic and includes work on the following innovation projects:1) Lead developer of an algorithm to determine terrestrial water heights using radar altimeter satellites (Jason-1, Jason-2, Jason-3, Sentinel-6, Surface Water Ocean Topography (SWOT)). 2) Calibration and validation efforts for SWOT, launched in December 2022, via field data collection on the North Saskatchewan River, and collaborative data analysis.3) Suspended sediment sampling on the Athabasca River for the calibration of new sediment monitoring equipment.

Ottawa, Ontario, Canada

1) R&D into the use of radar altimeter satellites to determine water level of terrestrial water bodies in anticipation of such data from one component of the Surface Water Ocean Topography (SWOT) satellite. 2) Continued collaborative development of an automated random-forest machine learning image classification procedure for the near-real time mapping of surface water extents. Continuation of work from my first Co-op term.

Ottawa, Ontario, Canada

I served to aid professors and graduate students in their research in various forms, not limited to the following: 1) Development of geospatial software using Python and a PostGIS geospatial database to organize, process, and analyze Synthetic Aperture Radar (SAR) imagery from RADARSAT-1, RADARSAT-2, and Sentinel-1 satellites. 2) Aid in the programming, assembly, testing, and shipment of both open and closed-source scientific equipment such as weather stations, ice penetrating radar, oceanographic instruments, and GNSS units in collaboration with other lab members. 3) Procurement, inventory, and packing of both standard and scientific supplies for numerous field campaigns to the high arctic on behalf of other lab members. 4) Participation in a three-week field campaign to Ellesmere Island, Nunavut, Canada (82.50° N, 80.50° W) to assist in the maintenance and deployment of long-term monitoring equipment, and the collection of new field data for various research projects. Included the successful operation of a Deep Trekker Revolution underwater ROV under ice.

Ottawa, Ontario, Canada

The goal of this internship was to create a time-series of construction activity in Canada between 1990 and 2020 to aid in the modelling of dust emissions. This was achieved by:1) Developing an algorithm in Google Earth Engine using Random Forest machine learning to classify the approximate area of construction activity in Landsat-5 and Landsat-8 satellite imagery.2) Identifying and classifying new infrastructure projects via vector data comparison of past and present sources.3) Matching classified construction activity in satellite imagery to identified new infrastructure to further classify the type of construction activity visualized.

Ottawa, Ontario, Canada

Further the development of an automated random-forest machine learning image classification procedure for the near-real time mapping of surface water extents in the Canadian Prairies using SAR data. My contributions included: 1) Adding compatibility for RADARSAT Constellation Mission (RCM) and Sentinel-1 SAR data to the procedure.2) Refinement of the training data/methods to improve classification accuracy.3) Transitioning the procedure to a dev environment on a Linux-based server for longer-term testing. This included collaborating with other computer scientists on code optimization/formatting work, environment setup, and job scheduling.