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Contributions, grants and contracts awarded

smartEarth aims to give Canada's downstream space sector (data exploitation) the support it needs to accelerate innovations in the creation and delivery of new Earth observation (EO) applications.

Request for proposals: smartWhales

As a result of a request for proposals published in , the Government of Canada is investing $5.3 million in five companies to advance solutions, using satellite data, that could help detect and monitor the presence of North Atlantic right whales (NARWs) in Canadian waters and predict their movements.

To fuel innovation and maximize the sharing of knowledge and expertise, each company has built a team of experts, including external collaborators from academia and non-government organizations, to carry out their projects.

The Canadian Space Agency (CSA) is leading smartWhales in collaboration with Fisheries and Oceans Canada and Transport Canada.

These projects fall under two streams: detection and monitoring of the NARW; and prediction and modelling of NARW behaviour and movement in their habitat.

The five funded projects are:

Lead company Collaborators Contract value Project description
Stream 1: Detection and monitoring
Hatfield Consultants Ltd.
  • University of New Brunswick
  • Dalhousie University
  • Duke University
  • AltaML
  • Canadian Wildlife Federation
$1,199,520 Develop a system that will detect NARWs, using deep-learning algorithms, high-resolution satellite imagery, automation, and geoscience computing.
Global Spatial Technology Solutions Inc. (GSTS)
  • Dalhousie University
  • Ocean Frontier Institute (OFI)
  • DeepSense
  • British Antarctic Survey
  • Bigelow Laboratory for Ocean Sciences
$1,102,417 Develop a system that will detect NARWs, using machine learning and high-resolution satellite imagery, hosted on the artificial intelligence based maritime management platform, OCIANA™.
Fluvial Systems Research Inc. (FSR)
  • INSARSAT Inc.
  • University of Ottawa
  • Canadian Whale Institute
$1,176,682 Develop a system that will monitor NARWs and their habitat, using high-resolution satellite imagery.
Stream 2: Prediction and modelling
Arctus Inc.
  • Takuvik (Laval University)
  • Hatfield Consultants
  • ACRI-ST
  • Anderson Cabot Center for Ocean Life, New England Aquarium
  • MExpertise Marine
  • Bigelow Laboratory for Ocean Sciences
  • Merinov
$900,000 Develop a modelling system to help predict the presence of NARW in the Northwest Atlantic shelf, including the Gulf of St. Lawrence and the Gulf of Maine.
WSP Canada Inc.
  • DHI Water & Environment
  • Canadian Whale Institute
  • Dalhousie University
  • Institut des sciences de la mer de Rimouski
$899,582 Develop a system that will provide near-real-time information about the forecasted presence of NARWs and potential risks of encountering a vessel.

Announcement of Opportunity: Bridging the information gap with space-based analytics

With the growing number of EO satellites, there is an unprecedented volume of space data available. We continually need innovative solutions to process and effectively use this data, which also fosters science excellence, economic growth and job creation.

Increased access to this data, combined with advanced analytic technologies such as artificial intelligence (AI), machine learning, deep learning and high-performance computing, will unlock the potential for a great deal of new cutting-edge solutions to meet today's and tomorrow's challenges on Earth.

The Canadian Space Agency (CSA) is supporting the downstream space sector (data exploitation) so that it can build its expertise to take full advantage of all the opportunities provided by space.

As a result of this Announcement of Opportunity Bridging the information gap with space-based analytics, published in , the CSA is funding 17 Canadian companies so that they can develop new disruptive applications with EO data. Applications will contribute to improving the lives of Canadians.

As part of these contributions, it is anticipated that 240 new jobs will also be created.

Organization Contribution value Project title Project description
Telesat Canada / Telesat Leo Inc.
Ottawa, Ontario
$300,000 Space-Based Analytics Solutions for Mitigating Rain Fade Use real-time precipitation data, AI and machine learning to predict rain fade attenuation and enable a more reliable connection for critical infrastructure and Internet connection.
A.U.G. Signals Ltd.
Toronto, Ontario
$299,853 Improving Space-Based Radar Reflectometry for Better Ocean State and Target Monitoring Using Advanced Data Processing Improve the performance of space-based radar reflectometry for ocean-surface target monitoring by using state-of-the-art data processing technology.
Global Spatial Technology Solutions Inc.
Dartmouth, Nova Scotia
$279,642 Deep learning system for enhanced spatio-temporal maritime analytics using big data streams from new Canadian EO constellations Develop a flexible and powerful AI capability that will benefit shipping lines, port and terminal operators and maritime regulatory authorities.
ASL Environmental Sciences Inc.
Saanichton, British Columbia
$299,989 Artificial Intelligence for Earth Observation Use big data and AI capabilities for monitoring trends in vegetation and lake dynamics in the Canadian North.
MDA Systems Ltd.
Richmond, British Columbia
$300,000 Detecting Object Behaviour of Interest Using Deep Learning Use advances in deep learning to develop a system for detecting object behaviour of interest from satellite imagery.
Complex System Inc.
Calgary, Alberta
$293,738 Urban monitoring using satellite data, ground, and mobile crowdsensing for hydrological modelling and change detection events Develop a short- and long-term urban monitoring system, with a focus on hydrological monitoring for flood risk.
GHGSat Inc.
Montreal, Canada
$300,000 Automated plume detection algorithm for high‐resolution methane measurements from GHGSat satellites Develop a new AI algorithm to detect methane emissions plumes measured by GHGSat's satellites, with little or no human intervention.
ADGA Group Consultants Inc.
Ottawa, Ontario
$300,000 Mixed Relevant Features Analysis for Deep Learning Ship Detection in RADARSAT Constellation Mission Data Incorporate RADARSAT Constellation Mission data into an existing AI-enabled Amari platform for automated ship detection.
Dromadaire Géo Innovations Inc.
Montreal, Quebec
$84,483 ICEBERG Put in place a Web platform for client orders to optimize imagery processing and classification.
BGC Engineering Inc.
Vancouver, British Columbia
$299,430 Space-Enabled Reservoir Slope Management Toolkit Update the approach to support quantitative risk management decisions by BC Hydro and other operators as part of structures and reservoir slopes performance monitoring.
Hatfield Consultants LLP
North Vancouver, British Columbia
$192,161 Evaluating Earth Observation Data and Deep Learning Methods to Support Landscape Disturbance Mapping Develop an EO-based solution through the use of deep learning methods to identify landscape disturbance areas for habitat restoration purposes for study sites in northeastern BC and northwestern Ontario.
HabitatSeven Inc.
Ottawa, Ontario
$216,401 Cloud-Based Delivery of Space-Based Analytics Build a cloud-based computing architecture that reliably predicts the costs for space data storage, delivery and use of cloud-based data analytics for projects of varying sizes.
Vertex Professional Services Ltd.
Sherwood Park, Alberta
$300,000 Automated Monitoring of Reclamation Status using Remote Sensing and Artificial Intelligence Develop new services in the areas of EO and AI for the natural resource development and oil and gas industry.
MDA Geospatial Services Inc.
Richmond, British Columbia
$157,924 Deep Learning for Classification of SAR-Derived Forest Change Use Canadian radar technology, combined with AI algorithms, to detect and map forest changes.
OODA Technologies Inc.
Montreal, Quebec
$295,154 Combining deep learning techniques with cloud computing and big remote sensing data towards a better situation understanding Develop a new cloud-based solution to process a high volume of remote sensing images using deep learning techniques for different applications, such as flood monitoring, ship detection and land use/cover classification.
NorthStar Earth and Space Inc.
Montreal, Quebec
$299,575 Development of Multi-Source Analysis Ready Data based on the fusion of Sentinel-1, Sentinel-2 and NorthStar-like hyperspectral data Use advances in multi-source date fusion and machine learning techniques to characterize a wetland area.
Arctus Inc.
Rimouski, Quebec
$299,995 Earth Observation Solutions for Environmental Monitoring of Industrial Port Zones Develop a cloud-based near-real-time EO monitoring system for environmental management of ports, tailored to meet the needs of industrial port zones.

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