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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.

Announcement of Opportunity: Research Opportunities in Satellite EO

Following the launch of the Announcement of Opportunity (AO) Research Opportunities in Satellite EO in , 17 projects submitted by 13 post-secondary institutions across Canada were selected. Grants for these projects total $5M over 3 years and will allow academia to be equipped with resources, to collaborate with national and international partners, and to train new highly qualified personnel (HQP). Most projects are expected to hire, support, or positively impact Indigenous communities, and all the projects will address climate change.

List of projects that received funding for the AO: Research Opportunities in Satellite EO
List of projects that received funding for the AO: Research Opportunities in Satellite EO
Organization Project title Description
The Governors of the University of Alberta Using Generative AI and Satellite EO Data for Uncertainty-Aware Downscaling of ALS Point Clouds with Case Study on Fuel Attribute and Fire Growth Modelling This project aims to create detailed 3D models of Canada's vast forests using satellite data and computer algorithms, improving the coverage of fine-detailed data across large areas. This innovative approach will aid in forest monitoring, wildfire mapping, and climate change impact assessment, offering a valuable tool accessible through an open data sharing portal for researchers and the public.
The Governors of the University of Calgary The joint Copernicus Expansion Missions Sea Ice Experiment (CEMSIE) The Copernicus Expansion Missions Sea Ice Experiment (CEMSIE), led by a consortium of Canadian and European universities, with support from the European Space Agency, aims to enhance satellite monitoring of Arctic sea ice. This is to be achieved by simultaneously deploying multiple surface-based electromagnetic instruments in Dease Strait, near the Canadian High Arctic Research Station in Cambridge Bay, Nunavut. These instruments mimic three soon-to-be-launched ESA Copernicus Sentinel Expansion mission satellites: CRISTAL, CIMR, and ROSE-L.

CEMSIE's primary objectives include demonstrating how data integration from these three sensors can provide more comprehensive information than the sum of their parts. This integration aims to reduce uncertainties and enhance the accuracy of microwave satellite estimates of sea ice concentration, snow depth, and sea ice thickness.

Carleton University (Ontario) Building Capacity in Satellite-Based EO and HQP Training This project aims to enhance Canada's training capacity in satellite-based EO to meet the growing demand for skilled professionals capable of handling large datasets and utilizing technologies like cloud computing and machine learning. Together with industry and government partners across various application areas, the project team will revise existing courses and develop new training materials to address emerging gaps, ensuring a mix of traditional university courses and flexible workshops accessible to professionals and students, ultimately providing long-lasting benefits to Canadians beyond the project's duration.
Dalhousie University (Nova Scotia) Fine Resolution Classification of Sea Ice Based on Feature Selection from RADARSAT Constellation Mission The project aims to develop machine-learning-based methods for automatic estimation of Arctic ice concentration, classification of sea ice types, and monitoring of pack ice leads in the Arctic Ocean, focusing on regions like the Beaufort Sea. By utilizing synthetic aperture radar (SAR) data from satellites such as RADARSAT Constellation Mission (RCM) and RADARSAT-2, along with future NISAR observations, the project aims to provide the Canadian Ice Service (CIS) with improved operational ice charts, enhancing marine nowcasts and forecasts in the Canadian Arctic without manual intervention.
Institut national de la recherche scientifique (INRS) (Quebec) Spatio-temporal mapping of slush and sea ice conditions using multimodal Earth observations to promote safe travel in Nunavik, Quebec This project aims to provide vital spatio-temporal maps of sea ice roughness, thickness, and slush conditions for Nunavik communities; these maps are crucial for safe and efficient travel in the face of changing climate conditions. By combining traditional knowledge with satellite and ground-based observations, including drone imagery and Ground Penetration Radar, the project will offer near-real-time access to reliable satellite maps through collaboration with the Kativik Regional Administration, benefiting the safety and well-being of Nunavummiut.
McGill University (Quebec) Advancing validation/ upscaling methods and algorithms for spaceborne reflectance products of Canadian peatlands This project focuses on developing advanced methodologies and artificial intelligence algorithms to validate satellite systems such as EnMAP, Sentinel-2, and PlanetScope, which are crucial for monitoring Canada's vast peatlands. By leveraging ground-based measurements and hyperspectral drone technology at sites like the Mer Bleue Bog, the project aims to enhance Canada's capability to monitor and understand peatland carbon storage and its implications for climate change mitigation.
Memorial University of Newfoundland (MUN) Satellite EO-based approaches to the creation of a framework and qualified workforce for synoptic study and prediction of one of Canada's most important ocean resources This project aims to develop a comprehensive mapping and predictive approach for Canada's kelp beds using satellite remote sensing technologies, in order to address critical gaps in understanding scale-dependent processes affecting these ecologically and economically significant marine habitats. Through a multidisciplinary team and training program, the project will fulfill specific research objectives, including the creation of learning modules, community engagement, development of detection models using deep learning, and advanced visualization tools, ultimately enhancing Canada's marine research capabilities and competitiveness on the global stage.
University of Saskatchewan Enhancing Woody Plant Encroachment Detection in Grasslands Using Multi-Source EO Data and Modern Data Processing Technologies Benefiting Canadian Environment and Economy This project aims to address the rapid disappearance of grasslands, particularly due to woody plant encroachment (WPE), which has become the second most significant cause of grassland loss after land conversion to cropping. By leveraging advanced technology and diverse satellite imagery, the project seeks to develop methods to accurately estimate woody plant cover, detect WPE at an early stage, investigate driving factors, identify vulnerable regions, and assess the economic and environmental benefits of WPE detection on Canadian grasslands, ultimately providing a comprehensive understanding of and methodologies for WPE detection and impacts.
University of Saskatchewan Wall to Wall Mapping of N2O Emission Hotspots on Prairie Cropland Nitrous oxide (N2O) emissions, primarily from agricultural activities, pose a significant challenge in terms of global warming, with Canada contributing substantially. By integrating satellite imagery and field-based measurements, this project aims to map high-risk areas for N2O emissions in western Canada, potentially reducing emissions by 40% through targeted mitigation strategies, with real-time recommendations for climate change adaptation.
Simon Fraser University (British Columbia) Remote predictive mapping of eskers This project aims to enhance understanding of Canada's surficial geology by developing an automated method using satellite imagery to map landforms like eskers and estimate their composition. By integrating machine learning and morphometric analysis, the project seeks to streamline natural resource projects, particularly those reliant on gravel from eskers, by providing precise remote estimates of aggregate deposits, benefiting infrastructure development initiatives.
University of Sherbrooke (Quebec) Adapting the products of the new SWOT satellite to the Canadian context The Surface Water Ocean Topography (SWOT) satellite mission that was launched in offers an unprecedented ability to measure water levels in Canada's vast network of lakes and rivers, which are essential to ecosystems as well as economic and cultural activities. Adapting SWOT data to the Canadian context as part of a research project, and in particular to the issue of ice cover, will improve water resource management for organizations such as Environment and Climate Change Canada and dam managers, and facilitate adaptation to the effects of climate change on water resources.
University of Sherbrooke (Quebec) AI-Driven Adjacency-Effect Corrections for Improved Remote Sensing of Inland Lakes The objective of this project is to develop an AI-based algorithm that can improve atmospheric correction of satellite images of Canadian lakes. This will address current inaccuracies that hinder monitoring efforts, which are crucial for various aspects of Canadian life. The project aims to create a hyperspectral algorithm for accurate atmospheric correction by collecting in-situ data and using advanced modeling techniques. AI will be leveraged to improve computational efficiency and enable more precise utilization of remote sensing data. This will ultimately advance the field of lake monitoring and benefit multiple stakeholders.
University of British Columbia Canada-Wide Mapping of Forest Fuel Attributes Using Space-borne LiDAR, Structural Simulations and Time Series Satellite Data This project aims to develop open-access tools integrating LiDAR-derived forest fuel assessments with satellite data to extrapolate critical forest fuel attributes across Canada's forested areas; this information is crucial for effective forest management and fire decision-making. By leveraging innovative modeling techniques and open data distribution, the project seeks to advance forest fuel assessment methods, potentially reaching an application readiness level of 6, offering valuable resources for stakeholders and enhancing wildfire risk management.
University of British Columbia FIRECAN: Enhancing Wildfire Plume Modelling in Canada through Sentinel Satellite Data Integration and Experimental Measurements This project aims to use satellite measurements and targeted experiments to evaluate and improve the current understanding of chemical emissions from Canadian forest fires, which is crucial for enhancing modeling of smoke plumes and assessing their impacts on human health and the environment. By focusing on obtaining glyoxal (ethanedial) and formaldehyde column densities and refining emission factors and branching ratios, the research seeks to advance forest fire smoke modeling, potentially mitigating the societal challenges posed by the increasing prevalence of forest fires.
University of Quebec in Rimouski Advancing our Understanding of Ocean Biological Carbon Pumps of the Arctic and Sub-Arctic Seas using Hyperspectral Observations of Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Mission This project, which involves remote sensing specialists and oceanographers from universities and government departments, aims to leverage NASA's PACE mission to improve the accuracy of ocean colour observations, particularly in eastern Canada, to better understand the ocean's capacity to uptake carbon and its changes over time. By enhancing phytoplankton biomass estimation and extracting additional information on phytoplankton properties, the research aligns with objectives to address climate change, foster partnerships, and enhance ocean monitoring efforts critical for ecosystem health and carbon management.
University of Victoria (British Columbia) Satellite-Based Kelp Mapping (SKeMa): A Software Framework for First Nations This project, conducted in collaboration with First Nations groups and other organizations, aims to develop a framework utilizing satellite imagery to monitor canopy-forming kelp forests in British Columbia, crucial for maintaining marine ecosystems and supporting culturally significant species. By creating software and providing training courses for First Nations communities, the project seeks to give local stakeholders the means to monitor and manage their marine territories more effectively, aligning with Canada's marine protection targets and strategies.
York University (Ontario) Accurate Forest Carbon Quantification from SEO Data to Drive Nature-Based Climate Solutions This project aims to leverage satellite EO data to advance forest carbon quantification, addressing the urgent need for accurate information on carbon sequestration and fostering expertise in climate change mitigation. By improving understanding of carbon dynamics, developing AI methods for carbon estimation, and assessing forest management impacts, the project aims to elevate the application readiness level of developed methods and contribute to informed decision-making, benefiting both the environment and Canadian communities while raising awareness of EO and climate science through outreach activities.

Request for proposals: Accelerating EO Innovations

Following the request for proposals Accelerating EO Innovations published on , the Government of Canada is investing $1.1 million in 22 companies to develop applications that use satellite data. The companies are tasked with finding innovative concept solutions in order to address Canada's key environmental and socioeconomic challenges.

The 22 companies will define their solutions during Stage 1 of this process. At the end of Stage 1, the Canadian Space Agency expects to have the information necessary to assess the potential of the proposed solutions and then select the companies that will move on to Stage 2, which is concept demonstration.

Each company is receiving a maximum of $50,000 for Stage 1. The 22 funded projects are as follows.

List of projects that received funding for the Request for proposals: Accelerating EO Innovations
List of projects that received funding for the Request for proposals: Accelerating EO Innovations
Organization Project title Description
A.U.G. Signals Ltd. (Ontario) Freshwater Monitoring and Enhanced Risk Assessment Using AI-Driven Remote Sensing Monitor the quality of Canada's freshwater by integrating RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR), Sentinel-1, Sentinel-2 Electro-Optical data, Sentinel-3 data, and in-situ sensor data from AUG's TRITON® freshwater monitoring system through Artificial Intelligence (AI).
Acden Vertex Limited Partnership (Alberta) Enhancing Canadian Oil Sands Resource Infrastructure Risk Monitoring Using EO for the Benefit of Canadian Indigenous Communities Vertex's Concept Solution will introduce a transformative approach to monitoring Canada's oil sands infrastructure with a specific focus on addressing the challenges faced by the Athabasca Chipewyan First Nation in Alberta and other Indigenous communities in Canada. Vertex will integrate space-based EO technology and machine learning to identify hazards, enhance early detection of anomalies, and provide currently unavailable real-time risk information to local communities.
AltaML Inc. (Alberta) GenWhales The GenWhales project will incorporate AI and machine learning methods to accurately generate synthetic satellite images from airborne data to create a library of training images to improve the classification and detection models within the smartWhales Space Based Detection System. The synthetic images will be used to train the Generative and other AI algorithms to recognize whales in real satellite image databases, resulting in much improved whale detection and monitoring processes.
ARCTUS Inc. (Quebec) A satellite-based monitoring system and services for Eeyou Istchee coastal habitats The impacts of climate changes are accelerating, and one of the most affected regions is the Eeyou Istchee ancestral territory, located south of Hudson Bay and east of James Bay. Arctus, in collaboration with the Niskamoon Corporation, academic partners and the Cree land users, will develop the concept of a satellite-based monitoring system for the aquatic and coastal environmental variables, empowering local communities to make informed decisions in their conservation efforts.
ASL Environmental Sciences Inc. (British Columbia) Detection and Classification of Anomalous Features (DeCAF) Rapid Response Toolkit DeCAF (Detection and Classification of Anomalous Features) is a robust, fully automated system that detects landscape disturbances using satellite time-series and machine learning. DeCAF offers a unique capability for wide-area monitoring and situational awareness to support Canadian Armed Forces (CAF) operations. Under the Accelerator track of the CSA's smartEarth initiative, a set of novel tools (Rapid Response Toolkit) will be developed to detect changes more rapidly, enabling the CAF to monitor vast landscapes, like the Canadian Arctic, and to be alerted to new human activity.
AstroCom Associates Inc. (Ontario) Scalable Innovations for the Iceberg Monitoring Process (SIIMP) The objective of this project is to improve and automate the detection, tracking and classification of icebergs using SAR data. Icebergs can be difficult to distinguish from non-cooperative vessels, which may be illegally in Canadian waters and therefore form potential security threats. In addition, icebergs form a natural hazard to navigation with consequent impacts on environmental security in the event of collisions.
BGC Engineering Inc. (British Columbia) Mine Water Management Tailings Bathymetry The project is focused on tailings bathymetry in operational mines. The water in tailings storage facilities (TSFs) has been in contact with mine tailings and chemicals and, consequently, TSF failures have resulted in catastrophic impacts on local communities and the environment. Since the presence of large volumes of water have been a contributor to most recent TSF failures, a means to measure the TSF bathymetry is needed.
C-CORE (Newfoundland and Labrador) Mitigating Arctic Challenges Using AI (MACAI) C‐CORE's proposed project is Mitigating Arctic Challenges with AI (MACAI). It will support, with remote sensing advances specific for the region, the following priority challenges: optimizing ice road operating seasons, determining priority areas where erosion will likely erase Indigenous history while threatening infrastructure, and detecting permafrost slumps for emissions monitoring and other stakeholders needs.
EarthDaily Analytics Corp. (British Columbia) Monitoring Methane Emissions at a Global Daily Scale EarthDaily Analytics is developing an innovative methane monitoring solution that brings together the EarthDaily Constellation's super-spectral scientific imagery with a variety of geospatial data sources into a large-scale AI model that will be able to accurately identify point source methane emitters on a near-daily global basis.
Fluvial Systems Research Inc. (British Columbia) Integration of Satellite Data into a North Atlantic Right Whale Alert System The project will demonstrate the operational value of a three-step methodology for the detection of North Atlantic right whales based on incorporating satellite synthetic aperture radar and optical imagery into the government whale alert system. Using advanced AI methods for the detection of the whales and the identification of their feeding areas in the satellite imagery will result in improvements into the effectiveness of the alert system.
GHGSat Inc. (Quebec) AI-Assisted Multi-Variable Integration of Discrete Satellite Measurements for Quantification of Site-Specific Greenhouse Gas Inventories The proposed work aims to develop and demonstrate an AI-assisted application, that once source emission rates are detected, quantified, and attributed to an emission site, will estimate the time-averaged emission rate over months and years.
H2O Geomatics Inc. (Ontario) Lakes Across Canada from Space (LACS) Lakes Across Canada from Space (LACS)
A Comprehensive Tool for monitoring water quality and quantity in Canadian inland waters using EO systems. LACS addresses Canada's pressing need for an efficient, scalable and accurate water monitoring system, providing second-to-none insights into water body dynamics and ensuring sustainable management of our freshwater resources.
Hatfield Consultants LLP (British Columbia) Eelgrass Explorer (E2) System The proposed Eelgrass Explorer System is a cloud-based mapping system that uses high-resolution satellite data to map the distribution of eelgrass habitat in the intertidal ecosystems of British Columbia. Despite their ecological importance and positive correlation to fish diversity and species richness, these habitats are in decline and continue to be threatened by various anthropogenic and climate stressors. Regular and comprehensive mapping of eelgrass is an important step to inform and support management and conservation strategies.
KorrAI Technologies Ltd. (Nova Scotia) Developing an Open Ground Motion Service Platform, Adapting to the Impact of Permafrost Thaw on Critical Infrastructure Resilience in Canadian Territories The project introduces an innovative solution to address the pressing challenge of climate change and infrastructure resilience in the northern Canada with a specific focus on the impact of permafrost thaw on critical infrastructure like airports. The commitment is to develop a Web-based, user-friendly platform for InSAR displacement monitoring, leveraging cutting-edge SAR satellite technology. This platform offers near-real-time, actionable displacement information, enhancing decision-making and climate resilience efforts, ensuring the long-term sustainability of infrastructure in regions affected by permafrost thaw.
MDA Geospatial Services Inc. (British Columbia) Innovative Application of SAR and Deep Learning for Improved Oil Spill Detection The proposed concept entails the development of a significantly improved and scalable deep-learning model, with the objective to provide faster and cost-effective oil pollution information to mitigate the environmental impact of an oil spill.
Metaspectral – MLVX Technologies Inc. (British Columbia) Spaceborne Hyperspectral Imagery Analysis by Means of a Cloud-Based Platform for Sustainable Agriculture Metaspectral's project seeks to integrate commercial hyperspectral satellite capabilities with its proprietary deep-learning software infrastructure for precision farming. The goal is to ultimately develop a dashboard providing daily to weekly maps of crop properties, emphasizing chlorophyll, carotenoid, anthocyanin content, and leaf area index using the VNIR spectral range. This initiative aims to enhance sustainable agriculture by furnishing high-resolution, accurate crop data to aid in improving crop health, quality, and yield. Ultimately, it aims to empower Canadian farmers to produce more food with reduced environmental impact.
Mission Control Space Services Inc. (Ontario) Onboard Satellite Detection for Real-Time Wildfire Response Canada's boreal forest is a crucial carbon sink, economic driver, and environmental wonder, and it is threatened by increasingly frequent and intense wildfires. Mission Control will develop a concept solution using onboard satellite neural networks for EO to integrate in-orbit wildfire detection and processing capability, reducing latency to on-the-ground wildfire first responders' action.
NextGen Environmental Research Inc. (Manitoba) Near-Real-Time Lake Ice Hazard Mapping Service in Canada The project will create a testing platform and service to identify, monitor, and validate lake ice hazards in near real time using RADARSAT Constellation Mission (RCM) imagery and new Machine Learning models to classify lakes of all sizes. The objective is to broaden the platform's scope to various types of lakes and different conditions. The output products and service will be used by local Indigenous communities and others to reduce the risk of traversing lakes in northern regions during regular freeze-up seasons.
NorthStar Ciel et Terre Inc. (Quebec) Development of a Forest Species Mapping System (FSMS) using Deep Learning and Space-Based Earth Observation (SBEO) The scope of the proposed concept is to develop a forest species mapping system (FSMS) by leveraging deep learning, and open and commercial space-based EO. The FSMS concept is a new processing pipeline that will be developed to streamline data processing, analysis, and integration of space-based, ancillary, and ground data. The pipeline will leverage cloud computing capabilities to handle big-data management and accelerate data processing and tree species map generation.
Remote Digital Twin Inc. (Newfoundland and Labrador) Enhancing Urban Green Spaces, Spaceborne Hyperspectral Solution for Tree Health Monitoring and Insect Management This project aims to revolutionize urban tree health monitoring and insect infestation management in Canada by leveraging hyperspectral spaceborne data and Artificial Intelligence (AI) models.
Terra Motion Canada (Ontario) Measuring and Monitoring GHG Emissions from Canadian Peatland Using Satellite InSAR This project aims at calibrating and validating a method to measure greenhouse gas emissions from peatlands throughout the country. It is a new and unique method to monitor the health of Canadian peatland and measure greenhouse gas emissions to preserve them as a major carbon sink.
TRE ALTAMIRA Inc. (British Columbia) Tailings Storage Facilities Water Mapping Benchmarking synthetic aperture radar (SAR) and optical data for tailings storage facilities (TSF) water mapping: a foundation for deep-learning classification techniques specifically designed for TSFs.

smartHarbour initiative: satellite data to help monitor and protect our ecosystems

As part of the smartHarbour initiative, the Canadian Space Agency (CSA) is collaborating with Public Services and Procurement Canada (PSPC) and the Montreal Port Authority (MPA) to develop innovative applications using satellite data as part of the Port of Montreal expansion in Contrecœur.

As a result of the request for proposals Intelliport - monitoring environmental variables using EO technologies published on February 28, 2023, and on behalf of the CSA, PSPC has awarded four research and development contracts, totalling $4 million, to the following Canadian companies.

These research and development projects would allow for tracking of different environmental variables that are important for conserving the biodiversity of natural habitats, both while the new MPA terminal is being built and afterwards.

List of projects that received funding for the smartHarbour initiative: satellite data to help monitor and protect our ecosystems
List of projects that received funding for the smartHarbour initiative: satellite data to help monitor and protect our ecosystems
Organization Partner(s) Contract value Project description
WSP Canada Inc.
Montreal, Quebec
  • University of Ottawa
  • Simon Fraser University
  • Fluvial Systems Research onc.
  • Wyvern Inc.
$999,979 Develop cutting-edge satellite EO technology solutions in order to follow up on aquatic environmental variables in the St. Lawrence River.
Hatfield Consultants LLP
North Vancouver, British Columbia
  • Ducks Unlimited Canada
  • Arctus Inc.
  • Université du Québec à Trois-Rivières
  • University of Victoria
$1,000,000 Develop and integrate innovative EO satellite solutions on the GEOAnalytics Canada platform in order to follow up on environmental variables in river and coastal environments.
Arctus Inc.
Sainte-Pétronille, Quebec
  • Université Laval
  • Hatfield Consultants LLP
  • Université du Québec à Rimouski
  • Northern Institute for Research in Environment and Occupational Health and Safety
  • Université du Québec à Trois-Rivières
$1,000,000 Develop an aquatic and geomorphic monitoring system using EO satellite technologies in order to assess the impacts of port expansion in a river environment.
AECOM Consultants Inc.
Montreal, Quebec
  • Institut national de la recherche scientifique
$999,980 Develop a scientific system of following up on environmental variables in terrestrial environments within river areas using EO satellite technologies and artificial intelligence.

AO: Canadian downstream space sector delivering on Canada's better future

Following the launch of the AO Canadian Downstream Space Sector Delivering on Canada's Better Future in organizations from across Canada were selected. Contributions for these projects range from $150K to $500K and total approximately $8M. By funding the development of new innovations, the Government of Canada helps for-profit and not-for-profit organizations accelerate their journey to market and helps create good middle-class jobs across Canada.

List of projects that received funding for the AO: Canadian downstream space sector delivering on Canada's better future
List of projects that received funding for the AO: Canadian downstream space sector delivering on Canada's better future
Organization Contribution value Technology description
3v Geomatics Inc.
Vancouver, British Columbia
$400,000.00 Create an automated data processing pipeline and provide access to this data through a web visualization platform that can be used for monitoring infrastructure extending across thousands of kilometres, while still highlighting displacement areas as small as tens of metres.
A.U.G. Signals Ltd.
Toronto, Ontario
$499,969.40 Develop a technology that can provide a reliable estimation of snow water equivalent for monitoring and forecasting of potential snowmelt flood events through utilizing RADARSAT Constellation Mission data.
AIRM Consulting Ltd.
Winnipeg, Manitoba
$400,000.00 Develop an innovative AI-driven device that integrates multi-spectral sensors and ground data leading to novel quantitative data and improved crop monitoring, protein management, decision support, and insurance applications, overcoming technological hurdles pertaining to cost, scale/range, image quality, computational intensity and seamless interoperability.
C-CORE
St. John's, Newfoundland and Labrador
$400,000.00 Develop the world's first high-resolution offshore platform Greenhouse Gas (GHG) emissions monitoring from satellites. This project will advance offshore emissions monitoring to an application solution ready for operational implementation.
CubeWerx Inc.
Gatineau, Quebec
$400,000.00 Develop a platform with an improved data access and usability allowing value adders of EO solutions to offer their applications as a service to users of the platform.
Deploy Software Solutions Inc.
Ottawa, Ontario
$331,899.87 Combine different observational approaches in a new method of environmental and disaster assessment using SBEO techniques and imagery. This will help close a critical communication gap and allow scientists and government officials to enlist citizens to validate and enhance the satellite image processing algorithms directly and in near real time, to determine the "ground truth."
EarthDaily Analytics Corp.
Vancouver, British Columbia
$499,999.30 Test the ability to use SBEO data to quantify both the amount of phosphorus phytoextracted and carbon sequestered for a set of varied field trials carried out by partners in the Lake Winnipeg basin.
Geosapiens Inc.
Quebec City, Quebec
$298,514.23 Improve knowledge and management of flood risks through an enhanced E-NUNDATION solution by allowing decision makers to have a global and up-to-date vision of the risk and allowing insurers to better assess the risks of their clients. This will contribute to ensure the safety of citizens and increase their resilience to this natural hazard, particularly in the context of climate change.
GHGSat Inc.
Montreal, Quebec
$400,000.00 Develop an innovative capability for validated dynamic three-dimensional greenhouse gas emissions estimation on a global scale using data from GHGSat satellites and third-party satellites.
HabitatSeven Inc.
Ottawa, Ontario
$429,335.00 Develop a software framework that can be used by a variety of stakeholders (agriculture, finance, government and others) to develop, visualize, and integrate historical and operational evapotranspiration estimates.
Kepler Space Inc.
Ottawa, Ontario
$500,000.00 Provide streamlined methodology and data to generate product for wide-area monitoring of ground deformation over the entire Quebec City–Windsor transportation corridor as well as the Hudson Bay Railway in northern Manitoba, and validate such data for use in railway and bridge infrastructure monitoring systems.
Kongsberg Geospatial Ltd.
Ottawa, Ontario
$221,293.39 Merge the airborne track picture with the maritime track picture (Automatic Identification System) integrated with geospatial decision support tools providing rapid situational awareness accessible anywhere in the world via space-based Internet access. This near-real-time picture of vehicle movements, combined with real-time weather and geospatial data will allow commanders to make informed decisions, anywhere, anytime, wherever deployed around the world.
KorrAI Technologies Ltd.
Halifax, Nova Scotia
$150,000.00 Provide near-real-time, dynamic surface deformation monitoring and commercialize the petabytes of over 20 years' worth of historical radar data collected from the previous RADARSAT-1 mission, as well as ongoing data collected by the RCM mission.
Liquid Geomatics Ltd.
Ottawa, Ontario
$292,875.00 Turn a prototype satellite-derived bathymetry into an operational product to map and detect shallow water from available satellite imagery, to help avoid accidents, environmental damage, rescue and salvage costs, and loss of life.
Lux Aerobot Inc.
Alma, Quebec
$351,247.00 Develop a platform-agnostic wildfire management system, in collaboration with INO and using requirements from SOPFEU and Natural Resources Canada, to accomplish near-real-time processing to provide a high-resolution thermal mapping of active wildfires within less than 15 minutes of the image being acquired.
MLVX Technologies Inc.
Vancouver, British Columbia
$150,000.00 Build a method to systematically and methodically quantify the carbon dioxide (CO2) level present at ground-elevation using hyperspectral data. Provide the information required for the governments and private entities such as farmers to track their carbon footprint and capture the associated economic benefits.
NextGen Environmental Research Inc.
Winnipeg, Manitoba
$499,946.71 Develop a commercial capacity to monitor freshwater lake ice hazards from space using satellite radar and distribution of ice hazard maps to user's cell phones and desktop computers in near real time.
SkyWatch Space Applications Inc.
Waterloo, Ontario
$399,000.00 Develop a state-of-the-art cloud-enabled cataloging, ordering, searching, processing, distribution and collaboration platform for EO data, catering to the unique needs of large organizations and governments.
The Arctic Eider Society
Sanikiluaq, Nunavut
$500,000.00 Develop an enhanced version of the SIKU Ice Map to identify persistent hazards in the landfast ice and set the groundwork for the first-ever Indigenous-trained machine learning algorithm that delivers EO derived products at scale for the benefit of northern shipping, sea ice travel safety and climate change research.
Vertex Professional Services Ltd.
Sherwood Park, Alberta
$299,998.20 Assist Vertex and the T'Sou-ke Nation SNA-QUA Centre in co-developing new environmental solutions relevant to Indigenous and coastal communities through analyses of EO big data.
Xona Space systems Canada Inc.
Vancouver, British Columbia
$495,120.00 Enable advanced remote sensing and navigation applications from a commercial PNT satellite constellation.

Request for proposals: smartWhales

As a result of the request for proposals smartWhales 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 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:

List of projects that received funding for the request for proposals: smartWhales
List of projects that received funding for the request for proposals: smartWhales
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
  • M – Expertise 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.

AO: 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 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 the AO 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.

List of projects that received funding for the AO: Bridging the information gap with space-based analytics
List of projects that received funding for the AO: Bridging the information gap with space-based analytics
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 EO 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 EO 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 EO 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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