Biodiversity and Habitat Restoration System

Biodiversity and Habitat Restoration System is sponsored by Canadian Space Agency. Develops a platform to monitor the Prairies annually to track the effects of climate change on habitat biodiversity.

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Funding programs and opportunities # 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: Satellite Mobilization for Biodiversity Action Following the launch of the AOSatellite Mobilization for Biodiversity Action in January 2025, 20 companies from across Canada were selected to develop applications that use satellite data to safeguard biodiversity.

The organizations were tasked with developing innovative concepts to support Canada's 2030 Nature Strategy, particularly in assessing ecosystems and biodiversity with a focus on restoration and conservation. Each company received up to$250,000. These projects will harness the transformative potential of artificial intelligence (AI) and Earth observation technologies and will contribute to meaningful progress on climate action.

List of projects that received funding for the AO: Satellite Mobilization for Biodiversity Action List of projects that received funding for the AO: Satellite Mobilization for Biodiversity Action | Arctus Inc. (Quebec) | EeyouSat | This project aims to enhance satellite-based mapping and monitoring of coastal ecosystems, with an initial focus on Eeyou Istchee, where the Cree Nation has reported habitat degradation.

It will conduct R&D to improve mapping of submerged vegetation and coastal ice. | | A. U.

G. Signals Ltd. (Ontario) | AI-powered satellite-based approach for freshwater biodiversity and risk assessment | This project aims to develop a web-based GIS software prototype that will provide remote sensing based algal bloom detection, algae concentration, and water quality assessments and monitoring. This technology will benefit Canadians by enabling healthier ecosystems that provide clean air, water, and local climate regulation.

| | ASL Environmental Sciences Inc. (British Columbia) | De CAF-RRT | This project aims to develop the De CAF-RRT, a wide-area monitoring tool using satellite Earth observation (SEO), to support salmon habitat monitoring. Effective monitoring promotes healthy ecosystems, sustainable biodiversity, and stable salmon populations for food and economic security.

| | Birds Canada (Ontario) | Applications to integrate SEO information into NatureCounts platform | NatureCounts, the largest biodiversity data repository in Canada, is a technology platform used to collect, analyze and share critical information on bird populations. This project aims to develop the tools needed to integrate SEO information into the collection and interpretation of biodiversity data.

| | Complex System Inc. (Alberta) | Satellite analytic | This project aims to develop a trustworthy AI software based on a data-driven predictive-3D technology from a single 2D satellite image. It will provide new high-resolution 3D maps and change-detection to aid in assessing land, agriculture, and provide resilience to topography changes.

| | Fluvial Systems Research Inc. (FSR) (British Columbia) | Arctic marine mammal ecosystem SEO monitoring | The objective of this project is to contribute to Fisheries and Oceans Canada's Arctic Sciences assessment of the impacts of climate change and human activities on the ecology of Arctic marine mammals by integrating satellite Earth observation data into marine ecosystem monitoring.

| | Habitat Inc. (Eco2Urb) (Quebec) | Detecting long-term trends in biodiversity change with EO | This project aims to develop a framework to guide investments by analyzing spatial and temporal changes in land cover and biodiversity indicators using Earth observation and AI in five case study watersheds.

| | Hatfield Consultants Partnership (British Columbia) | Hatfield SAVER | This project aims to integrate existing and novel SEO biodiversity products into a multimodal machine learning (MM-ML) model to assess ecosystem recovery, validated through two boreal forest case studies focusing on woodland caribou and birds.

| | Korotu Technology Inc. (Ontario) | Landsteward Farm | This project aims to leverage Earth observations from satellites, drones, and ground-based technologies (e.g., mobile phones) to improve the ability to quantify, map, and monitor biodiversity in the complex mosaic of land use and land management of agricultural landscapes.

| | Metaspectral, MLVX (British Columbia) | AI-driven detection and monitoring of invasive leafy spurge | This project aims to develop an AI-powered online platform using high-resolution satellite imagery to rapidly detect and monitor leafy spurge, a highly invasive plant threatening Canada's agriculture and biodiversity, mapping populations and tracking changes over time to support decision-making.

| | Northern Hardwoods Research Institute (New Brunswick) | Advancing biodiversity monitoring and ecosystem change detection | This project aims to develop an AI-powered system using satellite imagery and remote sensing technology to monitor biodiversity and track ecosystem changes in New Brunswick, including habitat features, forest regrowth, and the impacts of ecosystem management and climate change.

| | Orcinus Technologies Inc. (Newfoundland and Labrador) | Biodiversity-driven traffic optimization system | This project aims to develop an advanced traffic safety system using AI, satellite imagery, drones, and smart sensors to detect moose movements and warn drivers in real time. By predicting high-risk areas, the system will send alerts to navigation apps, adjust speed limits, and enhance road safety.

| | SkyWatch Space Applications Inc. (Ontario) | VHR land cover products for biodiversity | This project aims to deliver on-demand Earth observation tools for biodiversity monitoring using the SkyWatch cloud platform, combining VAP processing, VHR landcover, and specialized data to turn optical, SAR, and hyperspectral imagery into actionable insights.

| | Vanderkooij Consult Inc. (Ontario) | Vanderkooij Consult SAR time series | This initiative aims to develop cost-effective monitoring tools for Northern Canada's ecosystems, collaborating with government and Indigenous partners to track climate and biodiversity impacts and guide future SAR land monitoring strategies.

| | Wildlands League (Ontario) | EO&Indigenous knowledge for bird and community climate resilience | This project aims to map climate strongholds for migratory birds in Canada and their links to U.S. and Latin American sites, then uses satellite data and Indigenous knowledge to assess conditions breeding climate strongholds in the Hudson Bay Lowlands and connected nonbreeding areas.

| ## Request for proposals: Accelerating Earth Observation Innovations (Stage 2) Following the request for proposals Accelerating EO Innovations published on August 31,2023, 22 companies were selected to develop applications that use satellite data. The companies were tasked with finding innovative concept solutions in order to address Canada's key environmental and socioeconomic challenges.

In July 2024, a second request for proposals was published. Five of the companies that took part in Stage 1 were selected to further advance their concepts and received up to$780,000. This phase focuses on the development and demonstration of their proposed solutions for business and government users.

List of projects that received funding for the AO: Accelerating Earth Observation Innovations (Stage 2) List of projects that received funding for the AO: Accelerating Earth Observation Innovations (Stage 2) | Alta ML 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 improvedmuch-improved whale detection and monitoring processes. | | C-CORE (Newfoundland and Labrador) | Mitigating Arctic Challenges Using AI (MACAI) | C-CORE's 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.

| | 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.

| | Hatfield Consultants LLP (British Columbia) | Eelgrass Explorer (E2) System | The 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.

| | 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 Earth observation to integrate in-orbit wildfire detection and processing capability, reducing latency to on-the-ground wildfire first responders' action.

| ## Announcement of Opportunity: Research Opportunities in Satellite EO (ROSEO) Following the launch of the Announcement of Opportunity(AO) Research Opportunities in Satellite EO in October 2023, 17 projects submitted by 13 post-secondary institutions across Canada were selected.

Grants for these projects allowed academia to be equipped with resources, to collaborate with national and international partners, and to train new highly qualified personnel (HQP). All the projects 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 | 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 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 AI 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 2022 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 (Stage 1) Following the request for proposals Accelerating EO Innovations published on August 31, 2023, the Canadian Space Agency (CSA) is investing $1. 1 million in 22 companies to develop applications that use satellite data. The companies are tasked with finding innovative concept solutions to address Canada's key environmental and socioeconomic challenges.

The 22 companies will define their solutions during Stage 1 of this process. Then, the CSA assessed the potential of the proposed solutions and selected the companies that would receive up to $50,000 each and move on to Stage 2, concept demonstration.

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 | 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 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.

| | Alta ML 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.