Grants and Contributions

The Sustainable Protein Production program undertook a collaborative project (SPP-121) with Dr. Nathan Pelletier (UBC) to develop a data management strategy capable of capturing and using Life Cycle Inventory (LCI) and Technology Development Matrix (TDM) approaches to efficiently enable Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) of standard plant protein fractionation technologies. The SPP-121 project was successful in developing a framework with a platform to assess environmental and economic sustainability aspects of pulse processing, including industry partner engagement and field data collection. Several gaps were identified including upstream data related to feedstocks and logistics, lack of social indicators assessment, multiplicity of data sources and formats, and technology data gaps across the whole value chain. Furthermore, the current lack and/or public availability of relevant data sets hinders deployment of both current sustainability assessment methods and advanced machine leaning techniques to both develop data gap filling techniques and to identify best-fit technology solutions to known sustainability challenges. These issues will be addressed as part of the new project proposed herein.

Sport - Hosting Program - International Single Sport Events

The Women’s Economic Empowerment Through Advancing Women-Led Enterprises in Lebanon project aims to improve the economic security, stability, and prosperity of 1,200 women-led micro-, small and medium-sized enterprises (MSMEs) and entrepreneurs in productive sectors with high growth and export potentials in Lebanon. The project seeks to achieve this by improving the business-enabling environment by strengthening the capacities and procedures of public and private institutions to better serve and promote women-led businesses. It seeks to improve funding availability and related financial instruments through matching grants, an equity fund scheme and a gender-sensitive digital business matchmaking platform. It focuses on improving women-led business’ agencies’ access to financial products and engage with local and international markets by strengthening their financial, business, investment and export readiness skills.

This project aims to improve the climatic and economic resilience of women through the preservation and restoration of biodiversity and the sustainable use of forest and agroforestry ecosystems. It aims to reduce the technical, informational and socio-cultural barriers faced by women and young women in communities bordering the targeted ecosystems. Project activities include: (1) building technical capacity in agroforestry and agro-ecology; (2) strengthening skills in the management of green enterprises focusing on the sustainable harvesting and valorization of non-timber forest products; and (3) enhancing transformative leadership for active participation in local land and forest resource management and governance mechanisms.
The project seeks to benefit at least 4,475 people in 14 communities in Burkina Faso and Benin, including 4030 women, 1800 internally displaced people, and 28 women's associations. It also seeks to strengthen 14 local forest and land governance bodies.

This project aims to enhance Canada's training capacity in satellite-based Earth observation to meet the growing demand for skilled professionals capable of handling large datasets and utilizing technologies like cloud computing and machine learning. Collaborating with industry and government partners across various application areas, the project 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.

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 and Canadian Arctic waters. 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.

The objective of this project is to develop an AI-based algorithm that can improve atmospheric correction of satellite images over 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.

The Copernicus Expansion Missions Sea Ice Experiment (CEMSIE) project, led by a consortium of Canadian and European universities, with support from the European Space Agency (ESA), 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 its 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.

This project aims to enhance understanding of Canada's surficial geology by developing an automated method using remote 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.

Nitrous oxide (N2O) emissions, primarily from agricultural activities, pose a significant challenge to 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.