Grants and Contributions

The imagery will be used in the development of orthomosaic and resulting prescription maps that will be uploaded into self propelled sprayers and used as part of an emerging smart agricultural practices.

We will collect data that includes a users purchase patterns, heat map, user flow, top products clicked, top sections clicked, etc.

ECONSEC will conduct research on economic security and corporate espionage – with a particular focus on businesses and universities – as a key element of national security, Canadian defence and Canadian prosperity. ECONSEC intends to map and identify this new threat reality and connect The Department of National Defence and the Canadian Armed Forces (DND/CAF) with leading experts to inform the policy debate.

This project aims to empower diverse young women and men to be collaborative leaders driving peaceful change in the northern borderlands of Côte d’Ivoire and Ghana. It seeks to increase the prospects for sustained peace and security in the northern border regions by empowering young people to strengthen the emerging peacebuilding ecosystem in the region.

To this end, the NRC has developed an advanced numerical model (CaMPSim-3D) to simulate the fate and transport of microplastics in water bodies using the particle tracking method.

Lawrence River will be studied through multi-seasonal and multi-site sampling campaigns, analytical characterization and data integration into the NRC’s COMEX platform to validate its CaMPSim-3D model. The project will quantify the distribution of MNP in the River, identify their main sources, and analyze the influence of hydrodynamics on their transport through seasonal fieldwork and several analytical characterization techniques.

Outcomes involve establishing a community of practice through workshops, laying groundwork for MAP modules integration into existing MAP ecosystems, and fostering industry interactions.

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, 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.

This project will focus on the design and manufacturing of a mobile mapping system for geospatial data collection, that uses lidar, cameras, and other positioning and navigation sensors.