Natural Resources Canada / Ressources naturelles Canada

Predict performance, cost, and life cycle assessment properties for CO2 capture technologies.

Harnessing the power of AI to deliver value in the form of location-based data automatically extracted over time and space, to better inform mapping of Canada's land, water, and infrastructure.

Machine learning to create a national map showing how likely a given area is to be affected by flooding.

Development of foundation geospatial model to the Canadian context.

Provide modelers and industry with stochastic electric arc furnace (EAF) gas composition, flow rate, temperature, and pressure.

This study shows how artificial intelligence (AI) can make industrial decarbonization research faster, smarter, and more effective.

Tool to predict and optimize the interaction of different influencing parameters for CO2 mineralization of industrial waste feedstocks under different environments and operating conditions.

Semantic Search for GEO.ca, a web portal that consolidate all of Canada's open geospatial resources into a single location - the largest collection of Canadian geospatial data from federal, provincial, and territorial...

Provide users with free and open maps of vegetation variables able to satisfy user requirements conditional on available analysis ready satellite data and on the performance of algorithms provided by the user.