Mapping Canada's water and infrastructure

This project accelerates the creation of geospatial data layers and makes this data available for emergency management and response, flood mapping and change detection. This same data is also scalable for other data management and analysis applications.

Learn how artificial intelligence (AI) and big data techniques will enhance Canada’s foundational mapping layers.

Project objectives

The Canada Centre for Mapping and Earth Observation (CCMEO) maps and monitors Canada’s landmass to understand its shape, its changes and the various phenomena occurring over time. Given the size of Canada and the quantity of data that must be processed to map the country, this project uses deep learning (DL) a branch of artificial intelligence (AI) to extract and analyse the geospatial data. Results of this technique include the ability to automatically recognize water bodies, buildings, roads and vegetation.

Results of this technique include the ability to automatically recognize water bodies, buildings, roads and vegetation.

Digital and artificial intelligence techniques

• Predictive modelling
• Computer simulation
• Deep learning algorithms to classify imaging-recognized data
• High-performance computing environment to process big data

Data requirements

• Light detection and ranging (LIDAR), a remote sensing technique that uses laser light for high-resolution mapping
• High-resolution optical data (satellite and airborne imagery)