Natural Resources Canada

GeoAI are buildings, hydrography, forests, and roads automatically extracted using Deep Learning models applied to a source dataset, typically aerial or satellite images. The primary aim of GeoAI is to increase Canada's availability of high-resolution foundational geospatial data for both spatial...

The manmade features of the CanVec series include dams, protection structures (breakwater, dike/levees), liquid storage facilities (basin, swimming pool, etc.), tanks, buildings, delimiting structures (fence, walls, etc.), landmark features (cross, radar, crane, forts, etc.), chimneys, towers,...

“Automatically Extracted Buildings” is a raw digital product in vector format created by NRCan. It consists of a single topographical feature class that delineates polygonal building footprints automatically extracted from airborne Lidar data, high-resolution optical imagery or other sources.