GeoAI - GeoBase Series

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 and temporal coverage.

The infrastructure and expertise put in place by NRCan enables a rapid, efficient, and scalable data creation process through the use of leading-edge technology and Artificial Intelligence models. Published datasets for a given source can be revisited at a later date as more accurate models are developed and put into production. For now, only static files are available, but as the series develops, new products and services will be added.

Data and Resources

Additional Info

Field Value
Last Updated April 17, 2026, 19:28 (UTC)
Created April 17, 2026, 19:28 (UTC)
contact_email geoinfo@nrcan-rncan.gc.ca
contact_person {"en": "Government of Canada; Natural Resources Canada; Strategic Policy and Innovation Sector,geoinfo@nrcan-rncan.gc.ca", "fr": "Gouvernement du Canada; Ressources naturelles Canada; Secteur de la politique stratégique et innovation,geoinfo@nrcan-rncan.gc.ca"}
criticality_level []
data_dictionary ["imagery_base_maps_earth_cover"]
geographic_scope []
open_canada_collection fgp
open_canada_date_published 2023-10-01 00:00:00
open_canada_keywords {"en": ["Earth Sciences", "GeoBase", "GeoAI", "Artificial intelligence", "Deep learning", "Automatic Extraction", "Vector Data Production", "Topography", "Buildings", "Hydrography", "Forests", "Roads", "Geographic data"], "fr": ["Sciences de la Terre", "GéoBase", "GéoIA", "Intelligence artificielle", "Apprentissage Profond", "Extraction Automatique", "Production de données vectorielles", "Topographie", "Bâtiments", "Hydrographie", "Forêts", "Routes", "Données géographiques"]}
open_canada_subject ["form_descriptors"]
sensitivity_level unrestricted
title_fr GéoIA - Série GéoBase
update_frequency irregular