Canada Arterial Road Surface and Passability: 231,400 km AI-Derived Data

Supplying AI-derived attributes for 231,400 km of arterial roads in Canada, produced by HeiGIT using PlanetScope satellite imagery from 2020 and 2024. It maps road surface types, width classes, and a Humanitarian Passability Index (HPI) for segments classified in OpenStreetMap as motorway, trunk, primary, and secondary roads.

Use Cases

• Logistics planning for heavy vehicles using the Road Width Class to identify segments narrower than 3.5 meters
• Humanitarian access modeling using the Humanitarian Passability Index (HPI) to rank route accessibility
• Infrastructure monitoring by tracking Road Surface Change indicators between 2020 and 2024

Strengths

• High model accuracy of 89.2% for surface type prediction
• Temporal change detection identifying transitions from unpaved to paved surfaces over a four-year span
• Standardized width classification (Class 1-3) based on heavy truck flow capacity

Limitations

• Restricted to arterial road classes (motorway, trunk, primary, secondary), excluding local and residential streets
• Attributes are AI-derived from satellite imagery and may contain classification errors compared to ground-truth surveys

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

Deep learning analysis of PlanetScope satellite imagery integrated with OpenStreetMap road geometries

Time Range

2020-2024

Freshness

Last updated March 2026; utilizes satellite imagery from 2020 and 2024.

Geography

Canada