Argentina Road Surface and Passability Data for 109,700 km of Arterial Roads

HeiGIT produced this dataset of AI-derived road surface, width, and passability metrics for 109,700 km of arterial roads in Argentina using 2020 and 2024 PlanetScope imagery. It supplements OpenStreetMap data by providing surface predictions for segments lacking tags, achieving a validated accuracy of 89.2%.

Use Cases

• Logistics planning using the Humanitarian Passability Index (HPI) to identify routes with high blockage risk
• Infrastructure monitoring by identifying unpaved-to-paved transitions via the Road Surface Change indicator
• Fleet routing optimization based on Road Width Class to ensure heavy trucks only use Class 3 segments

Strengths

• 89.2% accuracy for AI-derived surface models compared to 64.7% for OSM tags
• Covers 109,700 km of arterial road segments
• Includes temporal change detection between 2020 and 2024 imagery

Limitations

• Focuses exclusively on arterial roads, excluding tertiary and local road networks
• AI-derived attributes are predictions and may contain errors despite high validation scores
• Geographic scope is limited to Argentina

Provenance

Source

Heidelberg Institute for Geoinformation Technology (HeiGIT)

Collection Method

Deep learning predictions derived from PlanetScope satellite imagery integrated with OpenStreetMap road geometries

Time Range

2020 - 2024

Freshness

Based on satellite imagery from 2020 and 2024; last updated March 2026.

Geography

Argentina