Spain Road Surface and Passability: 131,000 km of AI-Derived Metrics

Spanning 131,300 km of arterial roads in Spain, providing AI-derived surface types and width classifications generated by HeiGIT from 2020 and 2024 PlanetScope satellite imagery. It integrates OpenStreetMap (OSM) geometry with deep-learning predictions to fill gaps where OSM surface tags are missing for nearly 50% of the network.

Use Cases

• Logistics optimization using the Humanitarian Passability Index (HPI) to identify accessible routes for heavy machinery
• Infrastructure monitoring by tracking Road Surface Change (2020-2024) to identify recently paved segments
• Emergency transport planning using Road Width Class to filter for roads supporting two-lane heavy truck flow

Strengths

• 89.2% model accuracy for surface type prediction
• Covers 131,300 km of the Spanish arterial road network
• Fills surface data gaps for 48.3% of segments lacking OSM tags

Limitations

• Geographic scope limited to arterial roads only
• AI-derived predictions may have localized errors compared to ground-truth surveys

Provenance

Source

Heidelberg Institute for Geoinformation Technology (HeiGIT)

Collection Method

Deep learning analysis of PlanetScope satellite imagery integrated with OpenStreetMap vector data.

Time Range

2020-2024

Freshness

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

Geography

Spain