Andorra Road Surface and Passability Data from PlanetScope Imagery

A collection of AI-derived road surface, width, and passability metrics for approximately 300 km of arterial roads in Andorra, produced by HeiGIT using 2020 and 2024 PlanetScope satellite imagery. It integrates OpenStreetMap (OSM) attributes with deep-learning predictions to fill gaps in existing road infrastructure data, achieving 89.2% accuracy for surface classification.

Use Cases

• Logistics planning using the Humanitarian Passability Index (HPI) to identify accessible routes for heavy vehicles
• Infrastructure development monitoring by analyzing the Road Surface Change indicator between 2020 and 2024
• Vehicle routing optimization based on Road Width Class constraints for different vehicle types

Strengths

• 89.2% surface model accuracy compared to 64.7% for OSM tags
• Provides surface data for 97% of roads missing OSM surface tags
• Includes temporal change detection between 2020 and 2024
• Standardized Humanitarian Passability Index (HPI) for logistical planning

Limitations

• Small geographic scope restricted to Andorra
• AI-derived predictions may contain errors compared to ground-level truth
• Limited to high-capacity transportation backbone roads

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

Deep learning analysis of PlanetScope satellite imagery combined with OpenStreetMap data

Time Range

2020 - 2024

Freshness

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

Geography

Andorra