Yemen Road Surface and Passability: 15,100 km of AI-Derived Metrics

15,100 km of arterial roads in Yemen are mapped with AI-derived surface and width attributes generated by HeiGIT. Using PlanetScope satellite imagery from 2020 and 2024, the data provides a Humanitarian Passability Index (HPI) and identifies surface transitions from unpaved to paved. This analysis focuses on motorways, trunks, and primary/secondary roads that form the national transportation backbone.

Use Cases

• Logistical routing using the Humanitarian Passability Index (HPI) to rank segments from highest to lowest accessibility
• Infrastructure development tracking by filtering the Road Surface Change (2020-2024) indicator for unpaved-to-paved transitions
• Fleet management using Road Width Class to identify segments restricted to light vehicles versus heavy trucks

Strengths

• 89.2% surface model accuracy
• Covers 15,100 km of arterial road segments
• Provides data for 23.8% of roads missing surface tags in OSM

Limitations

• Focuses only on high-capacity arterial roads
• AI-derived predictions may contain errors compared to ground-truth verification

Provenance

Source

Heidelberg Institute for Geoinformation Technology (HeiGIT)

Collection Method

AI-derived predictions from PlanetScope satellite imagery (2020 and 2024) integrated with OpenStreetMap attributes

Time Range

2020-2024

Freshness

Last updated March 2026; temporal comparison covers imagery from 2020 and 2024.

Geography

Yemen