Sudan Road Surface and Passability Data for 16,600 km of Arterial Roads

Offering AI-derived road surface, width, and passability metrics for 16,600 km of arterial roads in Sudan, produced by HeiGIT using 2020 and 2024 PlanetScope satellite imagery. It covers motorway, trunk, primary, and secondary road classes, filling surface data gaps for approximately 4,500 km of the network where OpenStreetMap tags were missing.

Use Cases

• Logistics planning using the Humanitarian Passability Index (HPI) to identify accessible routes for heavy trucks.
• Infrastructure monitoring by analyzing the Road Surface Change column to identify newly paved segments between 2020 and 2024.
• Fleet management optimization using Road Width Class to determine if segments can support two-lane heavy truck flow.

Strengths

• 89.2% accuracy for surface model predictions
• Covers 16,600 km of the Sudanese arterial road network
• Provides temporal change detection between 2020 and 2024 imagery

Limitations

• Geographic scope is limited to Sudan
• Excludes lower-tier road classifications like residential or unclassified streets
• AI-derived predictions may contain errors inherent to satellite imagery analysis

Provenance

Source

Heidelberg Institute for Geoinformation Technology (HeiGIT)

Collection Method

Deep learning models applied to PlanetScope satellite imagery and integrated with OpenStreetMap road geometries.

Time Range

2020 - 2024

Freshness

Based on satellite imagery from 2020 and 2024, with the dataset last updated in March 2026.

Geography

Sudan