South Sudan Road Surface and Passability for 9,300 km of Arterial Roads

Approximately 9,300 km of arterial roads in South Sudan are mapped with AI-derived surface, width, and passability metrics produced by HeiGIT. Using PlanetScope satellite imagery from 2020 and 2024, the data achieves 89.2% accuracy in surface classification, filling gaps for 46.7% of segments lacking OpenStreetMap tags.

Use Cases

• Logistics planning using the Humanitarian Passability Index (HPI) to determine route accessibility for heavy trucks
• Infrastructure monitoring by tracking the Road Surface Change (2020-2024) indicator for unpaved-to-paved transitions
• Transport capacity analysis using Road Width Class (1-3) to identify bottlenecks for two-lane heavy truck flow

Strengths

• 89.2% model accuracy for surface type prediction
• 9,300 km of arterial road coverage
• Temporal change detection between 2020 and 2024 imagery

Limitations

• Limited to arterial road classifications (motorway, trunk, primary, secondary), excluding local or residential streets
• Potential for 'Unknown' classifications in areas where satellite imagery was obstructed or unavailable

Provenance

Source

Heidelberg Institute for Geoinformation Technology (HeiGIT)

Collection Method

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

Time Range

2020-2024

Freshness

Last updated March 2026; includes comparative data from 2020 and 2024.

Geography

South Sudan