Gambia Arterial Road Surface and Passability Data (2020-2024)

This geospatial dataset provides AI-derived road surface, width, and passability metrics for approximately 1,200 km of arterial roads in Gambia. Produced by HeiGIT using 2020 and 2024 PlanetScope satellite imagery, it supplements OpenStreetMap (OSM) data with deep-learning predictions for motorway, trunk, primary, and secondary road classes.

Use Cases

• Logistics planning using the Humanitarian Passability Index (HPI) to identify high-capacity transport routes
• Infrastructure development monitoring by analyzing Road Surface Change from 2020 to 2024
• Vehicle routing optimization based on Road Width Class constraints for heavy trucks

Strengths

• 89.2% accuracy for surface model predictions
• Covers 1,200 km of arterial road infrastructure
• Provides surface data for segments where OSM surface tags are missing
• Includes temporal change detection between 2020 and 2024

Limitations

• AI-derived predictions may have errors compared to ground-level verification
• Geographic scope is limited to the national borders of Gambia
• Excludes lower-tier road classifications which may be critical for last-mile delivery

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

Deep learning analysis of PlanetScope satellite imagery integrated with OpenStreetMap road segment geometries.

Time Range

2020 - 2024

Freshness

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

Geography

Gambia