Solomon Islands Road Surface and Passability Data (2020-2024)

AI-derived road surface, width, and passability metrics for arterial roads in the Solomon Islands, generated by HeiGIT using PlanetScope satellite imagery from 2020 and 2024. It covers motorway, trunk, primary, and secondary road classes, integrating OpenStreetMap attributes with deep-learning predictions that achieved 89.2% accuracy in surface classification.

Use Cases

• Logistics planning using the Humanitarian Passability Index (HPI) to identify high-risk blockage points
• Infrastructure development monitoring by tracking 'Road Surface Change' from unpaved to paved status
• Transportation capacity modeling using 'Road Width Class' to determine heavy truck flow feasibility

Strengths

• 89.2% surface model accuracy
• Multi-temporal surface change detection (2020-2024)
• Standardized Humanitarian Passability Index (HPI) scores

Limitations

• Restricted to arterial road network only
• AI-derived predictions may contain errors compared to ground-level verification
• Relies on OSM geometry which may have its own spatial inaccuracies

Provenance

Source

Heidelberg Institute for Geoinformation Technology (HeiGIT)

Collection Method

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

Time Range

2020 - 2024

Freshness

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

Geography

Solomon Islands