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

HeiGIT produced this dataset covering approximately 2,700 km of arterial roads in Haiti using PlanetScope satellite imagery from 2020 and 2024. It provides AI-derived classifications for road surface, width, and a Humanitarian Passability Index (HPI) to supplement missing OpenStreetMap (OSM) attributes. The analysis focuses on motorway, trunk, primary, and secondary road classes.

Use Cases

• Monitoring infrastructure development by tracking 'Road Surface Change' from unpaved to paved between 2020 and 2024
• Logistics planning for heavy vehicles using 'Road Width Class' to identify routes capable of unimpeded two-lane flow
• Prioritizing humanitarian aid delivery routes based on the 'Humanitarian Passability Index (HPI)' score

Strengths

• 89.2% surface model accuracy
• Fills surface tags for 2,600 km of roads missing data in OSM
• Multi-temporal analysis comparing 2020 and 2024 infrastructure

Limitations

• Restricted to arterial road classes only
• AI-derived predictions may contain errors compared to ground-truth verification
• Width and passability are estimated from satellite imagery rather than physical measurements

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

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

Time Range

2020-2024

Freshness

Last updated March 2026; utilizes satellite imagery from 2020 and 2024.

Geography

Haiti