Jamaica Road Surface and Passability Data for 2,500 km of Arterial Roads

HeiGIT produced this dataset covering approximately 2,500 km of arterial roads in Jamaica using AI analysis of PlanetScope satellite imagery from 2020 and 2024. It provides road surface types, width classifications, and a passability index to fill gaps in OpenStreetMap (OSM) data. The analysis focuses on motorway, trunk, primary, and secondary road classes.

Use Cases

• Monitoring infrastructure development by filtering 'Road Surface Change' for unpaved-to-paved transitions between 2020 and 2024
• Logistics routing for heavy machinery using 'Road Width Class' to identify segments supporting two-lane heavy truck flow (Class 3)
• Emergency accessibility mapping using the 'Humanitarian Passability Index (HPI)' to prioritize routes with high passability scores

Strengths

• 89.2% surface prediction accuracy compared to 64.7% for OSM tags
• Provides surface data for 16.9% of roads that lack OSM surface tags
• Includes temporal change detection between 2020 and 2024

Limitations

• Restricted to arterial road networks only
• AI-derived width and surface predictions may be affected by cloud cover or dense vegetation in satellite imagery

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

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

Time Range

2020 - 2024

Freshness

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

Geography

Jamaica