Martinique Road Surface and Passability Data for 700km of Arterial Roads

Offering AI-derived road surface, width, and passability metrics for approximately 700 km of arterial roads in Martinique, produced by HeiGIT using PlanetScope satellite imagery from 2020 and 2024. It integrates OpenStreetMap road segments with deep-learning predictions to assess logistical accessibility and surface transitions over a four-year period.

Use Cases

• Monitoring infrastructure development by analyzing 'Road Surface Change' from unpaved to paved between 2020 and 2024
• Planning humanitarian logistics using the 'Humanitarian Passability Index (HPI)' to identify high-access routes
• Assessing vehicle restrictions based on 'Road Width Class' to determine if segments support two-lane heavy truck flow

Strengths

• 89.2% surface model accuracy compared to 64.7% for standard OSM tags
• Multi-temporal coverage enabling change detection between 2020 and 2024
• Standardized Humanitarian Passability Index (HPI) for logistical planning

Limitations

• AI-derived predictions may contain errors compared to ground-level surveys
• Geographic scope is restricted to Martinique
• Excludes non-arterial road networks which may be critical for last-mile delivery

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

The dataset utilizes satellite imagery from 2020 and 2024, with the last metadata update in March 2026.

Geography

Martinique