Saint Barthélemy Road Surface, Width, and Passability (2020-2024)

HeiGIT produced this dataset of AI-derived road surface, width, and passability metrics for Saint Barthélemy's arterial road network using 2020 and 2024 PlanetScope imagery. It supplements OpenStreetMap (OSM) data with deep-learning predictions for motorway, trunk, primary, and secondary road segments.

Use Cases

• Assessing logistical constraints for emergency response using the Humanitarian Passability Index (HPI) scores
• Monitoring infrastructure development by analyzing the Road Surface Change indicator for transitions from unpaved to paved
• Planning heavy vehicle routes based on Road Width Class to identify segments capable of supporting two-lane truck flow

Strengths

• Surface model achieved 89.2% accuracy, significantly higher than OSM surface tags at 64.7%
• Provides multi-temporal surface data (2020 and 2024) for infrastructure change detection
• Standardized width classification based on vehicle capacity and blockage risk

Limitations

• Geographic scope is limited to the island of Saint Barthélemy
• Predictions are AI-derived and subject to model error despite high accuracy scores
• Excludes minor and residential roads which may be critical for last-mile logistics

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

Deep learning predictions generated from PlanetScope satellite imagery integrated with OpenStreetMap road segment attributes.

Time Range

2020-2024

Freshness

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

Geography

Saint Barthélemy