Guadeloupe Road Surface and Passability Data for 900km of Arterial Roads

HeiGIT generated this dataset of approximately 900 km of arterial roads in Guadeloupe using AI analysis of PlanetScope satellite imagery from 2020 and 2024. It supplements OpenStreetMap (OSM) data with deep-learning predictions for road surface, width, and a specialized Humanitarian Passability Index to fill gaps in existing mapping.

Use Cases

• Identifying logistical bottlenecks for emergency response using the 'Humanitarian Passability Index (HPI)'
• Monitoring national infrastructure development by analyzing 'Road Surface Change' between 2020 and 2024
• Estimating heavy vehicle accessibility for transport planning using 'Road Width Class' (1-3)

Strengths

• High surface prediction accuracy of 89.2% compared to 64.7% for standard OSM tags
• Multi-temporal coverage (2020 and 2024) enabling infrastructure change detection
• Standardized width classification (Class 1-3) based on heavy vehicle capacity

Limitations

• Geographic scope is limited to Guadeloupe
• AI predictions may be affected by environmental factors like dense canopy cover or cloud interference in satellite imagery

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

AI-derived predictions from PlanetScope satellite imagery integrated with OpenStreetMap road network data

Time Range

2020 - 2024

Freshness

The dataset was last updated in March 2026 and utilizes satellite imagery from 2020 and 2024.

Geography

Guadeloupe