Dominican Republic Road Surface and Passability for 6,800 km of Arterial Roads

Giving access to AI-derived road surface, width, and passability metrics for approximately 6,800 km of arterial roads in the Dominican Republic. Produced by HeiGIT using PlanetScope satellite imagery from 2020 and 2024, it supplements OpenStreetMap (OSM) data with deep-learning predictions. The analysis focuses on motorway, trunk, primary, and secondary road classifications.

Use Cases

• Assessing logistical accessibility for heavy vehicles using the 'Road Width Class' and 'Humanitarian Passability Index (HPI)'
• Monitoring national infrastructure development by analyzing 'Road Surface Change' between 2020 and 2024
• Improving emergency routing by identifying 'unpaved' segments in the 'DL Surface Prediction' columns

Strengths

• 89.2% accuracy for road surface model predictions
• Temporal change detection between 2020 and 2024 imagery
• Standardized Humanitarian Passability Index (HPI) for logistical planning

Limitations

• Restricted to arterial road networks, excluding local and residential streets
• AI-derived predictions may contain errors in areas with dense canopy cover or cloud interference

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

Deep learning model applied to 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

Dominican Republic