Aruba Arterial Road Surface and Passability Metrics (2020-2024)

HeiGIT produced this dataset of AI-derived road surface, width, and passability metrics for approximately 200 km of arterial roads in Aruba using 2020 and 2024 PlanetScope satellite imagery. It integrates OpenStreetMap (OSM) segments with deep-learning predictions to fill gaps where surface tags are missing.

Use Cases

• Assessing logistical constraints for heavy transport using the Road Width Class (1-3) and Humanitarian Passability Index (HPI)
• Monitoring infrastructure development by analyzing transitions in the Road Surface Change (2020-2024) indicator
• Validating or enriching OpenStreetMap data using the DL Surface Prediction 2024 field to fill missing surface tags

Strengths

• 89.2% surface classification accuracy outperforming standard OSM surface tags
• Multi-temporal coverage (2020 and 2024) for infrastructure change detection
• Standardized Humanitarian Passability Index (HPI) for logistical planning

Limitations

• Small geographic scope limited to Aruba's arterial network (~200 km)
• AI-derived predictions may contain errors despite high reported accuracy
• Excludes minor and residential road networks

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

AI-derived from PlanetScope satellite imagery and OpenStreetMap data

Time Range

2020-2024

Freshness

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

Geography

Aruba