Saint Kitts and Nevis Road Surface and Passability with 2020-2024 AI Analysis

HeiGIT generated this geospatial dataset for Saint Kitts and Nevis by applying deep learning to PlanetScope satellite imagery from 2020 and 2024. It maps surface types, width classes, and passability for approximately 100 km of arterial roads, including motorway, trunk, primary, and secondary classifications. The data supplements OpenStreetMap (OSM) attributes with AI-derived predictions to fill gaps in surface and width tagging.

Use Cases

• Emergency response planning using the Humanitarian Passability Index (HPI) to identify high-risk blockages
• Infrastructure development tracking by monitoring the Road Surface Change (2020-2024) indicator
• Transport logistics optimization using Road Width Class to filter segments capable of two-lane heavy truck flow

Strengths

• 89.2% accuracy for AI-derived surface predictions compared to 64.7% for OSM tags
• Temporal change detection between 2020 and 2024 imagery
• Standardized width classes based on physical vehicle constraints

Limitations

• Restricted to arterial road networks, omitting local streets
• Small total road length (approx. 100 km) due to the geographic size of the study area
• AI-derived predictions may contain errors inherent to satellite imagery resolution

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

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

Time Range

2020-2024

Freshness

Last updated March 2026; imagery analysis covers the period from 2020 to 2024.

Geography

Saint Kitts and Nevis