Saint Lucia Road Surface and Passability with 2020-2024 AI Predictions

HeiGIT generated this geospatial dataset covering approximately 200 km of arterial roads in Saint Lucia using AI analysis of PlanetScope satellite imagery from 2020 and 2024. It provides road surface classifications, width estimates, and passability indices for segments classified as motorway, trunk, primary, or secondary in OpenStreetMap.

Use Cases

• Logistics planning using the Road Width Class to determine if segments support two-lane heavy truck flow
• Infrastructure monitoring by identifying unpaved-to-paved transitions via the Road Surface Change field
• Emergency response routing using the Humanitarian Passability Index (HPI) to prioritize accessible routes

Strengths

• 89.2% surface model accuracy
• Temporal change detection between 2020 and 2024
• Standardized Humanitarian Passability Index (HPI) scores

Limitations

• Geographic scope limited to Saint Lucia
• Excludes minor and local road networks
• AI-derived predictions may have residual errors compared to physical ground-truth surveys

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

AI-derived predictions from PlanetScope satellite imagery integrated with OpenStreetMap road segments.

Time Range

2020-2024

Freshness

Contains imagery-derived data from 2020 and 2024; last updated March 2026.

Geography

Saint Lucia