El Salvador Road Surface and Passability Data for 3,700 km of Arterial Roads

HeiGIT produced this geospatial dataset covering approximately 3,700 km of arterial roads in El Salvador using AI analysis of PlanetScope satellite imagery from 2020 and 2024. It provides deep-learning predictions for road surface, width, and a Humanitarian Passability Index (HPI) to supplement OpenStreetMap (OSM) data. The analysis focuses on motorway, trunk, primary, and secondary road classes which form the national transportation backbone.

Use Cases

• Logistics planning using the Humanitarian Passability Index (HPI) to identify high-capacity transport routes
• Infrastructure monitoring by tracking Road Surface Change (2020-2024) for paving progress
• Emergency routing based on Road Width Class to ensure heavy truck accessibility

Strengths

• 89.2% surface model accuracy
• 3,700 km of arterial roads mapped
• Multi-temporal coverage (2020 and 2024)
• Expert-derived Humanitarian Passability Index

Limitations

• Geographic scope limited to El Salvador
• Excludes tertiary and local road networks
• AI-derived predictions may have residual errors compared to ground-level imagery

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology) via PlanetScope imagery

Collection Method

Deep learning models applied to PlanetScope satellite imagery and integrated with OpenStreetMap data

Time Range

2020-2024

Freshness

Last updated March 2026; contains imagery-derived data comparing 2020 and 2024 states.

Geography

El Salvador