Syria Road Surface, Width, and Passability for 20,500 km of Arterials

Mapping 20,500 km of arterial roads in the Syrian Arab Republic, this dataset provides AI-derived surface types, widths, and passability scores for 2020 and 2024. Developed by HeiGIT using PlanetScope satellite imagery, it fills gaps for the 87.6% of local OpenStreetMap segments that lack surface tags. The data achieves 89.2% accuracy in surface classification, significantly exceeding the 64.7% accuracy of existing crowdsourced tags.

Use Cases

• Humanitarian logistics planning using the Humanitarian Passability Index (HPI) to identify high-access routes for aid convoys
• Infrastructure development monitoring by analyzing the Road Surface Change column to detect segments that transitioned from unpaved to paved between 2020 and 2024
• Vehicle routing optimization using Road Width Class (1-3) to ensure heavy trucks only utilize segments capable of supporting unimpeded flow

Strengths

• 89.2% accuracy for AI-derived surface models
• Provides data for 19,700 km of roads missing surface tags in OSM
• Includes a standardized Humanitarian Passability Index (HPI) for logistical planning

Limitations

• Focuses exclusively on arterial roads, omitting minor and residential networks
• Surface and width attributes are AI-derived from satellite imagery and may contain classification noise compared to ground-truth surveys

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

Deep-learning predictions generated from PlanetScope satellite imagery (2020 and 2024) integrated with OpenStreetMap road geometries.

Time Range

2020-2024

Freshness

Contains temporal snapshots for 2020 and 2024; last updated in March 2026.

Geography

Syrian Arab Republic