Qatar Road Surface and Passability Data for 4,700 km of Arterial Roads

Qatar arterial road network data covering 4,700 km was developed by HeiGIT using PlanetScope satellite imagery from 2020 and 2024. It provides AI-generated surface classifications, width estimates, and passability indices for segments classified as motorway, trunk, primary, or secondary in OpenStreetMap.

Use Cases

• Logistics planning using 'Road Width Class' to identify routes suitable for two-lane heavy trucks
• Infrastructure monitoring by identifying 'Road Surface Change' from unpaved to paved
• Humanitarian access modeling using the 'Humanitarian Passability Index (HPI)' scores

Strengths

• 89.2% model accuracy for surface detection
• Covers 4,700 km of arterial roads
• Includes temporal change detection between 2020 and 2024

Limitations

• Excludes minor road classes like residential or service roads
• AI-derived predictions may contain errors in complex urban or desert environments

Provenance

Source

Heidelberg Institute for Geoinformation Technology (HeiGIT)

Collection Method

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

Time Range

2020-2024

Freshness

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

Geography

Qatar