Kyrgyzstan Arterial Road Surface and Passability Data (2020-2024)

HeiGIT produced this dataset covering approximately 7,500 km of arterial roads in Kyrgyzstan using AI analysis of PlanetScope satellite imagery from 2020 and 2024. It provides high-resolution predictions for road surface, width, and humanitarian passability for segments classified as motorway, trunk, primary, and secondary in OpenStreetMap.

Use Cases

• Logistical accessibility modeling for heavy vehicles using the Road Width Class and Humanitarian Passability Index (HPI)
• Infrastructure development tracking by analyzing the Road Surface Change column between 2020 and 2024
• Enhancing routing engine accuracy by utilizing DL Surface Prediction for segments missing OSM surface tags

Strengths

• 89.2% surface model accuracy outperforming standard OSM surface tags
• Fills data gaps for 1,700 km of road segments missing OSM surface information
• Includes multi-temporal change detection for infrastructure development monitoring

Limitations

• AI-derived predictions have a documented 10.8% error rate compared to ground truth
• Geographic scope is restricted to Kyrgyzstan arterial routes only
• Width classes are categorical (1-3) rather than continuous meter measurements

Provenance

Source

Heidelberg Institute for Geoinformation Technology (HeiGIT)

Collection Method

Deep learning predictions generated from PlanetScope satellite imagery integrated with OpenStreetMap vector data.

Time Range

2020-2024

Freshness

Based on satellite imagery from 2020 and 2024; last updated March 2026.

Geography

Kyrgyzstan