Ukraine Road Surface Classification from OpenStreetMap and AI

HeiGIT's dataset provides AI-derived road surface classifications for Ukraine, distinguishing paved from unpaved roads. It covers approximately 1.188 million kilometers of roads mapped in OpenStreetMap, with 11.5% classified as paved and 11.3% as unpaved. The data was last updated on March 2, 2026.

Use Cases

• Transportation planning based on road surface type and length estimates.
• Infrastructure analysis based on attributes like highway type, surface, and smoothness.
• Climate emissions assessment based on road network composition and urban/rural classification.
• GIS applications for routing and logistics based on geospatial road network data.

Strengths

• Covers approximately 1.188 million kilometers of roads in Ukraine.
• Provides AI-derived surface classifications for paved (0.1364 million km) and unpaved (0.1342 million km) roads.
• Integrates multiple data sources: OpenStreetMap, Mapillary imagery, and urban settlement layers.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

Heidelberg Institute for Geoinformation Technology (HeiGIT)

Collection Method

Derived from OpenStreetMap data and augmented with deep learning predictions based on Mapillary street-level imagery.

Time Range

null

Freshness

Last updated 2026-03-02 17:05:15.923523; freshness should be verified.

Geography

Ukraine