Slovakia Road Surface Classification from OSM and AI Predictions

A 2026 dataset from the Heidelberg Institute for Geoinformation Technology (HeiGIT) provides AI-derived road surface classifications for Slovakia. It covers approximately 218,900 kilometers of roads from OpenStreetMap, distinguishing paved and unpaved surfaces using a hybrid deep learning model. The data is augmented with predictions from Mapillary imagery and urban classifications from GHSU and AFRICAPOLIS layers.

Use Cases

• Transportation planning based on paved vs. unpaved road classifications.
• Infrastructure analysis using attributes like highway type, surface, and width.
• Climate emissions assessment based on road surface type and urban/rural classification.
• GIS applications for routing and network analysis using the geospatial road data.

Strengths

• Provides AI-derived surface classifications for approximately 218,900 km of roads.
• Includes multiple classification schemes (OSM-priority, DL-priority) and urban/rural flags.
• Augments OSM data with deep learning predictions to address missing surface information.

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

OpenStreetMap (OSM), augmented with deep learning predictions from Mapillary imagery and urban layers from GHSU and AFRICAPOLIS.

Collection Method

Surface classification derived using a hybrid deep learning approach, as detailed in the referenced arXiv papers.

Time Range

Mean timestamp of predictions (DL_mean_timestamp) is provided per feature, but overall temporal coverage is not specified.

Freshness

Last updated 2026-03-02 17:04:56.445625; freshness should be verified.

Geography

Slovakia.