Bosnia and Herzegovina Road Surface Classification from OSM and Satellite Imagery

Bosnia and Herzegovina road network data from OpenStreetMap, augmented with AI-derived surface classifications. The dataset contains approximately 0.1119 million kilometers of roads, with deep learning predictions distinguishing paved and unpaved surfaces. It was created by HeiGIT and last updated in March 2026.

Use Cases

• Transportation planning based on road surface type and highway classification.
• Infrastructure analysis based on attributes like smoothness, width, and bridge status.
• Climate emissions assessment based on paved versus unpaved road length estimates.
• GIS applications for urban-rural classification using the urban attribute.
• Data quality gap analysis for OpenStreetMap based on missing surface information statistics.

Strengths

• Contains approximately 0.1119 million kilometers of mapped roads.
• Provides AI-derived estimates for 0.0197 million km paved and 0.0101 million km unpaved roads.
• Integrates multiple data sources: OSM, Mapillary imagery, and global settlement layers.
• Includes detailed OSM attributes like highway type, surface, and smoothness.

Limitations

• Approximately 73.35% of road surface information is missing in the underlying OSM data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file size are unknown, which may limit suitability assessment.

Provenance

Source

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

Collection Method

Surface classification derived using a hybrid deep learning approach, with methodology detailed in linked research papers.

Time Range

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

Freshness

Last updated 2026-03-02 17:15:55.692180; freshness should be verified.

Geography

Bosnia and Herzegovina.