British Virgin Islands Road Surface Classification from OSM and AI

Approximately 0.7 km of roads are mapped in OpenStreetMap for the British Virgin Islands. The dataset, created by HeiGIT, classifies road surfaces as paved or unpaved using a hybrid deep learning approach based on Mapillary imagery and OSM data. It was last updated in March 2026.

Use Cases

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

Strengths

• Includes AI-derived surface classifications for approximately 0.7 km of roads.
• Combines OpenStreetMap attributes with deep learning predictions and urban classification layers.
• Available in geospatial formats (GEOJSON, GEOPACKAGE) for direct GIS use.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file size are unknown, which may limit suitability assessment.
• Approximately 41.5% of road surface information is reported as missing in the base OSM data.

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.

Time Range

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

Freshness

Last updated 2026-03-02 17:16:01.055554; freshness should be verified.

Geography

British Virgin Islands.