Vanuatu Road Surface Classification from OpenStreetMap and AI

HeiGIT's dataset provides detailed road surface information for Vanuatu, distinguishing paved from unpaved roads. The data originates from OpenStreetMap and is augmented with deep learning predictions based on Mapillary imagery, covering approximately 0.0049 million km of roads. It was last updated on March 2, 2026.

Use Cases

• Transportation planning based on paved versus unpaved road classifications.
• Infrastructure analysis using road attributes like surface type, smoothness, and width.
• Climate emissions assessment leveraging road surface data for vehicle emission modeling.
• GIS applications integrating urban classification attributes for rural/urban analysis.

Strengths

• Includes AI-derived surface classifications for roads where OSM data is missing.
• Combines multiple data sources: OSM, Mapillary imagery, and urban settlement layers.
• Provides specific statistics, such as 7.4681% of mapped roads being paved.

Limitations

• Approximately 67.7428% 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

Heidelberg Institute for Geoinformation Technology (HeiGIT)

Collection Method

Derived from OpenStreetMap and augmented using a hybrid deep learning approach on Mapillary street-level imagery.

Time Range

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

Freshness

Last updated 2026-03-02 17:09:32.873044; freshness should be verified.

Geography

Vanuatu