Road Surface Classification for Benin with AI-Derived Paved and Unpaved Estimates

A geospatial dataset providing detailed information on road surfaces in Benin, derived from OpenStreetMap and augmented with deep learning predictions from Mapillary imagery. The dataset includes approximately 0.09 million kilometers of mapped roads, with AI-derived estimates classifying 0.0083 million km as paved and 0.0324 million km as unpaved. It was created by the Heidelberg Institute for Geoinformation Technology (HeiGIT) and last updated in March 2026.

Use Cases

• Transportation planning based on paved and unpaved road classifications.
• Infrastructure analysis using road attributes like surface type, width, and lanes.
• 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 approximately 0.09 million km of roads.
• Combines multiple data sources: OpenStreetMap, Mapillary imagery, GHSU, and AFRICAPOLIS urban layers.
• Provides specific statistics, such as 9.2005% paved roads and 35.9634% unpaved roads.

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 and augmented with deep learning predictions based on Mapillary street-level imagery.

Time Range

The mean timestamp of predictions is provided in the DL_mean_timestamp field.

Freshness

Last updated 2026-03-02 17:12:13.665099; freshness should be verified.

Geography

Benin