Côte d'Ivoire Road Surface Data with AI-Derived Paved and Unpaved Classifications

HeiGIT's dataset provides detailed road surface information for Côte d'Ivoire, distinguishing between paved and unpaved roads. It covers approximately 0.1795 million kilometers of roads mapped in OpenStreetMap, with AI-derived estimates classifying 10.3493% as paved and 71.7843% as unpaved. The dataset was last updated on March 2, 2026.

Use Cases

• Transportation planning based on road surface type and length data.
• Infrastructure analysis using attributes like highway type, surface, and width.
• Climate emissions assessment leveraging road surface classifications for vehicle emission modeling.
• GIS applications utilizing the geospatial road network data for mapping and routing.

Strengths

• Includes AI-derived surface classifications for approximately 0.1795 million kilometers of roads.
• Integrates multiple data sources: OpenStreetMap, Mapillary imagery, and urban layers from GHSU and AFRICAPOLIS.
• Provides detailed attributes including predicted class, OSM tags, and urban classification.

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.
• About 17.8665% of road surface information is missing in the underlying OSM data.

Provenance

Source

Heidelberg Institute for Geoinformation Technology (HeiGIT)

Collection Method

Derived from OpenStreetMap (OSM) and augmented with deep learning predictions based on Mapillary street-level imagery.

Time Range

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Freshness

Last updated 2026-03-02 17:29:54.763966; freshness should be verified.

Geography

Côte d'Ivoire