Road Surface Classification for Wallis and Futuna Islands from OSM and Satellite Imagery

A March 2026 dataset from the Heidelberg Institute for Geoinformation Technology (HeiGIT) provides road surface classifications for the Wallis and Futuna Islands. It combines OpenStreetMap (OSM) data with deep learning predictions from Mapillary imagery and PlanetScope satellite data to distinguish paved from unpaved roads. The dataset is intended for transportation planning, infrastructure analysis, and climate emissions assessment.

Use Cases

• Transportation planning based on paved versus unpaved road classifications.
• Infrastructure analysis using attributes like highway type, surface, and width.
• Climate emissions assessment leveraging road surface data for vehicle emission models.
• GIS applications for humanitarian access and logistics planning in the region.
• Urban versus rural road analysis based on the urban classification attribute.

Strengths

• Integrates multiple data sources: OSM tags, Mapillary street-level imagery, and PlanetScope satellite imagery.
• Provides AI-derived surface classifications (pred_class, pred_label) alongside original OSM data (osm_surface_class).
• Includes combined classifications that prioritize either OSM data or deep learning predictions.
• Available in common geospatial formats: GEOJSON and GEOPACKAGE.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Row count and dataset size are unknown, which may limit suitability assessment.
• The statistics provided in the description show 0.0 million km for all road categories, suggesting placeholder values.

Provenance

Source

OpenStreetMap (OSM), augmented with Mapillary imagery and PlanetScope satellite data.

Collection Method

Surface classification derived using a hybrid deep learning approach, as detailed in referenced arXiv papers.

Time Range

The mean timestamp of predictions used is included in the DL_mean_timestamp attribute.

Freshness

Last updated 2026-03-02 17:18:34.484984; freshness should be verified.

Geography

Wallis and Futuna Islands.