Isle of Man Road Surface Classification from OSM and Deep Learning

Approximately 2.7 km of roads are mapped in OpenStreetMap for the Isle of Man, with AI-derived estimates classifying 36.1% as paved and 4.9% as unpaved. The dataset, created by HeiGIT and last updated in March 2026, combines OSM data with deep learning predictions from Mapillary imagery and urban classification layers. It provides attributes for surface type, road characteristics, and urban/rural classification.

Use Cases

• Transportation planning based on paved vs. unpaved road classifications.
• Infrastructure analysis using road attributes like surface, smoothness, and width.
• Climate emissions assessment informed by road network composition and urban/rural classification.
• GIS applications leveraging geospatial road data with AI-derived surface predictions.

Strengths

• Includes AI-derived surface predictions for paved and unpaved roads.
• Combines data from multiple sources: OSM, Mapillary imagery, and urban classification layers.
• Provides detailed OSM attributes including highway type, surface, smoothness, and width.

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

OpenStreetMap (OSM), augmented with deep learning predictions from Mapillary imagery and urban layers (GHSU, AFRICAPOLIS).

Collection Method

Surface classification derived using a hybrid deep learning approach, with methodology detailed in linked research papers.

Time Range

Mean timestamp of predictions is provided in the 'DL_mean_timestamp' field.

Freshness

Last updated 2026-03-02 17:27:52.061023; freshness should be verified.

Geography

Isle of Man.