Bangladesh Road Surface Classification from OpenStreetMap and AI

Approximately 0.3072 million kilometers of roads from OpenStreetMap in Bangladesh are classified by surface type using a hybrid deep learning approach. The dataset, created by HeiGIT and last updated in March 2026, distinguishes paved and unpaved roads and is augmented with predictions from Mapillary imagery and urban classification layers. It provides AI-derived estimates for 10.9845% paved and 5.798% unpaved roads, while noting 83.2175% of road surface information is missing in the original OSM data.

Use Cases

• Transportation planning based on road surface type and length estimates.
• Infrastructure analysis using attributes like highway type, surface, and bridge status.
• Climate emissions assessment leveraging the distinction between paved and unpaved road networks.
• GIS applications for routing and logistics using geospatial road data.
• Urban/rural development studies based on the urban classification attribute.

Strengths

• Provides AI-derived estimates for 0.0337 million km of paved and 0.0178 million km of unpaved roads.
• Integrates multiple data sources: OpenStreetMap, Mapillary imagery, and urban classification layers (GHSU, AFRICAPOLIS).
• Includes detailed attributes for analysis, such as highway type, surface, smoothness, and urban/rural classification.

Limitations

• A significant portion (0.2557 million km, 83.2175%) of road surface information is missing in the base 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

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

Collection Method

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

Time Range

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

Freshness

Last updated 2026-03-02 17:06:15.699662; freshness should be verified.

Geography

Bangladesh.