Papua New Guinea Arterial Roads: AI-Derived Surface and Passability Data

Stretching across approximately 6,300 km of arterial roads in Papua New Guinea, providing AI-derived surface and width attributes generated by HeiGIT. It utilizes PlanetScope satellite imagery from 2020 and 2024 to supplement OpenStreetMap data with logistical accessibility metrics for motorway, trunk, primary, and secondary road classes.

Use Cases

• Logistics planning using the Humanitarian Passability Index (HPI) to identify high-risk routes for heavy trucks
• Infrastructure monitoring by analyzing the Road Surface Change column to detect unpaved-to-paved transitions
• Transport modeling using Road Width Class to determine if segments support unimpeded two-lane heavy truck flow

Strengths

• 89.2% surface model accuracy compared to 64.7% for standard OSM tags
• Provides surface data for 56.8% of arterial roads previously missing tags in OSM
• Includes multi-temporal change detection for 2020-2024

Limitations

• Restricted to high-capacity arterial road classes only
• AI-derived predictions may contain errors in areas with heavy cloud cover or dense canopy

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

AI-derived predictions from PlanetScope satellite imagery integrated with OpenStreetMap road geometries.

Time Range

2020-2024

Freshness

Uses satellite imagery from 2020 and 2024; last updated in March 2026.

Geography

Papua New Guinea