Norfolk Island Road Surface and Passability with 2020-2024 AI Predictions

Norfolk Island arterial road network data featuring AI-derived surface and width attributes generated by HeiGIT from 2020 and 2024 PlanetScope imagery. It provides logistical metrics for motorway, trunk, primary, and secondary road classes to support humanitarian accessibility analysis.

Use Cases

• Logistics planning using the Humanitarian Passability Index (HPI) to assess vehicle accessibility and blockage risk
• Infrastructure development tracking via the Road Surface Change field to identify segments that transitioned from unpaved to paved
• Fleet routing optimization using Road Width Class to filter segments by heavy truck capacity

Strengths

• 89.2% accuracy for AI-derived surface models compared to 64.7% for OSM tags
• Multi-temporal surface data for 2020 and 2024 allows for change detection
• Standardized 6-point Humanitarian Passability Index for logistical modeling

Limitations

• Excludes non-arterial road classes such as residential or service roads
• Road width is categorized into three discrete classes rather than continuous meter measurements
• Geographic scope is limited to Norfolk Island

Provenance

Source

HeiGIT (Heidelberg Institute for Geoinformation Technology)

Collection Method

AI-derived predictions from PlanetScope satellite imagery integrated with OpenStreetMap vector data

Time Range

2020-2024

Freshness

Last updated March 2026; utilizes satellite imagery from 2020 and 2024.

Geography

Norfolk Island