GeoTwin Road 2030: A UAV-GIS and Digital-Twin Assurance Framework for Highway Earthworks, Pavement Delivery and Asset Handover

Highway delivery produces repeated surveys, earthwork quantities, pavement tests, inspections, change records and asset data, yet these records are often disconnected from chainage and time. This paper proposes GeoTwin Road 2030, a governance-first framework integrating unmanned aerial vehicle photogrammetry, ground survey, geographic information systems, design surfaces, quality records and structured asset metadata. Seven transparent criteria determine a handover-risk score: positional accuracy, coverage, earthwork conformity, surface-level conformity, pavement evidence, asset metadata and change closure. The artifact was computationally stress-tested using 144 reproducible synthetic segment-epochs representing a 12 km corridor divided into 24 half-kilometre segments across six monitoring epochs. No employer, client, flight, survey or live-project data were used. Scores ranged from 6.2 to 75.9, with a mean of 40.0. The framework classified 23 observations for routine acceptance, 70 for targeted verification, 41 for corrective action and 10 for handover hold. Median tier stability was 100% under 1,200 weight perturbations per observation; the least stable boundary case retained its tier in 46.7% of trials. A controlled survey-control, coverage, metadata and closeout improvement scenario lowered risk by 12.3 points on average. Treating missing pavement and asset evidence as satisfactory understated risk by 9.3 points. An illustrative formula reduced a residual-rework proxy by 1.2 units, but this is not observed performance. The contribution is an auditable assurance and handover workflow, not autonomous acceptance. Field calibration, checkpoint testing, independent pavement testing, aviation compliance, information governance and professional authorization remain mandatory.