The Cutting-Edge Approaches in Construction: Digital Solutions and Automated Processes

Abstract

The study creates a conceptual integration structure for automated management of the road infrastructure cadastre based on the systematic integration of building information modeling (IFC 4.3), geographic information systems (CityGML 3.0), three-dimensional cadastral systems (Land Administration Domain Model Edition II) and machine learning technologies. The study addresses the problem of data fragmentation in modern methods. The methodology is based on a comparative analysis of four national cases, including the Netherlands, Spain, the cross-border Belgian-German case and Ukraine, to validate the scalability of the framework. The framework offers a 4-layer architecture that ensures semantic preservation of 90-95% in high-quality data and 75-80% in transformation systems. The LADM extension adds three special classes of road infrastructure that have a formal demarcation between legal (a right-of-way, typically 3-8 meters wider than the physical pavement) and physical space. The seven-step registration process shows that it can save 60-80% of time compared to the traditional method, with coordinate transformation accuracies ranging from ±5 centimeters in developed systems to ±20 centimeters in developing systems. The integrated estimation model has a predicted accuracy of 7-10 % mean absolute error in mature systems and 13-17 % in data-limited environments, which is 15-25 % better than traditional methods. Comparative analysis shows that the Netherlands is able to achieve 85-90% automation of workflows, Spain – 60-70%, and Ukraine – 40-50% in the first stage, which is especially relevant for a post-war situation when infrastructure needs to be rebuilt.

Keywords: highway infrastructure, 3D cadastre, BIM-GIS integration, automated infrastructure valuation, digital twin, land administration, motorways, valuation of land and real estate, cadastre of settlements