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Algorithms for vector processing of laser scanning data of objects on the Earth’s surface for integration with satellite data

A.B. Murynin¹ , A.A. Riсhter²

¹ Federal Research Center “Computer Science and Control” RAS, Moscow, Russia
² JSC TAZMAR IT-SOLUTIONS, Saint Petersburg, Russia

Accepted: 02.07.2026
DOI: 10.21046/2070-7401-2026-23-5-35-49

This paper presents a method for vectorising laser scanning data (point clouds) of man-made objects, aimed at the automated construction of interpretable geometric models of road infrastructure. The approach is based on integrating terrestrial laser scanning data with satellite and cartographic data. A multi-stage processing scheme is proposed, including preprocessing and filtering of point clouds, their decomposition into connected components using clustering methods, vectorization of extracted elements based on computational geometry operations and morphological analysis, and subsequent calculation of geometric parameters of the objects. Particular attention is paid to processing of linearly extended objects (highways): algorithms for identifying centerlines, roadbed boundaries, and shoulders, as well as methods for longitudinal and transverse zoning for structuring space, have been developed. The effectiveness of the proposed solutions is demonstrated using an example of segmentation and construction of geometric models of road supports, with accuracy assessed using deviation histograms. The algorithmic and software implementation is based on the use of open-source tools, which ensures the reproducibility of the results.

Keywords: point cloud, laser scanning, lidar, vectorization, remote sensing, morphological analysis, computational geometry, road infrastructure, geometric model

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