Kuban State Agrarian University (Department of Geodesy, Associate Professor)
Krasnodar, Krasnodar, Russian Federation
student from 01.01.2025 until now
Krasnodar, Krasnodar, Russian Federation
UDC 528.441.2
UDC 347.214.2
The relevance of the study is due to the urgent need to increase the effectiveness of state land and construction supervision aimed at detecting and suppressing unauthorized construction. Traditional monitoring methods based on 2D data and spot checks do not provide the necessary efficiency, completeness and objectivity. The aim of the work is to develop scientific and methodological foundations and evaluate the effectiveness of the use of 3D identification technologies for real estate objects as part of automated monitoring systems for the detection of unauthorized construction. The research methods include a comparative analysis of modern measurement technologies (laser scanning, UAV photogrammetry, mobile cartographic systems, satellite imagery), spatial analysis and 3D modeling methods, as well as machine learning technologies for automatic comparison of reference and current 3D models of territories. The results of the study demonstrate that the integrated use of aerial laser scanning and drone imagery data makes it possible to create high-precision digital terrain doubles (digital models of terrain, terrain and objects) with the accuracy of identifying buildings and structures sufficient for legally significant conclusions. The concept of an automated system has been developed in which the 3D identification procedure consists of comparing the basic 3D model of a cadastral quarter with an updated one, followed by automatic indication of intruder objects based on spatial and geometric features. The scientific novelty lies in the systematization of the requirements for the initial geospatial data for 3D identification, the formalization of signs of unauthorized construction in three-dimensional space and the algorithmization of the process of their automatic detection. The practical significance of the study is confirmed by the fact that the introduction of the proposed methodology based on 3D identification technologies will make it possible to switch from reactive to proactive monitoring, significantly reduce labor costs and time to identify unauthorized objects, minimize the subjective factor and form a reliable evidence base for administrative and judicial procedures. The directions of further research are related to the integration of the proposed system with the EGRN and regional geoportals in a mode close to real time.
unauthorized construction, 3D identification, automated monitoring, digital terrain model, geospatial data, real estate cadaster, land supervision
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