The technique of using aerial laser scanning and neural networks to obtain reliable spatial data of the real estate cadastre

Cadastre
UDC: 
528.443
DOI: 
10.22389/0016-7126-2025-1020-6-54-63
1 Gura D.A.
2 Dyachenko R.A.
3 Samarin S.V.
4 Bespyatchuk D.A.
Year: 
2025
№: 
6
1020
Pages: 
54-63

Kuban State Agrarian University

1, 

Moscow Institute of Physics and Technology (National Research University)

2, 
3, 

Kuban State Technological University

4, 
Abstract:
The state cadastral registration as a regulator of the real estate market has a direct impact on the country`s economy. As practical experience shows, at the moment there are many objects that are not on the state cadastral register, and this fact, of course, negatively affects taxation and, consequently, the state and regional economies. To solve the problems of three-dimensional identification of objects, it is proposed to use a technique for recognizing private objects, which includes conducting aerial laser scanning with subsequent processing of the data obtained using a neural network. For this method, the DGCNN software is used, which allows solving the tasks of recognizing objects in a cloud of laser reflection points. The most time-consuming and important stage at working with neural networks is training. Therefore, in order to obtain the highest accuracy of segmentation of laser reflection points, a number of experiments were carried out
The study was carried out with the financial support of the Kuban Science Foundation within the framework of the scientific and innovative project No. NIP-20.1/22.16
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Citation:
Gura D.A., 
Dyachenko R.A., 
Samarin S.V., 
Bespyatchuk D.A., 
(2025) The technique of using aerial laser scanning and neural networks to obtain reliable spatial data of the real estate cadastre. Geodesy and cartography = Geodeziya i Kartografiya, 86(6), pp. 54-63. (In Russian). DOI: 10.22389/0016-7126-2025-1020-6-54-63
Publication History
Received: 24.04.2025
Accepted: 01.07.2025
Published: 20.07.2025

Content

2025 June DOI:
10.22389/0016-7126-2025-1020-6