Digital relief models of open-pit mining facilities: Analysis and optimization

The article discusses digital relief modeling using the common methods of spatial interpolation and with the new method based on the growth pole theory and optimization theory, with the accuracy rating of the results. Efficient production, including mineral mining, seems to be impossible without the analysis of geospatial information obtained from geodetic surveying among other things. The geospatial information is applicable to construction of digital relief models and to periodic monitoring of their variation by means of repeated observations and comparative analysis. This study describes the digital modeling algorithms in terms of an open pit mine. The geospatial data were semi-automatically classified using TerraScan and, then, were processed manually. The digital relief modeling in Surfer was performed, and the results were compared with the authorial method. The digital relief modeling used 6 common interpolations, namely, Kriging, Inverse Distance Weighting, Triangulation with Linear Interpolation, Minimal Curvature and Radial Basis Function. The proposed algorithm uses the growth pole theory and optimization theory which enable recovering additional connections inside a surface triangulation that serves as a basis. This approach reforms one of the disadvantages of triangulation—processing of data gaps between initial measurements. The comparative analysis shows that the estimated parameters—the average number and the mean square deviation—are the least in the proposed method. These results give grounds for application of the proposed methods in the digital relief modeling.

Keywords: digital relief model, spatial interpolation methods, growth pole theory, optimization theory, airborn laser scanning, point cloud, accuracy rating, kriging, triangulation, natural neighbor interpolation.
For citation:

Vasilev B. Yu., Mustafin M.G. Digital relief models of open-pit mining facilities: Analysis and optimization. MIAB. Mining Inf. Anal. Bull. 2023;(9):141-159. [In Russ]. DOI: 10.25018/0236_1493_2023_9_0_141.

Issue number: 9
Year: 2023
Page number: 141-159
ISBN: 0236-1493
UDK: 528.482
DOI: 10.25018/0236_1493_2023_9_0_141
Article receipt date: 05.05.2023
Date of review receipt: 09.06.2023
Date of the editorial board′s decision on the article′s publishing: 10.08.2023
About authors:

B.Yu. Vasilev1, Graduate Student, e-mail:, ORCID ID: 0000-0003-4119-4051,
M.G. Mustafin1, Dr. Sci. (Eng.), Assistant Professor, Head of Chair, e-mail:, ORCID ID: 0000-0001-9416-2358,
1 Saint-Petersburg Mining University, 199106, Saint-Petersburg, Russia.


For contacts:

B.Yu. Vasilev, e-mail:


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