Sources of spatial data in advancing technologies of subsoil use

The difference between the raster and vector data is studied. The basic types of data used in geo-spatial representations are determined. Advantages and disadvantages of the rastertype data storage are identified. The attributes, some key functions and types of the raster data are described. There are many sources of data for describing both space and attributes. The most popular sources of spatial data are: maps, air photos, remote sensing images, sample data of surveys and digitized information. Spatial data can exist in multiple formats and contain more various information rather than simply facts on a specific mineral deposit. There are two types of data in accordance with the storage technology, namely, raster and vector data. Spatial data can be classified as crude data and derived data. As data are being collected from the environment, map-makers use their perception to find patterns and to prepare the data for further mapping. Statistical data are the attributes of spatial objects. All sources of spatial data are formed by different classes of systems. The main difference between the spatial data and all other types of data, when we speak about the statistical analysis, is the requirement to take into account such factors as height, distance and area in the analysis.

Keywords: web-scraping, spatial data, geo-spatial modeling, automated control, analytical ecosystem.
For citation:

Nekrasov G. A., Polivoda D. E., Prokofeva E. N. Sources of spatial data in advancing technologies of subsoil use. MIAB. Mining Inf. Anal. Bull. 2020;(5):164-176. [In Russ]. DOI: 10.25018/0236-1493-2020-5-0-164-176.


The publication has been prepared during implementation of Project No. 20-04-033 in the framework of the Program of the Scientific Foundation of the National Research University—Higher School of Economics in 2020–2021 and under governmental support of the leading universities of the Russian Federation, Project 5–100.

Issue number: 5
Year: 2020
Page number: 164-176
ISBN: 0236-1493
UDK: 303.645.063
DOI: 10.25018/0236-1493-2020-5-0-164-176
Article receipt date: 08.02.2020
Date of review receipt: 17.03.2020
Date of the editorial board′s decision on the article′s publishing: 20.04.2020
About authors:

G.A. Nekrasov1, Student, e-mail:,
D.E. Polivoda1, Student, e-mail:,
E.N. Prokofeva1, Cand. Sci. (Eng.), Professor, e-mail:,
1 Higher School of Economics. National Research University, 143072, Moscow, Russia.


For contacts:

E.N. Prokofeva, e-mail:


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