Systems and Means of Informatics
2025, Volume 35, Issue 4, pp pp 129-142
MODERN METHODS OF EXTRACTING GEOGRAPHICAL KNOWLEDGE IN LARGE ARRAYS OF SPATIAL DATA
Abstract
The main spatial concepts of spatial data representation and a number of modern methods for analyzing and extracting geographical knowledge from geographic databases including current trends in the development of geographic artificial intelligence (AI) are presented. Searching for knowledge in geographical databases is a nontrivial process that requires understanding of fundamental geographical concepts taking into account the features of spatial or spatiotemporal representation of geoobjects and related specialized algorithms and which is difficult to implement using direct transfer of traditional methods of data mining. Geographical AI is a promising technology for intelligent spatial data processing for solving various tasks (such as clustering, classification, segmentation, interpolation, etc.), especially in the context of the analysis of spatial and temporal patterns. The results obtained should serve as a starting point for the development of new approaches to the extraction of geographical knowledge.
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[+] About this article
Title
MODERN METHODS OF EXTRACTING GEOGRAPHICAL KNOWLEDGE IN LARGE ARRAYS OF SPATIAL DATA
Journal
Systems and Means of Informatics
Volume 35, Issue 4, pp 129-142
Cover Date
2025-12-25
DOI
10.14357/08696527250409
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
geodata; geographical databases; methods of extracting geographical knowledge; geographical artificial intelligence
Authors
D. A. Nikishin 
Author Affiliations
Federal Research Center "Computer Science and Control", Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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