Methodological Aspects of Predictive Mineragenic Studies Using Earth Remote Sensing Data

The article considers methodological aspects of allocation and substantiation of exploration areas for scarce types of ore minerals taking into account the concept of of mineral systems and using Earth remote sensing data with the application of geoinformation and neural network technologies using t...

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Main Authors: Petrov Vladislav, Ustinov Stepan, Minaev Vasilii
Format: Article
Language:English
Published: Russian Academy of Sciences, The Geophysical Center 2025-03-01
Series:Russian Journal of Earth Sciences
Subjects:
Online Access:http://doi.org/10.2205/2025ES001002
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author Petrov Vladislav
Ustinov Stepan
Minaev Vasilii
author_facet Petrov Vladislav
Ustinov Stepan
Minaev Vasilii
author_sort Petrov Vladislav
collection DOAJ
description The article considers methodological aspects of allocation and substantiation of exploration areas for scarce types of ore minerals taking into account the concept of of mineral systems and using Earth remote sensing data with the application of geoinformation and neural network technologies using the example of the Argun metallogenic zone in South-Eastern Transbaikalia. Of the entire range of areas of fundamental and exploratory scientific research, the main attention within the framework of predictive and mineragenic studies is paid to solving the following problems: 1) allocation of lineaments (fault zones) based on processing of digital elevation models; 2) determination of hydraulically active fault structures for the period of ore formation based on tectonophysical reconstructions; 3) analysis of multispectral characteristics of pre-ore, ore-accompanying and post-ore metasomatites based on statistical processing of Landsat-8 satellite data; 4) assessment of fluid-dynamic settings of deposit formation based on data on the composition, properties and genesis of mineral-forming fluids. 5) creation of weight of evidence models based on statistical algorithms for processing data on the dynamics of ore-genetic processes. The feasibility of using such an approach for setting up predictive mineragenic studies on scarce types of strategic mineral raw materials in areas with complex climatic and landscape conditions is shown.
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publisher Russian Academy of Sciences, The Geophysical Center
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spelling doaj-art-34fda0cd743f433bac38b97fb91f68102025-08-20T02:46:21ZengRussian Academy of Sciences, The Geophysical CenterRussian Journal of Earth Sciences1681-12082025-03-0125311410.2205/2025ES001002Methodological Aspects of Predictive Mineragenic Studies Using Earth Remote Sensing DataPetrov Vladislav0https://orcid.org/0000-0002-7551-2516Ustinov Stepan1https://orcid.org/0000-0002-6679-9607Minaev Vasilii2https://orcid.org/0000-0001-9414-4678Institute of Geology of Ore Deposits, Petrography, Mineralogy and Geochemistry Russian Academy of SciencesThe Institute of Geology of Ore Deposits, Petrography, Mineralogy, and Geochemistry, Russian Academy of SciencesThe Institute of Geology of Ore Deposits, Petrography, Mineralogy, and Geochemistry, Russian Academy of SciencesThe article considers methodological aspects of allocation and substantiation of exploration areas for scarce types of ore minerals taking into account the concept of of mineral systems and using Earth remote sensing data with the application of geoinformation and neural network technologies using the example of the Argun metallogenic zone in South-Eastern Transbaikalia. Of the entire range of areas of fundamental and exploratory scientific research, the main attention within the framework of predictive and mineragenic studies is paid to solving the following problems: 1) allocation of lineaments (fault zones) based on processing of digital elevation models; 2) determination of hydraulically active fault structures for the period of ore formation based on tectonophysical reconstructions; 3) analysis of multispectral characteristics of pre-ore, ore-accompanying and post-ore metasomatites based on statistical processing of Landsat-8 satellite data; 4) assessment of fluid-dynamic settings of deposit formation based on data on the composition, properties and genesis of mineral-forming fluids. 5) creation of weight of evidence models based on statistical algorithms for processing data on the dynamics of ore-genetic processes. The feasibility of using such an approach for setting up predictive mineragenic studies on scarce types of strategic mineral raw materials in areas with complex climatic and landscape conditions is shown.http://doi.org/10.2205/2025ES001002South-Eastern Transbaikalia Argun metallogenic zone digital elevation model remote sensing of the Earth predictive mineragenic studies strategic metals lineaments tectonophysics mineral systems ore deposits geoinformation system
spellingShingle Petrov Vladislav
Ustinov Stepan
Minaev Vasilii
Methodological Aspects of Predictive Mineragenic Studies Using Earth Remote Sensing Data
Russian Journal of Earth Sciences
South-Eastern Transbaikalia
Argun metallogenic zone
digital elevation model
remote sensing of the Earth
predictive mineragenic studies
strategic metals
lineaments
tectonophysics
mineral systems
ore deposits
geoinformation system
title Methodological Aspects of Predictive Mineragenic Studies Using Earth Remote Sensing Data
title_full Methodological Aspects of Predictive Mineragenic Studies Using Earth Remote Sensing Data
title_fullStr Methodological Aspects of Predictive Mineragenic Studies Using Earth Remote Sensing Data
title_full_unstemmed Methodological Aspects of Predictive Mineragenic Studies Using Earth Remote Sensing Data
title_short Methodological Aspects of Predictive Mineragenic Studies Using Earth Remote Sensing Data
title_sort methodological aspects of predictive mineragenic studies using earth remote sensing data
topic South-Eastern Transbaikalia
Argun metallogenic zone
digital elevation model
remote sensing of the Earth
predictive mineragenic studies
strategic metals
lineaments
tectonophysics
mineral systems
ore deposits
geoinformation system
url http://doi.org/10.2205/2025ES001002
work_keys_str_mv AT petrovvladislav methodologicalaspectsofpredictivemineragenicstudiesusingearthremotesensingdata
AT ustinovstepan methodologicalaspectsofpredictivemineragenicstudiesusingearthremotesensingdata
AT minaevvasilii methodologicalaspectsofpredictivemineragenicstudiesusingearthremotesensingdata