Special Issue " Novel strategies in geospatial data fusion for resource potential mapping"

 

Special Issue Editors

 

Dr. Maysam Abedi

Associate Editor of IJMGE

Assistant Professor, School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran.

Email: maysamabedi@ut.ac.ir

Interests: Computational Geophysics, Applied Mathematics, Inverse Theory, Data Fusion, Decision Making

 

 

 Dr. Alok Porwal

Editorial Board of IJMGE

Professor, (1) Indian Institute of Technology Bombay, India, (2) Adjunct Prof., Centre for Exploration Targeting, University of Western Australia, Australia.
Email: aporwal@iitb.ac.in

Interests: Mineral systems and prospectivity modeling, Geologic remote sensing - Terrestrial and Planetary, Machine learning, Spatial data analysis.

Dr. Mahyar Yousefi

Guest Editor

Associated Professor, Faculty of Engineering, MalayerUniversity, Malayer, Iran.

Email: m.yousefi@malayeru.ac.ir

Interests: Exploration GeochemistryMineral Prospectivity mappingExploration information systems

 

Special Issue Information

 

Dear Colleagues,

With the reduction of surface mineral resources and the development of mining industries, natural resource exploration-related societies are often focused on the systematic exploration of deep-seated and blind targets. However, discovering such targets is a tough task and somewhat challenging, when geospatial data set (i.e. geological, geochemical, and geophysical indicators) have sophisticated exploratory patterns and even discordance with each other. Computational mathematical-based techniques (machine learning and MCDM tools) can assist in the fusion of such intricate evidence patterns in geoscience projects that are intimately related to the desired natural resource being sought. Thus, it is imperative to construct a powerful and comprehensive geospatial data set (in 2D/3D) for huge amounts of disparate data sets at different scales, while finally a mineral potential mapping “MPM” is generated. MPM is a research hot spot that has emerged in the field of Geosciences, while a series of computational techniques have been proposed to integrate explainable and interpretable geospatial evidences in complex geological environments, such as those based on machine learning and MCDM tools. Among all employed computational techniques, geospatial data analysis, visualization, and integration in association with the sought underground targets are the core of those researches. Parallel to advancements in computational techniques, geoscientists have used these algorithms in MPM with the same trend of progress, and this Special Issue seeks to present these developments by collecting the state-of-the-art approaches presented in papers on the following topics:

 

  • Machine learning algorithms (Supervised/Unsupervised/Semi-supervised/Reinforcement learning) for resource exploration
  • Multiple-criteria decision-making (MCDM) or multiple-criteria decision analysis (MCDA) in mineral prospectivity mapping (MPM)
  • Understanding of ore-forming processes and their translation into exploration criteria
  • Novel computational algorithms for MPM
  • Software development for MPM
  • Open access tools for MPM (developed in Python, Matlab, R statistics, ...)
  • Topics related to exploration data integration

 

Manuscript Submission Information

 

Manuscripts should be submitted online at https://ijmge.ut.ac.ir by registering and logging into this website. Manuscripts can be submitted until the deadline (31 August 2023). All submissions that successfully pass pre-check are peer-reviewed. Accepted papers will be published in the IJMGE journal and will be listed together in its last issue in 2023. Research articles, review articles as well as short communications are invited. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process, and two referees will review at least each work. A guide for authors and other relevant information for the submission of manuscripts is available on the Guide for Authors page. International Journal of Mining and Geo-Engineering “IJMGE” is an international peer review journal in the field of mining and relevant geo-engineering and geo-environmental issues and aims to publish original papers, review articles, technical reports, and short communications that are expected to be interesting for mining engineers, scientists, geologists, and environmental groups that are not published or not being considered for publication elsewhere. It is a free-of-charge and quarterly journal published by the University of Tehran, the first rank and most prestigious university in Iran.

 

Special Issue Keywords

 

  • Resource potential mapping
  • Data fusion
  • Machine learning algorithms
  • MCDM techniques
  • 2D/3D geospatial data preparation
  • Multispectral remote sensing data integration
  • Multiset Geology/Geochemistry/Geophysics data integration
  • Ore-forming process
  • Novel algorithms for MPM
  • Open access code for MPM
  • Software development for MPM