Mathematical Geosciences

Aims & Scope

Mathematical Geosciences (formerly Mathematical Geology) publishes original, high-quality, interdisciplinary papers in geomathematics focusing on quantitative methods and studies of the Earth, its natural resources and the environment.

This international publication is the official journal of the IAMG.

Mathematical Geosciences is an essential reference for researchers and practitioners of geomathematics who develop and apply quantitative models to earth science and geo-engineering problems.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	3.6
2024	2.80

SJR (SCImago Journal Rank)

Year	Value
2024	0.746

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	88

Journal Rank

Year	Value
2024	7452

Journal Citation Indicator

Year	Value
2024	687

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Earth and Planetary Sciences and Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Computations of Absolute Permeability on Micro-CT Images

  Citation: 380

  Authors: Peyman, Martin J., Branko

• Measurement of Areas on a Sphere Using Fibonacci and Latitude–Longitude Lattices

  Citation: 331

  Authors: Álvaro

• Surface-Based 3D Modeling of Geological Structures

  Citation: 324

  Authors: G., P., C., S., J.

• Ensemble Randomized Maximum Likelihood Method as an Iterative Ensemble Smoother

  Citation: 272

  Authors: Yan, Dean S.

• Machine Learning Feature Selection Methods for Landslide Susceptibility Mapping

  Citation: 248

  Authors: Natan, Loris, Sylvain, Michael, Andrea, Michel, Mikhail

• Support Vector Machines for Landslide Susceptibility Mapping: The Staffora River Basin Case Study, Italy

  Citation: 231

  Authors: Cristiano, Simone

• Stochastic Simulation of Patterns Using Distance-Based Pattern Modeling

  Citation: 215

  Authors: Mehrdad, Jef

• Representing Spatial Uncertainty Using Distances and Kernels

  Citation: 207

  Authors: Céline, Jef

• Outlier Detection for Compositional Data Using Robust Methods

  Citation: 180

  Authors: Peter, Karel

• An Improved Parallel Multiple-point Algorithm Using a List Approach

  Citation: 177

  Authors: Julien, Philippe, Grégoire, Roland, Olivier

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