Mathematical Geosciences

Top Research Topics at Mathematical Geosciences?

Mathematical Geosciences facilitates discussions on Hydrogeology, Statistics, Kriging, Algorithm and Mineralogy. The concepts on Hydrogeology presented in the journal can also apply to other research fields, including Soil science, Geometry and Permeability (earth sciences). It explores issues in Statistics which can be linked to other research areas like Econometrics and Applied mathematics.

The work tackled in it goes beyond the discipline of Applied mathematics as it also encompasses Mathematical optimization. The Kriging study featured in the journal draws parallels with the field of Geostatistics. Covariance function is a primary topic of Covariance research in it.

• Hydrogeology (26.73%)
• Statistics (25.14%)
• Kriging (12.10%)

What are the most cited papers published in the journal?

• Isometric Logratio Transformations for Compositional Data Analysis (1165 citations)
• The origins of kriging (1132 citations)
• Conditional Simulation of Complex Geological Structures Using Multiple-Point Statistics (1107 citations)

Research areas of the most cited articles at Mathematical Geosciences:

The most cited publications facilitate discussions on Statistics, Kriging, Variogram, Hydrogeology and Geostatistics. In addition to Statistics research, the most cited articles aim to explore topics under Algorithm and Econometrics. The most cited publications tackle studies in Geometry and the interrelated subject of Fractal and Fractal dimension to gain insights into Hydrogeology.

What topics the last edition of the journal is best known for?

• Statistics
• Artificial intelligence
• Normal distribution

The previous edition focused in particular on these issues:

Mathematical Geosciences focuses on Hydrogeology, Algorithm, Kriging, Artificial intelligence and Data mining. The Hydrogeology studies in Mathematical Geosciences expound on topics in

• Mineralogy which intersects with area such as Porosity,
• Statistical physics and related Statistical model, Multivariate statistics and Random field.. While work presented in it provided substantial information on Algorithm, it also covered topics in Covariance, Spatial analysis, Reservoir modeling and Inversion (meteorology).

The research on Spatial analysis tackled can also make contributions to studies in the areas of Variogram, Conditional probability distribution and Sample (statistics). The journal deals with Kriging in conjunction with Geostatistics and similar fields in Mineral resource estimation. In Mathematical Geosciences, Basis (linear algebra), Scale (ratio), Segmentation, Sampling (statistics) and Downscaling are investigated in conjunction with one another to address concerns in Data mining research.

The most cited articles from the last journal are:

• Robust Feature Extraction for Geochemical Anomaly Recognition Using a Stacked Convolutional Denoising Autoencoder (10 citations)
• Improving Automated Geological Logging of Drill Holes by Incorporating Multiscale Spatial Methods (9 citations)
• Spatiotemporal Precipitation Estimation from Rain Gauges and Meteorological Radar Using Geostatistics (6 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in Mathematical Geosciences (based on the number of publications) are:

• Andre G. Journel (42 papers) absent at the last edition,
• Clayton V. Deutsch (31 papers) published 2 papers at the last edition,
• Roussos Dimitrakopoulos (29 papers) published 2 papers at the last edition, 1 more than at the previous edition,
• Ian Lerche (28 papers) absent at the last edition,
• Donald E. Myers (28 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Mathematical Geosciences (based on the number of publications) are:

• Stanford University (139 papers) published 4 papers at the last edition, 3 more than at the previous edition,
• United States Geological Survey (96 papers) published 4 papers at the last edition,
• University of South Carolina (65 papers) absent at the last edition,
• Geological Survey of Canada (57 papers) published 1 paper at the last edition,
• University of Arizona (55 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 8.04% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 13.59% were posted by at least one author from the top 10 institutions publishing in the journal. Another 16.50% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 35.92% of all publications and 33.98% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.