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Earth Sciences & Geography | Mathematical Geosciences - incl. option to publish open access (Editorial Board)

Mathematical Geosciences

Mathematical Geosciences

Editor-in-Chief: Roussos Dimitrakopoulos

ISSN: 1874-8961 (print version)
ISSN: 1874-8953 (electronic version)

Journal no. 11004

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Editor-in-Chief
Roussos Dimitrakopoulos, McGill University, Canada

Associate Editors

Jo Eidsvik, NTNU, NORWAY

Pierre Goovaerts, BioMedware Inc., USA

Donald Allen Singer, U. S. Geological Survey, USA

Tuanfeng Zhang, Schlumberger-Doll Research, USA


Book Review Editor
Denis Marcotte, Ecole Polytechnique, Canada

Founding Editor
Daniel F. Merriam, USA

Editorial Board

P. Abrahamsen, Norwegian Computing Centre, Norway

D. Allard, INRA, France

A. Buccianti, Università degli Studi di Firenze, Italy

J. Rivoirard, Mines ParisTech, France           

G. Caumon, Université de Lorraine, France

N. Cressie, Ohio State University, USA        

C. V. Deutsch, University of Alberta, Canada  

P. A. Dowd, University of Adelaide, Australia

L. Durlofsky, Stanford University, USA

J. Gómez-Hernández, Universitat Politècnica de València, Spain

A. G. Journel, Stanford University, USA           

S. A. McKenna, IBM Research, Ireland

H. S. Pandalai, Indian Institute of Technology, India

P. Renard, Université  de Neuchâtel, Switzerland

H. Schaeben, TU Bergakademie Freiberg, Germany

A. Soares, Instituto Superior Tecnico, Portugal

C. Roberto de Souza Filho, University of Campinas, Brazil

S. Srinivasan, Pennsylvania State University, USA

F.-W. Wellmer, Technical University of Berlin, Germany 

 

 

Special Issues 

Special Issues

Special Issue on Geothermal Energy and Utilization 

Call for Papers

Guest editor: Kewen Li
Geothermal energy is one of the most important modern renewable energies. It has many advantages over solar and wind systems. These advantages include: 1) unaffected by weather; 2) it is a base-load power; 3) it is stable and has high capacity factor over 90% in many cases; 4) it requires less land and has less ecological effect; 5) it has high thermal efficiency.
Significant achievements have been made in geothermal industry, including fundamental mechanisms and utilizations in many aspects. These scientific and technological advances have contributed to the growth of the geothermal industry and the improvement of the environment around the world.
In order to further facilitate the promotion of geothermal energy, the goal of this special issue is to collect part of the accomplishments and the contributions about basic heories, methodologies, and technologies relevant to the geosciences of discovering and developing geothermal energy. Therefore, we are pleased to invite papers in the following areas:
• Geology and geophysics
• Geochemistry
• Geothermal reservoir modeling: principles, methods and algorithms
• Heat flow studies
• Evaluation of geothermal resources
• Utilization of geothermal energy
• Hybrid of geothermal with other renewable energies
• Geosciences related to geothermal energy coproduced from oil and gas fields
• Others
The timeline for the special issue is the following:
• Paper submission before May 31st 2018
• Return of reviews to authors before 15 July 2018
• Submission of final papers deadline: 15 September 2018
• Publication in December 2018.
Submit papers to: http://www.editorialmanager.com/matg
Submit questions to: kewenli@cugb.edu.cn

Special Issue: Data Science in Geosciences 

Call for Papers

Guest Editors:
Vasily Demyanov (Heriot-Watt University, Edinburgh, UK)
Erwan Gloaguen (INRS-ETE, Québec, Canada)
Mikhail Kanevski (University of Lausanne, Switzerland)
Modern geoscience is facing a step change in the view of the amounts of data to be processed in almost real time in modern day digital era. There are still large volumes of heritage monitoring data that encapsulate essential domain knowledge and is often underused especially while inferring uncertainty of Earth system behaviour. The challenge comes in the processing, integration and assimilation of big data sets consisting in a diversity of types and nature of
information. Emerging new field of data science, machine learning and data driven modelling attracts more and more attention across the geoscience audience.
The special issue aims to provide an overview of emerging data science links withgeoscience applications, including big data, challenging case studies in geosciences, adaptation
of data science tech to the domain content, comparative studies, etc. We are specifically looking for original contribution that are not limited to a somewhat mechanistic application of the existing data science technology but rather reveal new contextual scientific merit for the geoscience domain knowledge.
Main topics:
- Data science in Geosciences: new concepts, new tools
- Environmental data mining
- Big data in geoscience
- Machine learning in geosciences
- Visual analytics of geo- and environmental data
- Data driven prediction modelling
- Applications: geoscience data, environmental risks, natural hazards, other
Timelines:
- Paper submission before: October 31st, 2018
- Return of reviews to authors before: January 31st, 2019
- Submission of final papers deadline: March 31st
, 2019
- Publication in the Spring or Summer 2019
Submit papers on-line through the journal`s website
springer.com/journal/11004
When submitting you must choose the SI: “Data Science in Geosciences”.
Submitted manuscripts must fully comply with the journal’s Instructions for Authors in preparing manuscripts.
For inquiries please contact the Guest Editors:
Vasily Demyanov (V.Demyanov@hw.ac.uk)
Erwan Gloaguen (Erwan.Gloaguen@ete.inrs.ca)
Mikhail Kanevski (Mikhail.Kanevski@unil.ch)

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  • Journal Citation Reports®
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  • 2.022
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    Mathematical Geosciences 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.  


    5-year Impact Factor: 1.915   

     

     

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