Aims and scope

Vietnam Journal of Earth Sciences is a peer-reviewed journal sponsored by Vietnam Academy of Science and Technology to publish high-quality original and review articles on the entire range of Earth Sciences, focused on Vietnam and Asia Pacific region, and their correlations and connections on the globe. The journal publishes on fundamental and applied research in Earth Sciences, including geology, geophysics, geography, hydrology, meteorology, oceanography, petroleum, geohazards, environmental geosciences and sustainable development, geoinformatics, geodesy, GIS and remote sensing.





NOTE 2 - 2020


Call for paper: Special Issue

Technological Innovation and Advanced Machine Learning for Geo-Information Science

A special issue of Vietnam Journal of Earth Sciences, (ISSN: 0866-7187; 2615-9783).

Vietnam Journal of Earth Sciences (VJES) is a peer-reviewed and open-access journal, free of charge for authors, sponsored by the Vietnam Academy of Science and Technology (VAST), Vietnam.
- VJES is indexed Emerging Sources Citation Index (ESCI) of the Web of Science Core Collection.
- VJES is also indexed in Google ScholarNRSJ (Norway),  CrossrefGeoRef (American Geosciences Institute)VCGScilit (Switzerland)Copernicus InternationalAsean Citation Index; CiteFactor
Deadline for manuscript submissions: 30 June 2021

1. Special Issue Editors

Prof. Dieu Tien Bui Website
Guest Editor
GIS Group, Department of Business and IT, University of South-Eastern Norway, Gullbringvegen 36, N-3800 Bø i Telemark, Norway.

Interests: Technological Innovation; UAV; LiDAR; remote sensing; GIS; cartography; geo-hazards, artificial intelligence, environmental management.

Dr. José Lázaro Amaro-Mellado Website
Guest Editor
Department of Graphic Engineering, University of Seville, 41092, Seville, Spain
Interests: Technological Innovation; GIS; earthquake; seismic; cartography; environmental hazard.

Dr. Thu Trang Le Website
Guest Editor
Laboratoire Magmas et Volcans, Université Clermont Auvergne, F-63000 Clermont-Ferrand, France
Department of Photogrammetry and Remote Sensing, Hanoi University of Mining and Geology, 18 Vien Street, Hanoi, Vietnam.
Interests: Multivariate SAR image processing; information extraction and fusion from remote sensing data; GIS; natural hazards.

Assoc.Prof. Quang Thanh Bui Website
Guest Editor
Center for Applied Research in Remote Sensing and GIS (CARGIS), Faculty of Geography, VNU University of Science, Hanoi, Vietnam.
Interests: Technological Innovation; natural resource management; remote sensing; artificial intelligence; environmental hazard.

Dr. Nhat-Duc Hoang Website
Guest Editor
Faculty of Civil Engineering, Duy Tan University, Da Nang, Vietnam.
Interests: Civil engineering; technological innovation; artificial intelligence; metaheuristics optimization.

Dr. Viet-Ha Nhu Website
Guest Editor
Department of Geological-Geotechnical Engineering, Hanoi University of Mining and Geology, Hanoi, Viet Nam.
Interests: Geo-hazards; GIS and geospatial technology; geotechnical engineering; artificial intelligence; data mining.

Dr. Luyen Bui Website
Guest Editor
School of Earth and Planetary Sciences, Curtin University, WA, Australia.
Faculty of Geomatics and Land Administration, Hanoi University of Mining and Geology, Hanoi, Vietnam.
Interests: InSAR, Environmental Geodesy, Machine Learning.

Assoc. Prof. Duc-Tan Tran Website
Guest Editor
Faculty of Electrical and Electronic Engineering, Phenikaa University, Hanoi, Vietnam.

Interests: Signal processing; smart sensing; wireless sensor networks, IoT applications.

2. Special Issue Information

Dear Colleagues,

Earth science encompasses a broad spectrum, which includes geology, oceanography, meteorology, and astronomy. Geo-information science, which is an advanced domain of earth science, has explosive developments in recent years, where advanced geospatial technologies, novel artificial intelligence, and technological innovations have provided new ways to analyze and process geo-information data to obtain valuable insights. As a result, innovative and efficient solutions could be developed, and some have proven their efficiency in engineering problems, natural resource management, climate changes, and natural disaster mitigation.

In this Special Issue, we warmly invite researchers to submit their contributions, focusing on technological innovation, advanced geospatial technologies, and novel machine learning and metaheuristic optimization for geo-information science. We are looking for submissions on, but not limited to, the following topics:

  • Machine learning, metaheuristic optimization, and technological innovations for civil engineering,  geotechnical engineering, and geological exploration
  • Application of sensors, electronics, telecommunication, wireless sensor networks, internet of things, and smart systems in Earth sciences
  • Novel methods and techniques for time series forecasting and anomaly detection in Earth sciences, i.e., hydropower dam and marine anomaly.
  • Geospatial data science, cartography, map production, geo-visualization, land survey, GNSS, and location-based service.
  • Ensemble learning and transfer learning approaches in Earth sciences.
  • GIS-based decision support systems, GIS for policy, management, and service of humanity.
  • Real-life case studies in Earth science and engineering projects with findings of definite interest to the scientific community.
  • Remotely sensed image segmentation and classification with deep convolutional neural networks and their applications in Earth sciences.
  • Recent advances in geospatial technology, data mining, and artificial intelligence for natural hazard and environmental problems, i.e., seismic, earthquake, landslide, land subsidence, soil salinity, erosion, groundwater, flood, flash flood, fluvial and coastal floods, forest fire, and air quality.
  • Remote Sensing, LiDAR, UAV/drone photogrammetry, image processing, and their application in Earth sciences.

Finally, authors are encouraged to share codes and data so that their studies are easily reproducible and serve as the seeds for future improvements.

We look forward to receiving your submissions in this interesting area of specialization.

Prof. Dieu Tien Bui
Dr. José Lázaro Amaro-Mellado
Dr. Le Thu Trang
Assoc. Prof. Quang Thanh Bui
Dr. Nhat-Duc Hoang
Dr. Viet-Ha Nhu
Dr. Bui Khac Luyen
Assoc. Prof. Tran Duc Tan

Guest Editors

3. Manuscript Submission Information

Please visit the Instructions for Authors page before submitting a manuscript. Manuscripts should be submitted online at by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts could be submitted until the deadline. All manuscripts will be peer-reviewed through the double-blind peer-review process.
Accepted manuscripts will be published continuously in the journal as soon as they have been accepted, and will be listed together on the Special issue website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere. Free of charge for authors is applied for all publications. Submitted papers should be well formatted and use good English.

You can download more information about the special issue here.

Posted: 2020-06-18

NOTICE 1 - 2020

We are happy that the Vietnam Journal of Earth Sciences has been included in the Web of Sciences as Emerging Sources Citation Index (ESCI). We would like to express our deep gratitude to all editorial board members and authors of VJES. On this occasion, we cordially invite scientists to submit high-quality articles to our journal. Please share this news with your colleagues and friends.
Posted: 2020-04-21

NOTICE 2-2019


Call for paper:  Special Issues “Data mining in Earth Sciences”

Data mining has been widely used to solve a lot of problems in Earth Sciences such as geo-hazards assessment and prediction, groundwater quality and potential prediction, land use-land cover detection, etc. Nowadays, with the emergence of new technologies such as GIS, remote sensing, automation, smart equipment like mobile phone, a huge amount of data is being generated in Earth Sciences, which creates challenges on how to analyze this data to discover the useful knowledge for solving real-world problems.

In recent years, new advanced techniques like Artificial Intelligence - AI (Machine learning and deep learning) have been developed and applied effectively in data mining of many earth sciences problems such as geo-environmental and geotechnical problems. Many new hybrid and advanced AI techniques are being proposed. Development and application of these techniques in data mining of Earth Sciences are required with new case studies.

The main objective of the special issue is to collect state-of-the-art research findings on the latest developments and challenges in the field of data mining for earth sciences. High-quality original research papers that present theoretical frameworks, methodologies, and application o case studies from a single- or cross-country perspective are welcome, as well as review articles.

Potential topics of interest include but are not limited to the following:

      Data mining techniques, including classification, association, outlier detection, clustering, regression, and prediction, for decision-making, used in Earth Sciences

      Cutting-edge data mining methods, such as machine learning and deep learning for data mining in Earth Sciences

      Real-world problems in Earth Sciences such as geohazards (landslides, floods, and earthquakes), forest fire, groundwater quality and potential assessment, geo-environmental and geotechnical problems, land use/land cover detection, and any Earth Sciences related problems.

 Guest Editors

Lead Guest Editor: Binh Thai Pham, University of Transport Technology, email:

Guest Editors

Submitted deadline: 30 April 2020.

Posted: 2019-10-09
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