Big Earth Data

Aims & Scope

Big Earth Data publishes gold open access research in the earth sciences, including earth system science, earth observation, earth systems monitoring, and environmental processes.

Big Earth Data is published on behalf of The International Society of Digital Earth.

Big Earth Data aims to provide an efficient and high-quality platform for promoting ‘big data’ sharing, processing and analyses, thereby revolutionising the cognition of the Earth’s systems.

The journal primarily features the fundamentals of ‘big Earth data’ handling, as well as the channels and technologies used for ‘big Earth data’ collection, management, analysis and visualisation.

To showcase the benefits of data-driven research, submissions on the applications of 'big Earth data' in exploring the Earth's history and its future evolution are highly encouraged.

Metrics & Ranking

Abstracting & Indexing

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

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)
• Web of Science

Subjects & Keywords

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

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Copyright url
• Plagiarism url
• Preservation url
• Apc url
• License

Plagiarism Policy

This journal follows a plagiarism policy. All submitted manuscripts are screened using reliable plagiarism detection software to ensure originality and academic integrity. Authors are responsible for proper citation and acknowledgment of all sources, and any form of plagiarism, including self-plagiarism, will not be tolerated.

For more details, please refer to our official: Plagiarism Policy.

APC Details

The journal’s Article Processing Charge (APC) policies support open access publishing in Computer Science and Earth and Planetary Sciences, ensuring accessibility and quality in research dissemination.

This journal requires an Article Processing Charge (APC) to support open access publishing, covering peer review, editing, and distribution. The current APC is 1,200.00 EUR. Learn more.

Explore journals without APCs for alternative publishing options.

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.

• Mapping landslide susceptibility and types using Random Forest

  Citation: 219

  Authors: Khaled, Tao, Yang

• Global spatio-temporally harmonised datasets for producing high-resolution gridded population distribution datasets

  Citation: 219

  Authors: Christopher T., Heather, David, Greg, Linda, Forrest R., Andrea E., Jeremiah J., Graeme, Kytt, Parmanand, Maksym, Alessandro, Andrew J.

• A survey of remote sensing image classification based on CNNs

  Citation: 176

  Authors: Jia, Shaohua, Yunqiang, Chenyan

• Big Earth data: A new frontier in Earth and information sciences

  Citation: 169

  Authors: Huadong

• Building an Earth Observations Data Cube: lessons learned from the Swiss Data Cube (SDC) on generating Analysis Ready Data (ARD)

  Citation: 154

  Authors: Gregory, Bruno, Andrea, Denisa, Jean-Philippe, Karin, Hy, Pascal

• Automated global delineation of human settlements from 40 years of Landsat satellite data archives

  Citation: 123

  Authors: Christina, Martino, Thomas, Panagiotis, Aneta J., Vasileios, Michele, Filip, Pierre

• Big earth data analytics on Sentinel-1 and Landsat imagery in support to global human settlements mapping

  Citation: 100

  Authors: Christina, Martino, Panagiotis, Vasileios, Aneta J., Pierre, Luca, Armin, Veselin, Dario, Filip, Lewis, Thomas

• A generalized supervised classification scheme to produce provincial wetland inventory maps: an application of Google Earth Engine for big geo data processing

  Citation: 87

  Authors: Meisam, Brian, Majid, S. Mohammad, Sahel, Sayyed Mohammad Javad, Weimin, Jean

• Monitoring land degradation at national level using satellite Earth Observation time-series data to support SDG15 – exploring the potential of data cube

  Citation: 85

  Authors: Gregory, Bruno, Antonio, Pierre, Mattia, Paolo

• Digital earth Australia – unlocking new value from earth observation data

  Citation: 78

  Authors: Trevor, Bex, Ben, Leo, Norman, Erin, Adam, Alexis, Stuart, Claire