Publications

Big Earth Data

Sep 20, 2018

The journal of Big Earth Data was launched in December 2017. This journal is an interdisciplinary, open access and peer-review academic journal. It is published by the International Society for Digital Earth jointly with the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, the Strategic Priority Research Program of Chinese Academy of Sciences, the Taylor & Francis Group and the Science Press. The Academician of Chinese Academy of Sciences, Huadong Guo is the Editor-in-Chief of the journal. Aiming to provide an efficient and high-quality platform for promoting ‘big data’ sharing, processing and analyses, thereby revolutionizing the cognition of the Earth’s systems, the journal Big Earth Data was inaugurated. 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. Big Earth Data supports an open data policy and serves as a direct link between the published manuscript and its relevant supporting data in the advancement of data sharing and reuse. The journal publishes research topics on ‘big data’ studies across the entire spectrum of Earth sciences, including but not limited to Earth Observation, Geography, Geology, Atmospheric Science, Marine Science, Geophysics, Geochemistry and so on. It accepts original research articles, review articles, data papers, technical notes and letters. Along with research papers and data papers describing data sets, the journal also publishes paper-related data sets deposited in the public repositories.

Big Earth Data is an Open Access electronic online journal. Papers published in the inauguration issue of Big Earth Data have been listed below for your refer:

Big data drives the development of Earth science

Huadong Guo

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

Huadong Guo

Exploring the depths of the global earth observation system of systems

Max Craglia, Jiri Hradec, Stefano Nativi & Mattia Santoro

A new big data approach based on geoecological information-modeling system

Costas A. Varotsos & Vladimir F. Krapivin

Digital earth Australia – unlocking new value from earth observation data

Trevor Dhu, Bex Dunn, Ben Lewis, Leo Lymburner, Norman Mueller, Erin Telfer, Adam Lewis, Alexis McIntyre, Stuart Minchin & Claire Phillips

A view-based model of data-cube to support big earth data systems interoperability

Stefano Nativi, Paolo Mazzetti & Max Craglia

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

Gregory Giuliani, Bruno Chatenoux, Andrea De Bono, Denisa Rodila, Jean-Philippe Richard, Karin Allenbach, Hy Dao &Pascal Peduzzi

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

Christina Corbane, Martino Pesaresi, Panagiotis Politis, Vasileios Syrris, Aneta J. Florczyk, Pierre Soille, Luca Maffenini,Armin Burger, Veselin Vasilev, Dario Rodriguez, Filip Sabo, Lewis Dijkstra & Thomas Kemper

Optimizing Sentinel-2 image selection in a Big Data context

P. Kempeneers & P. Soille

Semantics all the way down: the Semantic Web and open science in big earth data

Tom Narock & Adam Shepherd

GSio: A programmatic interface for delivering Big Earth data-as-a-service

Pablo R. Larraondo, Sean Pringle, Jian Guo, Joseph Antony & Ben Evans

Scalable near-repeat and event chain calculations over heterogeneous computer architecture and systems

Xinyue Ye, Xuan Shi & Zhong Chen

The journal welcomes all submissions from the researchers who are interested in studying and publishing works related to big Earth data. For more information, please browse the weblink below:

Journal website: http://www.tandfonline.com/toc/tbed20/current  

Submission website: http://www.editorialmanager.com/TBED/default.aspx  

Should you have any questions, please contact the journal Editorial Office at bedj@radi.ac.cn or call us 86-10-8217 8902 / 8217 8196.

 

Appendix: