We use cookies to improve your website experience. To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy. By closing this message, you are consenting to our use of cookies.

Big Earth Data Analytics

Big Earth Data Special Issue Call for Papers

Deadline: 1 June 2019

Massive volumes of Earth data are being produced at an increasingly faster velocity from a variety of location-aware sensors and model simulations with increasing spatial, temporal, and spectral resolutions. Big Earth Data, characterized by the three Vs coupled with location information, offers great opportunities for advancing scientific discoveries and practices in society. For example, satellite sensors are collecting petabytes data on a daily basis. Climate model simulations by Intergovernmental Panel on Climate Change scientists are producing hundreds of petabytes of climate data. The mass account of Earth data, however, demands efficient geospatial analytics to investigate the unknown and complex patterns, which are critical to a wide range of applications including climate, natural hazards prediction and mitigation, public health, environmental sustainability and human behaviors. In the rapidly evolving Big Data era, this special issue will describe the latest efforts on Big Earth Data analytics towards addressing such challenges.

Potential topics include (but are not limited to) the following:

  • New tools and algorithms for Big Earth data analytics, particularly in regard to efficient data collection and management, machine-learning enabled information extraction, large scale geospatial data visualization and dissemination.
  • Big Earth data analytics for supporting climate change, oceanography, environmental science, natural hazards and public health research and applications.
  • Advances of new Earth observation technologies ranging from new satellite sensors to small unmanned aerial systems (sUAS).
  • Innovative approaches focusing on heterogeneous Big Earth data fusion with other data sources such as Big Social Data for advancing scientific discovery and practices in society.
  • Other research, development, education, and visions related to Big Earth Data analytics

Big Earth Data

Table of Contents for Big Earth Data. List of articles from both the latest and ahead of print issues.

Language: en-US

Publisher: tandf

Visit Journal Articles

Submission guidelines

Important Dates

  • February 15, 2019    Abstract submission to guest editors
  • March 1, 2019    Full paper submission invited
  • June 1, 2019        Full paper submission online
  • August 1, 2019      Decision to Authors
  • October 1, 2019     Revised Paper Submission
  • December 31, 2019  Publication

Please note that the manuscript will be reviewed upon submission and the accepted paper will be published online. Each paper will receive comments from at least two peer reviewers. The special issue will include a maximum of 8 papers.

We look forward to your contributions. Please do not hesitate to contact the Guest Editors in case of questions.

Manuscript Submission Information

Please visit the Instructions for Authors page before submitting a manuscript. When the manuscript is well prepared, please submit through Editorial Manager System and choose the right Special Issue. All APCs will be waived for invited manuscripts submitted to the Big Earth Data. If you need further assistance regarding on this matter, please contact the Editorial Office on this email address: TBED-peerreview@journals.tandf.co.uk.

Editorial Information

  • Special Issue Guest Editor: Zhenlong Li, Department of Geography, University of South Carolina, USA(zhenlong@sc.edu)
  • Special Issue Guest Editor: John L. Schnase, Goddard Space Flight Center, National Aeronautics and Space Administration (NASA), USA (john.l.schnase@nasa.gov)
  • Special Issue Guest Editor: Susan Wang, Department of Geography, University of South Carolina, USA(cwang@mailbox.sc.edu)
  • Special Issue Guest Editor: Hsiuhan Lexie Yang, Oak Ridge National Laboratory, USA (yangh@ornl.gov)