Call for papers: Big Data Advances in Exploration and Environment Geochemistry
Geochemistry: Exploration, Environment, Analysis (GEEA) is calling for papers to be submitted to
the above thematic collection.
With the advent of the era of big data, scientific research has moved into the fourth research
paradigm: data intensive science. Big data and machine learning have brought earth sciences into an
artificial-intelligence research stage. Machine learning algorithms and models have been applied to
study large-scale, multi-resolution, multi-time, multi-type Earth observation data and socio-
economic data.
The goal of this thematic collection is to highlight recent progress in the research and applications of
big data and machine learning in the fields of exploration and environment geochemistry, for
instance:
- geochemical mineral resources prediction
- elemental migration and distribution
- anomaly identification
- global geochemical baselines
- geochemical analysis
- processing optimization
Please note that the thematic collection focuses exclusively on research based on real data, rather
than theoretical discussions of mathematical techniques.
Papers should be submitted no later than 30 April 2020.
Submission of a manuscript for possible inclusion in this thematic collection is no guarantee of
eventual acceptance and publication. All published contributions must meet the normal, rigorous
GEEA review standards with regard to both content and presentation. Authors who are non-native
English speakers should consider having a native English speaker edit their manuscript prior to
submission.
- Any queries contact us
- Author guidelines can be found here
- Submit your paper here