"Earth Informatics and Geophysical Inversion: More ways to learn from our data" -Professor Anya M. Reading, School of Physical Sciences (Earth Sciences), University of Tasmania

In geophysics, we most usually use geophysical modelling and inversion to make an inference from observed data.  Multi-layered datasets are now becoming more common in Earth Sciences and enable us to add a further set of techniques, based on Machine Learning or Informatics, to our data-inference toolbox.  Machine Learning and geophysical inversion both represent ways that the applied geophysicist might gain knowledge from field observations and remote sensed data.  The two approaches represent contrasting philosophies based respectively on statistics and physics.
This presentation will show Informatics-based approaches to prediction and pattern identification, that complement geophysical inversion.  It is also possible to combine techniques and use machine learning and geophysical inversion in a combined workflow.  In a wider sense, the presentation will also discuss how humans and computers can work together for the best use of (often hard-won) Earth Sciences data.