Machine learning applications in geophysical studies are often used to predict geophysical observations in areas with sparse or not data or recognize patterns and similarities in data. This session should provide different techniques to improve the information of constraining data used in a lithopsheric modelling process. Data like seismic information, surface geology, rock classifications etc. is often used during the interpretation step of lithospheric modelling to aid the qualitative interpretation. Consensus between additional data and the own model is assessed by comparison and used to describe the model goodness consistency.

The quantification and further explotation of constraining data with new techniques should be covered by abstracts submitted to this session.

The combination of the different geophysical and geological data available with the geological data should improve our tectonic modelling.