El Hierro megalandslide dynamics analysed using "big data" to predict the future behaviour of megalandslides on other volcanic islands

El Hierro megalandslide dynamics analysed using "big data" to predict the future behaviour of megalandslides on other volcanic islands

Researchers from the Institute of Rock Structure & Mechanics began monitoring landslide detachment planes around a potential megalandslide on El Hierro in 2013. The proposed project extends this by building a comprehensive automated deformation monitoring system. These data will be analysed alongside other sources of freely available primary data using the big data paradigm in order to provide a comprehensive assessment of megalandslide dynamics. The results will be supplemented by comprehensive investigations of megalandslides and megalandslide reactivation at both the global and regional scales. Despite the myriad of geophysical datasets which lend themselves to the big data paradigm it is extremely rare for geoscientific research to place data analysis at the heart of a project. Big data focuses on the simultaneous analysis of disparate heterogeneous data and as a result it has a tremendous predictive capacity. The latter allows us to use our data from El Hierro in order to inform discussion about the risks posed by megalandslides on other volcanic islands across the globe.

Grant No.

GJ16-12227Y - Junior Grants (2015-2022)

Grant Agency

Grant Agenency Czech Republic

Resolved in

2016-2018

Principal investigator

Dr. Jan Blahůt

Members of the project team:

Dr. Matt D. Rowberry

Dr. Xavier Martí

Jan Balek

Institute of Rock Structure and Mechanics of the CAS

State
Archived