A data-driven complex systems approach to early prediction of landslides

A Tordesillas; Z Zhou; R Batterham

Journal article

A data-driven complex systems approach to early prediction of landslides

A Tordesillas, Z Zhou, R Batterham

Mechanics Research Communications | Published : 2018

DOI: 10.1016/j.mechrescom.2018.08.008

Abstract

Landslides are a common natural disaster that claims countless lives and causes huge devastation to infrastructure and the environment. The recent spate of landslides worldwide has prompted renewed calls for better forecasting methods which could boost the performance of early warning systems in real time. Although the variety, volume and precision of monitoring data have steadily increased, methods for analysing such data sets for landslide prediction have not kept pace with the rapid advances in complex systems data analytics and micromechanics of granular failure. Here we help close this gap by developing a new model to analyse kinematic data using complex networks. Like no other, our mod..

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University of Melbourne Researchers

Antoinette Tordesillas Author

Robin Batterham Author

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Grants

Awarded by Air Force Office of Scientific Research

Funding Acknowledgements

This work was supported by the US Air Force (AFOSR 15IOA059), the Australian Research Council (DP120104759) and the US Army Research Office (W911NF-11-1-0175).

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Keywords

Micromechanics

4005 Civil Engineering