Machine Learning Improves Debris Flow Warning

[1]  M. Ripepe,et al.  Infrasound Array Analysis of Debris Flow Activity and Implication for Early Warning , 2019, Journal of Geophysical Research: Earth Surface.

[2]  N. Hovius,et al.  Seismic monitoring of torrential and fluvial processes , 2016 .

[3]  Lorenz Meier,et al.  Near Real-Time Automated Classification of Seismic Signals of Slope Failures with Continuous Random Forests , 2020 .

[4]  K. Allstadt,et al.  A physical model of the high‐frequency seismic signal generated by debris flows , 2019, Earth Surface Processes and Landforms.

[5]  Brian W. McArdell,et al.  Sediment transfer patterns at the Illgraben catchment, Switzerland: Implications for the time scales of debris flow activities , 2011 .

[6]  N. Hovius,et al.  Testing seismic amplitude source location for fast debris-flow detection at Illgraben, Switzerland , 2017 .

[7]  D. Weber,et al.  Murgang-Beobachtungsstationen in der Schweiz , 2001 .

[8]  A. Badoux,et al.  Natural hazard fatalities in Switzerland from 1946 to 2015 , 2016 .

[9]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[10]  J. W. Kean,et al.  Evolution of a natural debris flow: In situ measurements of flow dynamics, video imagery, and terrestrial laser scanning , 2010 .

[11]  Alessio Ferrari,et al.  Monitoring and prediction in early warning systems for rapid mass movements , 2014 .

[12]  Jeffrey A. Coe,et al.  Alpine debris flows triggered by a 28 July 1999 thunderstorm in the central Front Range, Colorado , 2007 .

[13]  Yoshua Bengio,et al.  Speaker Recognition from Raw Waveform with SincNet , 2018, 2018 IEEE Spoken Language Technology Workshop (SLT).

[14]  M. Jakob,et al.  Debris-flow Hazards and Related Phenomena , 2005 .

[15]  J. B. Smith,et al.  Estimating rates of debris flow entrainment from ground vibrations , 2015 .

[16]  Clément Hibert,et al.  Implementation of a Multistation Approach for Automated Event Classification at Piton de la Fournaise Volcano , 2017 .

[17]  Stephen V. Stehman,et al.  Selecting and interpreting measures of thematic classification accuracy , 1997 .

[18]  F. Schlunegger,et al.  Direct measurement of channel erosion by debris flows, Illgraben, Switzerland , 2011 .

[19]  C. Humphreys,et al.  Machine Learning Predicts Laboratory Earthquakes , 2017, Geophysical Research Letters.

[20]  Jean-Philippe Malet,et al.  Automatic classification of endogenous landslide seismicity using the Random Forest supervised classifier , 2017 .

[21]  Joel B. Smith,et al.  Debris-flow monitoring and warning: Review and examples , 2019, Earth-Science Reviews.

[22]  Alessandro Simoni,et al.  Experimental evidences and numerical modelling of debris flow initiated by channel runoff , 2005 .

[23]  Andreas Schimmel,et al.  Automatic Identification of Alpine Mass Movements by a Combination of Seismic and Infrasound Sensors , 2018, Sensors.

[24]  K. Aki,et al.  Location of seismic events and eruptive fissures on the Piton de la Fournaise volcano using seismic amplitudes , 2003 .

[25]  Gregory C. Beroza,et al.  Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking , 2020, Nature Communications.

[26]  Jean-Philippe Malet,et al.  Automatic identification of rockfalls and volcano-tectonic earthquakes at the Piton de la Fournaise volcano using a Random Forest algorithm , 2017 .

[27]  K. Allstadt,et al.  Seismic and acoustic signatures of surficial mass movements at volcanoes , 2018, Journal of Volcanology and Geothermal Research.

[28]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[29]  Scott McDougall,et al.  Entrainment of material by debris flows , 2005 .

[30]  R. Iverson,et al.  Grain-size segregation and levee formation in geophysical mass flows , 2012 .

[31]  M. Arattano,et al.  Seismic Characterization of Debris Flows: Insights into Energy Radiation and Implications for Warning , 2019, Journal of Geophysical Research: Earth Surface.

[32]  C. Graf,et al.  Field and monitoring data of debris-flow events in the Swiss Alps , 2003 .

[33]  R. Iverson,et al.  U. S. Geological Survey , 1967, Radiocarbon.

[34]  Paul A. Johnson,et al.  Continuous chatter of the Cascadia subduction zone revealed by machine learning , 2018, Nature Geoscience.

[35]  S. Cronin,et al.  Seismic signals of snow‐slurry lahars in motion: 25 September 2007, Mt Ruapehu, New Zealand , 2009 .

[36]  P. Bartelt,et al.  Field observations of basal forces and fluid pore pressure in a debris flow , 2006 .

[37]  Jakob Rhyner,et al.  A debris-flow alarm system for the Alpine Illgraben catchment: design and performance , 2009 .

[38]  Lorenzo Marchi,et al.  Systems and Sensors for Debris-flow Monitoring and Warning , 2008, Sensors.

[39]  Peter Molnar,et al.  Limits of sediment transfer in an alpine debris-flow catchment, Illgraben, Switzerland , 2009 .

[40]  M. Lamb,et al.  The Seismic Signature of Debris Flows: Flow Mechanics and Early Warning at Montecito, California , 2018, Geophysical Research Letters.

[41]  G. Dalla Fontana,et al.  The triggering of debris flow due to channel‐bed failure in some alpine headwater basins of the Dolomites: analyses of critical runoff , 2008 .