Landslide seismic magnitude

Lin, Cheng‐Horng; Jan, Jyh Cherng; Pu, Hsin‐Chieh; Tu, Yoko; Chen, C.C.; Wu, Yih‐Min

doi:10.1016/j.epsl.2015.07.068

Cited by 24 publications

(25 citation statements)

References 14 publications

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“…Equivalent earthquake magnitudes are sometimes computed for mass movement signals using amplitude or duration-based methods (e.g., Pankow et al, 2014). However, due to the difference in the physical process, such magnitudes do not hold the same physical meaning as for earthquake magnitudes (e.g., Lin et al, 2015)…”

Section: Accepted Manuscript 34mentioning

confidence: 99%

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Seismic and acoustic signatures of surficial mass movements at volcanoes

Allstadt

Matoza

Lockhart

et al. 2018

Journal of Volcanology and Geothermal Research

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Surficial mass movements, such as debris avalanches, rock falls, lahars, pyroclastic flows, and outburst floods, are a dominant hazard at many volcanoes worldwide. Understanding these processes, cataloging their spatio-temporal occurrence, and detecting, tracking, and characterizing these events would advance the science of volcano monitoring and help mitigate hazards. Seismic and acoustic methods show promise for achieving these objectives: many surficial mass movements generate observable seismic and acoustic signals, and many volcanoes are already monitored. Significant progress has been made toward understanding, modeling, and extracting quantitative information from seismic and infrasonic signals generated by surficial mass movements. However, much work remains. In this paper, we review the state of the art of the topic, covering a range of scales and event types from individual rock falls to sector collapses. We consider a full variety of volcanic settings, from submarine to subaerial, shield volcano to stratovolcano. Finally, we discuss future directions toward operational seismoacoustic monitoring of surficial mass movements at volcanoes.

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Section: Accepted Manuscript 34mentioning

confidence: 99%

“…Landslides can be located within 20 to 100 km of the actual source. Potential landslide detections are not automatically reported currently, to our knowledge, though a real-time algorithm has been proposed by Lin et al (2015).…”

Section: Long-period Detection and Locationmentioning

confidence: 99%

Seismic and acoustic signatures of surficial mass movements at volcanoes

Allstadt

Matoza

Lockhart

et al. 2018

Journal of Volcanology and Geothermal Research

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“…Topography correction is necessary because rockfalls and other gravitational mass wasting processes generate surface waves that propagate following the topography (Dammeier et al, 2011;Hibert et al, 2014;Lin et al, 2015;Burtin et al, 2016). The results of this correction were stored in distance maps.…”

Section: Seismic Data Processing: Event Locationmentioning

confidence: 99%

Seismic monitoring of small alpine rockfalls – validity, precision and limitations

Dietze

Mohadjer²,

Turowski

et al. 2017

Earth Surf. Dynam.

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Abstract. Rockfall in deglaciated mountain valleys is perhaps the most important post-glacial geomorphic process for determining the rates and patterns of valley wall erosion. Furthermore, rockfall poses a significant hazard to inhabitants and motivates monitoring efforts in populated areas. Traditional rockfall detection methods, such as aerial photography and terrestrial laser scanning (TLS) data evaluation, provide constraints on the location and released volume of rock but have limitations due to significant time lags or integration times between surveys, and deliver limited information on rockfall triggering mechanisms and the dynamics of individual events. Environmental seismology, the study of seismic signals emitted by processes at the Earth's surface, provides a complementary solution to these shortcomings. However, this approach is predominantly limited by the strength of the signals emitted by a source and their transformation and attenuation towards receivers. To test the ability of seismic methods to identify and locate small rockfalls, and to characterise their dynamics, we surveyed a 2.16 km 2 large, near-vertical cliff section of the Lauterbrunnen Valley in the Swiss Alps with a TLS device and six broadband seismometers. During 37 days in autumn 2014, 10 TLS-detected rockfalls with volumes ranging from 0.053 ± 0.004 to 2.338 ± 0.085 m 3 were independently detected and located by the seismic approach, with a deviation of 81 +59 −29 m (about 7 % of the average inter-station distance of the seismometer network). Further potential rockfalls were detected outside the TLS-surveyed cliff area. The onset of individual events can be determined within a few milliseconds, and their dynamics can be resolved into distinct phases, such as detachment, free fall, intermittent impact, fragmentation, arrival at the talus slope and subsequent slope activity. The small rockfall volumes in this area require significant supervision during data processing: 2175 initially picked potential events reduced to 511 potential events after applying automatic rejection criteria. The 511 events needed to be inspected manually to reveal 19 short earthquakes and 37 potential rockfalls, including the 10 TLS-detected events. Rockfall volume does not show a relationship with released seismic energy or peak amplitude at this spatial scale due to the dominance of other, process-inherent factors, such as fall height, degree of fragmentation, and subsequent talus slope activity. The combination of TLS and environmental seismology provides, despite the significant amount of manual data processing, a detailed validation of seismic detection of small volume rockfalls, and revealed unprecedented temporal, spatial and geometric details about rockfalls in steep mountainous terrain.Published by Copernicus Publications on behalf of the European Geosciences Union.

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“…There is still an argument and debate among the landslide researchers whether traditional detection of landslides, for example through direct field surveys or remote sensing based analysis is better. Both of the aforementioned approach has some merits and demerits such as in the case of field investigation which is highly time consuming and very laborious act, on the other hand satellite image processing techniques also need rigorous validation steps to produce an accurate landslide inventory map (Lin et al, 2015). High-resolution imagery is an indispensable data source to model and validate landslide features appropriately (Akcay, 2015).…”

Section: Introductionmentioning

confidence: 99%

A novel hybrid integration model using support vector machines and random subspace for weather-triggered landslide susceptibility assessment in the Wuning area (China)

et al. 2017

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This study proposed a hybrid modelling approach using two methods: support vector machines and random subspace to create a novel model namely Random SubSpace based Support Vector Machines (RSSVM) for landslide susceptibility assessment. The newly developed model was then tested at Wuning area, China to produce landslide susceptibility map. To achieve the objective of the study, first a spatial dataset was constructed that includes a landslide inventory map consisting of 445 landslide locations; and various landslide conditioning factors, such as slope, aspect, altitude, topographic wetness index (TWI), stream power index (SPI), sediment transport index (STI), soil, lithology, normalized difference vegetation index (NDVI), land use, rainfall, distance to roads, distance to rivers, distance to faults. Next, the result of RSSVM model was validated using statistical index-based evaluations and receiver operating characteristic curve method. Next, to assess the performance of the proposed RSSVM model, a comparison analysis was performed with other existing methods such as ANN (Artificial Neural Network), NB (Naïve Bayes) and SVM (Support Vector Machine). In general, the performance of the RSSVM model showed higher than the rest of the models for spatial prediction of landslides. The AUC results of the applied models are: RSSVM (AUC=0.857), followed by MLP (AUC=0.823), SVM model (AUC=0.814) and NB model (AUC=0.783). The present study indicates that RSSVM can be used for spatial prediction of landslides and the result is very useful for the lcoal government and people lived in the Wuning area.

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Landslide seismic magnitude

Cited by 24 publications

References 14 publications

Seismic and acoustic signatures of surficial mass movements at volcanoes

Seismic and acoustic signatures of surficial mass movements at volcanoes

Seismic monitoring of small alpine rockfalls – validity, precision and limitations

A novel hybrid integration model using support vector machines and random subspace for weather-triggered landslide susceptibility assessment in the Wuning area (China)

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