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N-SHAKE Network

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Journal Article
Published: 14 October 2015
Seismological Research Letters (2015) 86 (6): 1533–1539.
... and aftershock response in regions where conventional instrumentation and open-access seismic data are limited. Initial pilot installations of QCN instruments in 2014 are now being expanded to create the Nepal–Shaking Hazard Assessment for Kathmandu and its Environment (N-SHAKE) network. In this study, we...
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Journal Article
Published: 29 December 2021
Seismological Research Letters (2022) 93 (2A): 827–839.
... take the example of earthquake network, an independent, voluntary, community‐based and free system that offers a PEEW service. Through a quantitative survey ( n = 2625), we studied users’ perception and reaction to a warning sent related to an M 8.0 earthquake in Peru (where no national system existed...
FIGURES
Journal Article
Published: 01 August 1999
Bulletin of the Seismological Society of America (1999) 89 (4): 1025–1036.
..., elongated in the N-S direction. Concerning historical seismicity, only two large events have been reported for the last 2000 years, but they are still poorly constrained. The seismicity recorded since installation of regional networks in the early 1980s had been characterized by a low background level...
Journal Article
Published: 01 October 2001
Bulletin of the Seismological Society of America (2001) 91 (5): 895–913.
...Tzay-Chyn Shin; Ta-liang Teng Abstract The Chi-Chi earthquake was the largest onland earthquake to occur in Taiwan in the twentieth century. It inflicted severe damage in central western Taiwan: the excited strong shaking projected impact at cities as far as 150 km away and destroyed several high...
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... The Mineral, Virginia (USA), earthquake occurred at 17:51:3.9 UTC (Coordinated Universal Time) on 23 August 2011; the hypocenter was at 37.905°N, 77.975°W and depth was 8 km. The widely reported moment magnitude (M w ) was 5.7 ± 0.1. The m b (teleseismic short-period) magnitude estimated here...
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(a) Maximum possible warning times at ShakeAlert stations as a function of ...
Published: 16 August 2024
Figure 4. (a) Maximum possible warning times at ShakeAlert stations as a function of hypocentral distance from the 2021  M 6.2 Petrolia earthquake, calculated using MMI alert 2.5 (data from networks contributing to ShakeAlert, see Data and Resources ). This figure shows times at which
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(a) Maximum possible warning times at ShakeAlert stations as a function of ...
Published: 16 August 2024
Figure 8. (a) Maximum possible warning times at ShakeAlert stations as a function of hypocentral distance from the 2022  M 6.4 Ferndale earthquake, calculated using MMI alert  2.5 (data from networks contributing to ShakeAlert, refer to Data and Resources ). This figure shows times
Journal Article
Published: 27 January 2025
Bulletin of the Seismological Society of America (2025)
... characteristics, as well as ( n ) number of stations spanning from zero (i.e., no stations—unconditioned ground shaking) to 421 (i.e., the entire seismic network of Taiwan, according to the network configuration at the time of the 1999 M  7.7 Chi‐Chi earthquake). We use the seismic source model from Chan et al...
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Series: Geological Society, London, Special Publications
Published: 01 January 2017
EISBN: 9781862399709
... Abstract The Government of Indonesia has committed to deploying a network of 500 strong-motion sensors throughout the nation. The data from these sensors have the potential to provide critical near-real-time information on the level of ground shaking and potential impact from Indonesian...
Journal Article
Published: 14 February 2025
The Seismic Record (2025) 5 (1): 83–96.
... network in mid‐August 2022. This permanent seismic network captured the swarm’s decline. EQTransformer identified short S – P times on the first two locally deployed seismometers, both Raspberry Shake sensors, to constrain the swarm’s distance from Ta‘ū Island. Modern seismological processing methods...
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Journal Article
Published: 20 September 2024
Bulletin of the Seismological Society of America (2024) 114 (6): 2912–2925.
... seismic events affecting the Italian territory is tested using the 2016 Norcia, Italy, earthquake showing the method reconstruction capabilities, its robustness to noise and to network geometry changes, and its real‐time potential. KEY POINTS Real‐time ground‐shaking map reconstructions can...
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Journal Article
Published: 01 February 2025
Earthquake Spectra (2025) 41 (1): 5–33.
...—by hindcasting with data from previous earthquakes—the utility of our new variational inference, causal Bayesian network model to not only separate and map out different earthquake-induced hazards (shaking, landslides, and soil liquefaction) but also to then identify damage to buildings and attribute their cause...
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Journal Article
Published: 06 February 2025
Bulletin of the Seismological Society of America (2025) 115 (2): 533–561.
... Laboratory (ASL)/U.S. Geological Survey (USGS) ( 2014 ). Global Seismograph Network (GSN ‐ IRIS/USGS) (Data set), International Federation of Digital Seismograph Networks, doi: 10.7914/SN/IU . Aoi S. Asano Y. Kunugi T. Kimura T. Uehira K. Takahashi N. Ueda H. Shiomi K...
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Journal Article
Published: 28 May 2024
Seismological Research Letters (2024) 95 (4): 2538–2553.
... and relevant. Data from research‐grade broadband seismometers enable us to record time series of vibrations at a broad range of frequencies; however, these sensors are costly and are often deployed in remote places. Participation in the Raspberry Shake citizen science network enables seismology educators...
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Journal Article
Published: 08 December 2022
Bulletin of the Seismological Society of America (2023) 113 (1): 453–467.
... of ground motion are extracted using a TFR of ground shaking. The network is trained using the amplitude part of the TFR of ground shaking provided by the KiK‐net seismic network (Japan). Motivated by Florez et al. (2022) , we make use of conditional information such as distance, magnitude, and V S...
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Journal Article
Published: 16 March 2022
Seismological Research Letters (2022) 93 (3): 1636–1649.
... measured at N stations from the past T timesteps. This process enables the neural networks to learn both the spatial information between N stations and the temporal information between T timesteps. After encoding, two dense layers decode the information from LSTM layers to predict ground shaking...
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Journal Article
Published: 01 July 2024
The Seismic Record (2024) 4 (3): 151–160.
... to intensity using Worden et al. (2012) . The black line shows a simplified surface projection of fault rupture. The Northridge earthquake, which generated damaging shaking across the densely populated Los Angeles region, drove further development of monitoring networks, leading to the establishment...
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Journal Article
Published: 15 August 2023
Bulletin of the Seismological Society of America (2023) 113 (6): 2574–2595.
... of liquefaction (19.1 cm or 7.5 inch). Figure  14b presents 10 4 realizations of N repairs network that include uncertainty in spatially correlated ground shaking. Comparing this figure against Figure  13b demonstrates that inclusion of uncertainty in ground shaking increases...
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Journal Article
Published: 21 August 2024
Seismological Research Letters (2025) 96 (1): 526–537.
... the intensity of ground shaking. Therefore, acceleration waveforms were used as the input data, and they were collected from seismic networks in three countries, namely Taiwan, Japan, and Italy. In Taiwan, waveforms between 2014 and 2020 were collected from the CWBSN and between 1991 and 2020 from the TSMIP...
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Journal Article
Published: 01 August 2024
Earthquake Spectra (2024) 40 (3): 2092–2115.
... waveform data continuously at 50 sps within ± 2 g maximum amplitude levels. The sensors relay continuous 24/7/365 acceleration waveform data and shaking intensity parameters using the Amazon Web Services cloud environment. The network consists of about 1200 sensors located mainly in the Los Angeles basin...
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