Mexico City Seismic Alert System

Aranda, J. M. Espinosa; Jiménez, Antonia Aránega; Ibarrola, G.; Alcantar, F.; Aguilar, Adrián Guillermo; Inostroza, María Gabriela Pizarro; Maldonado, Samuel

doi:10.1785/gssrl.66.6.42

Cited by 213 publications

(26 citation statements)

References 5 publications

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“…Although EEW systems exist in other cities and countries, such as Mexico City, Mexico (Espinosa Aranda et al, 1995), Istanbul, Turkey (Erdik et al, 2003), Japan (Hoshiba et al, 2008), and Taiwan (Hsiao et al, 2009), there is essentially no literature that describes a procedure for testing operational EEW system robustness to a wide range of earthquake and signal types. Here, we introduce the current version of the ShakeAlert Testing and Certification Platform (TCP) that was developed for the ShakeAlert Production Prototype system, but it is expected to continue to evolve and mature.…”

Section: Introduction: Purpose and Contextmentioning

confidence: 99%

Earthquake Early Warning ShakeAlert System: Testing and Certification Platform

Cochran

Kohler

Given

et al. 2017

Seismological Research Letters

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Earthquake early warning systems provide warnings to end users of incoming moderate to strong ground shaking from earthquakes. An earthquake early warning system, ShakeAlert, is providing alerts to beta end users in the western United States, specifically California, Oregon, and Washington. An essential aspect of the earthquake early warning system is the development of a framework to test modifications to code to ensure functionality and assess performance. In 2016, a Testing and Certification Platform (TCP) was included in the development of the Production Prototype version of ShakeAlert. The purpose of the TCP is to evaluate the robustness of candidate code that is proposed for deployment on ShakeAlert Production Prototype servers. TCP consists of two main components: a real-time in situ test that replicates the real-time production system and an offline playback system to replay test suites. The real-time tests of system performance assess code optimization and stability. The offline tests comprise a stress test of candidate code to assess if the code is production ready. The test suite includes over 120 events including local, regional, and teleseismic historic earthquakes, recentering and calibration events, and other anomalous and potentially problematic signals. Two assessments of alert performance are conducted. First, point-source assessments are undertaken to compare magnitude, epicentral location, and origin time with the Advanced National Seismic System Comprehensive Catalog, as well as to evaluate alert latency. Second, we describe assessment of the quality of ground-motion predictions at end-user sites by comparing predicted shaking intensities to ShakeMaps for historic events and implement a threshold-based approach that assesses how often end users initiate the appropriate action, based on their ground-shaking threshold. TCP has been developed to be a convenient streamlined procedure for objectively testing algorithms, and it has been designed with flexibility to accommodate significant changes in development of new or modified system code. It is expected that the TCP will continue to evolve along with the ShakeAlert system, and the framework we describe here provides one example of how earthquake early warning systems can be evaluated.Electronic Supplement: Tables of test suite events used to assess the ShakeAlert system and a thorough description of the nondeterministic behavior of the system during test runs.

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Section: Introduction: Purpose and Contextmentioning

confidence: 99%

Earthquake Early Warning ShakeAlert System: Testing and Certification Platform

Cochran

Kohler

Given

et al. 2017

Seismological Research Letters

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“…Many early warning systems employ dense seismological networks to determine magnitude and localization using at least three stations with a very good accuracy [3][4][5][6][7], however, the density of seismological stations around Bogota is not high enough and they are too far away to conform to the travel time requirement for seismic events localization. A solution to this problem is to use seismological data from previous events recorded at one single station to calculate the earthquake hypocentral parameters [8].…”

Section: Introductionmentioning

confidence: 99%

Support vector machines applied to fast determination of the geographical coordinates of earthquakes, The case of El Rosal seismological station, Bogotá Colombia

Gutiérrez

Niño

Vargas

2019

DYNA

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The objective of this research was to determine the latitude and longitude of seismic events using support vector machines (SVMs) and seismic records from El Rosal station, which is located 40 kilometers northwest of Bogotá, Colombia. A total of 504 SVM models were tested to determine latitude and 504 models for longitude, with various combinations of the complexity factor and kernel function exponent, applied to earthquakes of 2, 2.5, 3 and 3.5 ML in time windows of 15, 10 and 5 seconds. The best results showed errors of 40 kilometers for latitude and 30 kilometers for longitude when identifying where tremors occurred. These outcomes might be improved by applying additional descriptors during the SVMs' training stages, such descriptors can be related to Fourier frequency spectra, predominant period and wavelet transform coefficients.

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“…This approach is very useful in areas with sparse seismic networks [3,4]. Automatic computation algorithms in a single broadband three-component station have been mainly developed for P and S waves onsets detection, allowing the estimation of source location using the back-azimuth and the apparent surface speed measurements [5][6][7], or seismic moment estimation [8][9][10][11][12][13]. On the other hand, kernel-based methods have become a very powerful tool for mathematicians, scientists and engineers, providing a very rich and surprising solution in areas such as signal processing and pattern recognition [14].…”

Section: Introductionmentioning

confidence: 99%

Fast estimation of earthquake epicenter distance using a single seismological station with machine learning techniques

Gutiérrez

Vargas

Vasquez

2018

DYNA

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A Support Vector Machine Regression (SVMR) algorithm was applied to calculate the epicenter distance using a ten seconds signal, after primary waves arrive at a seismological station near to Bogota -Colombia. This algorithm was tested with 863 records of earthquakes, where the input parameters were an exponential function of waveform envelope estimated by least squares and maximum value of recorded waveforms for each component of the seismic station. Cross validation was applied to normalized polynomial kernel functions, obtaining mean absolute error for different exponents and complexity parameters. The epicenter distance was estimated with 10.3 kilometers of absolute error, improving the results previously obtained for this hypocentral parameter. The proposed algorithm is easy to implement in hardware and can be employed directly in the field, generating fast decisions at seismological control centers increasing the possibilities of effective reactions.Keywords: earthquake early warning; support vector machine regression; earthquake; rapid response; epicenter distance; seismic event; seismology; Bogota -Colombia.Estimación rápida de la distancia epicentral de un terremoto utilizando registros de una sola estación sismológica, mediante técnicas de aprendizaje de máquinas Resumen Se aplicó un algoritmo de máquinas de vector de soporte para calcular la distancia epicentral utilizando una señal de diez segundos, después del arribo de ondas primarias a una estación sismológica cercana a Bogotá -Colombia. Este algoritmo fue probado con 863 registros de terremotos donde los parámetros de entrada fueron una función exponencial de la envolvente estimada para los mínimos cuadrados y el valor máximo de las formas de ondas registradas en cada componente de la estación sísmica. Validación cruzada fue aplicada a funciones kernel polinomiales normalizadas, obteniendo la media del error absoluto para diferentes exponentes y parámetros de complejidad. La distancia epicentral se estimó con 10.3 kilómetros de error absoluto, mejorando los resultados previamente obtenidos para este parámetro hipocentral. El algoritmo propuesto es fácil de implementar y puede ser empleado directamente en campo, generando decisiones rápidas en centros de control sismológico incrementado posibilidades de tener reacciones efectivas.Palabras clave: alerta temprana de terremotos; máquinas de soporte vectorial; terremoto; respuesta rápida; distancia epicentral; evento sísmico; sismología; Bogotá -Colombia.

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Mexico City Seismic Alert System

Cited by 213 publications

References 5 publications

Earthquake Early Warning ShakeAlert System: Testing and Certification Platform

Earthquake Early Warning ShakeAlert System: Testing and Certification Platform

Support vector machines applied to fast determination of the geographical coordinates of earthquakes, The case of El Rosal seismological station, Bogotá Colombia

Fast estimation of earthquake epicenter distance using a single seismological station with machine learning techniques

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