scholarly journals An automated local and regional seismic event detection and location system using waveform correlation

1999 ◽  
Vol 89 (3) ◽  
pp. 657-669 ◽  
Author(s):  
Mitchell Withers ◽  
Richard Aster ◽  
Christopher Young
Keyword(s):  
New Mexico ◽  
Event Detection ◽  
Detection System ◽  
Grid Point ◽  
Matrix Multiplication ◽  
Phase Identification ◽  
Time Step ◽  
Location System ◽  
Ctbt Monitoring ◽  
Mexico Tech

Abstract We report on the development of an automated Local Waveform Correlation Event Detection System (LWCEDS) and its application to the New Mexico Tech Seismic Network. LWCEDS is an adaptation of a global system, WCEDS, a matched filtering algorithm for global Comprehensive Test Ban Treaty (CTBT) monitoring applications developed at Sandia National Laboratories and New Mexico Tech. Although the current CTBT monitoring system is based on teleseismic phase detection, effort is being placed on research to highlight specific areas of the globe for which local and regional seismic networks could be employed. An automated waveform correlation regional location system could also serve as a rapid alert and automated location system by providing magnitude and hypocenter information within a few minutes of the occurrence of a hazardous earthquake. In the LWCEDS algorithm, processed waveforms are correlated with theoretical travel-time envelopes, and a grid search is performed to identify the space-time solutions that yield the highest correlations. High correlation indicates that an event has occurred and that a good approximation to the correct origin time and hypocenter has been determined; explicit phase identification is not required. To avoid the large computational expense of calculating a complete correlation for each grid point, we use a laterally homogeneous velocity model and reformulate the problem into a single matrix multiplication and matrix assessment for each time step. LWCEDS has been successfully tested on a suite of local and regional seismic events selected to span the range of expected event quality. Preliminary results from our sparse network show typical epicentral errors of less than 3 km for local events and, with notable exceptions, to within 10 to 20 km for regional events. Similar results were obtained during an on-line experiment conducted to generate daily bulletins during the time period from 3 December 1996 through 7 January 1997. Data from 156 triggers were processed, including 33 teleseisms, 102 regional events (includes explosions), and 21 local earthquakes. Results from this expanded test set are encouraging but reveal the need for a method to mask or flag various electronic and telemetry spikes.

scholarly journals Real-time spatio-temporal event detection on geotagged social media

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yasmeen George ◽  
Shanika Karunasekera ◽  
Aaron Harwood ◽  
Kwan Hui Lim
Keyword(s):  
New York ◽  
Social Media ◽  
Event Detection ◽  
Detection System ◽  
Time And Space ◽  
Social Media Data ◽  
Event Time ◽  
Spatio Temporal ◽  
Geographical Space ◽  
Media Data

AbstractA key challenge in mining social media data streams is to identify events which are actively discussed by a group of people in a specific local or global area. Such events are useful for early warning for accident, protest, election or breaking news. However, neither the list of events nor the resolution of both event time and space is fixed or known beforehand. In this work, we propose an online spatio-temporal event detection system using social media that is able to detect events at different time and space resolutions. First, to address the challenge related to the unknown spatial resolution of events, a quad-tree method is exploited in order to split the geographical space into multiscale regions based on the density of social media data. Then, a statistical unsupervised approach is performed that involves Poisson distribution and a smoothing method for highlighting regions with unexpected density of social posts. Further, event duration is precisely estimated by merging events happening in the same region at consecutive time intervals. A post processing stage is introduced to filter out events that are spam, fake or wrong. Finally, we incorporate simple semantics by using social media entities to assess the integrity, and accuracy of detected events. The proposed method is evaluated using different social media datasets: Twitter and Flickr for different cities: Melbourne, London, Paris and New York. To verify the effectiveness of the proposed method, we compare our results with two baseline algorithms based on fixed split of geographical space and clustering method. For performance evaluation, we manually compute recall and precision. We also propose a new quality measure named strength index, which automatically measures how accurate the reported event is.

A comparison of select trigger algorithms for automated global seismic phase and event detection

1998 ◽  
Vol 88 (1) ◽  
pp. 95-106 ◽  
Author(s):  
Mitchell Withers ◽  
Richard Aster ◽  
Christopher Young ◽  
Judy Beiriger ◽  
Mark Harris ◽  
...  
Keyword(s):  
Real Time ◽  
Data Streams ◽  
Event Detection ◽  
Spectral Characteristics ◽  
Digital Data ◽  
Robust Detection ◽  
Location System ◽  
Global Correlation ◽  
Seismic Coda ◽  
Wide Range

Abstract Digital algorithms for robust detection of phase arrivals in the presence of stationary and nonstationary noise have a long history in seismology and have been exploited primarily to reduce the amount of data recorded by data logging systems to manageable levels. In the present era of inexpensive digital storage, however, such algorithms are increasingly being used to flag signal segments in continuously recorded digital data streams for subsequent processing by automatic and/or expert interpretation systems. In the course of our development of an automated, near-real-time, waveform correlation event-detection and location system (WCEDS), we have surveyed the abilities of such algorithms to enhance seismic phase arrivals in teleseismic data streams. Specifically, we have considered envelopes generated by energy transient (STA/LTA), Z-statistic, frequency transient, and polarization algorithms. The WCEDS system requires a set of input data streams that have a smooth, low-amplitude response to background noise and seismic coda and that contain peaks at times corresponding to phase arrivals. The algorithm used to generate these input streams from raw seismograms must perform well under a wide range of source, path, receiver, and noise scenarios. Present computational capabilities allow the application of considerably more robust algorithms than have been historically used in real time. However, highly complex calculations can still be computationally prohibitive for current workstations when the number of data streams become large. While no algorithm was clearly optimal under all source, receiver, path, and noise conditions tested, an STA/LTA algorithm incorporating adaptive window lengths controlled by nonstationary seismogram spectral characteristics was found to provide an output that best met the requirements of a global correlation-based event-detection and location system.

An Impact Event Detection System for Composite Box Structures

2020 ◽  
pp. 1063-1073
Author(s):  
Vafa Soltangharaei ◽  
Rafal Anay ◽  
Deepak Begrajka ◽  
Matthijs Bijman ◽  
Mohamed Khaled ElBatanouny ◽  
...  
Keyword(s):  
Event Detection ◽  
Detection System ◽  
Impact Event ◽  
Box Structures

scholarly journals Version 2 of the EUMETSAT OSI SAF and ESA CCI Sea Ice Concentration Climate Data Records

2018 ◽  
Author(s):  
Thomas Lavergne ◽  
Atle Macdonald Sørensen ◽  
Stefan Kern ◽  
Rasmus Tonboe ◽  
Dirk Notz ◽  
...  
Keyword(s):  
Sea Ice ◽  
Satellite Data ◽  
Grid Point ◽  
Ice Cover ◽  
Quantitative Information ◽  
Horizontal Resolution ◽  
Climate Data ◽  
Time Step ◽  
Sea Ice Concentration ◽  
Ice Concentration

Abstract. We introduce the OSI-450, the SICCI-25km and the SICCI-50km climate data records of gridded global sea-ice concentration. These three records are derived from passive microwave satellite data and offer three distinct advantages compared to existing records: First, all three records provide quantitative information on uncertainty and possibly applied filtering at every grid point and every time step. Second, they are based on dynamic tie points, which capture the time evolution of surface characteristics of the ice cover and accommodate potential calibration differences between satellite missions. Third, they are produced in the context of sustained services offering committed extension, documentation, traceability, and user support. The three records differ in the underlying satellite data (SMMR & SSM/I & SSMIS or AMSR-E & AMSR2), in the imaging frequency channels (37 GHz and either 6 GHz or 19 GHz), in their horizontal resolution (25 km or 50 km) and in the time period they cover. We introduce the underlying algorithms and provide an initial evaluation. We find that all three records compare well with independent estimates of sea-ice concentration both in regions with very high sea-ice concentration and in regions with very low sea-ice concentration. We hence trust that these records will prove helpful for a better understanding of the evolution of the Earth's sea-ice cover.

Graduate programs at New Mexico Tech

BIOS ◽  
2021 ◽  
Vol 91 (4) ◽  
Author(s):  
Linda DeVeaux
Keyword(s):  
New Mexico ◽  
Graduate Programs ◽  
Mexico Tech

scholarly journals Pickless Event Detection and Location: The Waveform Correlation Event‐Detection System (WCEDS) Revisited

2016 ◽  
Vol 106 (5) ◽  
pp. 2037-2044 ◽  
Author(s):  
Stephen Arrowsmith ◽  
Christopher Young ◽  
Sanford Ballard ◽  
Megan Slinkard ◽  
Kristine Pankow
Keyword(s):  
Event Detection ◽  
Detection System
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