Regional Seismic Signals from Chemical Explosions, Nuclear Explosions and Earthquakes: Results from the Arizona Source Phenomenology Experiment

Walter, William R.; Gök, R.; Mayeda, Kevin; Sicherman, A.; Bonner, Jessie L.; Leidig, Mark

doi:10.2172/877819

Cited by 2 publications

(4 citation statements)

References 17 publications

(14 reference statements)

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“…The location of these tests has not been formally released. Barker et al [5] estimated a yield of 4-6 kT, while Walter [4] estimated a yield of 3-11 kT. Using Barker's coordinates for the May 30th test as the center of imagery, two regions of interest were found as shown in Figs.…”

Section: B Pakistani Test May 30 1998mentioning

confidence: 99%

“…A closer look with high-resolution panchromatic Worldview-I or Quickbird imagery shows the area has evidence of bull dozing, several buildings, and a fence around the south eastern area, making it unclear whether the changes are from a UNE or human activity. May 11, 1998 On May 11, 1998, India claims to have detonated three devices simultaneously in underground shafts located beneath the Khetolai Military Range [4]. Coordinates provided by the CTBTO's Prototype International Data Center Reviewed Event Bulletin are (27.0716N, 71.7612E) [18].…”

Section: B Pakistani Test May 30 1998mentioning

confidence: 99%

“…There is extensive published work on the locations of the 1998 nuclear tests that occurred in India and Pakistan. Several authors [4]- [6] have demonstrated the use of seismic techniques to determine the approximate locations of these tests. Pabian and van Genderen [7] demonstrated a multisource data integration approach for locating the test site used by the Pakistanis on May 28, 1998.…”

Section: Introductionmentioning

confidence: 99%

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Use of Landsat 5 for Change Detection at 1998 Indian and Pakistani Nuclear Test Sites

Zelinski

Henderson

Smith

2014

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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An underground nuclear explosion (UNE) can generate a shock wave that lofts surface material, resulting in surface changes that might be detectable. The Comprehensive Nuclear Test-Ban Treaty (CTBT) allows ground and airborne spectral and thermal imaging to help locate such events. Landsat 5 data on the 1998 Indian and Pakistani tests are used here to demonstrate that there are detectable changes in surface features which might be used to localize an underground nuclear test and to develop change detection techniques specific to the use of satellite data to support a CTBT on-site inspection. Landsat 5 has been active for over 20 years providing repeat coverage of the Earth's surface every 16 days. Most locations have Landsat data available for a variety of dates, allowing for statistical analysis of the data to understand temporal trends and data variability on a pixel-by-pixel basis. Given the right conditions, these usual patterns of change (such as seasonal changes or weathering) can be discerned from unusual patterns of change, such as features relating to a UNE. This paper extends known change detection techniques to a temporal series of data and shows that multispectral change detection can be used to help localize a UNE.

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Section: B Pakistani Test May 30 1998mentioning

confidence: 99%

Section: B Pakistani Test May 30 1998mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Use of Landsat 5 for Change Detection at 1998 Indian and Pakistani Nuclear Test Sites

Zelinski

Henderson

Smith

2014

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…One area of particular activity in this field is the observation and identification of natural earthquakes and nuclear explosions. Extensive research on regional earthquake event identification has shown that the spectral amplitude ratio of P-waves and S-waves, known as P/S ratio, is an effective method for distinguishing earthquakes from underground nuclear explosions [1][2][3] . Subsequently, the development of Magnitude and Distance Amplitude Correction (MADC) techniques has been used to refine the P/S discriminant [4][5][6] .…”

Section: Introductionmentioning

confidence: 99%

Research on the seismic signal classification algorithm based on SE-DenseNet

Wang,

Huang,

Ding

2024

Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023)

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Addressing the issue of seismic signal classification and recognition for natural earthquakes and artificial blasting, a deep learning model suitable for seismic signal classification and recognition is proposed. In this study, a dataset is created by selecting 14,001 natural earthquake waveforms and 12,870 artificial blasting waveforms from the seismic waveform data provided by the China National Earthquake Science Data Sharing Centre for the years 2010-2016. Based on the DenseNet architecture, an attention mechanism is introduced into the original Dense Block, adaptively enhancing valuable feature channels, thereby improving the model's perception and expression capabilities for important information. The model achieves an accuracy of 96.25% on the test set, surpassing the compared methods. Experimental results demonstrate that the attention-enhanced DenseNet exhibits excellent classification effectiveness and generalization ability when applied to seismic signals.

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Regional Seismic Signals from Chemical Explosions, Nuclear Explosions and Earthquakes: Results from the Arizona Source Phenomenology Experiment

Cited by 2 publications

References 17 publications

Use of Landsat 5 for Change Detection at 1998 Indian and Pakistani Nuclear Test Sites

Use of Landsat 5 for Change Detection at 1998 Indian and Pakistani Nuclear Test Sites

Research on the seismic signal classification algorithm based on SE-DenseNet

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