Analysis of seismic noise in the Romanian-Bulgarian cross-border region

Grecu, Bogdan; Neagoe, Cristian; Tǎtaru, Dragoș; Borleanu, Felix; Zaharia, Bogdan

doi:10.1007/s10950-018-9767-4

Cited by 6 publications

(4 citation statements)

References 36 publications

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“…However, recent studies that have focused on the analysis of urban seismic noise variations provided insights into the sources responsible for generating seismic noise in different frequency bands. Road traffic has an important contribution to the seismic noise wave field in various frequency bands, such as 2-9 and 10-20 Hz (Dias et al, 2020), 2.5-10 Hz (Green et al, 2017), 8-35 Hz (Boese et al, 2015, and 8-12 Hz (Diaz et al, 2017). Overground and subway trains generate seismic noise at very low frequencies (∼ 0.01-0.05 Hz) (Sheen et al, 2009;Diaz et al, 2017;Green et al, 2017) and at high frequencies (20-40 Hz) (Diaz et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

“…Road traffic has an important contribution to the seismic noise wave field in various frequency bands, such as 2-9 and 10-20 Hz (Dias et al, 2020), 2.5-10 Hz (Green et al, 2017), 8-35 Hz (Boese et al, 2015, and 8-12 Hz (Diaz et al, 2017). Overground and subway trains generate seismic noise at very low frequencies (∼ 0.01-0.05 Hz) (Sheen et al, 2009;Diaz et al, 2017;Green et al, 2017) and at high frequencies (20-40 Hz) (Diaz et al, 2017). Furthermore, industrial activities can also contribute to the seismic noise spectra in the 1-25 and 25-40 Hz bands (Groos and Ritter, 2009).…”

Section: Discussionmentioning

confidence: 99%

“…In urban areas, road traffic, the underground and surface transportation system (tram, train), and industry represent the most important noise sources responsible for generating high-frequency anthropogenic vibrations (Long, 1971;Green et al, 2017). These sources are different from one city to another and even can vary within cities.…”

Section: Free-field Stationsmentioning

confidence: 99%

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The effect of 2020 COVID-19 lockdown measures on seismic noise recorded in Romania

et al. 2021

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Abstract. After the World Health Organization declared COVID-19 a pandemic in March 2020, Romania followed the example of many other countries and imposed a series of restrictive measures, including restricting people's mobility and closing social, cultural, and industrial activities to prevent the spread of the disease. In this study, we analyze continuous vertical component recordings from the stations of the Romanian Seismic Network – one of the largest networks in Europe, consisting of 148 stations – to explore the seismic noise variation associated with the reduced human mobility and activity due to the Romanian measures against COVID-19 in detail. We focused our investigation on four frequency bands – 2–8, 4–14, 15–25 and 25–40 Hz – and found that the largest reductions in seismic noise associated with the lockdown correspond to the high-frequency range of 15–40 Hz. We found that all the stations with large reductions in seismic noise (>∼ 40 %) are located inside and near schools or in buildings, indicating that at these frequencies the drop is related to the drastic reduction of human activity in these edifices. In the lower-frequency range (2–8 and 4–14 Hz) the variability of the noise reduction among the stations is lower than in the high-frequency range, corresponding to about 35 % on average. This drop is due to reduced traffic during the lockdown, as most of the stations showing such changes in seismic noise in these bands are located within cities and near main or side streets. In addition to the noise reduction observed at stations located in populated areas, we also found seismic noise lockdown-related changes at several stations located far from urban areas, with movement of people in the vicinity of the station explaining the noise reductions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Free-field Stationsmentioning

confidence: 99%

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The effect of 2020 COVID-19 lockdown measures on seismic noise recorded in Romania

et al. 2021

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“…Seismometer monitoring and evaluation activities at the InaTEWS are carried out through a seismometer sensor calibration system using the Seismic Data Quality Analysis software or known as SQLX [1]. SQLX software produces digital images in the form of power spectrum density, also known as Power Spectral Density (PSD), and probability density, also called Probability Density Function (PDF), derived from seismometer measurements [2][3]. The digital image can describe the condition of the seismometer that operates following the spectrum result.…”

Section: Introductionmentioning

confidence: 99%

Seismic Data Quality Analysis Based on Image Recognition Using Convolutional Neural Network

2022

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Seismometer monitoring and evaluation activities at the Indonesia Tsunami Early Warning System (InaTEWS) station can be carried out through a seismometer sensor calibration system with the use of the software of Seismic Data Quality Analysis. The software output is in the form of a spectrum image that represents the conditions of the seismometer following the spectrum results. The identification of the seismometer condition can be made by pattern recognition in the spectrum image. This study employed a neural network, specifically the Convolutional Neural Network (CNN), to analyse the pattern condition. The test results show that the performance of the system will be excellent if 1024 hidden layers are used. In addition, the epoch test shows that the system works well when given a maximum epoch value of 50. The test of image size gives the result that the system performance will result in good using input with a size of 30x20 pixels. The final results of the classification of spectrum images using CNN will exhibit the identification of seismometer. For the validation, the confusion matrix test shows that the corresponding findings are 80%, while the conflicting results are 20%.

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Estimating Geophysical Bedrock Depth Using Single Station Analysis and Geophysical Data in the Extra-Carpathian Area of Romania

Manea

Cioflan

Coman

et al. 2020

Pure Appl. Geophys.

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Analysis of seismic noise in the Romanian-Bulgarian cross-border region

Cited by 6 publications

References 36 publications

The effect of 2020 COVID-19 lockdown measures on seismic noise recorded in Romania

The effect of 2020 COVID-19 lockdown measures on seismic noise recorded in Romania

Seismic Data Quality Analysis Based on Image Recognition Using Convolutional Neural Network

Estimating Geophysical Bedrock Depth Using Single Station Analysis and Geophysical Data in the Extra-Carpathian Area of Romania

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