This study presents geophysical data from two passive seismic measurements conducted at two different sites in Antarctica. We analyzed the signals mainly in the frequency domain through the multitaper method to extract some spectral characteristics of the signals that would have been out of reach through the usual FFT approach. The power spectral density of the signals carries information about the processes that generated them, allowing its correlation with their source origin and type, either natural or anthropogenic. We deal with three different source types: calving, wind, and anthropogenic origins. The former is closely related to glacier dynamics, being modulated by the prevailing atmospheric processes. At both locations the wind noise is prevalent, complicating the analysis of other events like calving. We have used data classification, estimation of the source azimuth, and seismic apparent velocity to demonstrate the viability of using geophysical methods to study glacier elastic parameters and dynamics. Moreover, the calving rate can yield a wider and more independent understanding of glacier hydrodynamics and may help to estimate the future response of the polar areas to a changing environment.

Download full-text PDF

Source
http://dx.doi.org/10.1590/0001-3765202420230752DOI Listing

Publication Analysis

Top Keywords

natural seismic
4
seismic event
4
event analysis
4
analysis based
4
based signal
4
source
4
signal source
4
source characteristics
4
characteristics experiments
4
experiments antarctica
4

Similar Publications

Complexity measure in natural time analysis identifying the accumulation of stresses before major earthquakes.

Sci Rep

December 2024

Institute of Oceanic Research and Development, Tokai University, 3-20-1, Orido, Shimizu-ku, Shizuoka, 424-0902, Japan.

Here, we suggest a procedure through which one can identify when the accumulation of stresses before major earthquakes (EQs) (of magnitude M 8.2 or larger) occurs. Analyzing the seismicity in natural time, which is a new concept of time, we study the evolution of the fluctuations of the entropy change of seismicity under time reversal for various scales of different length i (number of events).

View Article and Find Full Text PDF

In the context of rapid urbanization, the proliferation of high-density residential zones and intricate infrastructure networks markedly amplifies a city's susceptibility to natural calamities, notably seismic events. Thus, a precise evaluation of a city's emergency capability for seismic events is imperative. This research proposes a novel and all-encompassing evaluation framework for indicators, grounded in crisis management theory, covering the entire spectrum of disaster mitigation, preparedness, response, and recovery.

View Article and Find Full Text PDF

Claims of industrially induced seismicity vary from indisputable to unpersuasive and yet the veracity of industrial induction is vital for regulatory and operational practice. Assessment schemes have been developed in response to this need. We report here an initial assessment of the reliability of all globally known cases of proposed human-induced earthquakes and invite specialists on particular cases to refine these results.

View Article and Find Full Text PDF

In Song dynasty, Dou-Gong construction techniques, Tou-Xin-Zao and Ji-Xin-Zao, varied by the number of Fang connecting to the exterior. This study examines the impact of Fang connections on the mechanical characteristics of Dou-Gong. Six full-scale models were constructed and subjected to quasi-static loading tests in the horizontal Beam and Fang directions under vertical load.

View Article and Find Full Text PDF

The accurate classification of seismic events into natural earthquakes (EQ) and quarry blasts (QB) is crucial for geological understanding, seismic hazard mitigation, and public safety. This paper proposes a machine-learning approach to discriminate seismic events, particularly differentiating between natural EQs and man-made QBs. The core of this study is to integrate different features into a unified dataset to train some linear and nonlinear supervised machine learning (ML) models.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!