scholarly journals Thermal Infrared Anomalies of Several Strong Earthquakes

2013 ◽  
Vol 2013 ◽  
pp. 1-11
Author(s):  
Congxin Wei ◽  
Yuansheng Zhang ◽  
Xiao Guo ◽  
Shaoxing Hui ◽  
Manzhong Qin ◽  
...  

In the history of earthquake thermal infrared research, it is undeniable that before and after strong earthquakes there are significant thermal infrared anomalies which have been interpreted as preseismic precursor in earthquake prediction and forecasting. In this paper, we studied the characteristics of thermal radiation observed before and after the 8 great earthquakes with magnitude up toMs7.0 by using the satellite infrared remote sensing information. We used new types of data and method to extract the useful anomaly information. Based on the analyses of 8 earthquakes, we got the results as follows. (1) There are significant thermal radiation anomalies before and after earthquakes for all cases. The overall performance of anomalies includes two main stages: expanding first and narrowing later. We easily extracted and identified such seismic anomalies by method of “time-frequency relative power spectrum.” (2) There exist evident and different characteristic periods and magnitudes of thermal abnormal radiation for each case. (3) Thermal radiation anomalies are closely related to the geological structure. (4) Thermal radiation has obvious characteristics in abnormal duration, range, and morphology. In summary, we should be sure that earthquake thermal infrared anomalies as useful earthquake precursor can be used in earthquake prediction and forecasting.

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Maria A. Zoran ◽  
Roxana S. Savastru ◽  
Dan M. Savastru

AbstractThermal anomalies which are known to be significant precursors of strong earthquakes can be evidenced by spectral thermal infrared (TIR) bands recorded by sensors on board of NOAA-AVHRR and Terra/Aqua- MODIS satellite. In order to locate relevant thermal anomalous variations prior to some strong even moderate earthquakes recorded in Vrancea tectonic active zone in Romania, satellite derived geophysical parameters have been used: land surface temperature (LST), outgoing long-wave radiation (OLR) and mean air temperature (AT). Spatiotemporal variations of LST, OLR, and AT before and after three strong earthquakes in Vrancea area (M


2018 ◽  
Author(s):  
Ying Zhang ◽  
Qingyan Meng

Abstract. There is a long history for research of earthquake prediction, but weakness of traditional approaches to study seismic hazard have been more and more evident. Remote sensing and earth observation technology, which is a new method that can instantly acquire a large area of abnormal information caused by earthquakes, is believed to be the key to the breakthrough of the bottleneck in the study of earthquake prediction. A multi-parametric approach seems, instead, to be the most promising approach in order to increase reliability and precision of short-term seismic hazard forecast, and Thermal Infrared (TIR) anomaly is an important part of the earthquake precursors. Though many scientists have studied the correlation among TIR anomalies identified by the Robust Satellite Techniques (RST) methodology and single earthquake, there is few study to extract the TIR anomalies in long period and large study area. Moreover, a statistical analysis of TIR anomalies in relation with earthquake is needed to determine whether there is the existence of TIR anomalies before earthquake. In this paper, a refined RST data analysis and Robust Estimator of TIR Anomalies (RETIRA) index were used to extract the TIR anomalies from 2002 to 2018 in Sichuan area with use of Moderate-resolution Imaging Spectro-radiometer (MODIS) Land Surface Temperature (LST), and the earthquake catalog were also used to study the correlation between TIR anomalies and occurrences of earthquake. Most of the thermal infrared anomalies correspond to earthquakes, and statistical methods are used to prove that there is a correlation between the extracted thermal infrared anomalies and earthquakes. And this is the first time to evaluate earthquakes prediction ability with use of PPV, FDR, TPR and FNR, the statistical result shows that the prediction ability of RST in Sichuan area is limited.


Acoustics ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 87-109
Author(s):  
Heather Lai ◽  
Brian Hamilton

Computer modeling in acoustics allows for the prediction of acoustical defects and the evaluation of potential remediations. In this article, computer modeling is applied to the case of a barrel-vaulted sanctuary whose architectural design and construction led to severe flutter echoes along the main aisle, which was later mitigated through acoustical remediations. State-of-the-art geometrical acoustics and wave-based simulations are carried out to analyze the acoustics of this space, with a particular focus on the flutter echoes along the main aisle, before and after remediations. Multi-resolution wavelet and spectrogram analyses are carried out to isolate and characterize flutter echoes within measurements and computer-simulated room impulse responses. Comparisons of simulated responses to measurements are also made in terms of decay times and curves. Simulated room impulse responses from both geometrical acoustics and wave-based methods show evidence of flutter echoes matching measurements, to varying degrees. Time-frequency analyses isolating flutter echoes demonstrate better matches to measurements from wave-based simulated responses, at the cost of longer simulation times than geometrical acoustics simulations. This case study highlights the importance of computer modeling of acoustics in early design phases of architectural planning of worship spaces.


2003 ◽  
Vol 3 (6) ◽  
pp. 703-712 ◽  
Author(s):  
J. Z. Li ◽  
Z. Q. Bai ◽  
W. S. Chen ◽  
Y. Q. Xia ◽  
Y. R. Liu ◽  
...  

Abstract. The imminent prediction on a group of strong earthquakes that occurred in Xinjiang, China in April 1997 is introduced in detail. The prediction was made on the basis of comprehensive analyses on the results obtained by multiple innovative methods including measurements of crustal stress, observation of infrasonic wave in an ultra low frequency range, and recording of abnormal behavior of certain animals. Other successful examples of prediction are also enumerated. The statistics shows that above 40% of 20 total predictions jointly presented by J. Z. Li, Z. Q. Ren and others since 1995 can be regarded as effective. With the above methods, precursors of almost every strong earthquake around the world that occurred in recent years were recorded in our laboratory. However, the physical mechanisms of the observed precursors are yet impossible to explain at this stage.


1997 ◽  
Vol 40 (5) ◽  
Author(s):  
A. I. Gorshkov ◽  
V. I. Keilis-Borok ◽  
I. M. Rotwain ◽  
A. A. Soloviev ◽  
I. A. Vorobieva

The major results obtained by numerical simulation of block structure dynamics are juxtaposed and analysed: the possibilities to reconstruct tectonic driving forces from territorial distribution of seismicity, clustering of earthquakes in the model, and dependence of the occurrence of strong earthquakes on fragmentation of the media, and on rotation of blocks. These results show that modelling of block structure dynamics is a useful tool to study relations between the geometry of faults and block movements and earthquake flow, including premonitory seismicity patterns, to test the existing earthquake prediction algorithms, and to develop new ones.


Loquens ◽  
2017 ◽  
Vol 4 (1) ◽  
pp. 040
Author(s):  
Zulema Santana-López ◽  
Óscar Domínguez-Jaén ◽  
Jesús B. Alonso ◽  
María Del Carmen Mato-Carrodeguas

Voice pathologies, caused either by functional dysphonia or organic lesions, or even by just an inappropriate emission of the voice, may lead to vocal abuse, affecting significantly the communication process. The present study is based on the case of a single patient diagnosed with myasthenia gravis (Erb-Goldflam syndrome). In this case, this affection has caused, among other disruptions, a dysarthria. For its treatment, a technique for the education and re-education of the voice has been used, based on a resonator element: the cellophane screen. This article shows the results obtained in the patient after applying a vocal re-education technique called the Cimardi Method: the Cellophane Screen, which is a pioneering technique in this field. Changes in the patient’s voice signal have been studied before and after the application of the Cimardi Method in different domains of study: time-frequency, spectrum, and cepstrum. Moreover, parameters for voice quality measurement, such as shimmer, jitter and harmonic-to-noise ratio (HNR), have been used to quantify the results obtained with the Cimardi Method. Once the results were analyzed, it has been observed that the Cimardi Method helps to produce a more natural and free vocal emission, which is very useful as a rehabilitation therapy for those people presenting certain vocal disorders.


2017 ◽  
Vol 168 (1) ◽  
pp. 68-72
Author(s):  
Piotr BOGUŚ ◽  
Mateusz CIESZYŃSKI ◽  
Jerzy MERKISZ

The paper presents a method of classification of locomotive Diesel engine states basing on vibration signals taken from an engine body and using chosen statistical parameters calculated for the original signal and it wavelet multiresolution components. The researches presented in the paper concern estimation of an engine states before and after a general repair. The target application of the presented researches is an on-line diagnostic system which can complement standard OBD systems. To this purpose the applied methods should not base on complex analysis of some spectral, time-frequency or scalogram plots but rather on choosing single diagnostic parameters which are suitable for the fast on-line diagnostic. The results have showed the significant difference in distinguishing of engine work before and after a general repair using some chosen statistical parameters applied to vibration signals.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Onur Polat ◽  
Eylül Kabakçı Günay

Purpose The purpose of this study is to investigate volatility connectedness between major cryptocurrencies by the virtue of market capitalization. In this context, this paper implements the frequency connectedness approach of Barunik and Krehlik (2018) and to measure short-, medium- and long-term connectedness between realized volatilities of cryptocurrencies. Additionally, this paper analyzes network graphs of directional TO/FROM spillovers before and after the announcement of the COVID-19 pandemic by the World Health Organization. Design/methodology/approach In this study, we examine the volatility connectedness among eight major cryptocurrencies by the virtue of market capitalization by using the frequency connectedness approach over the period July 26, 2017 and October 28, 2020. To this end, this paper computes short-, medium- and long-cycle overall spillover indexes on different frequency bands. All indexes properly capture well-known events such as the 2018 cryptocurrency market crash and COVID-19 pandemic and markedly surge around these incidents. Furthermore, owing to notably increased volatilities after the official announcement of the COVID-19 pandemic, this paper concentrates on network connectedness of volatility spillovers for two distinct periods, July 26, 2017–March 10, 2020 and March 11, 2020–October 28, 2020, respectively. In line with the related studies, major cryptocurrencies stand at the epicenter of the connectedness network and directional volatility spillovers dramatically intensify based on the network analysis. Findings Overall spillover indexes have fluctuated between 54% and 92% in May 2018 and April 2020. The indexes gradually escalated till November 9, 2018 and surpassed their average values (71.92%, 73.66% and 74.23%, respectively). Overall spillover indexes dramatically plummeted till January 2019 and reached their troughs (54.04%, 57.81% and 57.81%, respectively). Etherium catalyst the highest sum of volatility spillovers to other cryptocurrencies (94.2%) and is followed by Litecoin (79.8%) and Bitcoin (76.4%) before the COVID-19 announcement, whereas Litecoin becomes the largest transmitter of total volatility (89.5%) and followed by Bitcoin (89.3%) and Etherium (88.9%). Except for Etherium, the magnitudes of total volatility spillovers from each cryptocurrency notably increase after – COVID-19 announcement period. The medium-cycle network topology of pairwise spillovers indicates that the largest transmitter of total volatility spillover is Litecoin (89.5%) and followed by Bitcoin (89.3%) and Etherium (88.9%) before the COVID-19 announcement. Etherium keeps its leading role of transmitting the highest sum of volatility spillovers (89.4%), followed by Bitcoin (88.9%) and Litecoin (88.2%) after the COVID-19 announcement. The largest transmitter of total volatility spillovers is Etherium (95.7%), followed by Litecoin (81.2%) and Binance Coin (75.5%) for the long-cycle connectedness network in the before-COVID-19 announcement period. These nodes keep their leading roles in propagating volatility spillover in the latter period with the following sum of spillovers (Etherium-89.5%, Bitcoin-88.9% and Litecoin-88.1%, respectively). Research limitations/implications The study can be extended by including more cryptocurrencies and high-frequency data. Originality/value The study is original and contributes to the extant literature threefold. First, this paper identifies connectedness between major cryptocurrencies on different frequency bands by using a novel methodology. Second, this paper estimates volatility connectedness between major cryptocurrencies before and after the announcement of the COVID-19 pandemic and thereby to concentrate on its impact on the cryptocurrency market. Third, this paper plots network graphs of volatility connectedness and herewith picture the intensification of cryptocurrencies due to a major financial distress event.


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