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662 results for “seismicity”
Seismic Velocity Model of P- and S-waves for the Italian Lithosphere
<p>P- and S- seismic waves 3D velocity model of the Italian Lithosphere obtained by linearized seismic local earthquake tomography (LET) method by <a href="https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/92JB00603">Zhao et al., 1992</a>.</p> <p>The inversion for the model parameters is performed using a combination of pseudo-bending and Snell's Law for ray tracing on a 3D grid of nodes on spherical coordinates and the LSQR algorithm by <a href="https://dl.acm.org/doi/10.1145/355984.355989">Page and Saunders, 1982</a>. The method allows to model first order seismic discontinuities like the Moho, for which the Moho for the Italian region by <a href="https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2011GC003649">Di Stefano et al., 2011</a>.</p> <p>A previous version of the same tomographic inversion was produced and discussed in <a href="https://www.sciencedirect.com/science/article/abs/pii/S0264370714001306?via%3Dihub">Di Stefano and Ciaccio, 2014</a> but not released in digital file format.</p> <p>The present file is an updated version of the model by <a href="https://www.sciencedirect.com/science/article/abs/pii/S0264370714001306?via%3Dihub">Di Stefano and Ciaccio, 2014</a>, based on a slightly different gridding but with the same P- and S- travel-times and earthquakes locations dataset.</p> <p>The model is here released in csv, pipe (|) separated, file.</p> <p><strong>Header Explanation</strong></p> <ul> <li><strong>lon</strong>: longitude in decimal degrees positive eastward from Greenwich</li> <li><strong>lat</strong>: latitude in decimal degrees positive northward</li> <li><strong>depth</strong>: depth in km positive downward</li> <li><strong>type</strong>: type of model parameter (vp= P-wave velocity; vs= S-wave velocity)</li> <li><strong>value</strong>: seismic velocity value</li> <li><strong>units</strong>: units measure of the velocity value</li> </ul> <p>The external bounding box of the model is:</p> <ul> <li>Minimum Longitude = 5°E</li> <li>Maximum Longitude = 20°E</li> <li>Minimum Latitude = 36°N</li> <li>Maximum Latitude = 48°N</li> <li>Minumum Depth = 0 km</li> <li>Maximum Depth = 80 km</li> </ul> <p>Lines 2 to 43093 report the Vp model</p> <p>Lines 43094 to 86185 report the Vs model</p>
Evolution of coseismic and post-seismic landsliding after the 2015 Mw 7.8 Gorkha earthquake, Nepal
<p>Landslide area density grid used in the analysis of the spatial evolution of landsliding following the 2015 Mw 7.8 Gorkha earthquake in Nepal. The data include 11 epochs of landslide area density, including bi-annual assessments between 2014 and 2018 (pre- and post-monsoon), and an additional coseismic assessment from 2015. </p> <p>This research has been supported by the UKRI-DFID SHEAR program (201844-112). </p>
Application of an ensemble earthquake rate model in Italy, considering seismic catalogs and fault moment release - Models and Catalogs
<p>Models and Catalogs for "Application of an ensemble earthquake rate model in Italy, considering seismic catalogs and fault moment release" , Murru et al. 2020</p>
Stress conditions and seismic activity around the rupture zone of the 2016 Kumamoto earthquake in Kyushu, southwest Japan
<p>This archive includes the dataset for the Stress conditions and seismic activity around the rupture zone of the 2016 Kumamoto earthquake in Kyushu, southwest Japan. Most of the datasets are arranged from the JMAhypocenter data. Text and xlsx type files are included. Some "read me" files are also in folders.</p> <p> </p>
Experimental Data for "Seismic wave attenuation and dispersion due to partial fluid saturation: Direct measurements and numerical simulations based on X-Ray CT"
<p>Experimental Data from a Berea sandstone sample. Includes X-ray CT scans and mechanical response of sample.</p> <p>Abstract</p> <p>Quantitatively assessing seismic attenuation caused by fluid pressure diffusion (FPD) in partially saturated rocks is challenging because of its sensitivity to the spatial fluid distribution. To address this challenge we performed depressurisation experiments to induce the exsolution of carbon dioxide from water in a Berea sandstone sample. In a first set of experiments we used medical X-ray computed tomography (CT) to characterise the fluid distribution. At an equilibrium pressure of ~1 MPa and applying a fluid pressure decline rate of ~0.6 MPa per minute, we allowed a change in saturation of less than 1 %. The gas was heterogeneously distributed along the length of the sample, with most of the gas exsolving near the sample outlet. In a second set of experiments, at the same pressure and temperature, following a very similar exsolution protocol, we measured the frequency dependent attenuation and modulus dispersion between 0.1 and 1000 Hz using the forced oscillation method. We observed significant attenuation and dispersion in the extensional and bulk deformation modes, however not in the shear mode. Lastly, we use the fluid distribution derived from the X-ray CT as an input for numerical simulations of FPD to compute the attenuation and modulus dispersion. The numerical solutions are in close agreement with the attenuation and modulus dispersion measured in the laboratory. Our methodology allows for accurately relating attenuation and dispersion to the fluid distribution, which can be applied to improving the seismic monitoring of the subsurface.</p>
The Altotiberina Low-angle normal fault and Gubbio fault in seismic cluster of 2014-2015 period.
<p>Seismology data fron INGV and ISC catalogue.</p>
Data from: Predicting the maximum earthquake magnitude from seismic data in Israel and its neighboring countries
This paper explores several data mining and time series analysis methods for predicting the magnitude of the largest seismic event in the next year based on the previously recorded seismic events in the same region. The methods are evaluated on a catalog of 9,042 earthquake events, which took place between 01/01/1983 and 31/12/2010 in the area of Israel and its neighboring countries. The data was obtained from the Geophysical Institute of Israel. Each earthquake record in the catalog is associated with one of 33 seismic regions. The data was cleaned by removing foreshocks and aftershocks. In our study, we have focused on ten most active regions, which account for more than 80% of the total number of earthquakes in the area. The goal is to predict whether the maximum earthquake magnitude in the following year will exceed the median of maximum yearly magnitudes in the same region. Since the analyzed catalog includes only 28 years of complete data, the last five annual records of each region (referring to the years 2006–2010) are kept for testing while using the previous annual records for training. The predictive features are based on the Gutenberg-Richter Ratio as well as on some new seismic indicators based on the moving averages of the number of earthquakes in each area. The new predictive features prove to be much more useful than the indicators traditionally used in the earthquake prediction literature. The most accurate result (AUC = 0.698) is reached by the Multi-Objective Info-Fuzzy Network (M-IFN) algorithm, which takes into account the association between two target variables: the number of earthquakes and the maximum earthquake magnitude during the same year.
Data from: Short-term disturbance by a commercial two-dimensional seismic survey does not lead to long-term displacement of harbour porpoises
Assessments of the impact of offshore energy developments are constrained because it is not known whether fine-scale behavioral responses to noise lead to broader-scale displacement of protected small cetaceans. We used passive acoustic monitoring and digital aerial surveys to study changes in the occurrence of harbour porpoises across a 2000 km2 study area during a commercial 2-D seismic survey in the North Sea. Acoustic and visual data provided evidence of group responses to air-gun noise from the 470 cu inch array over ranges of 5-10 km, at received peak-to-peak sound pressure levels of 165-172 dB re 1 µPa and sound exposure levels of 145-151 dB re. 1µPa2 s. However, animals were typically detected again at affected sites within a few hours, and the level of response declined through the 10 day survey. Overall, acoustic detections decreased significantly during the survey period in the impact area compared to a control area, but this effect was small in relation to natural variation. These results demonstrate that prolonged seismic survey noise did not lead to broader-scale displacement into sub-optimal or higher-risk habitats, and suggest that impact assessments should focus on sub-lethal effects resulting from changes in foraging performance of animals within affected sites.
Data from: Natural regeneration on seismic lines influences movement behaviour of wolves and grizzly bears
Across the boreal forest of Canada, habitat disturbance is the ultimate cause of caribou (Rangifer tarandus caribou) declines. Habitat restoration is a focus of caribou recovery efforts, with a goal to finding ways to reduce predator use of disturbances, and caribou-predator encounters. One of the most pervasive disturbances within caribou ranges in Alberta, Canada are seismic lines cleared for energy exploration. Seismic lines facilitate predator movement, and although vegetation on some seismic lines is regenerating, it remains unknown whether vegetation regrowth is sufficient to alter predator response. We used Light Detection and Ranging (LiDAR) data, and GPS locations, to understand how vegetation and other attributes of seismic lines influence movements of two predators, wolves (Canis lupus) and grizzly bears (Ursus arctos). During winter, wolves moved towards seismic lines regardless of vegetation height, while during spring wolves moved towards seismic lines with higher vegetation. During summer, wolves moved towards seismic lines with lower vegetation and also moved faster near seismic lines with vegetation <0.7 m. Seismic lines with lower vegetation height were preferred by grizzly bears during spring and summer, but there was no relationship between vegetation height and grizzly bear movement rates. These results suggest that wolves use seismic lines for travel during summer, but during winter wolf movements relative to seismic lines could be influenced by factors additional to movement efficiency; potentially enhanced access to areas frequented by ungulate prey. Grizzly bears may be using seismic lines for movement, but could also be using seismic lines as a source of vegetative food or ungulate prey. To reduce wolf movement rate, restoration could focus on seismic lines with vegetation <1 m in height. However our results revealed that seismic lines continue to influence wolf movement behaviour decades after they were built, and even at later stages of regeneration. Therefore it remains unknown at what stage of natural regeneration, if any, wolves cease to respond to seismic lines. To reduce wolf response to seismic lines, active restoration tactics like blocking seismic lines and tree planting, along with management of alternate prey, could be evaluated.
Data from: Variation in harbour porpoise activity in response to seismic survey noise
Animals exposed to anthropogenic disturbance make trade-offs between perceived risk and the cost of leaving disturbed areas. Impact assessments tend to focus on overt behavioural responses leading to displacement, but trade-offs may also impact individual energy budgets through reduced foraging performance. Previous studies found no evidence for broad-scale displacement of harbour porpoises exposed to impulse noise from a 10 day two-dimensional seismic survey. Here, we used an array of passive acoustic loggers coupled with calibrated noise measurements to test whether the seismic survey influenced the activity patterns of porpoises remaining in the area. We showed that the probability of recording a buzz declined by 15% in the ensonified area and was positively related to distance from the source vessel. We also estimated received levels at the hydrophones and characterized the noise response curve. Our results demonstrate how environmental impact assessments can be developed to assess more subtle effects of noise disturbance on activity patterns and foraging efficiency.
Seismic noise cross-correlation functions for East Asia
<p>The files uploaded here contain the ambient seismic noise cross-correlation functions used to measure Rayleigh and Love wave group velocity dispersion in East Asia.</p>
Data Set From Molisan Regional Seismic Network Events
<p>Abstract:</p> <p><em>After the earthquake occurred in Molise (Central Italy) on 31st October 2002<br /> (Ml 5.4, 29 people dead), the local Servizio Regionale per la Protezione Civile<br /> to ensure a better analysis of local seismic data, through a convention with<br /> the Istituto Nazionale di Geofisica e Vulcanologia (INGV), promoted the design<br /> of the Regional Seismic Network (RMSM) and funded its implementation. The 5<br /> stations of RMSM worked since 2007 to 2013 collecting a large amount of seismic<br /> data and giving an important contribution to the study of seismic sources<br /> present in the region and the surrounding territory. This work reports about<br /> the dataset containing all triggers collected by RMSM since July 2007 to March<br /> 2009, including actual seismic events; among them, all earthquakes events<br /> recorded in coincidence to Rete Sismica Nazionale Centralizzata (RSNC) of INGV<br /> have been marked with S and P arrival timestamps. Every trigger has been<br /> associated to a spectrogram defined into a recorded time vs. frequency domain.<br /> The main aim of this structured dataset is to be used for further analysis with<br /> data mining and machine learning techniques on image patterns associated to the<br /> waveforms.</em></p> <p>Link arXiv: http://arxiv.org/abs/1607.02607</p>
Sentinel-1 T117 co-seismic interferogram of Amatrice earthquake (Italy) generated through the ESA G-POD platform
<p>Sentinel-1 T117 co-seismic interferogram (wrapped) of Amatrice earthquake (Italy).<br /> Data Type: wrapped Interferogram (radians)<br /> Sensor: Sentinel-1<br /> Observation interval: 15082016S1A_27082016S1A<br /> Applied Phase Filter: None<br /> Wavelength: 5.5465760 [cm]<br /> Look Angle: 39.060890 [deg]<br /> Projection: Geografic Lat-Long (WGS84)<br /> Author: IREA - CNR</p> <p><em>Acknowledgments</em>:<br /> Contains modified Copernicus data (2016), ESA GEP, G-POD, CNR-IREA, Italian DPC</p> <p> </p>
Dataset for "Anisotropy of thermal conductivity, thermal expansion coefficient, and seismic wave velocity in oceanic lithosphere--asthenosphere system"
<p>This is the dataset for "Anisotropy of thermal conductivity, thermal expansion coefficient, and seismic wave velocity in oceanic lithosphere--asthenosphere system" by M. Morishige.</p>
Enhanced seismicity catalog and output files of geomechanical modeling in the changning shale gas field
Open the record for dataset details and reuse information.
Arroyo de los Pinos Bedload and Seismic Data
<p>This dataset contains hydrologic and power-spectral density data during several flash flood events at the Arroyo de los Pinos. Velocity miniseed files (seismic data) for each event is also included.</p>
Machine-learning-based seismic detection and location around the Tanlu fault zone in eastern China
<p>REAL, HypoInverse, and HypoDD catalog around the Tanlu fault zone in eastern China.</p>
cigChannel: A large-scale 3D seismic dataset with labeled paleochannels for advancing deep learning in seismic interpretation
<h2>Assorted channel subset of the cigChannel dataset (V1.0)</h2> <h2>Expansion package of folded and faulted structures</h2> <div> <p>This version includes the last 100 samples (400 samples in total) of the assorted channel subset. Each sample features folded and faulted structures. Explanations of the uploaded zip files are listed below: </p> </div> <ul> <li>Assorted_Channel_Ip_xx-xx.zip: Seismic impedance volumes of sample No.xx to No.xx.</li> <li>Assorted_Channel_Label_xx-xx.zip: Binary-class label volumes of sample No.xx to No.xx, where the value 0 represents the background (non-channel areas) and 1 represents the channel.</li> <li>Assorted_Channel_Seismic_xx-xx.zip: Seismic (amplitude) volumes of sample No.xx to No.xx.</li> </ul> <h3>Portal to the assorted channel subset (main package, the first 300 samples):</h3> <ul> <li>Assorted channel subset: <a href="https://doi.org/10.5281/zenodo.11044512" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.11044512</a></li> </ul> <h3>Portals to the other subsets:</h3> <ul> <li>Submarine canyon subset: <a href="https://doi.org/10.5281/zenodo.11079950" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.11079950</a></li> <li>Meandering channel subset: <a href="https://doi.org/10.5281/zenodo.11078794" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.11078794</a></li> <li>Tributary channel network subset: <a href="https://doi.org/10.5281/zenodo.11073030" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.11073030</a></li> </ul>
Numerical Sheet for "Station-orientation catalog for Australian broadband seismic stations"
<p>This XLSX file includes the numerical values for Tables S1-S3.</p> <p>This XLSX file includes the station orientation catalog for all stations estimated in Tarumi & Yoshizawa (2024, submitted to Seismica) (Sheet Tab1: Permanent stations excluding the S1 network; Sheet Tab2: the S1 network stations; Sheet Tab3: Temporary stations). The first column is an index number; the second includes the network code and station name. The third and fourth columns represent the period (start and end time) for calculating two statistical values (the median and mean) of station orientation (in the fifth and sixth columns, respectively) and its standard errors (seventh columns). The last column indicates the number of earthquakes used to estimate the misorientation during the designated period. All information is the same as in Tables S1–S3. </p> <p>"codesample.zip" includes the sample program (Jupyter notebook) and the sample data. </p>
Bridging seismic and aseismic slip during and after the complex rupture of the 2023 Kahramanmaraş earthquake doublet
<p>Strong motion data of the 20230206 Mw6.6 aftershock(01:28:16 Nurdağı (Gaziantep) Earthquake)of the 2023 Mw 7.8 Nurdağı-Pazarcık earthquake</p>
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