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70 results for “ambient noise”
PAN-AR: A Multimodal Dataset of Higher-Order Ambisonics Room Impulse Responses, Ambient Noise and Spherical Pictures
<h1>PAN-AR</h1> <p>This is <strong>PAN-AR</strong> (Panoramas, Ambient Noise & Ambisonics RIRs), a dataset described in the following <a href="https://doi.org/10.1145/3678299.3678332" target="_blank" rel="noopener">paper</a>:</p> <blockquote> <p>Filippo Denti, Davide Fantini, Federico Avanzini and Giorgio Presti. PAN-AR: A Multimodal Dataset of Higher-Order Ambisonics Room Impulse Responses, Ambient Noise and Spherical Pictures. In <em>Proceedings of the 19th International Audio Mostly Conference</em>, Milan, Italy, September 2024.</p> </blockquote> <p>The dataset includes Spatial Room Impulse Responses (SRIRs) in second-order Ambisonics format, ambient noise recordings, and spherical photos. These data have been captured in four environments with different configurations of the source and listener positions:</p> <ol> <li>Printer room</li> <li>Meeting room</li> <li>Classroom</li> <li>Underground parking area</li> </ol> <p>Panoramas and planimetries are provided in a temporary version. The final version with post-processed panoramas and complete planimetries will be available soon. An example of the final panoramas is provided for position A of the printer room, while an example of complete planimetry is provided for the printer and the meeting rooms.</p> <h2>SOFA</h2> <p>The SRIRs are also provided in SOFA format <a href="https://sofacoustics.org/data/database/pan-ar/" target="_blank" rel="noopener">here</a>.</p> <h2>How to cite</h2> <p>If you use the PAN-AR dataset, please cite the following <a href="https://doi.org/10.1145/3678299.3678332" target="_blank" rel="noopener">paper</a>:</p> <pre><code>@inproceedings{denti2024panar,</code><br><code> title = {{PAN-AR}: A Multimodal Dataset of Higher-Order Ambisonics Room Impulse Responses, Ambient Noise and Spherical Pictures},</code><br><code> author = {Denti, Filippo and Fantini, Davide and Avanzini, Federico and Presti, Giorgio},</code><br><code> year = {2024},</code><br><code> month = {September},</code><br><code> booktitle = {Proceedings of the 19th International Audio Mostly Conference (AM '24)},</code><br><code> location = {Milan, Italy},</code><br><code> publisher = {ACM},</code><br><code> isbn = {979-8-4007-0968-5/24/09},</code><br><code> doi = {10.1145/3678299.3678332}</code><br><code>}</code></pre>
Final models for "Global-Scale Full-Waveform Ambient Noise Inversion" by Sager et al. (2020)
<p>The exodus model contains the inverted structure model and the source distribution can be found in the HDF5 file. Both can be visualized in ParaView. For the source model, we recommend opening it with the correspoding XDMF file (select "XDMF Reader" in the dialogue box).</p>
Short-Term Synchronous and Asynchronous Ambient Noise Tomography in Urban Areas: Application to Karst Investigation
<p>We used DSurfTomo (<a href="https://github.com/HongjianFang/DSurfTomo">HongjianFang/DSurfTomo: Direct inversion of surface dispersion data based on ray tracing (github.com)</a>) for the tomography.</p> <p>ABC2_2023.dat is the travel time of C1 and C2 cross-correlation functions, used in our tomography.</p> <p>ManualDSurfTomoV1.3.pdf is the manual of DSurfTomo, including the data format description for ABC2_2023.dat.</p> <p>yunqiVs3D.txt is the interpolated 3D Vs model, including longitude, latitude, depth (meter), Vs (m/s).</p> <p>Previous version error: I forgot to write the Vs value.</p>
Low Frequency Ambient Noise Dynamics and Trends: Cape Leeuwin, Australia
<p>Data files and code for : Low Frequency Ambient Noise Dynamics and Trends: Cape Leeuwin, Australia</p> <p>R version 4.X used for plots and analysis. Packages: entropy, foreach, rEDM</p> <ol> <li>Plots.R : Create plots for manuscript. </li> <li>MI.R : Evaluate lagged Mutual Information of random data segments</li> <li>CCM.R : Convergent cross mapping of Ambient Noise with teleconnections</li> <li>EMM_Surrogate.R : Evaluate CCM significance with randomized surrogates</li> </ol> <p>Python 3.X used for plots and analysis. Packages: pandas, matplotlib, emd, pyEDM</p> <ol> <li>Figure5,py Figure14.py : Create plots for manuscript</li> <li>EMD.py : Compute empirical mode decompositions</li> </ol> <p> </p>
Data for "Variation in Upper Plate Crustal and Lithospheric Mantle Structure in the Greater and Lesser Antilles from Ambient Noise Tomography"
<p>This is the phase velocity information and the shear wave model for the g-cubed paper:</p> <p>"Variation in Upper Plate Crustal and Lithospheric Mantle Structure in the Greater and Lesser Antilles from Ambient Noise Tomography"</p>
Repository: Rayleigh-wave attenuation and phase velocity maps of the greater Alpine region from ambient noise
<p><br>Repository organized by Henrique Berger Roisenberg for the paper Roisenberg et al. (2024). The files are organized as follows:</p> <p><strong>Folders:</strong></p> <p><strong>-dispersion_curves:</strong><br>inside this folder there is a .zip file that contains all the dispersion curves calculated;</p> <p><strong>-attenuation:</strong><br>comprising three files with the results of attenuation calculations, i.e., the attenuation values, the grid, and the periods;</p> <p><strong>-c:</strong><br>comprising three files with the results of phase velocity calculations, i.e., the phase velocity values, the grid, and the periods;</p> <p><strong>-scripts: </strong><br>contains two python scripts, one called 'figures' to plot the figure 1, 4, and 6 of the paper, and another called 'alparray_computations' to perform the computations with the original alparray data, using seislib, resulting on the figures 2, 3, and 5 of the paper.</p> <p>Inside the folder '<strong>inputs</strong>' there are three folders that serve as input for the figures of the paper, to be used in the scripts. These are:</p> <p><strong>-raster: </strong><br>contains the topography raster used to plot the map of the study area;</p> <p><strong>-shapefiles:</strong><br>contains the shapefiles used in the regionalization analysis;</p> <p><strong>-station locations: </strong><br>contains the latitudes and longitudes of the stations used in this study.</p> <p> </p>
Magmatic System of the Hainan Hotspot Revealed by Ambient Noise Tomography
<p>The datasets consists of three parts:</p> <p>1.Cross-correlation Functions Data(all_CCFs.zip):<br>Format:<br> Lon (station A) Lat (station A) Elevation (A)<br> Lon (station B) Lat (station B) Elevation (B)<br> Time (t=0) GAB(t) GBA(t)<br> Time (t=dt) GAB(t) GBA(t) <br> Time (t=2dt) GAB(t) GBA(t)</p> <p><br>2. Rayleigh Wave Phase Dispersion Data (CDisp.zip):<br>Format:<br> Lon (station A) Lat (station A)<br> Lon (station B) Lat (station B)<br> Period (s) Vs (km/s)</p> <p>3.S-Velocity Model:<br>Format:<br> Longitude Latitude Depth Absolute_velocity Average_velocity Relative_velocity</p>
Ocean ambient noise data on the Chukchi Plateau from August 2018 to October 2019
<p>The noise spectrum level under different sea ice conditions, and monthly and hourly ambient noise level on the Chukchi Plateau from August 1st, 2018 to October 31st, 2019.</p>
Adjoint tomography data for LASSIE array by ambient noise differential adjoint tomography
<p>The LASSIE array shear-wave velocity model from ambient noise differential adjoint tomography. </p><p>If you use this dataset, please cite the article published online: </p><p>Liu, X., Beroza, G.C. & Li, H. Ambient noise differential adjoint tomography reveals fluid-bearing rocks near active faults in Los Angeles. <i>Nat Commun</i> <strong>14</strong>, 6873 (2023). <a href="https://doi.org/10.1038/s41467-023-42536-4">https://doi.org/10.1038/s41467-023-42536-4</a> </p><p>Here are the explanations for each of the five columns of the CSV file:<br>- lat: Latitude is a geographic coordinate <br>- lon: Longitude is a geographic coordinate <br>- depth: Depth from surface of the earth<br>- Vs_init: the initial shear wave velocity from ray theory and layered-cake inversion below each surface location<br>- Vs_adj: the adjoint shear wave velocity tomography result from ambient noise differential adjoint tomography</p><p> </p>
Data and program codes to reproduce the results presented in "Crustal structure beneath Central Kamchatka inferred from ambient noise tomography"
<p>This archive contains the SURF_TOMO code for the surface-wave tomography (<em>Koulakov et al., 2016</em>) and all the necessary files and instructions for reproducing the results presented in the paper “Crustal structure beneath Central Kamchatka inferred from ambient noise tomography” by Igor Egorushkin, Ivan Koulakov, Andrey Jakovlev, Hsin-Hua Huang, Eugeny I. Gordeev, Ilyas Abkadyrov, and Danila Chebrov.</p>
Accuracy of the Group Velocity of Love Waves Extracted from Ambient Seismic Noise
<p>Love wave waveforms derived from the empirical Green's functions and Ground Truth earthquake in my manuscript submitted to Journal of Geophysical Research: Solid Earth.</p>
Lateral Variations in Upper Mantle Discontinuities beneath Northeast China Revealed by Seismic Ambient Noise
<div>Data description:</div> <div> </div> <div>CCdata.zip:</div> <div>Re-sampling Cross-Correlation functions (4Hz) which contain three seismic arrays.</div> <div>CEA contains HL, JL, LN and NM networks. </div> <div>NECESSarray contains YP network. NECsaids contains DB network. </div> <div>All the stations are located east of 122E, between 41N and 46N. </div> <div>The cross-correlations are used to retrieved body-wave reflections from mantle transition zone discontinuities.</div> <div> </div> <div>Syntheticdata.zip:</div> <div>contains four parts: rawdata1d, rawdata2d, stackedwaveform-2d, and compare-1d</div> <div> </div> <div>rawdata1d: </div> <div>raw synthetic waveforms calculated by Qseis (Wang, 1999) after data-processings.</div> <div>H is increased from 0 to 30 km. </div> <div>The distance is 100 km. </div> <div> </div> <div>rawdata2d: </div> <div>raw synthetic waveforms calculated by SPECFEM2D (Tromp et al., 2008).</div> <div>Three models with depressed d660 (model 1-3) and with a slab on the d660 (model 4). </div> <div>100 receiver stations (surface), from 305 km to 1295 km in 10 km increments.</div> <div>49 vertical single-force sources (surface), from 320 km to 1280 km in 20 km increments </div> <div> </div> <div>stackedwaveform-2d:</div> <div>The final depth results with different models.</div> <div> </div> <div>compare-1d:</div> <div>The waveforms used to compare the rf and cc.</div> <div> </div> <div>Code:</div> <div>These codes can be used to make the figures of synthetic and NCFs results. </div> <div> </div> <div> </div> <div>NECsaidsDescription.docx:</div> <div>Detailed description about the NECsaids project conducted in northeast China from October, 2010 to September, 2017.</div> <div> </div> <div>station_loc.txt:</div> <div>Coordinate file (station, longitude, latitude) of the stations.</div> <div> </div> <div>Reference</div> <div>Wang, R. (1999). A simple orthonormalization method for stable and efficient computation of Green's functions. Bulletin of the Seismological Society of America, 89(3), 733-741. doi: 10.1785/BSSA0890030733</div> <div>Tromp, J., Komatitsch, D. and Liu, Q. Y. (2008). Spectral-element and adjoint methods in seismology. Commun Comput Phys 3, 1-32.</div>
Ambient noise from the atmosphere within the seismic hum period band: A case study of hurricane landfall
<p>Spectral analysis results, synthetic Green's functions, and seismic modeling results of this study.</p> <p>This work can be found at GitHub: <a href="https://github.com/NickJi98/Atm_Noise_2024_EPSL.git">https://github.com/NickJi98/Atm_Noise_2024_EPSL.git</a></p>
Mechanisms for Layered Anisotropy and Anomalous Magmatism of Alaska Subduction System Revealed by Ambient Noise Tomography and the Wave Gradiometry Method
<p>Depth Coverage: 2.0 - 230.0 km<br>Areal Coverage: Latitude: 54.8 to 72.0 Longitude: -168.0 to -129.0<br>Model Description: A high-resolution 3D azimuthal anisotropic shear wave velocity model beneath Alaska and its surroundings on a ~50‐km grid extracted by ambient noise tomography and wave gradiometry method .</p> <p>Columns in the subfile, from left to right, are latitude, longitude, shear wave velocity, fast direction, and the magnitude of anisotropy, respectively. </p>
Upper Crustal Structure of the Xinfengjiang Reservoir from Ambient Noise Double Beamforming Tomography and Its Implications for Induced Seismicity
<p>The file "CC.tar.gz" contains the linearly stacked ZZ component cross-correlations for all station pairs.</p> <p>The file "Model.tar.gz" contains the 3-D upper crustal model of the Xinfengjiang Reservoir via ambient noise Double-Beamforming tomograpy.</p>
Ambient noise data and velocity model from DEEPEN array in Hengill geothermal field, Iceland
<p>This repository contains the data and velocity model associated with the manuscript entitled "<em>Crustal characterization of the Hengill geothermal fields: Insights from isotropic and anisotropic seismic noise imaging using a 500-node array</em>" by Wu et al. (2024), to be published in <em>Journal of Geophysical Research: Solid Earth</em>. </p> <p>The dataset is the nine component cross-correlation functions (ZZ, ZN, ZE, NZ, NN, NE, EZ, EN, EE) after stacking over seismic array deployment time period (summer 2021) and after spatial averaging (bin stacking). The bin locations are provided in "bin_locations.txt".</p> <p>The derived VOIGT velocity and radial anisotropy model can be found in "Hengill_Voigt_Aniso_DEEPEN_4share.txt".</p> <p> </p>
Three-dimensional crustal channel flows beneath the southeastern Tibetan Plateau revealed by full-waveform ambient noise tomography
<p>This is a new version of Vp and Vs models for paper titled "Three‐Dimensional Crustal Channel Flows Beneath the Southeastern Tibetan Plateau Revealed by Full‐Waveform Ambient Noise Tomography" published in Geophysical Research Letters.</p> <p>Modification history: new Vs model includes from surface downward to 120 km depth.</p> <p>Please ignore the models in version 1 and 2.</p>
dispersion curvers of southeastern Tibetan Plateau obtained by wave gradiometry and ambient noise cross correlation
<p>azimuth-dependant dispersion curves: bk.gridID.deg.backazimuth.dsp</p> <p>T=5:20s obtained from ambient noise tomography<br> T=21:60s obtained from wave gradiometry<br> grid information: xyloc.txt</p>
Geothermal and structural features of La Palma island (Canary Islands) imaged by ambient noise tomography
<p>These folders contain all the results obtained in the ambient noise tomography of La Palma for geothermal exploration. </p>
Continental Reworking in the Eastern South China Block and Its Adjacent Areas Revealed by F-J Multimodal Ambient Noise Tomography
<p><span>It contains ZZ-component cross-correlation functions and the 3-D Vsv model in the eastern South China Block.</span></p>
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