Bibliografías temáticas / NCF (Noise Correlation Function)

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Literatura académica sobre el tema "NCF (Noise Correlation Function)"

Autor: Grafiati

Publicado: 10 de marzo de 2023

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Artículos de revistas sobre el tema "NCF (Noise Correlation Function)"

Peng, Hanshu, Zhongliang Wu, and Changsheng Jiang. "Pre-seismic changes of noise correlation function (NCF) before the Wenchuan earthquake?" Concurrency and Computation: Practice and Experience 22, no. 12 (2009): 1774–83. http://dx.doi.org/10.1002/cpe.1517.

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Kuponiyi, Ayodeji Paul, and Honn Kao. "Temporal Variation in Cultural Seismic Noise and Noise Correlation Functions during COVID-19 Lockdown in Canada." Seismological Research Letters 92, no. 5 (2021): 3024–34. http://dx.doi.org/10.1785/0220200330.

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Abstract The COVID-19 pandemic of 2020 led to a widespread lockdown that restricted human activities, particularly land, air, and maritime traffic. The “quietness” on land and ocean that followed presents an opportunity to measure an unprecedented reduction in human-related seismic activities and study its effect on the short-period range of ambient noise cross-correlation functions (NCFs). We document the variations in seismic power levels and signal quality of short-period NCFs measured by four seismographs located near Canadian cities across the pandemic-defined timeline. Significant drops in seismic power levels are observed at all the locations around mid-March. These drops coincide with lockdown announcements by the various Canadian provinces where the stations are located. Mean seismic power reductions of ∼24% and ∼17% are observed near Montreal and Ottawa, respectively, in eastern Canada. Similar reductions of ∼27% and 17% are recorded in western Canada near Victoria and Sidney, respectively. None of the locations show full recovery in seismic power back to the pre-lockdown levels by the end of June, when the provinces moved into gradual reopening. The overall levels of seismic noise during lockdown are a factor of 5–10 lower at our study locations in western Canada, relative to the east. Signal quality of NCF measured in the secondary microseism frequency band for the station pair in western Canada is maximum before lockdown (late February–early March), minimum during lockdown (mid–late March), and increased to intermediate levels in the reopening phase (late May). A similar pattern is observed for the signal quality of the eastern Canada station pair, except for a jump in levels at similar periods during the lockdown phase. The signal quality of NCF within the secondary microseism band is further shown to be the lowest for the western Canada station pair during the 2020 lockdown phase, when compared with similar time windows in 2018 and 2019.

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Hawkins, Rhys, and Malcolm Sambridge. "An Adjoint Technique for Estimation of Interstation Phase and Group Dispersion from Ambient Noise Cross Correlations." Bulletin of the Seismological Society of America 109, no. 5 (2019): 1716–28. http://dx.doi.org/10.1785/0120190060.

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Abstract A method of extracting group and phase velocity dispersions jointly for Love‐ and Rayleigh‐wave observations is presented. This method uses a spectral element representation of a path average Earth model parameterized with density, shear‐wave velocity, radial anisotropy, and VP/VS ratio. An initial dispersion curve is automatically estimated using a heuristic approach to prevent misidentification of the phase. A second step then more accurately fits the observed noise correlation function (NCF) between interstation pairs in the frequency domain. For good quality cross correlations with reasonable signal‐to‐noise ratio, we are able to very accurately fit the spectrum of NCFs and hence obtain reliable estimates of both phase and group velocity jointly for Love and Rayleigh surface waves. In addition, we also show how uncertainties can be estimated with linearized approximations from the Jacobians and subsequently used in tomographic inversions.

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Jiang, Changsheng, and Zhongliang Wu. "Temporal variation of noise correlation function (NCF) in Beijing and surroundings: Its relation with climate events and implications." Earthquake Science 22, no. 1 (2009): 75–81. http://dx.doi.org/10.1007/s11589-009-0075-5.

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Ragland, John, and Shima Abadi. "Exploring surface source distributions for ocean ambient noise interferometry with airgun shots." Journal of the Acoustical Society of America 151, no. 4 (2022): A190. http://dx.doi.org/10.1121/10.0011063.

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Ambient noise interferometry utilizes the cross-correlations of ambient sound to estimate the time domain Green’s function (TDGF). We have previously shown that ambient noise interferometry can resolve multi-path arrivals between two bottom-mounted hydrophones separated by 3.2 km, at a depth of 1500 m, and located 470 km off the Oregon coast. In 2019, a seismic reflection survey was conducted directly over the two hydrophones for 28 days covering a 763 km2 area. The airgun shots occurred every 37.5 m while the ship moved at a speed of ∼4.5 knots, equivalent to a shooting interval of 16 s. The hydrophone recordings during this survey provide the unique opportunity to understand the effects of the surface source distribution on the noise cross correlation function (NCCF). In this talk, we show the sensitivity of the NCCF to the surface source locations using simulated and experimental data. Then, we use the image source method to analytically define the location of the sound sources that contribute to different delay times in the NCCF. [Work supported by ONR.]

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Steinmann, René, Céline Hadziioannou, and Eric Larose. "Effect of centimetric freezing of the near subsurface on Rayleigh and Love wave velocity in ambient seismic noise correlations." Geophysical Journal International 224, no. 1 (2020): 626–36. http://dx.doi.org/10.1093/gji/ggaa406.

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SUMMARY About a decade ago, noise-based monitoring became a key tool in seismology. One of the tools is passive image interferometry (PII), which uses noise correlation functions (NCF) to retrieve seismic velocity variations. Most studies apply PII to vertical components recording oceanic low-frequent ambient noise ( &lt; 1 Hz). In this work, PII is applied to high-frequent urban ambient noise ( &gt; 1 Hz) on three three-component sensors. With environmental sensors inside the subsurface and in the air, we are able to connect observed velocity variations with environmental parameters. Temperatures below 0 °C correlate well with strong shear wave velocity increases. The temperature sensors inside the ground suggest that a frozen layer of less than 5 cm thickness causes apparent velocity increases above 2 % , depending on the channel pair. The observations indicate that the different velocity variation retrieved from the different channel pairs are due to different surface wave responses inherent in the channel pairs. With dispersion curve modelling in a 1-D medium we can verify that surfaces waves of several tens of metres wavelength experience a velocity increase of several percent due to a centimetres thick frozen layer. Moreover, the model verifies that Love waves show larger velocity increases than Rayleigh waves. The findings of this study provide new insights for monitoring with PII. A few days with temperature below 0 °C can already mask other potential targets (e.g. faults or storage sites). Here, we suggest to use vertical components, which is less sensitive to the frozen layer at the surface. If the target is the seasonal freezing, like in permafrost studies, we suggest to use three-component sensors in order to retrieve the Love wave response. This opens the possibility to study other small-scale processes at the shallow subsurface with surface wave responses.

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Tian, Jinyu, Jian Lin, Fan Zhang, et al. "Time Correction of Ocean-Bottom Seismometers Using Improved Ambient Noise Cross Correlation of Multicomponents and Dual-Frequency Bands." Seismological Research Letters 92, no. 3 (2021): 2004–14. http://dx.doi.org/10.1785/0220200358.

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Abstract An effective approach was developed for identifying and correcting ocean-bottom seismometer (OBS) time errors through improving ambient noise cross-correlation function (NCCF) analysis and combination with other methods. Significant improvements were illustrated through analyzing data from a passive-source seismic experiment in the southwestern sub-basin of the South China Sea. A novel method was first developed that can effectively identify errors in the sampling frequency of the OBS instruments. The traditional NCCF method was then expanded by increasing the analyzed data spectrum from a single-frequency band to dual-frequency band pairs, thus doubling the number of available data points and substantially improving the time correction quality. For data with relatively low signal-to-noise ratios, the average time errors were reduced from the original average values of 60–80 ms by the conventional methods to &lt;40 ms using the improved approaches. The new multistep procedure developed in this study has general applicability to analysis of other OBS experiments. The demonstrated significant improvements in the data quality are critical for advancing seismic tomography and other modern marine geophysical studies that require high accuracy in the OBS data.

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Cheng, Wei, Lintao Liu, and Guocheng Wang. "A new method for estimating the correlation of seismic waveforms based on the NTFT." Geophysical Journal International 226, no. 1 (2021): 368–76. http://dx.doi.org/10.1093/gji/ggab047.

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SUMMARY We propose a new correlation function called the similarity coefficient (SC) based on the normal time–frequency transform (NTFT) to evaluate the similarity between two non-stationary seismic signals as a function of the delay time. The SC is defined in the time–frequency spectrum of the NTFT, and the instantaneous phase and amplitude of each frequency component in a signal are used to calculate the SC. Our simulation experiments demonstrate that the SC method can effectively recognize similar signals compared to the conventional normalized cross-correlation coefficient (NCC) under high background noise conditions. The SC presents good robustness in identifying similar signals and performs well in the case of an extremely low signal-to-noise ratio (SNR), which makes it suitable for detecting weak seismic signals concealed by noise. As a real application case, we use the SC method to detect quasi-Love (QL) surface waves. QL waves are scattered Love waves and are important indicators for lateral anisotropic gradients in the upper mantle. We detect the QL waves at 21 stations deployed across Japan after the 23 December 2004 Mw 8.1 Macquarie earthquake by using the SC method. Obvious QL waves are observed at 19 stations, and we locate the Love-to-Rayleigh scatterers by applying the delay times between the QL and main Love waves. Our results show that the QL wave scatterers were mostly generated in two areas: Mariana subduction and Papua New Guinea. The observations of QL waves suggest the presence of lateral gradients in anisotropy beneath those two areas. The spatial distribution of the 13 scatterers in the Mariana subduction zone agrees well with the Mariana Island Arc, and we infer that the Mariana slab may have melted and coupled with the surrounding mantle at depth.

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Wang, Jian, Xiaolei Lv, Zenghui Huang, and Xikai Fu. "An Epipolar HS-NCC Flow Algorithm for DSM Generation Using GaoFen-3 Stereo SAR Images." Remote Sensing 15, no. 1 (2022): 129. http://dx.doi.org/10.3390/rs15010129.

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Radargrammetry is a widely used methodology to generate the large-scale Digital Surface Model (DSM). Stereo matching is the most challenging step in radargrammetry due to the significant geometric differences and the inherent speckle noise. The speckle noise results in significant grayscale differences of the same feature points, which makes the traditional Horn–Schunck (HS) flow or multi-window zero-mean normalized cross-correlation (ZNCC) methods degrade. Therefore, this paper proposes an algorithm named Epipolar HS-NCC Flow (EHNF) for dense stereo matching, which is an improved HS flow method with normalized cross-correction constraint based on epipolar stereo images. First, the epipolar geometry is applied to resample the image to realize the coarse stereo matching. Subsequently, the EHNF method forms a global energy function to achieve fine stereo matching. The EHNF method constructs a local normalized cross-correlation constraint term to compensate for the grayscale invariance constraint, especially for the SAR stereo images. Additionally, two assessment methods are proposed to calculate the optimal cross-correlation parameter and smoothness parameter according to the refined matched point pairs. Two GaoFen-3 (GF-3) image pairs from ascending and descending orbits and the open Light Detection and Ranging (LiDAR) data are utilized to fully evaluate the proposed method. The results demonstrate that the EHNF algorithm improves the DSM elevation accuracy by 9.6% and 27.0% compared with the HS flow and multi-window ZNCC methods, respectively.

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Perez-Cham, Oscar E., Cesar Puente, Carlos Soubervielle-Montalvo, Gustavo Olague, Carlos A. Aguirre-Salado, and Alberto S. Nuñez-Varela. "Parallelization of the Honeybee Search Algorithm for Object Tracking." Applied Sciences 10, no. 6 (2020): 2122. http://dx.doi.org/10.3390/app10062122.

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Object tracking refers to the relocation of specific objects in consecutive frames of a video sequence. Presently, this visual task is still considered an open research issue, and the computer science community attempted solutions from the standpoint of methodologies, algorithms, criteria, benchmarks, and so on. This article introduces a GPU-parallelized swarm algorithm, called the Honeybee Search Algorithm (HSA), which is a hybrid algorithm combining swarm intelligence and evolutionary algorithm principles, and was previously designed for three-dimensional reconstruction. This heuristic inspired by the search for food of honeybees, and here adapted to the problem of object tracking using GPU parallel computing, is extended from the original proposal of HSA towards video processing. In this work, the normalized cross-correlation (NCC) criteria is used as the fitness function. Experiments using 314 video sequences of the ALOV benchmark provides evidence about the quality regarding tracking accuracy and processing time. Also, according to these experiments, the proposed methodology is robust to high levels of Gaussian noise added to the image frames, and this confirms that the accuracy of the original NCC is preserved with the advantage of acceleration, offering the possibility of accelerating latest trackers using this methodology.

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