A Seismic Event Relative Location Benchmark Case Study

"Precision seismology'' encompasses a set of methods which use differential measurements of time-delays to estimate the relative locations of earthquakes and explosions.&#160; Delay-times estimated from signal correlations often allow far more accurate estimates of one event location relative to another than is possible using classical hypocenter determination techniques.&#160; Many different algorithms and software implementations have been developed and different assumptions and procedures can often result in significant variability between different relative event location estimates.&#160; We present a Ground Truth (GT) database of 55 military surface explosions in northern Finland in 2007 that all took place within 300 meters of each other.&#160; The explosions were recorded with a high signal-to-noise ratio to distances of about 2 degrees, and the exceptional waveform similarity between the signals from the different explosions allows for accurate correlation-based time-delay measurements.&#160; With exact coordinates for the explosions, we can assess the fidelity of relative location estimates made using any location algorithm or implementation.&#160; Applying double-difference calculations using two different 1-d velocity models for the region results in hypocenter-to-hypocenter distances which are too short and the wavefield leaving the source region is more complicated than predicted by the models.&#160; Using the GT event coordinates, we can measure the slowness vectors associated with each outgoing ray from the source region. We demonstrate that, had such corrections been available, a significant improvement in the relative location estimates would have resulted.&#160; In practice we would of course need to solve for event hypocenters and slowness corrections simultaneously, and significant work will be needed to upgrade relative location algorithms to accommodate uncertainty in the form of the outgoing wavefield.&#160; We present this dataset, together with GT coordinates, raw waveforms for all events on six regional stations, and tables of time-delay measurements, as a reference benchmark by which relative location algorithms and software can be evaluated.

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A benchmark case study for seismic event relative location

Geophysical Journal International ◽

10.1093/gji/ggaa362 ◽

2020 ◽

Vol 223 (2) ◽

pp. 1313-1326

Author(s):

S J Gibbons ◽

T Kværna ◽

T Tiira ◽

E Kozlovskaya

Keyword(s):

Time Delay ◽

Signal To Noise Ratio ◽

Source Region ◽

Ground Truth ◽

Double Difference ◽

High Signal ◽

Relative Location ◽

Data Set ◽

Velocity Models ◽

Event Location

Summary ‘Precision seismology’ encompasses a set of methods which use differential measurements of time-delays to estimate the relative locations of earthquakes and explosions. Delay-times estimated from signal correlations often allow far more accurate estimates of one event location relative to another than is possible using classical hypocentre determination techniques. Many different algorithms and software implementations have been developed and different assumptions and procedures can often result in significant variability between different relative event location estimates. We present a Ground Truth (GT) dataset of 55 military surface explosions in northern Finland in 2007 that all took place within 300 m of each other. The explosions were recorded with a high signal-to-noise ratio to distances of about 2°, and the exceptional waveform similarity between the signals from the different explosions allows for accurate correlation-based time-delay measurements. With exact coordinates for the explosions, we are able to assess the fidelity of relative location estimates made using any location algorithm or implementation. Applying double-difference calculations using two different 1-D velocity models for the region results in hypocentre-to-hypocentre distances which are too short and it is clear that the wavefield leaving the source region is more complicated than predicted by the models. Using the GT event coordinates, we are able to measure the slowness vectors associated with each outgoing ray from the source region. We demonstrate that, had such corrections been available, a significant improvement in the relative location estimates would have resulted. In practice we would of course need to solve for event hypocentres and slowness corrections simultaneously, and significant work will be needed to upgrade relative location algorithms to accommodate uncertainty in the form of the outgoing wavefield. We present this data set, together with GT coordinates, raw waveforms for all events on six regional stations, and tables of time-delay measurements, as a reference benchmark by which relative location algorithms and software can be evaluated.

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ACE-FTS observation of a young biomass burning plume: first reported measurements of C2H4, C3H6O, H2CO and PAN by infrared occultation from space

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-7-7907-2007 ◽

2007 ◽

Vol 7 (3) ◽

pp. 7907-7932 ◽

Cited By ~ 5

Author(s):

P.-F. Coheur ◽

H. Herbin ◽

C. Clerbaux ◽

D. Hurtmans ◽

C. Wespes ◽

...

Keyword(s):

Biomass Burning ◽

Atmospheric Chemistry ◽

Signal To Noise Ratio ◽

Source Region ◽

High Signal ◽

Upper Troposphere ◽

Organic Species ◽

Specific Biomass ◽

Chemistry Experiment ◽

Very High

Abstract. In the course of our study of the upper tropospheric composition with the infrared Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE–FTS), we found an occultation sequence that on 8 October 2005, sampled a remarkable plume near the east coast of Tanzania. Model simulations of the CO distribution in the Southern hemisphere are performed for this period and they demonstrate that the emissions for this event originated from a nearby forest fire, after which the plume was transported from the source region to the upper troposphere. Taking advantage of the very high signal-to-noise ratio of the ACE–FTS spectra over a wide wavenumber range (750–4400 cm−1), we present in-depth analyses of the chemical composition of this plume in the middle and upper troposphere, focusing on the measurements of weakly absorbing pollutants. For this specific biomass burning event, we report simultaneous observations of an unprecedented number of organic species. Measurements of C2H4 (ethene), C3H4 (propyne), H2CO (formaldehyde), C3H6O (acetone) and CH3COO2NO2 (peroxyacetylnitrate, abbreviated as PAN) are the first reported detections using infrared occultation spectroscopy from satellites. Based on the lifetime of the emitted species, we discuss the photochemical age of the plume and also report, whenever possible, the enhancement ratios relative to CO.

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Sensitivity analysis of the backprojection imaging method for seismic event location

CT&F - Ciencia Tecnología y Futuro ◽

10.29047/01225383.167 ◽

2021 ◽

Vol 11 (1) ◽

pp. 21-32

Author(s):

Cristian Alexis Murillo Martínez ◽

William Mauricio Agudelo

Keyword(s):

Sensitivity Analysis ◽

Signal To Noise Ratio ◽

Synthetic Data ◽

Spatial Location ◽

Noise Removal ◽

Image Resolution ◽

Imaging Method ◽

Velocity Models ◽

Event Location ◽

Location Methods

Accuracy of earthquake location methods is dependent upon the quality of input data. In the real world, several sources of uncertainty, such as incorrect velocity models, low Signal to Noise Ratio (SNR), and poor coverage, affect the solution. Furthermore, some complex seismic signals exist without distinguishable phases for which conventional location methods are not applicable. In this work, we conducted a sensitivity analysis of Back-Projection Imaging (BPI), which is a technique suitable for location of conventional seismicity, induced seismicity, and tremor-like signals. We performed a study where synthetic data is modelled as fixed spectrum explosive sources. The purpose of using such simplified signals is to fully understand the mechanics of the location method in controlled scenarios, where each parameter can be freely perturbed to ensure that their individual effects are shown separately on the outcome. The results suggest the need for data conditioning such as noise removal to improve image resolution and minimize artifacts. Processing lower frequency signal increases stability, while higher frequencies improve accuracy. In addition, a good azimuthal coverage reduces the spatial location error of seismic events, where, according to our findings, depth is the most sensitive spatial coordinate to velocity and geometry changes.

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Fluids Triggered the 2021 Mw 6.1 Yangbi Earthquake at an Unmapped Fault: Implications for the Tectonics at the Northern End of the Red River Fault

Seismological Research Letters ◽

10.1785/0220210227 ◽

2022 ◽

Author(s):

Quan Sun ◽

Zhen Guo ◽

Shunping Pei ◽

Yuanyuan V. Fu ◽

Yongshun John Chen

Keyword(s):

Source Region ◽

High Stress ◽

Red River ◽

Earthquake Sequence ◽

Rupture Zone ◽

Double Difference ◽

Data Set ◽

Upward Migration ◽

Velocity Models ◽

Red River Fault

Abstract On 21 May 2021 a magnitude Mw 6.1 earthquake occurred in Yangbi region, Yunan, China, which was widely felt and caused heavy casualties. Imaging of the source region was conducted using our improved double-difference tomography method on the huge data set recorded by 107 temporary stations of ChinArray-I and 62 permanent stations. Pronounced structural heterogeneities across the rupture source region are discovered and locations of the hypocenters of the Yangbi earthquake sequence are significantly improved as the output of the inversion. The relocated Yangbi earthquake sequence is distributed at an unmapped fault that is almost parallel and adjacent (∼15 km distance) to the Tongdian–Weishan fault (TWF) at the northern end of the Red River fault zone. Our high-resolution 3D velocity models show significant high-velocity and low-VP/VS ratios in the upper crust of the rupture zone, suggesting the existence of an asperity for the event. More importantly, low-VS and high-VP/VS anomalies below 10 km depth are imaged underlying the source region, indicating the existence of fluids and potential melts at those depths. Upward migration of the fluids and potential melts into the rupture zone could have weakened the locked asperity and triggered the occurrence of the Yangbi earthquake. The triggering effect by upflow fluids could explain why the Yangbi earthquake did not occur at the adjacent TWF where a high-stress accumulation was expected. We speculate that the fluids and potential melts in the mid-to-lower crust might have originated either from crustal channel flow from the southeast Tibet or from local upwelling related to subduction of the Indian slab to the west.

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ACE-FTS observation of a young biomass burning plume: first reported measurements of C2H4, C3H6O, H2CO and PAN by infrared occultation from space

Atmospheric Chemistry and Physics ◽

10.5194/acp-7-5437-2007 ◽

2007 ◽

Vol 7 (20) ◽

pp. 5437-5446 ◽

Cited By ~ 105

Author(s):

P.-F. Coheur ◽

H. Herbin ◽

C. Clerbaux ◽

D. Hurtmans ◽

C. Wespes ◽

...

Keyword(s):

Biomass Burning ◽

Atmospheric Chemistry ◽

Signal To Noise Ratio ◽

Source Region ◽

High Signal ◽

Upper Troposphere ◽

Organic Species ◽

Specific Biomass ◽

Chemistry Experiment ◽

Very High

Abstract. In the course of our study of the upper tropospheric composition with the infrared Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE–FTS), we found an occultation sequence that on 8 October 2005, sampled a remarkable plume near the east coast of Tanzania. Model simulations of the CO distribution in the Southern hemisphere are performed for this period and they suggest that the emissions for this event likely originated from a nearby forest fire, after which the plume was transported from the source region to the upper troposphere. Taking advantage of the very high signal-to-noise ratio of the ACE–FTS spectra over a wide wavenumber range (750–4400 cm−1), we present in-depth analyses of the chemical composition of this plume in the middle and upper troposphere, focusing on the measurements of weakly absorbing pollutants. For this specific biomass burning event, we report simultaneous observations of an unprecedented number of organic species. Measurements of C2H4 (ethene), C3H4 (propyne), H2CO (formaldehyde), C3H6O (acetone) and CH3COO2NO2 (peroxyacetylnitrate, abbreviated as PAN) are the first reported detections using infrared occultation spectroscopy from satellites. Based on the lifetime of the emitted species, we discuss the photochemical age of the plume and also report, whenever possible, the enhancement ratios relative to CO.

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ENHANCEMENT OF STEREO IMAGERY BY ARTIFICIAL TEXTURE PROJECTION GENERATED USING A LIDAR

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b5-599-2016 ◽

2016 ◽

Vol XLI-B5 ◽

pp. 599-606 ◽

Cited By ~ 3

Author(s):

Joshua Veitch-Michaelis ◽

Jan-Peter Muller ◽

David Walton ◽

Jonathan Storey ◽

Michael Foster ◽

...

Keyword(s):

Signal To Noise Ratio ◽

Speckle Pattern ◽

Ground Truth ◽

Laser Speckle ◽

Image Texture ◽

High Signal ◽

Optical Elements ◽

Image Texture Analysis ◽

Ground Truth Data ◽

Pattern Projection

Passive stereo imaging is capable of producing dense 3D data, but image matching algorithms generally perform poorly on images with large regions of homogenous texture due to ambiguous match costs. Stereo systems can be augmented with an additional light source that can project some form of unique texture onto surfaces in the scene. Methods include structured light, laser projection through diffractive optical elements, data projectors and laser speckle. Pattern projection using lasers has the advantage of producing images with a high signal to noise ratio. We have investigated the use of a scanning visible-beam LIDAR to simultaneously provide enhanced texture within the scene and to provide additional opportunities for data fusion in unmatched regions. The use of a LIDAR rather than a laser alone allows us to generate highly accurate ground truth data sets by scanning the scene at high resolution. This is necessary for evaluating different pattern projection schemes. Results from LIDAR generated random dots are presented and compared to other texture projection techniques. Finally, we investigate the use of image texture analysis to intelligently project texture where it is required while exploiting the texture available in the ambient light image.

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Arrival-time picking uncertainty: Theoretical estimations and their application to microseismic data

Geophysics ◽

10.1190/geo2019-0589.1 ◽

2020 ◽

Vol 85 (4) ◽

pp. U65-U76

Author(s):

Ivan Abakumov ◽

Aurelian Roeser ◽

Serge A. Shapiro

Keyword(s):

Seismic Waves ◽

Arrival Time ◽

Signal To Noise Ratio ◽

Estimation Error ◽

Additive White Gaussian Noise ◽

Accurate Determination ◽

Microseismic Monitoring ◽

High Signal ◽

Arrival Times ◽

Velocity Models

Traveltime-based methods depend on the accurate determination of the arrival times of seismic waves. They further benefit from information on the uncertainty with which the arrival times are determined. Among other applications, arrival-time uncertainties are used to weight data in inversion algorithms and to define the resolution of reconstructed velocity models. The most physically meaningful approaches for the estimation of arrival-time uncertainties are based on probabilistic formulations. The two approaches for the assessment of the lower bound of arrival-time uncertainties, the Cramér–Rao Bound (CRB) and the Ziv–Zakai Bound (ZZB), have been reviewed. The CRB determines the minimum-achievable estimation error under the assumption of a high signal-to-noise ratio (S/N) but underestimates said error for small S/N. The ZZB provides a better result for noisy data because it utilizes a priori information. The CRB and ZZB require knowledge of the spectral variance of the signal, which often is hard to determine in seismic experiments. Furthermore, both bounds assume additive white Gaussian noise (AWGN), which does not hold for seismic data. To overcome these problems, alternative expressions have been proposed, which yield comparable estimates as CRB and ZZB but are solely based on the S/N and the dominant period in the data. Moreover, a recipe to correct the S/N and account for the difference between the seismic noise and AWGN has been provided. For a case study of downhole microseismic monitoring, it is determined that the new expressions provide station-dependent arrival-time uncertainties, which are used as weights to improve source location uncertainties.

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Effect of Scan Time on Neuro 18F-Fluorodeoxyglucose Positron Emission Tomography Image Generated Using Deep Learning

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2021.3316 ◽

2021 ◽

Vol 11 (3) ◽

pp. 681-687

Author(s):

Jaewon Kim ◽

Sungsik Kang ◽

Konsu Lee ◽

Jin Ho Jung ◽

Garam Kim ◽

...

Keyword(s):

Deep Learning ◽

Performance Test ◽

Signal To Noise Ratio ◽

Ground Truth ◽

High Signal ◽

Ct Scanner ◽

Signal To Noise ◽

Scan Time ◽

Mean Square Errors

The purpose of this study was to generate the PET images with high signal-to-noise ratio (SNR) acquired for typical scan durations (H-PET) from short scan time PET images with low SNR (L-PET) using deep learning and to evaluate the effect of scan time on the quality of predicted PET image. A convolutional neural network (CNN) with a concatenated connection and residual learning framework was implemented. PET data from 27 patients were acquired for 900 s, starting 60 minutes after the intravenous administration of FDG using a commercial PET/CT scanner. To investigate the effect of scan time on the quality of the predicted H-PETs, 10 s, 30 s, 60 s, and 120 s PET data were generated by sorting the 900 s LMF data into the LMF data acquired for each scan time. Twenty-three of the 27 patient images were used for training of the proposed CNN and the remaining four patient images were used for test of the CNN. The predicted H-PETs generated by the CNN were compared to ground-truth H-PETs, L-PETs, and filtered L-PETs processed with four commonly used denoising algorithms. The peak signal-to-noise ratios (PSNRs), normalized root mean square errors (NRMSEs), and average regionof- interest (ROI) differences as a function of scan time were calculated. The quality of the predicted H-PETs generated by the CNN was superior to that of the L-PETs and filtered L-PETs. Lower NRMSEs and higher PSNRs were also obtained from predicted H-PETs compared to the L-PETs and filtered L-PETs. ROI differences in the predicted H-PETs were smaller than those of the L-PETs. The quality of the predicted H-PETs gradually improved with increasing scan times. The lowest NRMSEs, highest PSNRs, and smallest ROI differences were obtained using the predicted H-PETs for 120 s. Various performance test results for the proposed CNN indicate that it is possible to generate H-PETs from neuro FDG L-PETs using the proposed CNN method, which might allow reductions in both scan time and injection dose.

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