Besides, it includes modules to plot the results and conduct H- k stacking directly. The toolbox can automatically import local SAC data, calculate their RFs, and selects high-quality results with convenient keyboard shortcuts.
#Enable rf toolbox in matlab software#
SplitRFLab, as an improved version of SplitLab toolbox, is a GUI-based software for RF and some other seismic data analysis under MATLAB environment. We also add the H- k stacking module (Zhu and Kanamori 2000) that obtains the crustal thickness and the average v P/ v S in the crust under a station. Therefore, in this study, we integrate the RF analysis modules in the SplitLab toolbox, which inherits many nice functions for quick data preprocessing and convenient estimation of the final results. However, it lacks some nice functions such as automatically matching the local data with the earthquake catalog and interactively checking the results. FuncLab (Eagar and Fouch 2012) is a similar GUI-based toolbox for RF analysis. The GUI module of the toolbox provides very convenient and fast way to estimate the results interactively and efficiently, which makes it one of the most popular tools in shear-wave splitting analysis. Users may preprocess the waveforms (e.g., removing average and linear trends, filtering with certain filters) quickly with defined keyboard shortcuts, which are then used for shear-wave splitting analysis and other related purposes.
#Enable rf toolbox in matlab windows#
It first links SAC data in the local directory to the earthquake catalog automatically, and then cuts the waveform in proper time windows by calculating the theoretical arrival times with Taup Toolkit (Crotwell et al.
2008) developed under MATLAB environment by French scientist is an open-source GUI toolbox for shear-wave splitting analysis. 2013), the FuncLab toolbox for RF analysis (Eagar and Fouch 2012), and SplitLab toolbox for shear-wave splitting analysis (Wüstefeld et al. Thanks to the rapid development of computer science, more GUI-based seismological softwares bring much convenience and power efficiency in seismic data analysis, such as the AIMBAT for picking arrival times (Lou et al.
However, users have to write many small codes to obtain the preprocessed data first, e.g., selecting teleseismic events, removing average and linear trend from the waveforms, filtering, and selecting phases in proper time windows. These codes generally import the preprocessed seismic data to calculate RFs from teleseismic radial and vertical components. Many open-source codes have been released for RF analysis in recent years, such as the CPS 330 system, the RF module under Python, and the process RFmatlab module under MATLAB. Zhu and Kanamori ( 2000) further proposed the H- k stacking method with a grid-search algorithm that determines the v P/ v S ratio and Moho depth ( H) with the obtained P-wave RFs at a station, which is very important in determining one-dimensional structure in the Earth. The routines of RF analysis include the following procedures: (a) selecting the proper events (e.g., epicentral distance, magnitude) from the earthquake catalog and matching them with seismic data in the local directory (b) preprocessing the waveforms, such as removing average shift of amplitude, removing the linear trend, and filtering the waveforms with certain bandpass filters (c) picking P-wave arrivals and (d) calculating P-wave RFs by deconvolving the radial component with the vertical component. 2002), which makes it one of the most popular methods in seismology. The RF method is stable and efficient in determining the crustal and upper mantle structures (e.g., Dueker and Sheehan 1997 Kind et al. The time delay between the Ps converted phase and direct P-wave is sensitive to the depth of the velocity discontinuities and the average S-wave velocity above it (Zhu and Kanamori 2000). P-wave RF deconvolves the radial component with the vertical component and obtains the Ps phase converted at velocity discontinuities (e.g., Moho) in the Earth. Receiver function (RF) analysis, proposed by Langston ( 1979), is one of routine tools to determine the one-dimensional structure of the crust and mantle. Seismology is becoming the most popular tool in studying the interior structure of the Earth thanks to the development of digital seismology and the rapidly accumulated seismic data in recent years.
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