Imaging Submarine Fault Zones Using Reflected S-waves Extracted by Ambient Noise Interferometry from Distributed Acoustic Sensing

1. Data Description This dataset contains the processed data and/or scripts used to generate the figures in the aforementioned publication. The data is organized and named according to the figures in the paper for straightforward reference. Publication Title: Imaging Submarine Fault Zones Using Reflected S-waves Extracted by Ambient Noise Interferometry from Distributed Acoustic SensingCorresponding Author: [Zhufeng Lu/Co-author Xiaodong Yang and Jizhong Yang]Contact Email: [ [e-mail]]2. Data Structure and File Naming ConventionAll data files are named using the convention Figure[Figure Number][Sub-figure Letter], which corresponds directly to the figures presented in the manuscript. Examples:Figure2a.mat: Contains the data used to plot Figure 2a. Important Note: Some figures may be composed of multiple sub-figures (e.g., a, b, c). The data for each panel is provided in a separate file. 3. File Format DescriptionData Files: The primary data files are in [.mat / .csv / .h5 / .txt] format. .mat: MATLAB data file. Can be loaded in MATLAB using the load('filename.mat') command. For use in Python, you can use scipy.io.loadmat('filename.mat'). .csv: Comma-separated values. Can be opened with any text editor, spreadsheet software (Excel, Google Sheets), or imported into data analysis environments (Python/pandas, R). .h5: Hierarchical Data Format. Suitable for large and complex datasets. Can be read using h5py in Python or specialized tools in MATLAB and other languages. 4. CodesThe repository also includes MATLAB scripts used for data processing and figure generation. These scripts are organized by data type and plotting purpose (e.g., Figure 4), allowing users to reproduce the main results of the paper. ACFs.m is used to visualize all ambient-noise autocorrelation functions (ACFs). NCFs.m is used to plot noise cross-correlation functions (NCFs), as shown for example in Figure 6. VSGs.m and Dispersion_energy.m are used together to generate virtual shot gathers from the noise cross-correlations and to compute the corresponding dispersion-energy images (e.g., Figure 5). Plt_tf.m is a general plotting routine for both time-domain and frequency-domain representations of the data and is used to produce figures such as Figure 2a, 2b, and Figure 7.