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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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InSAR Time Series Analysis (2018-2021) for Volcanic Monitoring in Northern Chile

Authors: Liu, Fei; Elliott, John Ross; Ebmeier, Susanna K; Craig, Timothy James; Hooper, Andrew; Lizama, Camila Novoa; Delgado, Francisco;

InSAR Time Series Analysis (2018-2021) for Volcanic Monitoring in Northern Chile

Abstract

This dataset is for the paper "First onset of unrest captured at Socompa: A Recent Geodetic Survey at Central Andean volcanoes in Northern Chile" which is published in GRL: https://doi.org/10.1029/2022GL102480. InSAR Data: The folder of InSAR_149A.rar stores the InSAR time series analysis dataset on ascending track 149. The 'Imagedate' folder stores the empty *.rslc files to indicate the date of each SLCs. Data_Asc.mat stores the main InSAR time series data, which includes the UTC time of the acquisition (for accurate time calculation), the length of perpendicular baselines (unit is meter), the number of days counting from the first epoch, the unwrapped time series data (ifg), the unwrapped time series data with GACOS correction (ifg_aps), the look angles (la, unit is rad), and lat&lon. parms.mat stores the parameters used during the data processing by StaMPS. semi_fit.mat stores the results of the semi-variogram fitting of each interferogram on time series. It provides two versions for the original dataset (semi) and the GACOS-corrected dataset (semi_aps). This file is mainly used to weight the data during the time series fitting. runTSA.m, the main function to run the InSAR time series fitting. See more details in the Code part. The folder of InSAR_156D.rar stores the same content as the InSAR_149A.rar but for descending track 156. Code: This folder contains the codes of the InSAR time series fitting for this dataset, and the GBIS software. TSA_findref.m, this function is used to search the reference point of the InSAR data. TSA_EQ_fit.m, is the main function to perform InSAR time series fitting. rb_pixel_fit.m, is the robust way to fit the linear model. TSA_EQ_pixel.m, is the function used to plot the results. To perform the InSAR time series fitting, you need to put these four functions under your Matlab path, and then run the runTSA.m function in the data folder. The GBIS folder stores the updated version of the GBIS software, which allows you to perform the pCDM, CDM, and pECM. The core functions of these models are provided by Dr. Mehdi Nikkhoo, and you could find them here: https://www.volcanodeformation.com/software GBIS_Modelling_Results: This folder stores the data of InSAR and GPS joint inversion for Socompa Uplift. The folder Socompa stores the modelling results using the models of Okada(D), pECM(E), Mogi(M), pCDM(N), and Yang(Y), respectively. GPS_data.txt stores the cumulative displacements and the uncertainties of the SOCM station in three directions. Socompa.inp is the configuration file for GBIS running. Vol_asc.mat and Vol_asc_ds.mat stores the original and the downsampled ascending data, while Vol_dsc.mat and Vol_dsc_ds.mat store those of descending. Many thanks for using our dataset and please let me know if you have any further questions!

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Keywords

InSAR, Socompa, Northern Chile, Volcanic Deformation

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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