INTRODUCTION:
The shared code and data here is an example used for coseismic deforamtion field reconstruction via InSAR time series fitting. InSAR data was processed by LiCSAR (Lazecky et al., 2020) and StaMPS software (Hooper et al., 2007), using the descending track 006 InSAR time series data from Oct 2014 to Sep 2019 in Iran. We used this data to detect and model the shallow earthquakes happened in Iran, following the Mw 7.3 mainshock in 2017.
FILES:
slclist.mat: the dates of SLC images
parms_aps.mat: StaMPS file, here is used to read the UTC time of the acquistion
ref*.mat: reference pixels, with and without GACOS tropospheric corretion (Yu et al., 2018). Storing the information of reference area, including the centre location and radius of the reference circle area, number of referencing pixels, RMSE of a linear fitting to the reference pixels, and the LOS of reference pixels.
TSA_ifg_ds.mat: the time series data on deformation area, downsampled by ratio 10 for quick data sharing
semi_fit.mat: store the semi-variogram fitting (Webster & Oliver, 2007) results using the GBIS software (Bagnardi & Hooper, 2018), later used as the covariance matrix. Here, the sill values of the mainshock interferogram is mannually set as the avarage values of all other interferograms, as the large coseismic deformations greatly bias the estimation.
runTSA.m: the main function
TSA_EQ_fit.m: the fitting function
TSA_EQ_pixel.m: the plotting function used to plot the results
HOW TO RUN:
Simply run the runTSA.m and the reconstructed coseismic deformation fields will pop out, and you can further click the 'TSA_EQ' button at the bottom left cornor to plot the time series data for individual pixels.
CITATION:
Please cite the following paper if you use our code:
Liu, F., Elliott, J. R., Craig, T. J., Hooper,A., & Wright, T. J. (2021). Improving the resolving power of InSAR for earthquakes using time series: A case study in Iran. Geophysical Research Letters, 48, e2021GL093043. https://doi.org/10.1029/2021GL093043
Fei Liu, Sep 2021