Geodetic data and modelling files for Mauna Loa volcano, Hawaii used in Varugu & Amelung, 2021.
Description
This repository contains data used in the publication “Varugu, B., Amelung, F. (2021) Southward growth of Mauna Loa’s dike-like magma body driven by topographic stress” [In Review]. Please contact the author and seek permission for re-use in public.
The repository has the following files:
InSAR data:
Data saved as roi_pac (.unw) and MintPy (.he5) formats for the overall and multiple time periods used in the study. InSAR ascending datasets correspond to relative track 10 and descending datasets correspond to track 91 of Cosmo SkyMed imagery. The data is obtained through Group on Earth Observation’s (GEO) Geohazard Supersites and Natural Laboratory Initiative (GSNL). For raw data, please refer to https://web-services.unavco.org/brokered/ssara/gui.
GBIS inputs:
InSAR velocity data is converted into .mat files for input into Geodetic Bayesian Inversion Software – GBIS [Bagnardi et al.2018] for modelling. Please refer to https://comet.nerc.ac.uk/gbis/ to download the software and get a description of input data.
Files
GBIS_modelling_inputs_Varugu_Amelung_2021_MaunaLoa.zip
Additional details
References
- Yunjun, Z., H. Fattahi, F. Amelung (2019). Small baseline InSAR time series analysis: Unwrapping error correction and noise reduction, Computers & Geosciences, 133, 104331, doi:10.1016/j.cageo.2019.104331
- Bagnardi, M., Hooper, A. (2018). Inversion of surface deformation data for rapid estimates of source parameters and uncertainties: A Bayesian approach. Geochemistry, Geophysics, Geosystems, 19(7), 2194-2211. doi:10.1029/2018GC007585