Pre-processing?

[iandalekelly]

Hi Joseph,

Thanks for putting together this amazing package!

I'm doing some initial exploration with a raw data set collected from East Antarctica and encountered some 'interesting' spectra: Being a relative beginner with HVSR processing, I wanted to ask what your recommended data pre-processing steps are before HVSR analysis in hvsrpy, beyond the implemented time-domain filtering and spectral smoothing? I understand instrumental response correction may not be necessary if responses across components are similar, but can, e.g., detrending, static shift corrections be implemented in hvsrpy? What are the typical steps you take? I'd be grateful for any advice you could give!

Cheers,

Ian

[jpvantassel]

Hi @iandkelly,

Glad to hear you are finding hvsrpy useful in your work. Regarding pre-processing, as you noted, band-pass filtering is provided but optional with the default (and my preference) being not to band-pass filter the time series. In addition, detrending of the time series is performed automatically with hvsrpy to avoid artifacts in the frequency spectra. Yes, you are correct, instrument response correction is unnecessary if the three components have similar responses. Other than the aforementioned I am not aware of any other pre-processing techniques for HVSR; if there is something you are looking for specifically I can considering adding it in an upcoming release.

Additionally, it may be of interest to you to see (Vantassel et al., 2021) that contains a brief discussion of the processing parameters that most-significantly control the HVSR calculation (e.g., window length, smoothing coefficient, and method for combining the horizontal spectra) with some examples.

All the best, Joe