# The Contribution of Near-Surface Geophysics for the Site Characterization of Seismological Stations
## 2 Methodology
### Seismic Method
#### 2.1.2 Processing  
In the present study, we employed the _GEOPSY_ software, which was developed within the framework of the European Research Project SESAME/2003-2007 [52]. This software provides important parameterization capabilities concerning window selection and smoothing filters. The input signal is the background ground noise, i.e., the ground motion caused by distant excitations and waves arriving at the recording site after being scattered, particularly within a volume around the site, thus providing a type of sampling of the subsurface of the recording area. Therefore, various environmental or local anthropogenic noises, such as wind, footsteps close to the recording instrument, passing cars, etc., or even an earthquake, are unwanted noises that could pose a problem in the application of the HVSR technique with ambient noise data. For that reason, the _GEOPSY_ software provides the possibility of using \"anti-triggering\" filters, employing the classical Short-term Average to Long-term Average \"STA/LTA\" technique [53] used in seismology to detect the arrival of seismic waves by estimating the \"Signal-to-Noise Ratio\" (SNR). A sharp increase in SNR to values above a threshold, usually 2.0-3.0, is an indication that an impulsive signal of high amplitude is entering the window under consideration. In the application of the HVSR technique, the arrival of a strong \"signal\" is an indication that the following window contains unwanted \"noise\", and thus should be rejected (anti-triggering). In the _GEOPSY_ software, both the length of the STA and LTA windows and the minimum and maximum STA/LTA ratios (Figure 2) can be configured to determine whether a specific window is used or not. For the present study, which explores the site effects at the locations of permanent seismological stations, we used 6 h long recordings during the relatively quiet hours of the night to early morning to study the HVSR of microtremors. The recordings were detrended, and a high-pass Butterworth filter with a corner frequency of 0.1 Hz was applied in the original recordings to remove long-period noise. After testing windows of various lengths, we chose to apply measurements in 60 s long windows, with a 5% overlap permitted for consecutive ones. This achieves smoother results than the 30 s window and is small enough to permit a large number of different windows. An STA/LTA anti-triggering filter was applied to both the raw waveform and a 5.0 Hz high-pass filtered version to detect earthquakes or other instances of unwanted transient noise. An average of around 100 windows with the least amount of transient noise was selected at each station for the application of the HVSR method. Figure 2: Example from the construction of HVSR curves, for the recordings of station MDRA on 5 November 2022. (**a**) Selection of 81 windows of 60 s length each (vertical colored rectangles) from 6 h continuous records using STA/LTA anti-trigger criteria; (**b**) individual HVSR spectra, with the color of each line corresponding to the colors of the respective windows in panel (**a**), average spectra (solid black line), and respective errors (dashed black lines). The vertical light and dark gray bands indicate the frequency bands corresponding to the dominant peak frequency, \(f_{p}\); (**c**) a simplified figure of the average HVSR curve (bold blue line), including error bars for each frequency (vertical thin blue lines). The semi-transparent rectangle corresponds to the frequency range depicted by the light and dark gray vertical bands in panel (**b**), with its height corresponding to the average minimum and maximum amplifications for this specific frequency range, with the average frequency depicted by a yellow (with blue outline) diamond symbol. The blue circle indicates the global peak frequency of the average HVSR spectrum. The red circles mark the local maxima of the HVSR curve, corresponding to secondary peaks, with the frequencies labeled with red text.