Last chance! 50% off unlimited learning
Sale ends in
The function picks (identifies) events from continuous data using the kurtosis of the signal, and when it reaches beyond a defined threshold value. The end of an event is determined by the signal-to-noise ratio (SNR)
pick_kurtosis(
data,
on,
off = 1,
dur_min = 0,
dur_max,
window_kurt,
window_amp,
time,
dt
)
data.frame
, picked events.
eseis
object, numeric
vector or list of
objects, data set to be processed.
Numeric
value, kurtosis threshold that defines the
onset of an event.
Numeric
value, ratio of average post and pre event
signal amplitude inside a running window. Default is 1
.
Numeric
value, minimum duration of the event. This
is required as the kurtosis routine tends to identify multipe picks in
the beginning of an event.
Numeric
value, maximum duration of the event. This
value can be omitted but would increase computational speed as it
determines the length of samples to look for the amplitude ratio that
signals the end of an event
Numeric
value, size of the running window (in
number of samples) in which the kurtosis is calculated.
Numeric
value, size of the running window (in
number of samples) in which the running mean is calculated.
POSIXct
vector, time vector of the signal(s). If not
provided, a synthetic time vector will be created.
Numeric
value, sampling period. If omitted, either
estimated from time
or set to 0.01 s (i.e., f = 100 Hz).
Michael Dietze
Further reading:
Baillard, C., Crawford, W.C., Ballu, V., Hibert, C., Mangeney, A., 2014. An automatic kurtosis-based p- and s-phase picker designed for local seismic networks. Bull. Seismol. Soc. Am. 104 (1), 394–409.
Hibert, C., Mangeney, A., Grandjean, G., Baillard, C., Rivet, D., Shapiro, N.M., Satriano, C., Maggi, A., Boissier, P., Ferrazzini, V., Crawford, W., 2014. Automated identification, location, and volume estimation of rockfalls at Piton de la Fournaise Volcano. J. Geophys. Res. Earth Surf. 119 (5), 1082–1105. http://dx.doi.org/10.1002/2013JF002970.
## load example data set
data(rockfall)
## preprocess signal (aggregate to increase speed, filter, envelope)
s <- signal_aggregate(data = rockfall_eseis, n = 4)
s <- signal_filter(data = s, f = c(5, 20), lazy = TRUE)
e <- signal_envelope(data = s)
## pick events based on signal kurtosis
p <- eseis::pick_kurtosis(data = e,
window_kurt = 200,
on = 15,
off = 5,
dur_min = 10,
dur_max = 90,
window_amp = 300)
p$picks
Run the code above in your browser using DataLab