I am using 120 x one hour acoustic files ( according to "Guidelines for the use of acoustic indices in environmental research, https://doi.org/10.1111/2041-210X.13254) to describe my soundscapes using the maad.util.plot_features in python. This means I take the hourly average for my indices (ACI, NDSI, BI, Hf, ADI, AEI) over a day. Additionally I plot the mean spl in each 1000 Hz frequency domain from 0-22000 kHz, for each hour over a day, with
Can this method represent some characteristics (i.e the variations of selected indices ACI, NDSI, BI, Hf, ADI, AEI) for a day, by simply taking their mean value?
yes I described it wrong, what I actually wanted to say and what I actually do is that I use 120 hours (not minutes), or about 5 days of one minute continuous recordings (=5x24hr=120hr=7200min).
In order to find a motive of the daily sound variations of a soundscape , and describe it in a general way (in my case mixed cupressus/pine forests ) I resample the calculated indices on a daily average for every hour. This means the average hourly rate from all five days on a 24hr graph (I post a relevant graph). My question is if this method is sufficient or if there is another suggested methodology.
Regards,
Daily average of selected indices from 7200 minutes recording
