01783nas a2200193   4500008004100000022001300041245010000054210006900154260001600223300001200239490000800251520099800259100002101257700002001278700002001298700001901318700001901337856023301356       2019                        eng d  a0003682X00aImproved visualization of large temporal series for the evaluation of good environmental status0 aImproved visualization of large temporal series for the evaluati  cJan-05-2019  a55 - 610 v1483 a<p>Passive acoustic monitoring of underwater sounds is an emerging discipline that can be used to guarantee that anthropogenic noise meets acceptable limits, to detect the presence of cetacean species, and to ensure sustainable exploitation of our oceans and seas. In this scenario, graphical representation techniques play a key role in helping to reveal seasonal structures of human made noises. Nevertheless, for very long temporal series, it might be challenging to find a graphic visualization technique that allows representing a time range that is long enough to capture these seasonal events, while at the same time preserving short isolated events. We propose a framework for the creation of such visualization techniques and analyze the different stages involved: data reduction, color encoding, and signal processing on graphs. All of this is applied to data from deployments in two marine protected areas in order to provide an acoustic panorama and identify seasonal events.</p>
1 aMiralles, Ramón1 aLara, Guillermo1 aGosalbez, Jorge1 aBosch, Ignacio1 aLeón, Antonio  uhttps://linkinghub.elsevier.com/retrieve/pii/S0003682X18306261https://api.elsevier.com/content/article/PII:S0003682X18306261?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0003682X18306261?httpAccept=text/plain