Improved visualization of large temporal series for the evaluation of good environmental status

作     者：Miralles, Ramon Lara, Guillermo Gosalbez, Jorge Bosch, Ignacio Leon, Antonio 

作者机构：Univ Politecn Valencia Inst Telecommun & Multimedia Applicat iTEAM Valencia Spain Univ Politecn Valencia Dept Comunicac Valencia Spain 

出 版 物：《APPLIED ACOUSTICS》 (应用声学)

年 卷 期：2019年第148卷

页      面：55-61页

核心收录：

学科分类：07[理学] 082403[工学-水声工程] 08[工学] 070206[理学-声学] 0824[工学-船舶与海洋工程] 0702[理学-物理学] 

基　　金：Fundacion Biodiversidad European Commission -DG ENV [11.0661/2016/748066/SUB/ENV.C2] 

主　　题：Big data visualization Acoustic images Ambient noise characterization Submarine environment Surveillance Data reduction Hough transform 

摘      要：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. (C) 2018 Elsevier Ltd. All rights reserved.