摘要
声景包含来自生物、地理和人类社会的丰富信息,可以作为反映生态系统特征的一个综合性指标。声景的监测是环境监测与管理的重要一环,其产生的声景数据已逐渐在声环境质量主观评价、声景规划、物种识别、生物多样性评估、人体身心健康评价等方面得到应用,数据价值日益凸显。目前市场上能进行声景数据采集的设备技术参数各不相同,设备的使用方式也多样,不利于研究结果的对比。文章详细梳理了声景数据采集设备的关键指标,包括传声器的灵敏度、频率响应、采样率等。总结了开放空间的人工调查、大尺度的参与式感知和固定站点的长期监测三大常用的声景数据采集模式的实践方法与应用场景对比。面对日益丰富的声景大数据,急需从数据格式、数据存储方式和元数据信息等入手实现数据采集的标准化,从而完善声景大数据的管理和共享,针对生物发声的特殊性,还需要充分考虑其生物生理等特征。同时对未来声景监测网络化发展进行了展望,期待推动我国声景数据采集技术的完善。
Soundscape contains rich information from biology,geography,and human society,and it is a comprehensive index of the ecosystem.The monitoring of soundscape can thus be a significant content of environmental monitoring and management,and the generated soundscape data has been gradually applied in subjective evaluation of acoustic environment quality,soundscape planning,species identification,biodiversity assessment,human physical and mental health evaluation,and other aspects,with the value of which has become increasingly prominent.Nowadays,the technical parameters of the equipment that can collect soundscape data vary in the market.The ways to use the equipment are also diverse,which is not beneficial for the comparison of research results.The paper describes the critical indicators of the soundscape data acquisition equipment in detail,including the sensitivity,frequency response,and sampling rate of the microphone.The practice methods and advantages and disadvantages of three common soundscape data acquisition patterns,including manual investigation in open spaces,participatory sensing on a large scale,and long-term monitoring with fixed stations,are also summarized.With the increasing soundscape data,these issues are urgent to be considered to standardize data acquisition,including data format,data storage method,and metadata information,to improve the management and sharing of soundscape data.The biological and physiological characteristics should be taken into account regarding the heterogeneity of organisms’vocalization.Meanwhile,the future direction of the soundscape monitoring network was presented,which hopes to improve the acquisition techniques of soundscape data in our country.
作者
王静怡
李春明
林婴伦
翁辰
焦亚冉
李大锋
WANG Jingyi;LI Chunming;LIN Yinglun;WENG Chen;JIAO Yaran;LI Dafeng(Key Lab of Urban Environment and Health,Institute of Urban Environment,Chinese Academy of Sciences,Xiamen 361021,China;University of Chinese Academy of Sciences,Beijing 100048,China;Fujian Agriculture and Forestry University,Fuzhou 350002,China;Guangdong Academy of Forestry,Guangzhou 510520,China)
出处
《生态科学》
CSCD
北大核心
2024年第4期219-225,共7页
Ecological Science
基金
福建省科技计划项目(2021Y0071)
中国科学院战略性先导科技专项(A类)资助(XDA23030402)
中国科学院国际合作局国际伙伴计划(132C35KYSB20200007)。
关键词
声环境
声景生态学
物种识别
生物多样性
采集技术
sound environment
soundscape ecology
species identification
biodiversity
acquisition techniques