地球科学进展 ›› 2014, Vol. 29 ›› Issue (6): 748 -755. doi: 10.11867/j.issn.1001-8166.2014.06.0748

学科发展与研究 上一篇    下一篇

海洋浮游生物图像观测技术及其应用
孙晓霞, 孙松 *   
  1. 中国科学院海洋研究所胶州湾海洋生态系统国家野外科学观测研究站, 海洋生态与环境科学重点实验室, 山东 青岛 266071
  • 出版日期:2014-06-10
  • 通讯作者: *通讯作者:孙松(1959-)男,山东莱阳人,研究员,主要从事海洋生态学研究. E-mail:sunsong@qdio.ac.cn
  • 基金资助:

    中国科学院战略先导科技专项“热带西太平洋典型区域生物多样性与生物生产过程”(编号:XDA11030204); 科技部创新方法工作专项“海洋科学创新方法研究”(编号:2011IM010700) 资助

Automated Marine Plankton Image Techniques and Its Application

Sun Xiaoxia, Sun Song   

  1. Jiaozhou Bay Marine Ecosystem Research Station, Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
  • Online:2014-06-10 Published:2014-06-10

浮游生物图像自动识别技术是当前海洋浮游生态学的研究热点。该技术结合水体成像系统和自动识别软件,能够对浮游生物的种类组成和丰度进行快速自动识别和定量分析,从而获得关于浮游生物分布和丰度更及时、更准确的信息,为大尺度、实时、连续地研究浮游生物分类学和生态学特征提供了一种有效手段。重点分析了当前国际上浮游生物图像识别技术研究的最新进展、主要应用领域、存在的问题以及未来的发展方向,旨在进一步推进该技术在我国近海及大洋浮游生态学及相关研究领域中的应用。

Automated marine plankton image identification technique is a hot issue in the research of marine plankton ecology. By combining imaging systems and automatic classification software, these techniques are good at rapid identification and quantitative analysis on composition and abundance of plankton samples, which provides an efficient way to study the ecology and taxonomy of plankton continuously on a large scale. The development of planktonimaging systems, including ZooScan, Video Plankton Recoder, Underwater Video Profiler, FlowCAM, CytoSense and Holography, was reviewed. The techniques for automated identification of plankton images were introduced accordingly. The application of this technique in the field of marine ecosystem long term observation, size spectra and plankton biomass estimation was analyzed. The perspective and challenge were proposed finally. It is anticipated to promote the application of this technique in the research of coastal and oceanic plankton ecology and relevant fields in China.

中图分类号: 

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