地球科学进展 ›› 2022, Vol. 37 ›› Issue (8): 863 -870. doi: 10.11867/j.issn.1001-8166.2022.046

研究论文 上一篇    下一篇

利用双平行激光器法获取深海底栖生物大小及其误差分析
王维波 1 , 2( ), 何雪宝 3, 靖春生 1 , 2, 林辉 4   
  1. 1.自然资源部第三海洋研究所海洋动力学研究室,福建 厦门 361005
    2.福建省海洋物理和地质过程 重点实验室,福建 厦门 361005
    3.自然资源部第三海洋研究所海洋生物多样性研究室,福建 厦门 361005
    4.自然资源部第三海洋研究所海洋生态环境预警监测研究室,福建 厦门 361005
  • 收稿日期:2022-03-08 修回日期:2022-06-04 出版日期:2022-08-10
  • 基金资助:
    自然资源部第三海洋研究所基本科研业务(海三科2016023);全球变化与海气相互作用二期专项(GASI-01-NPAC-STsum)

Remote Measurement and Error Analysis of Deep-sea Benthic Megafauna Using Paired-Laser Photogrammetry

Weibo WANG 1 , 2( ), Xuebao HE 3, Chunsheng JING 1 , 2, Hui LIN 4   

  1. 1.Ocean Dynamic Laboratory, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China
    2.Fujian Provincial Key Laboratory of Marine Physical and Geological Processes, Xiamen 361005, China
    3.Laboratory of Maine Biodiversity Research, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China
    4.Laboratory of Marine Ecological Environment Early Warning and Monitoring, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China
  • Received:2022-03-08 Revised:2022-06-04 Online:2022-08-10 Published:2022-09-13
  • About author:WANG Weibo (1986-), male, Shucheng County, Anhui Province, Associate professor. Research areas include remote sensing and physical oceanography. E-mail: wangwb@tio.org.cn
  • Supported by:
    the Scientific Research Foundation of the Third Institute of Oceanography, MNR, China(2016023);The Global Change and Air-sea Interaction II(GASI-01-NPAC-STsum)

摄像拖体是深海底栖生物调查中一个有力的新技术,具有调查范围广、持续时间长、原位无破坏等特点。已有研究较少关注自动化识别和误差分析。选取中国大洋协会第50航次太平洋摄像拖体观测图像,构建了深海生物个体形态测量方法,并对摄像拖体进行误差分析。该系统成功获取了太平洋深处12幅海参形态大小信息,观察到长达70.8 cm的绿色巨型海参。通过分析系统误差、安装误差以及观测误差发现激光器彼此不平行对观测结果影响最大。摄像托体摆动是观测中常见的误差来源,其订正方法依据理论分析获得。自动化识别和系统地分析摄像托体误差来源有利于合理得制定深海生物调查技术标准,推动深海底栖生物大范围普查。

Image sampling of megafauna using a towed camera is immensely beneficial in deep-sea biological investigations because of the benefits of a wide investigation range, long duration, and no risk of specimen destruction. However, its automatic identification and error analysis are still understudied. A deep-sea megafauna body size measurement method was developed using towed camera observation photographs from the COMRA 50th cruise. We successfully obtained body size information of 12 sea cucumbers in the Pacific Ocean and observed a green giant sea cucumber 70.8 cm long. We examined the towed-camera system, installation, and observation errors, which imply that nonparallel lasers cause the most significant errors. A technique for correcting the inaccuracy caused by the swing of the towed camera was developed. Based on the above results, it is beneficial to logically develop the technical requirements for the examination of deep-sea megafauna with a towed camera and to encourage extensive investigation of deep-sea benthic megafauna.

中图分类号: 

1 LI Xinzheng, DONG Dong, KOU Qi, et al. Advances in research on deep-sea macrobenthic biodiversity with the progress in China[J]. Acta Oceanologica Sinica, 2019, 41(10): 169-181.
李新正, 董栋, 寇琦, 等. 深海大型底栖生物多样性研究进展及中国现状[J]. 海洋学报, 2019, 41(10): 169-181.
2 WANG Fengping, CHEN Yunru. Progress and prospect in deep biosphere investigation[J]. Advances in Earth Science, 2017, 32(12): 1 277-1 286.
王风平, 陈云如. 深部生物圈研究进展与展望[J]. 地球科学进展, 2017, 32(12): 1 277-1 286.
3 SNELGROVE P V R. An ocean of discovery: biodiversity beyond the census of marine life[J]. Planta Medica, 2016, 82(9/10): 790-799.
4 ALEXANDER V, MILOSLAVICH P, YARINCIK K. The census of marine life—evolution of worldwide marine biodiversity research[J]. Marine Biodiversity, 2011, 41(4): 545-554.
5 AUSUBEL J, CRIST D, WAGGONER P. First census of marine life 2010[M]// Census of Marine Life. Washington, D. C., 2010.
6 DUNLOP K M, KUHNZ L A, RUHL H A, et al. An evaluation of deep-sea benthic megafauna length measurements obtained with laser and stereo camera methods[J]. Deep Sea Research Part I: Oceanographic Research Papers, 2015, 96: 38-48.
7 MACDONALD I R, BLUHM B A, IKEN K, et al. Benthic macrofauna and megafauna assemblages in the Arctic deep-sea Canada Basin[J]. Deep Sea Research Part II: Topical Studies in Oceanography, 2010, 57(1/2): 136-152.
8 LAMPITT R S, BILLETT D S M, RICE A L. Biomass of the invertebrate megabenthos from 500 to 4100 m in the northeast Atlantic Ocean[J]. Marine Biology, 1986, 93(1): 69-81.
9 PIEPENBURG D, BLACKBURN T H, VONDORRIEN C F, et al. Partitioning of benthic community respiration in the Arctic (northwestern Barents Sea)[J]. Marine Ecology Progress Series, 1995, 118(1/2/3): 199-214.
10 PIEPENBURG D, CHERNOVA N V, von DORRIEN C F, et al. Megabenthic commmunities in the waters around svalbard[J]. Polar Biology, 1996, 16(6): 431-446.
11 WANG Pinxian. Deep-sea coral forest[J]. Advances in Earth Science, 2019, 34(12): 1 222-1 233.
汪品先. 深水珊瑚林[J]. 地球科学进展, 2019, 34(12): 1 222-1 233.
12 Meyer K S, Bergmann M, Soltwedel T. Interannual variation in the epibenthic megafauna at the shallowest station of the HAUSGARTEN observatory (79°N, 6°E)[J]. Biogeosciences Discussions, 2012, 9(12):3 479-3 492.
13 SSWAT M, GULLIKSEN B, MENN I, et al. Distribution and composition of the epibenthic megafauna north of Svalbard (Arctic)[J]. Polar Biology, 2015, 38(6): 861-877.
14 BERGMANN M, LANGWALD N, ONTRUP J, et al. Megafaunal assemblages from two shelf stations west of Svalbard[J]. Marine Biology Research, 2011, 7(6): 525-539.
15 LAUERMAN L M L, KAUFMANN R S, SMITH K L. Distribution and abundance of epibenthic megafauna at a long time-series station in the abyssal northeast Pacific[J]. Deep Sea Research Part I: Oceanographic Research Papers, 1996, 43(7): 1 075-1 103.
16 RUHL H A, BETT B J, HUGHES S J M, et al. Links between deep-sea respiration and community dynamics[J]. Ecology, 2014, 95(6): 1 651-1 662.
17 LINLEY T D, LAVALEYE M, MAIORANO P, et al. Effects of cold-water corals on fish diversity and density (European continental margin: Arctic, NE Atlantic and Mediterranean Sea): data from three baited lander systems[J]. Deep Sea Research Part II: Topical Studies in Oceanography, 2017, 145: 8-21.
18 LAVALEYE M, DUINEVELD G, BERGMAN M, et al. Long-term baited lander experiments at a cold-water coral community on Galway Mound (Belgica Mound Province, NE Atlantic)[J]. Deep Sea Research Part II: Topical Studies in Oceanography, 2017, 145: 22-32.
19 D’ONGHIA G, CAPEZZUTO F, CARLUCCI R, et al. Using a benthic lander to explore and monitor vulnerable ecosystems in the Mediterranean Sea[J]. Acta IMEKO, 2018, 7(2): 45.
20 RIZZO A A, WELSH S A, THOMPSON P A. A paired-laser photogrammetric method for in situ length measurement of benthic fishes[J]. North American Journal of Fisheries Management, 2017, 37(1): 16-22.
21 BERGERON P. Parallel lasers for remote measurements of morphological traits[J]. The Journal of Wildlife Management, 2007, 71(1): 289-292.
22 ROHNER C A, RICHARDSON A J, MARSHALL A D, et al. How large is the world’s largest fish? Measuring whale sharks Rhincodon typus with laser photogrammetry[J]. Journal of Fish Biology, 2011, 78(1): 378-385.
23 Open C V. Camera calibration With OpenCV [Z/OL]. .
24 SHIH Y, LAI W S, LIANG C K. Distortion-free wide-angle portraits on camera phones[J]. ACM Transactions on Graphics, 2019, 38(4): 61.
[1] 汪品先. 深水珊瑚林[J]. 地球科学进展, 2019, 34(12): 1222-1233.
[2] 黄小平,江志坚. 海草床食物链有机碳传递过程的研究进展[J]. 地球科学进展, 2019, 34(5): 480-487.
[3] 王芳慧, 陈莹, 王波, 李好文, 周升钱. 海洋微生物气溶胶的丰度、群落结构及影响机制[J]. 地球科学进展, 2018, 33(8): 783-793.
[4] 王风平, 陈云如. 深部生物圈研究进展与展望[J]. 地球科学进展, 2017, 32(12): 1277-1286.
[5] 张亮, 秦蕴珊. 深海热液生态系统特征及其对极端微生物的影响[J]. 地球科学进展, 2017, 32(7): 696-706.
[6] 孟伟庆, 胡蓓蓓, 刘百桥, 周俊. 基于生态系统的海洋管理:概念、原则、框架与实践途径[J]. 地球科学进展, 2016, 31(5): 461-470.
[7] 宋敏, 杨群慧, 王华, 季福武, 王虎, 潘安阳, 周怀阳. 完整极性脂质化合物对海洋微生物活动的指示及应用局限性[J]. 地球科学进展, 2015, 30(10): 1162-1171.
[8] 李佳霖, 秦松. 海洋微微型蓝细菌分子生态学研究进展[J]. 地球科学进展, 2015, 30(4): 477-486.
[9] 黄邦钦, 柳欣. 边缘海浮游生态系统对生物泵的调控作用[J]. 地球科学进展, 2015, 30(3): 385-395.
[10] 高会旺, 姚小红, 郭志刚, 韩志伟, 高树基. 大气沉降对海洋初级生产过程与氮循环的影响研究进展[J]. 地球科学进展, 2014, 29(12): 1325-1332.
[11] 芮晓庆, 刘传联, 李志明. 颗石藻室内培养及应用研究进展[J]. 地球科学进展, 2014, 29(11): 1303-1313.
[12] 余克服, 张光学, 汪稔. 南海珊瑚礁: 从全球变化到油气勘探—第三届地球系统科学大会专题评述[J]. 地球科学进展, 2014, 29(11): 1287-1293.
[13] 孙松, 孙晓霞. 海洋生物功能群变动与生态系统演变 *[J]. 地球科学进展, 2014, 29(7): 854-858.
[14] 孙晓霞, 孙松. 海洋浮游生物图像观测技术及其应用[J]. 地球科学进展, 2014, 2014(6): 748-755.
[15] 孙晓霞, 孙松. 海洋浮游生物图像观测技术及其应用[J]. 地球科学进展, 2014, 29(6): 748-755.
阅读次数
全文


摘要