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ISSN 1674-5566

主管 上海市教委

主办 上海海洋大学

基于DIDSON的水库鱼类资源探测与时空分析

沈蔚 彭战飞 龚小玲 张进 朱振宏

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沈蔚, 彭战飞, 龚小玲, 张进, 朱振宏. 2022. 基于DIDSON的水库鱼类资源探测与时空分析. 上海海洋大学学报, 31(6): 1457-1466. doi: 10.12024/jsou.20210903565
引用本文: 沈蔚, 彭战飞, 龚小玲, 张进, 朱振宏. 2022. 基于DIDSON的水库鱼类资源探测与时空分析. 上海海洋大学学报, 31(6): 1457-1466. doi: 10.12024/jsou.20210903565
SHEN Wei, PENG Zhanfei, GONG Xiaoling, ZHANG Jin, ZHU Zhenhong. 2022. Detection of fish resources in reservoir and spatial and temporal analysis based on DIDSON. Journal of shanghai ocean university, 31(6): 1457-1466. doi: 10.12024/jsou.20210903565
Citation: SHEN Wei, PENG Zhanfei, GONG Xiaoling, ZHANG Jin, ZHU Zhenhong. 2022. Detection of fish resources in reservoir and spatial and temporal analysis based on DIDSON. Journal of shanghai ocean university, 31(6): 1457-1466. doi: 10.12024/jsou.20210903565

基于DIDSON的水库鱼类资源探测与时空分析

  • 基金项目:

    2020年上海海洋大学科技发展专项基金(A2-2006-20-200202);上海城投原水有限公司项目(D-8006-19-0088)

详细信息
    作者简介:

    沈蔚(1977—),男,博士,教授,研究方向为海洋测绘和水声探测。E-mail:wshen@shou.edu.cn

    通讯作者: 龚小玲, E-mail: xlgong@shou.edu.cn
  • 中图分类号: S923.4

Detection of fish resources in reservoir and spatial and temporal analysis based on DIDSON

  • Fund Project: 2020年上海海洋大学科技发展专项基金(A2-2006-20-200202);上海城投原水有限公司项目(D-8006-19-0088)
More Information
  • 为获取上海市陈行水库鱼类时空分布特征,分别于2019年4月17日、8月15日和11月13日,采用双频识别声呐(dual-frequency identification sonar,DIDSON)对陈行水库进行鱼类资源探测,利用ECHOVIEW水声数据处理软件构建鱼类目标分析模型,开展鱼类目标的提取与计数,分析并绘制鱼类资源密度的水平和垂直分布图,揭示水库鱼类数量和时空分布特征。结果表明:陈行水库中小型鱼类(体长<60 cm)居多,占比达80.90%;春季至秋季库区鱼类体长逐渐增加,密度不断增大,数量和总质量也在增加;水平空间尺度上,库区鱼类个体主要集聚水库南部,夏季分布相对集中,秋季相对分散;垂直空间尺度上,库区鱼类主要分布在水深2~6 m区域,占比达84.85%,春季鱼类分布平均水深为3.89 m,夏季为4.34 m,秋季为5.12 m,库区鱼类垂直分布随季节有向底层移动趋势。所研究的水声探测方法和鱼类目标分析模型为类似的鱼类资源调查分析工作提供了有益参考,探测结果为水库采取合理的鱼类资源管理提供了依据。
  • 加载中
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出版历程
收稿日期:  2021-09-22
修回日期:  2021-12-17

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