基于VMS的张网渔船捕捞努力量与网位坐标提取方法

Extraction method of fishing effort and net position in stow net vessels based on vessel monitoring system data

摘要:

捕捞努力量是渔业资源管理和评估领域的重要参数之一，传统捕捞努力量计算方法无法满足实时、大范围、快速统计的需要。以我国近海作业的某张网渔船为研究对象，采用BP（back propagation）神经网络模型，对张网船155在2016年和2017年北斗渔船监控系统所获取的若干连续航次的经纬度坐标、航速和航向等信息进行分析和判断，提取各航次作业的网位坐标，通过阈值筛选渔船布网位置和时间，计算放网时长，把网口迎流面积与放网时长的乘积作为网次的捕捞努力量。结合BP神经网络和阈值分析的判断结果，网位判断准确率为82%，4个航次累计捕捞时长3 562.62 h，累计捕捞努力量712 524（m²·h）。设计的张网渔船状态判断、确定网位、放网时长提取和捕捞努力量计算方法为张网作业分析和其捕捞强度量化提供新的研究思路。

Abstract:

Fishing effort is one of the important parameters in the field of fishery resource management and assessment. Traditional fishing effort calculation methods cannot satisfy the needs of real-time, large-scale and rapid statistics. This study takes the stow net vessels operating offshore in China as the research object, and adopts the BP (Back Propagation) neural network model. Through the state judgment of the latitude and longitude coordinates, speed, heading and other information of the five consecutive voyages acquired by the Beidou Fishing Vessel Monitoring System in 2016 and 2017 of Zhangwangchuan 155, the net position coordinates of each voyage operation were obtained. By screening the position and time of the fishing net through the threshold and calculating the fishing time, the fishing effort can be calculated by the fishing net opening area multiplied the fishing time. Combined with the judgment results of BP neural network and threshold analysis, the accuracy of obtaining the network position data is 82%. The cumulative fishing time of the four voyages was 3 562.62 h, and the accumulated fishing effort was 712 524 (m²·h). The state judgment, net position identification, extraction of release time, and calculation method of fishing effort designed by this paper may provide new research ideas for the analysis of the net operation and the quantification of its fishing intensity.