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A comparative study of spatial interpolation methods for determining fishery resources density in the Yellow Sea

机译:确定黄海渔业资源密度的空间插值方法的比较研究

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摘要

Spatial interpolation is a common tool used in the study of fishery ecology, especially for the construction of ecosystem models. To develop an appropriate interpolation method of determining fishery resources density in the Yellow Sea, we tested four frequently used methods, including inverse distance weighted interpolation (IDW), global polynomial interpolation (GPI), local polynomial interpolation (LPI) and ordinary kriging (OK). A cross-validation diagnostic was used to analyze the efficacy of interpolation, and a visual examination was conducted to evaluate the spatial performance of the different methods. The results showed that the original data were not normally distributed. A log transformation was then used to make the data fit a normal distribution. During four survey periods, an exponential model was shown to be the best semivariogram model in August and October 2014, while data from January and May 2015 exhibited the pure nugget effect. Using a paired-samplest test, no significant differences (P>0.05) between predicted and observed data were found in all four of the interpolation methods during the four survey periods. Results of the cross-validation diagnostic demonstrated that OK performed the best in August 2014, while IDW performed better during the other three survey periods. The GPI and LPI methods had relatively poor interpolation results compared to IDW and OK. With respect to the spatial distribution, OK was balanced and was not as disconnected as IDW nor as overly smooth as GPI and LPI, although OK still produced a few “bull’s-eye” patterns in some areas. However, the degree of autocorrelation sometimes limits the application of OK. Thus, OK is highly recommended if data are spatially autocorrelated. With respect to feasibility and accuracy, we recommend IDW to be used as a routine interpolation method. IDW is more accurate than GPI and LPI and has a combination of desirable properties, such as easy accessibility and rapid processing.
机译:空间插值是渔业生态学研究中常用的工具,尤其是用于生态系统模型的构建。为了开发一种确定黄海渔业资源密度的合适插值方法,我们测试了四种常用方法,包括距离反距离加权插值(IDW),全局多项式插值(GPI),局部多项式插值(LPI)和普通克里格法(OK)。 )。使用交叉验证诊断程序分析插值的有效性,并进行目视检查以评估不同方法的空间性能。结果表明原始数据不是正态分布的。然后使用对数转换使数据适合正态分布。在四个调查期内,指数模型被证明是2014年8月和10月的最佳半变异函数模型,而2015年1月和2015年5月的数据则显示出纯金块效应。使用配对样本检验,在四个调查期间的所有四种插值方法中,预测数据和观察数据之间均未发现显着差异(P> 0.05)。交叉验证诊断的结果表明,OK在2014年8月表现最好,而IDW在其他三个调查期间表现更好。与IDW和OK相比,GPI和LPI方法的插值结果相对较差。在空间分布上,OK保持平衡,没有IDW断开连接,也没有GPI和LPI那么平滑,尽管OK在某些区域仍然产生了一些“牛眼”图案。但是,自相关度有时会限制OK的应用。因此,如果数据在空间上是自相关的,强烈建议您使用OK。考虑到可行性和准确性,我们建议将IDW用作常规插值方法。 IDW比GPI和LPI更为准确,并且具有所需属性的组合,例如易于访问和快速处理。

著录项

  • 来源
    《海洋学报(英文版)》 |2016年第12期|65-72|共8页
  • 作者单位

    Institute of 0ceanology, Chinese Academy of Sciences, Qingdao 266071, China;

    Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266100, China;

    Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266100, China;

    Key Laboratory of Sustainable Development of Marine Fisheries of Ministry of Agriculture, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China;

    Key Laboratory of Sustainable Development of Marine Fisheries of Ministry of Agriculture, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China;

    State Key Laboratory of 0ceanography in the Tropics, South China Sea Institute of 0ceanology, Chinese Academy of Sciences, Guangzhou 510301, China;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-19 03:57:52
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