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首页> 外文期刊>International Journal of Geographical Information Science >A stratified optimization method for a multivariate marine environmental monitoring network in the Yangtze River estuary and its adjacent sea
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A stratified optimization method for a multivariate marine environmental monitoring network in the Yangtze River estuary and its adjacent sea

机译：长江口及邻近海域多变量海洋环境监测网的分层优化方法

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摘要

An efficient monitoring network is very important in accessing the marine environmental quality and its protection and management. In an estuary, there are fronts that separate distinctly different water masses and affect material transport, nutrient distribution, pollutant aggregation, and diffusion. This stratified heterogeneous surface neither satisfies the stationary requirements of kriging, nor can be handled adequately by removing a spatially continuous trend. This article presents a stratified optimization method for a multivariate monitoring network. In this method, principal component analysis (PCA) was used to reduce the dimensionality of the correlated targets, and the mean of surface with nonhomogeneity (MSN) method was adopted to produce the best linear unbiased estimator for a spatially stratified heterogeneous surface that failed to satisfy the requirements for a kriging estimate. The existing monitoring network in the Yangtze River estuary and its adjacent sea, which was designed by purposive sampling year ago was optimized as an illustration. The optimization consisted of two steps: reduce the redundant monitoring sites and then optimally add new sites to the remaining sites. After optimization, the inclusion of 51 sites in the monitoring network was found to produce a smaller total estimated error than that of the current network, which has 70 sites; moreover, the use of 55 sites can produce a higher precision of estimation for all three principal components (PCs) than that of the current 70 sites. The results demonstrated that the proposed method is suitable for optimizing environmental monitoring sites that have dominant stratified nonhomogeneity and that involve multiple factors.
机译：一个有效的监测网络对于获取海洋环境质量及其保护和管理非常重要。在河口中，有一些前沿将明显不同的水团分开，并影响物质的运输，养分分布，污染物的聚集和扩散。这种分层的异质表面既不能满足克里金法的固定要求，也不能通过消除空间连续趋势来进行适当处理。本文提出了一种用于多变量监控网络的分层优化方法。该方法使用主成分分析（PCA）来减少相关目标的维数，并且采用非均匀表面的均值（MSN）方法为空间分层的异质表面生成最佳线性无偏估计量，满足克里金估计的要求。作为示例，对一年前通过有目的采样设计的长江口及其邻近海域的现有监测网络进行了优化。优化包括两个步骤：减少冗余监视站点，然后以最佳方式将新站点添加到其余站点。经过优化后，发现在监视网络中包含51个站点所产生的总估计误差要小于当前网络中有70个站点的估计误差。此外，与当前的70个站点相比，使用55个站点可以对所有三个主要成分（PC）产生更高的估计精度。结果表明，所提出的方法适合于优化具有分层不均匀性且涉及多个因素的环境监测点。

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