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A locating method based on the Anselin elocal spatial autocorrelation model which researches in the heavy metal pollution source

机译:基于Anselin Elecal空间自相关模型的定位方法,其重金属污染源研究

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Based on the given data of As content in the soil, using Log transformation, the Box-Cox transformation to exclude outlier for preprocessing data to meet the normal distribution. Using Anselin elocal spatial autocorrelation model to carry on local spatial clustering in order to cluster the similar attribute values to a class. Preliminary view is that the sources of pollution distribute within the region of tne distribution of these points. The thesis build Cokriging interpolation model to interpolate of the global by the ArcGis software in order to higher concentration of the surface domain. The similar points obtained by spatial clustering properties fall on the higher concentration of the surface domain obtained by Cokriging interpolation is the region for the location of pollution sources. We focus on the analysis of As, finalize two As sources of pollution of surface domain, one of the sources of pollution range is (9277,11121), (16148,16432)]and the other is [(3573, 4777),(6213,4897)]. Then the artical uses the cross validation error analysis methods to test Cokriging interpolation model and found that cross-validation result is very good, model checking has reached a certain accuracy.
机译:基于在土壤中作为内容的给定数据,使用日志转换,盒式Cox转换排除预处理数据的异常值以满足正态分布。使用Anselin Elocal Spatial Auto相关性模型携带局部空间群集,以便将类似的属性值群集到类。初步认为,污染源在这些点的TNE分布区域内分布。论文将Cokriging插值模型构建到ArcGIS软件的全局内插,以便更高浓度的表面域。通过空间聚类特性获得的类似点属于通过Cokriging插值获得的表面域的较高浓度是污染源位置的区域。我们专注于分析,最终确定两个表面域污染源,污染范围之一(9277,11121),(16148,16432)],另一个是[(3573,4777),( 6213,4897)]。然后艺术用途使用跨验证误差分析方法来测试Cokriging插值模型,发现交叉验证结果非常好,模型检查已达到一定的准确性。

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