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首页> 外文期刊>Computers & geosciences >Exploring spatial variation and spatial relationships in a freshwater acidification critical load data set for Great Britain using geographically weighted summary statistics
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Exploring spatial variation and spatial relationships in a freshwater acidification critical load data set for Great Britain using geographically weighted summary statistics

机译:使用地理加权汇总统计数据探索英国淡水酸化临界负荷数据集中的空间变化和空间关系

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摘要

In this study, geographically weighted summary statistics (GWSSs) are used to investigate spatial variation and spatial relationships in a freshwater acidification critical load data set covering Great Britain. This use of GWSSs not only provides valuable insight into the critical load process prior to a geographically weighted regression (GWR) calibration, but also helps in interpreting its output. GWSSs are similarly useful prior to the calibration of other spatial models, such as those used in geostatistics. Results agree with those of previous research, where relationships between critical load and contextual catchment data can vary across space. However the more sophisticated models used here are shown to be much more flexible and informative, allowing more spatial patterns to be revealed than before.
机译:在这项研究中,使用地理加权汇总统计量(GWSS)来研究覆盖英国的淡水酸化关键负荷数据集中的空间变化和空间关系。 GWSS的这种使用不仅可以为地理加权回归(GWR)校准之前的关键负载过程提供有价值的见解,而且还有助于解释其输出。在校准其他空间模型(例如,地统计学中使用的模型)之前,GWSS同样有用。结果与以前的研究一致,在这些研究中,关键负荷与环境流域数据之间的关系可能会在空间中变化。但是,这里使用的更复杂的模型显示出更加灵活和丰富的信息,从而可以显示比以前更多的空间模式。

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