A Method for Extending the Geostatistical Functions in Spatial Information Processing

文献类型： 外文期刊

第一作者： Ma, Kai

作者： Ma, Kai;Ma, Kai;Wang, Jihua;Chen, Zehua;Zhu, Xiaobo;Pan, Ligang

作者机构：

关键词： R language;geostatistical function;spatial information processing;Python

期刊名称：INTELLIGENT AUTOMATION AND SOFT COMPUTING （ 影响因子：1.647； 五年影响因子：1.469 ）

ISSN： 1079-8587

年卷期： 2016 年 22 卷 2 期

页码：

收录情况： SCI

摘要： Geostatistics is widely used in many fields. However, the geostatistical functions of many commercial geographic information platforms are not rich enough. The geostatistical interpolation and analysis is a typical spatial information processing. Aiming to overcome the deficiency of geostatistical functions in geographic information platform, this paper studies the spatial information processing model, and proposes a new method based on the model. R language package has various geostatistical interpolation interfaces and detailed parameter setting functions. By invoking R language package through Python scripts and PypeR, which can make full use of the R language analysis function and provide more interpolation algorithms and flexible parameter settings. The expansion method was applied in the soil heavy metal distribution system. The experimental results show that, it can be integrated seamlessly with commercial geographic information platform, without disturbing other modules. Compared with the original method, the extended method has similar performance in the realization of the same interpolation algorithm.

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