A Method for Extending the Geostatistical Functions in Spatial Information Processing. Issue 2 (2nd April 2016)

• Record Type: Journal Article
• Authors: Ma, Kai; Wang, Jihua; Chen, Zehua; Zhu, Xiaobo; Pan, Ligang
• Is Part Of: Intelligent automation & soft computing. Volume 22:Issue 2(2016)
• Page Start: 261
• Page End: 266
• Publication Date: 2016-04-02
• Subjects: R language -- geostatistical function -- spatial information processing -- Python; Artificial intelligence -- Periodicals; Intelligent control systems -- Periodicals; 003.5
• DOI: 10.1080/10798587.2015.1095481
• Languages: English
• ISSNs: 1079-8587

Abstract

Abstract: 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.