Geostatistics and Gaussian process models

Daisuke Murakami, Yoshiki Yamagata, Toshihiro Hirano

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

In this chapter, Section 4.1 briefly introduces the history of geostatistics. Section 4.2 explains stationary spatial processes and the basic geostatistical model to describe the process; Section 4.3 explains how to estimate the model parameters. After introducing Kriging, which is the spatial interpolation approach, in Section 4.4, Section 4.5 introduces its extensions including linear and non-linear kriging approaches. Then, Sections 4.6, 4.7, and 4.8, respectively, explain semiparametric, Bayesian, and spatiotemporal extensions of the geostatistical approach. Finally, Section 4.9 explains geostatistical approaches for large samples.

Original languageEnglish
Title of host publicationSpatial Analysis Using Big Data
Subtitle of host publicationMethods and Urban Applications
PublisherElsevier
Pages57-112
Number of pages56
ISBN (Electronic)9780128131329
ISBN (Print)9780128131275
DOIs
Publication statusPublished - 2019 Nov 2
Externally publishedYes

Keywords

  • Geostatistics
  • Kriging
  • Spatial interpolation
  • Spatial process
  • Stationary

ASJC Scopus subject areas

  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)

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