本課程以英語授課。

Geostatistics provides quantitative descriptions of variables in space and time. It deals with spatiotemporal data based on regionalization variable theory, and contributes to the linear estimation of spatial random variables. Spatial structure of the spatial variables can be done by using semi-variogram (variogram). The best linear unbiased estimation (BLUE) and geostatistical simulations can be utilized to deal with spatial estimations and simulations of the random variables. This course will introduce the basic geostatistics and the above approaches. The relevant software of geostatistics will be introduced in this course.

The aims of the course are to introduce the theories of the random processes, spatial covariances and the semi-variogram. Students will learn how to do linear spatial estimations using kriging and co-kriging as well as non-linear estimation such as indicator kriging. Students will learn how to utilize geostatistical simulation approaches in dealing the random variable. Finally, the students will learn how to use software in geostatistical analysis.

Students should have basic statistical background

Mining Geostatistics, A.G. Journel and C.J. Huijbregts, Academic press, 1978. Geostatistics for environmental sceinces, R. Wbster and M. A. Oliver, Wiley, 2001. Geostatistics-modeling spatial uncertainty, J-P. Chiles and P. Delfiner, Wiley, 1999. Introduction to Geostatistics, Kitanidis, Cambridge, 1997. Geostatistical Software Library and User's Guide, C. V. Deutsch and A. G. Journel, OXFORD,1992. Random Field Models in Earth Sciences, George Christakos,Academic Press, 1992.

Introduction to Geostatistics