Andreas Jürg Papritz: Catalogue data in Spring Semester 2021

Name Dr. Andreas Jürg Papritz
Inst. f. Terrestrische Oekosysteme
ETH Zürich, CHN E 35.1
Universitätstrasse 16
8092 Zürich
DepartmentEnvironmental Systems Science

701-0104-00LStatistical Modelling of Spatial Data3 credits2GA. J. Papritz
AbstractIn environmental sciences one often deals with spatial data. When analysing such data the focus is either on exploring their structure (dependence on explanatory variables, autocorrelation) and/or on spatial prediction. The course provides an introduction to geostatistical methods that are useful for such analyses.
ObjectiveThe course will provide an overview of the basic concepts and stochastic models that are used to model spatial data. In addition, participants will learn a number of geostatistical techniques and acquire familiarity with R software that is useful for analyzing spatial data.
ContentAfter an introductory discussion of the types of problems and the kind of data that arise in environmental research, an introduction into linear geostatistics (models: stationary and intrinsic random processes, modelling large-scale spatial patterns by linear regression, modelling autocorrelation by variogram; kriging: mean square prediction of spatial data) will be taught. The lectures will be complemented by data analyses that the participants have to do themselves.
Lecture notesSlides, descriptions of the problems for the data analyses and solutions to them will be provided.
LiteratureP.J. Diggle & P.J. Ribeiro Jr. 2007. Model-based Geostatistics. Springer.
Prerequisites / NoticeFamiliarity with linear regression analysis (e.g. equivalent to the first part of the course 401-0649-00L Applied Statistical Regression) and with the software R (e.g. 401-6215-00L Using R for Data Analysis and Graphics (Part I), 401-6217-00L Using R for Data Analysis and Graphics (Part II)) are required for attending the course.