Webster R., Oliver M.A., Geostatistics for Environmental Scientists. John Wiley & Sons Ltd, 2007, II edition. ISBN-13: 978-0-470-02858-2 (HB).
Plant R.E., Spatial data analysis in Ecology and Agriculture using R. CRC Press, Taylor & Francis Group, 2019. ISBN 978-0-8153-9275-0.
Oliver M.A., Webster R., Basic step in Geostatistics: the variogram and kriging. Springer, 2015. ISBN 978-3-319-15864-8.
Bivand R.S., Pebesma E., Gomez-Rubio V., Applied Spatial Data Analysis with R. Springer, II edition, ISBN 978-1-4614-7617-7.
The student acquires competences to develop a correct analysis of natural phenomena characterized by spatial dependence. The aim is the description and the modeling of complex natural systems.
Knowledges on Mathematics, Informatics, Geology, Ecology are recommended.
Simple blackboard, slides for projector, Moodle platform, R and Q-GIs software.
The students is invited to use the own laptop to make the exercise in the classroom.
Type of Assessment
Oral exam with the presentation of a graphical-numerical analysis with data given by the teacher. At least 3 question on the developed course program.
Univariate description of data. Frequency tables and histograms. Probability plots. Summary statistics. Bivariate description. Scatterplots, covariance and correlation.
Spatial description and the concept of spatial continuity. Autocovariance and h-scatterplot. The variograms. The kriging method. R and Q-GIS will be used for data analysis.
Application examples for the analysis of complex natural systems.