Modellierung dynamischer und räumlicher Prozesse

Winter Semester 2009/2010

Lecture material

Organisation

The full course will be graded by a single mark.
The grade will be computed from the final test (50%) and the assignment (50%).
Presence during exercises or lectures is recommended, but not compulsory.
In order to pass you need: 50% of hand ins (where only correct submissions or serious attempts count), hand in the assignment within 14 days after the last day of the Vorlesungszeit, and have at least a 4.0 as test grade.
Hand-in time for the exercises is Monday, 10:00, following the day that the exercises are dealt with in class.
Exercises will be corrected randomly (i.e., not all of them).
Details about the assignment/mini project will follow.

Lecture slides

Lecture slides are found here; the file is updated shortly before each lecture.

Exercise material

The exercises use the open source statistical environment R (an implementation of the S language for data analysis). You can find introductory/tutorial material through its respective web sites.

Austal2000 material

Exercise and model input are found here

Literature

C. Chatfield, The analysis of time series: an introduction. Chapman and Hall: chapters 1, 2 and 3
Applied Spatial Data Analysis with R, by R. Bivand, E. Pebesma and V. Gomez-Rubio Springer, New York:
- Ch 1, 2, 3
- Ch 4, 5, 6 (whatever is convenient from it)
- Ch 8 (geostatistics)

If needed, these two books can be borrowed from me.

Data and scripts

As an introduction to R, you could go through the first 6 chapters (up to "lists and data frames") of An Introduction to R: go to the R home page, click Manuals under Documentation, and open the Introduction. You can copy and paste commands to an R session, started in the CIP pool.
Introductory exercises for use in the CIP pools: pdf
course excercises: html, pdf.
The French meteo data: meteo data, and R script
The classic Irish wind data set; an script analyzing it, the original paper on it, and a more recent one.

Test

The test will be held Tue, 02.02.2010 10:00 s.t., Seminar room, third floor, ifgi 2.0 Weseler Str. 253 (where the lecture is held).

Assignment

Hand-in deadline is Mar 15, 2010 12:00 (will be handled strictly).

The assignment will be a written report of max 5 pages (regular fonts/margins/page size, including figures and/or tables) on a modelling topic taken from the list with suggestions below, or otherwise approved by me. The minimum requirements are (i) data should be analyzed, and (ii) the analysis should explicitly address spatial variation, temporal variation, or spatio-temporal variation.

The written report should include an introduction, a central research question, a description of the data, a description of the analysis and the results, and concluding remarks answering the central research question. Write in scientific style. It is allowed to do the research in couples, but the written report should be made individually. German is allowed, English is encouraged (but does give bonus points). If you have used R, please attach the R script used as appendix (additional to the max. 5 pages).

For each topic: take care that you do not compute Euclidian distances based on long/lat coordinates. See the KML example in the exercises on how to (re)project data.

list with possible topics:

Analyze meteorological variables (temperature, rainfall) in a spatial or temporal context
Analyze the Irish wind data given above; focus on one of the research questions in the Haslett and Raftery 1989 paper, or on a different research question.
Analyze air quality data in relation to EU regulations; air quality data can be obtained from the UBA or EEA
Analyze the sediment pollution data in R package gstat
Try to find an optimal sampling strategy for spatial data (e.g. for the tull data in package gstat) or for a temporal sampling problem.