Modellierung dynamischer und räumlicher Prozesse
Winter Semester 2009/2010
- 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 are found here; the file is updated
shortly before each lecture.
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.
Exercise and model input are found here
If needed, these two books can be borrowed from me.
- 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)
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.
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).
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
- 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
- Analyze air quality data in relation to EU regulations; air quality data can
be obtained from the UBA
- 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.