| Kommentar |
The course shall be conducted by Dr. Nanki Sidhu for the WS. It will be held digitally with some session at the university. The classes will be taught in English.
Course Themes: 1. Installation and Introduction to R 2. Pesticide Modelling 3. Geostatistical methods (Kriging, Co-Kriging, etc) 4. Terrain Modelling. Exercise material links shall be provided in the classes.
Evaluation: The course evaluation is based on a final project submission in groups of 3-4 students. The project consists of two parts : written 5 page project (Incl. aims, materials, methods, results and discussion) and an oral presentation. Attendance for the oral presentations is compulsory. Written projects may be submitted in English or German. Topics for the projects will be provided or students are also free to select an appropriate topic of their choice. |
| Literatur |
Bivand, R., Pebesma, E., Rubio, V., 2013. Applied Spatial Data Analysis with R. Use R Series, Springer, Heidelberg, 378 p.
Bolstad, P., 2012. GIS fundamentals. 4th ed. Eider Press. 620 p.
P.J. Diggle, P. J. Ribeiro, 2007. Model-based Geostatistics. Springer. 242 p.
Lloyd, C. D. 2010. Spatial Data Analysis: An Introduction for GIS Users. Oxford: Oxford University Press, 206pp.
Hengl, T., 2009. A Practical Guide to Geostatistical Mapping, 2nd edition. University of Amsterdam, 291 p. Free downloadable: http://spatial-analyst.net/book/system/files/Hengl_2009_GEOSTATe2c1w.pdf
Neteler, M., Mitasova, H., 2008. Open Source GIS: A GRASS GIS Approach, 3rd Edt. Springer, The International Series in Engineering and Computer Science: Volume 773. 406 p.
Schabenberger, O., Gotway, C.A., 2005. Statistical Methods for Spatial Data Analysis. Boca Raton, FL: Chapman & Hall/CRC, 488 pp |
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