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Fakultät für Biologie, Chemie und Geowissenschaften

Masterstudiengang - Global Change Ecology

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/Global Change Ecology M.Sc.

M: Methods

NummerTitelCredit PointsSemesterKurs Nr.
M1Introduction to R2 
 Introduction to R (M1)2174047
M2Statistical Modelling with R2 
 Statistical Modelling with R (M2)2174048
M3Vegetation Science32 
 Vegetation Mapping and Sampling (M3b)3274075
M4Foundations of Biogeographical Modelling2 
 Foundations of Biogeographical Modelling (M4)2274051
M5Remote Sensing3 
 Remote Sensing (M5)3174052
M6Time Series Analysis5 
 Time Series Analysis (M6a)2174053
 Time Series Analysis (M6b)3174054
M7Research at the Natural and Social Science Interface51 
 Research at the Natural and Social Science Interface (M7)21
M8Ecosystem Services Assessment of Landscapes2 
 Ecosystem Services Assessment of Landscapes (M8)2274057
M9Life Cycle Assessment of Products2 
 Life Cycle Assessment of Products (M9)2174058
M10Scientific Writing in Biogeography and Disturbance Ecology1 
 Scientific Writing (M10)1174059, 74059
M11Project Management2 
 Project Management and Scientific Coordination (M11)2174060
M12Introduction to GIS2 
 Introduction to GIS (M12)2174061
M13Advanced Geostatistical Methods3 
 Advanced Geostatistical Methods (M13a)1274062
 Advanced Geostatistical Methods (M13b)2274063
M14International Environmental Law3 
 International Environmental Law (M14)3200056
M15Science and Communication3 
M16Modeling Ecosystem Functions with the Soil and Water Assessment Tool (SWAT)5 
 Modeling Ecosystem Functions with the Soil and Water Assessment Tool (SWAT) (M16)5228368
M17Academic working methods and skills2 
 Academic working methods and skills (M17)2174071
M18Impact Assessment of Markets and Policies on Land Use and Ecosystem Services31 
 Impact Assessment of Markets and Policies on Land Use and Ecosystem Services (M18)3174073
M19Quantitative Methods51 
 Quantitative Sport Ecology (M19)5157030
M20Methods in Dynamic Vegetation Ecology [Details]52 
 Methods in Dynamic Vegetation Ecology5200763
M21Spatial Statistics and Visualization with R

Exercise, 3 ECTS

Learning Objectives:

Spatial data require specific methods of analysis. The aim of this exercise is the development of skills in dealing with different types of spatial datasets. The focus is on learning statistical methods for the analysis of spatial patterns.

Course Content:

Different methodological approaches will be presented and  practically implemented with the statistical software R. An exemplary selection of covered topics are: Visualization of spatial data, spatial point pattern analysis, variograms, and the modeling of areal data using SAR and CAR models.

 Spatial Statistics and Visualization with R3274084
-O Overview- -A Environmental Change- -B Ecological Change- -C Societal Change- -M Methods- -F Free Choice- -I Internships- -S International Science Schools- -T Master Thesis-
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