Course module: Regression modelling for digital soil mapping
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| Course title: | Regression modelling for digital soil mapping |
| Course Code: | |
| Subject areas (Curriculum): | Soil and environmental sciences |
| Duration: | 1 day |
| Short description: | This module introduces regression modelling for digital soil mapping, focussing on linear regression, CART and random forests modelling. |
| Moderators: | Bas Kempen |
| Target audience: | Soil and environmental scientists with an interest in quantitative methods for mapping soil and environmental properties. |
| Requirements: | Basic understanding of statistics; basic knowledge of the statistical software R |
| Programme: | Lecture (2h); Computer exercises (6h) |
| Objective: | Introducing regression modelling for digital soil mapping: model theory and assumptions, model selection, random forest modelling |
| Software / materials: |
R, RStudio R packages: gstat, sp, randomForest, plyr, e1071, ggplot2, aqp, rgdal, GSIF, plotKML |
| Case studies: | Edgeroi (Australia) |
| Literature: | |
| Minimum number of participants: | 10 |
| Maximum number of participants: | 35 |
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