Course module: Regression modelling for digital soil mapping
="width: 761px;" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack">
Regression modelling for digital soil mapping
Subject areas (Curriculum):
Soil and environmental sciences
This module introduces regression modelling for digital soil mapping, focussing on linear regression, CART and random forests modelling.
Soil and environmental scientists with an interest in quantitative methods for mapping soil and environmental properties.
Basic understanding of statistics; basic knowledge of the statistical software R
Lecture (2h); Computer exercises (6h)
Introducing regression modelling for digital soil mapping: model theory and assumptions, model selection, random forest modelling
Software / materials:
Minimum number of participants:
Maximum number of participants:
R packages: gstat, sp, randomForest, plyr, e1071, ggplot2, aqp, rgdal, GSIF, plotKML