Regression modelling for digital soil mapping

Course title: Regression modelling for digital soil mapping
Course Code:  
Subject areas (Curriculum): Soil and environmental sciences
Duration: 0.5 days
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 (1.5h); Computer exercises (2.5h)
Objective: Introducing regression modelling for digital soil mapping: model theory and assumptions, model selection
Software / materials:

R, RStudio

R packages: gstat, sp, randomForest, plyr, e1071, ggplot2, aqp, rgdal, GSIF

RegressionModelling.zip

Case studies: Edgeroi (Australia)
Literature:  
Minimum number of participants: 5
Maximum number of participants: 35
Further inquiries: Bas Kempen