Module 1 · Introduction to R, spatial data and soil data preparation

Digital Soil Mapping
R and RStudio basics, spatial data with terra and sf, quality control and harmonisation of the KSSL soil dataset, and building the covariate stack.

Format: 4 sessions · Level: Beginner · Runs in: Google Colab (R) · Material: SoilFER Training Manual + Training Resources

Read the manual chapter

What you will learn

  • work with R and the tidyverse
  • import, check and clean laboratory and site data (KSSL, Kansas)
  • harmonise soil depths and units and apply property thresholds
  • handle vector and raster data and extract environmental covariates at soil points

Notebooks

Each notebook opens in Google Colab with the R runtime. Run the Setup cell first: it downloads the training project, installs the R packages and gets the course data. Then run the cells in order.

Notebook
Session 1 · Introduction to R for soil science

Open in Colab.ipynb
Session 2 · Soil data preparation with the KSSL dataset (part 1)

Open in Colab.ipynb
Session 3 · Soil data preparation with the KSSL dataset (part 2)

Open in Colab.ipynb
Session 4 · Spatial analysis and covariates

Open in Colab.ipynb

First time in Colab? Read Getting started.

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