Data Preparation for Digital Soil Mapping

This tutorial shows how to process and prepare input data for digital soil mapping (DSM) using the statistical software R. The processing steps are illustrated with a sample dataset from North Macedonia. The tutorial consists of three parts:

1. ‘Point Data’: loading and processing a soil point dataset.

2. ‘Covariates’: loading and processing a stack of gridded covariate (GIS) layers.

3. ‘Regression matrix’: creating a regression matrix, which is a data object that is used as input to fit a statistical DSM model.

After completing this tutorial you will be able to:

• Load data tables and GIS raster (GeoTiff) files in R.
• Carry out a number of common data processing steps.
• Convert tabular objects to spatial data (and vice versa).
• Mask and project a covariate stack.
• Extract raster values at locations of data points.
• Create a regression matrix.

Materials

• Tutorial
  
• Scripts and datasets

License: This tutorial is released under the GNU GPL v3.0 license. GNU GPL v3.0 is a strong copyleft license. This means that you may use the code and change/modify the code. If you distribute copies or modifications of the code, you are required to release these updates under the GPL v3 license.

Disclaimer: This tutorial is provided without warranty. ISRIC is not obliged to provide updates or “bug fixes” of any kind. ISRIC will not provide user support for this tutorial.

Even though this tutorial is created with utmost care, ISRIC cannot be held liable for any damage caused by using this tutorial or any content therein in whatever form, whether or not caused by possible errors or faults nor for any consequences thereof.