Sampling theory for estimating soil organic carbon change - a tutorial

This tutorial shows how sampling theory from statistics can be used to estimate the total Soil Organic Carbon (SOC) stock for an area, or to estimate the change in total SOC stock for an area between two points in time. Sampling theory requires a probability sample from the area of interest and uses so-called design-based statistical inference. This has the important advantages that the estimates are unbiased, model-free (i.e., makes no model assumptions), and that the estimation accuracy can be quantified. The latter is for instance important to derive confidence intervals and evaluate whether an estimated increase or decrease of the SOC stock over time is ‘real’ and statistically significant.

The tutorial explains the underlying theory but the emphasis is on practical application using a concrete example and the R language for statistical computing. The tutorial provides all R scripts and datasets for the example area.

We developed this tutorial such that it should not be difficult to adapt it to other case studies, thus supporting the verification step of Monitoring, Reporting and Verification (MRV) projects.

We assume that users of the tutorial have basic knowledge of statistics, geo-information science and basic experience with R. Note that we also assume that R and required packages have been installed (version 4.4.3 or higher).

Materials

• Tutorial HTML
  
• Tutorial PDF
  
• 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.

Acknowledgements: This tutorial was developed within the ORCaSa project, which received funding from the European Union’s Horizon Europe research programme under grant agreement n°101059863.

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.