The statistical programming environment R has been of continuous interest for development of applications and tools implementing state-of-the-art knowledge of pedometrics. Under R umbrella already many Special Interest Groups (SIGs) exist that cover e.g. spatial data, environmental problems and similar.

This workshop aims at bringing together experienced R package developers that have, over the years, produced some frequently used tools for importing, organizing and processing soil data. We will try to educate and inform Pedometrics conference participants on possibilities of analyzing and visualizing their data using Open Source software tools, especially for the purpose of making reproducible research and for data processing automation. The workshop will also be a chance for Pedometrics conference participants to meet the original package developers and get an insight into development trends and opportunities.

Specific tutorials will cover:

➢ Importing soil data in R and conversion and harmonization of data, soil data classes (aqp, GSIF, sp, sf, rgdal packages),
➢ Plotting soil-depth relationships (aqp package),
➢ Using Machine Learning Algorithms for predictive modelling and soil data analytics (caret, ranger, randomForestSRC, xgboost, h2o packages)
➢ Using R for the production of web maps and visualisations (mapview, shiny, leaflet packages)
➢ Exporting soil data to standard formats (OGC standards and similar)

Preliminary timetable

  • 8:30–9:00 Arrival and setting up of computers (Gaia 1)
  • 9:00–10:30 Programme overview, software installation and first steps (Tom Hengl and Alessandro Samuel-Rosa)
  • 10:30–11:00 Coffee break
  • 11:00–12:30 R tutorials: importing and organizing soil data (Pierre Roudier)
  • 12:30–13:30 Lunch break (Lumen terrace)
  • 13:30–15:30: R tutorials: predictive modelling using Machine Learning algorithms (Tom Hengl)
  • 15:30–16:00 Coffee break
  • 16:00–17:00 R tutorials: visualizing soil data and models using the aqp, mapview, shiny and leaflet packages (Pierre Roudier)
  • 17.30–19.30 Welcome reception Terraszaal (Hof van Wageningen)
 From the Hands-on Global Soil Information Facilities 2016 (Gaia 1 lecture room).

From the Hands-on Global Soil Information Facilities 2016 (Gaia 1 lecture room).



  • Laptop computer (preferably with Linux OS and/or Windows 7+ OS) with at least 4GB RAM and wifi
  • Preinstalled software following the installation instructions
  • Bringing your own data sets is highly recommended but not required


T. (Tom) Hengl is a senior researcher at ISRIC — World Soil Information with core speciality in big data analytics and automated soil mapping. Tom has backgrounds in soil mapping and geo-information science. He is currently the project leader of the Global Soil Information Facilities — a suite of software tools, web-facilities and data sets (SoilGrids, soil profiles) for automated global soil mapping. ORCID ID: 

A. (Alessandro) Samuel-Rosa is a post-doc researcher at Federal University of Santa Maria in Brazil. His main research interest is on soil spatial modelling with a focus on sampling strategies, model selection and calibration, and uncertainty analysis. He is the author of the R-package spsann, an implementation of simulated annealing to optimize spatial sample configurations.


P. (Pierre) Roudier is a soil scientists at Landcare Research National Institute in New Zealand. He has over 10 years of experience with developing tools and software solutions for soil sampling, soil spectroscopy and soil data analytics. Pierre is author of multiple R package including aqp, inspectr, clhs and plotKML. ORCID ID: