Hands-on Digital Soil Mapping 2021

Five-day course from Monday 17 May to Friday 21 May 2021

The course will be given on-line this year, which has had some implications for the programme. We will have a longer lunch break and shorter days, because on-line learning is more tiresome than on-site learning.

 

Preliminary programme

Sections: Overview  |  Who is it for?  |  Software installation  |  Programme  | Materials  | Registration

 

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Overview

This course introduces methods and software for management, analysis and mapping of soil type and soil properties within the R environment for statistical computing. The course alternates between lectures and computer exercises and covers a variety of subjects, such as geostatistics, machine learning for soil mapping, soil functional mapping, proximal soil sensing, quantification of uncertainty, sampling for mapping and statistical validation. The course aims at soil geographers and environmental scientists who want to learn more about the theory and practice of digital soil mapping. After this course, participants will be able to apply the methods learnt to their own datasets. Lecturers are experienced pedometricians and soil data analysis specialists.

 

Who is it for? 

This course is intended for soil and environmental professionals, researchers and PhD-students interested in producing soil maps and/or using local, regional and global soil datasets for digital soil mapping. Participants must have a basic level of statistics, geo-information science and soil/environmental science. Experience with computer programming in R is advantageous but not required. Those not familiar with R will be asked to run a self-study tutorial prior to the course. A number of recorded sessions from a previous Spring School can be accessed via the ISRIC YouTube channel at: http://youtube.com/c/ISRICorg.

 

Registration

The maximum number of participants (50) has been reached for this course. 

 

Software installation

Please note that to participate in the DSM course you need to install R and RStudio software prior to the course. Software installation instructions can be found here, and the associated R code to test your installation here. Please read and follow these carefully to ensure you are fully prepared to the Spring School.

 

Preliminary programme

All times are Central European Time zone (CET), that is UTC+1.

 

DAY 1 (Monday, 17 May 2021)

Time Topic Type Lecturer
9.00 – 9.30 Course introduction and overview Lecture Gerard Heuvelink
9.30 – 10.30 Geostatistics for soil mapping Lecture Gerard Heuvelink
10.30 – 11.00 Morning break    
11.00 – 12.30 Geostatistics for soil mapping Lecture Gerard Heuvelink
12.30 – 14.00 Lunch    
14.00 – 15.30 Geostatistics for soil mapping Computer practical

Gerard Heuvelink

David Rossiter

15.30 – 16.00 Afternoon break    
16.00 – 17.00 Geostatistics for soil mapping

Computer practical and feedback

Gerard Heuvelink

David Rossiter

 

DAY 2 (Tuesday, 18 May 2021)

Block

Topic

Type

Lecturer

9.00 – 10.30

Geostatistics for soil mapping

Lecture

Gerard Heuvelink

10.30 – 11.00 Morning break    
11.00 – 12.30 Soil and covariate data preparation Lecture Bas Kempen
12.30 – 14.00 Lunch    

14.00 – 15.30

Soil and covariate data preparation

Lecture & computer practical

Bas Kempen

Laura Poggio

David Rossiter

15.30 – 16.00

Afternoon break

 

 

16.00 – 17.00 Soil and covariate data preparation

Computer practical and feedback

Bas Kempen

Laura Poggio

David Rossiter

 

DAY 3 (Wednesday, 19 May 2021)

Block

Topic

Type

Lecturer

9.00 – 10.30 Remote and proximal soil sensing Lecture Titia Mulder

10.30 – 11.00

Morning break

   

11.00 – 12.30

Remote and proximal soil sensing

Computer practical and feedback

Titia Mulder

Fenny van Egmond

12.30 – 14.00

Lunch

   

14.00 – 15.30

Machine learning for soil mapping

Lecture

Bas Kempen

15:30 – 16.30

Afternoon Break

   

15.30 – 17.00

Machine learning for soil mapping

Computer practical

Bas Kempen

Laura Poggio

 

DAY 4 (Thursday, 20 May 2021)

Block

Topic

Type

Lecturer

9.00 – 10.30

Machine learning for soil mapping

Computer practical and feedback

Bas Kempen

Laura Poggio

10.30 – 11.00

Morning break

   

11.00 – 12.30

Sampling for statistical validation

Lecture

Dick Brus

12.30 – 14.00

Lunch

   

14.00 – 15.30

Sampling for statistical validation

Lecture & computer practical

Dick Brus

David Rossiter

15.30 – 16.00

Afternoon break

   

16.00 – 17.00

Sampling for statistical validation

Computer practical and feedback

Dick Brus

David Rossiter

 

DAY 5 (Friday, 21 May 2021)

Block

Topic

Type

Lecturer

9.00 – 10.30

Mapping plant-available soil water and nutrients

Lecture

Johan Leenaars

10.30 – 11.00

Morning break

   

11.00 – 12.30

Mapping plant-available soil water and nutrients

Computer practical and feedback

Johan Leenaars

Maria Ruiperez-Gonzalez

12.30 – 14.00

Lunch

   
14.00 – 14.40 Virtual excursion World Soil Museum   Stephan Mantel

14.40 – 15.00

Course evaluation and certificates

 

Gerard Heuvelink

15.00 – 15.15 Afternoon break    
15.15 – 16.15 Valuing the soil resource Invited lecture David Rossiter

16.15 – 16.30

Closing words

 

Rik van den Bosch

 

Materials

You must use your own computer or laptop and have recent releases of R and RStudio installed (see above). Participants receive all workshop materials (test datasets, R scripts, lecture slides, tutorials) during the workshop.