Hands-on Digital Soil Mapping 2020

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 soil map 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

Hands-on Digital Soil Mapping (DSM) course, register now!

Note that when registering, you will be redirected to a Wageningen University & Research page in a new window to process your registration and payment. Please read carefully our cost and payment section.

 

Software installation

Please note that to participate in the DSM course you have to bring your own laptop computer, with R and RStudio software installed. Also, do not forget a power plug (travel) adapter if you need one. In the Netherlands the power sockets are of type C and F. We will not be able to provide you with these.

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 come fully prepared to the Spring School.

 

Preliminary programme

DAY 1 (Monday, 11 May 2020)

Time Topic Room/ type Lecturer
8.30 – 9.00 Registration and Coffee Hall Gaia building  
9.00 – 9.45

Official opening of the ISRIC Spring School

Group photo

Gaia 1 Rik van den Bosch (ISRIC director), Maria Ruiperez Gonzalez
9.45 – 10.15

Course introduction and overview

Lumen 1&2 Gerard Heuvelink
10.15 – 10.45 Geostatistics for soil mapping

Lumen 1&2

lecture

Gerard Heuvelink
10.45 – 11.15 Coffee break    
11.15 – 12.30 Geostatistics for soil mapping

Lumen 1&2

lecture

Gerard Heuvelink
12.30 – 13.30 Lunch GAIA first floor  
13.30 – 15.00

Geostatistics for soil mapping

Lumen 1&2

computer practical

Gerard Heuvelink

David Rossiter

15.00 – 15.30 Coffee break    
15.30 – 17.30 Geostatistics for soil mapping

Lumen 1&2

computer practical

Gerard Heuvelink

David Rossiter

 

DAY 2 (Tuesday, 12 May 2020)

Block

Topic

Room/ type

Lecturer

9.00 – 10.00

Soil and covariate data preparation

Lumen 1&2

lecture

Bas Kempen

10.00 – 10.30

Soil and covariate data preparation

Lumen 1&2

computer practical

Bas Kempen

Laura Poggio

David Rossiter

10.30 – 11.00

Coffee break

   

11.00 – 12.30

Soil and covariate data preparation

Lumen 1&2

computer practical

Bas Kempen

Laura Poggio

David Rossiter

12.30 – 13.30

Lunch

   
13.30 - 14.30 Accessing the WOSIS soil database in R

Lumen 1&2

lecture and computer practical

David Rossiter

Eloi Ribeiro

14.30 – 15.00

Coffee break

 

 

15.00 – 15.45 Remote and proximal soil sensing

Lumen 1&2

lecture

Titia Mulder

15.00 – 16.45

Remote and proximal soil sensing

Lumen 1&2

computer practical

Titia Mulder

Fenny van Egmond

16.45 – 17.30 Field and lab demonstration proximal soil sensing lab and field visit

Titia Mulder

Fenny van Egmond

19.00 – 22.00

Dinner in town (Colours World Food restaurant)

 

 

DAY 3 (Wednesday, 13 May 2020)

Block

Topic

Room/ type

Lecturer

9.00 – 10.30

Machine learning for soil mapping

Lumen 1&2

lecture

Bas Kempen

10.30 – 11.00

Coffee break

   

11.00 – 12.30

Machine learning for soil mapping

Lumen 1&2

computer practical

Bas Kempen

Laura Poggio

12.30 – 13.30

Lunch

   

13.30 – 15.00

Uncertainty quantification with Quantile Regression Forests and uncertainty propagation

Lumen 1&2

lecture

Gerard Heuvelink

15:00 – 15:30

Coffee Break

   

15.30 – 17:30

Uncertainty quantification with Quantile Regression Forests and uncertainty propagation

Lumen 1&2

computer practical

Gerard Heuvelink

Laura Poggio

 

DAY 4 (Thursday, 14 May 2020)

Block

Topic

Room/ type

Lecturer

9.00 – 10.30

Sampling for mapping and statistical validation

Lumen 1&2

lecture

Dick Brus

10.30 – 11.00

Coffee break

   

11.00 – 12.30

Sampling for mapping and statistical validation

Lumen 1&2

computer practical

Dick Brus

David Rossiter

12.30 – 13.30

Lunch

   

13.30 – 14.30

Mapping soil water and nutrient properties

Lumen 1&2

lecture

Johan Leenaars

14.30 – 15.00

Coffee break

   

15.00 – 17.00

Mapping soil water and nutrient properties

Lumen 1&2

computer practical

Johan Leenaars

Maria Ruiperez Gonzalez

Gerard Heuvelink

17.00 – 18.30 Meet the Experts    

 

DAY 5 (Friday, 15 May 2020)

Block

Topic

Room/ type

Lecturer

9.00 – 10.30

Visit to World Soil Museum and assignment

WSM

Stephan Mantel

10.30 – 11.00

Coffee break

   

11.00 – 12.30

Interactive Workshop

Opportunity for participants to present their work and receive feedback

Lumen 1+2

Gerard Heuvelink

12.30 – 13.30

Lunch

   

13.30 – 14.30

Course evaluation and certificates

Lumen 1+2

Gerard Heuvelink

14.30 – 15.30

Guest lecture

Gaia 1

guest lecture

David Rossiter

15.30 – 17.00

Closing words, drinks and snacks

Gaia 1, Hall Gaia building

Rik van den Bosch

 

Materials

You must bring your own 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.