Hands-on Digital Soil Mapping

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, 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.

• Gerard Heuvelink, course coordinator (geostatistics, uncertainty assessment, validation)

• Bas Kempen (introduction to R, data preparation, machine learning, validation)

• Laura Poggio (geostatistics, data preparation, machine learning, uncertainty assessment)

• Eloi Ribeiro (soil databases)

• Fenny van Egmond (remote and proximal soil sensing)

• Titia Mulder guest lecturer (remote and proximal soil sensing)

• Dick Brus guest lecturer (sampling for mapping)

 

Registration

Registration is open. 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.

 

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. A number of recorded sessions from a previous Spring School can be accessed via the ISRIC YouTube channel at: http://youtube.com/c/ISRICorg.

 

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.

 

Programme*

*Working programme subject to changes.

DAY 0 (OPTIONAL, Friday, 17 May 2019):

Block	Topic	Room/ type	Lecturer
9.00 – 17.30	Introduction to the statistical software R download ithir package	Lumen 1&2 guided self-study	Bas Kempen

 

DAY 1 (Monday, 20 May 2019):

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 Laura Poggio
15.00 – 15.30	Coffee break
15.30 – 17.30	Geostatistics for soil mapping	Lumen 1&2 computer practical	Gerard Heuvelink Laura Poggio

 

DAY 2 (Tuesday, 21 May 2019):

Block	Topic	Room/ type	Lecturer
9.00 – 10.00	Data preparation for DSM	Lumen 1&2 lecture	Bas Kempen
10.00 – 10.30	Data preparation for DSM	Lumen 1&2 computer practical	Bas Kempen Laura Poggio
10.30 – 11.00	Coffee break
11.00 – 12.30	Data preparation for DSM	Lumen 1&2 computer practical	Bas Kempen Laura Poggio
12.30 – 13.30	Lunch
13.30 – 15.00	Accessing the WOSIS database for soil profile data	Lumen 1&2 lecture and exercise	Eloi Ribeiro (Laura Poggio)
15.00 – 15.30	Coffee break
15.30 – 17.30	Remote and proximal soil sensing	Lumen 1&2 lecture and exercise	Titia Mulder (Fenny van Egmond)
19.00 – 22.00	Dinner in town (Colours World Food restaurant)

 

DAY 3 (Wednesday, 22 May 2019):

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 and propagation	Lumen 1&2 lecture	Gerard Heuvelink
15:00 – 15:30	Coffee Break
15.30 – 17:30	Uncertainty quantification and propagation	Lumen 1&2 computer practical	Gerard Heuvelink, Laura Poggio

 

DAY 4 (Thursday, 23 May 2019):

Block	Topic	Room/ type	Lecturer
9.00 – 10.30	Sampling for mapping	Lumen 1&2 lecture	Dick Brus
10.30 – 11.00	Coffee break
11.00 – 12.30	Sampling for mapping	Lumen 1&2 computer practical	Dick Brus David Rossiter
12.30 – 13.30	Lunch
13.30 – 15.00	Statistical validation of soil maps	Lumen 1&2 lecture	Bas Kempen
15.00 – 15.30	Coffee break
15.30 – 17.30	Statistical validation of soil maps	Lumen 1&2 computer practical	Bas Kempen David Rossiter

 

DAY 5 (Friday, 24 May 2019):

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, certificates	Lumen 1+2	Gerard Heuvelink
14.30 – 15.30	Measuring the value of the soil resource	Lumen 1+2 guest lecture	David Rossiter
15.30 – 17.00	Closing words, drinks and snacks	Lumen 1+2	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.