GSIF Course: Programme and Registration

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Sections: Overview  |  Who is it for?  |  Tentative programme  | Dates and Venue  |

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Overview  

Global Soil Information Facilities (GSIF) are various software and data components  including the underlying webservices (WoSIS Web Feature Service, SoilGrids and Web Coverage  Services). GSIF aims at supporting the generation of spatial prediction of soil properties and soil  classes. It provides a platform to develop static and dynamic soil models. The aim of this course is to  introduce various components of GSIF and provide hands-on training within the R environment for  statistical computing. Lecturers are experienced R programmers and soil data analysis specialists.

  • Tomislav Hengl (importing data to R, 3D soil mapping and visualisation, global data sets)

  • Gerard Heuvelink (geostatistics for soil mapping,  uncertainty assessment)

  • Madlene Nussbaum (machine learning and data mining, modeling uncertainty)

  • Bas Kempen (introduction to R, regression modelling for soil mapping)

 

Who is it for? 

This course is intended for soil and environmental scientists and students interested in producing soil maps and/or using regional and global soil datasets for spatial modelling purposes. We typically work in group consisting of 30–40 participants. The course assumes a basic level of statistics and some experience with programming. A number of recorded sessions from the Spring School  can be accessed via the ISRIC YouTube channel at: http://youtube.com/c/ISRICorg. Several GSIF tutorials can be followed from http://gsif.isric.org

 

Course programme 

*Working programme subject to changes.

DAY 0 (OPTIONAL, Friday, 25 May 2018)*:

Block Topic Room/ type Lecturer
9.00 – 17.30 Introduction to the statistical software R* Lumen 1&2 Guided self-study B. Kempen

(* A minimum size of participants is required for the optional day)

 

DAY 1 (Monday, 28 May 2018):

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 H (Rik) van den Bosch (ISRIC director), B. Kempen
9.45 – 10.45

Course overview (day by day)

Introduction to the GSIF framework Introduction to the Spatial Prediction Competition

Lumen 1&2 T. Hengl
10.45 – 11.00 Coffee break    
11.00 – 12.30 Geostatistics for soil mapping Lumen 1&2 lecture G. Heuvelink
12.30 – 13.30 Lunch    
13.30 – 15.00 Geostatistics for soil mapping Lumen 1&2 computer practical G. Heuvelink, B. Kempen
15.00 – 15.30 Coffee break    
15.30 – 17.00 Geostatistics for soil mapping Lumen 1&2 computer practical G. Heuvelink, B. Kempen

17.00 – 18.00

Dinner break at Campus restaurant for those following the optional 'Scripting in R' session

Forum ground floor

 

18.00 – 20.00

Scripting in R / Combining R, SAGA GIS and Google Earth (optional session)*

Lumen 1&2

computer practical

T. Hengl

 

DAY 2 (Tuesday, 29 May 2018):

Block

Topic

Room/ type

Lecturer

9.00 – 10.00

Preparing covariate layers for soil mapping

Lumen 1&2

lecture

T. Hengl

10.00 – 10.30

Coffee break

   

10.30 – 12.30

Preparing covariate layers for soil mapping (tutorial)

Lumen 1&2

computer practical

T. Hengl,

B. Kempen

12.30 – 13.30

Lunch

   

13.30 – 14.30

Predictive modelling using machine learning algorithms for soil mapping

Lumen 1&2

lecture

B. Kempen

14.30 – 15.00

Predictive modelling using machine learning algorithms for soil mapping

Lumen 1&2

computer practical

B. Kempen

15.00 – 15.30

Coffee break

   

15.30 – 17.30

Predictive modelling using machine learning algorithms for soil mapping

Lumen 1&2

computer practical

B. Kempen

19.00 – 22.00

Dinner in town (Colours World Food restaurant)

 

 

DAY 3 (Wednesday, 30 May 2018):

Block

Topic

Room/ type

Lecturer

9.00 – 10.15

Optimizing spatial predictions: model selection, fine-tuning and evaluation

Lumen 1&2

lecture

M. Nussbaum

10.15 – 10.30

Coffee break

   

10.30 – 12.30

Optimizing spatial predictions: model selection, fine-tuning and evaluation

Lumen 1&2

computer practical

M. Nussbaum,
T. Hengl

12.30 – 13.30

Lunch

   

13.30 – 15.00

Derivation of Organic Carbon stock and uncertainty propagation

Lumen 1&2

G. Heuvelink

15:00 – 15:30

Coffee Break

   

15.30 – 17:30

Derivation of Organic Carbon stock and uncertainty propagation

Lumen 1&2

G. Heuvelink, B. Kempen

 

DAY 4 (Thursday, 31 May 2018):

Block

Topic

Room/ type

Lecturer

9.00 – 10.15

Building Pedo-Transfer Functions using machine learning

Lumen 1&2

lecture

M. Nussbaum

10.15 – 10.30

Coffee break

   

10.30 – 12.30

Building Pedo-Transfer Functions using machine learning

Lumen 1&2

lecture + demo

M. Nussbaum,
T. Hengl

12.30 – 13.30

Lunch

   

13.30 – 15.00

Space-time modelling with soil data

Lumen 1&2

lecture + demo

T. Hengl

15.00 – 15.30

Coffee break

   

15.30 – 17.00

Space-time modelling with soil data

Lumen 1&2

lecture + demo

T. Hengl

17.00 – 18.00

Working with large rasters in R

Lumen 1&2

T. Hengl

 

DAY 5 (Friday, 1 June 2018):

Block

Topic

Room/ type

Lecturer

9.00 – 10.30

Visit to World Soil Museum and assignment

WSM

S. Mantel

10.30 – 11.00

Coffee break

   

11.00 – 12.30

GSIF workshop: participants are provided the opportunity to present their work and receive feedback

Lumen 1+2

all

12.30 – 13.30

Lunch

   

13.30 – 14.30

Course evaluation, certificates

Best spatial prediction award ceremony

Lumen 1+2

T. Hengl

14.30 – 15.30

Digital soil resource inventories
Status and prospects (guest lecture)

Lumen 1+2

D. Rossiter

15.30 – 17.00

Closing words + ISRIC borrel (drinks and snacks)

Lumen 1+2

H (Rik) van den Bosch

Please note that to participate in the GSIF course you have to bring your own laptop computer. Contact us if you are not able to bring your own laptop or want to run a virtual machine on your own laptop. Some basic software installation instructions you can find via the GSIF.isric.org tutorials page.

To get an idea about the GSIF course, take also a look at some of the video-recordings from 2015 and 2017.

 

Dates and Venue

Venue

The 2018 spring school will be held at the Wageningen Campus, the Netherlands, from 28 May - 1 June 2018. We offer participants the optional  “Introduction to the statistical software R"  guided self-study practical on Friday 25 May 2018, if sufficient requests have been received.

 

Good to know

Course may be cancelled if the minimum number of 15 participants is not reached.  We will inform you latest  12 March 2018. In that case the amount paid will be automatically refunded to your bank account. Please note that the refund will be done to the same bank account number used to pay the course fee

100% of the participation fee must be paid at the time of registration.

Please read carefully the Costs and Payment section.

Important  dates

  • Deadline for Early-Bird registration: 31 December 2017
  • Deadline for registration: 10 February 2018
  • Confirmation of participation: 12 February 2018
  • Letter of invitation (for visa application): 16 February 2018
  • Final programme of the spring school: 7 May 2018
  • Spring school:  28 May - 1 June 2018.