Uncertainty Analysis and Statistical Validation of Spatial Environmental Models (UA&SV) 

Monday 9 - Friday 13 December 2024

Scope

Input data for spatial environmental models may have been measured in the field or laboratory, spatially interpolated, derived from remotely sensed imagery or obtained from expert elicitation. In all these cases errors are introduced. Although users may be aware that errors propagate through their models, they rarely pay attention to this problem. However, the accuracy of the data may be insufficient for the intended use, causing inaccurate model results, wrong conclusions and poor decisions. The purpose of this course is to familiarize participants with statistical methods to analyse uncertainty propagation in spatial environmental modelling, such that they can apply these methods to their own models and data. It also teaches methods that quantify the contribution of individual uncertainty sources and statistical validation methods to assess the accuracy of spatial model outputs with independently sampled data. Quantification of model parameter uncertainty is covered using Bayesian calibration techniques. The methodology is illustrated with real-world examples. Computer practicals make use of the R language for statistical computing.

This course differs from the “Statistical Uncertainty Analysis of Dynamic Models” (SUADM) course, in that it:
• focuses on uncertainty propagation in spatial models, while SUADM concentrates on uncertainty analysis of dynamic models;
• uses basic to intermediate statistical approaches and graphical tools to analyse uncertainty and uncertainty propagation, while SUADM uses more advanced statistical approaches;
• dedicates a full day to statistical validation of outputs of spatial models using spatial sampling theory, while SUADM draws specific attention to stochastic sensitivity analysis.

Programme

Day 1, morning: Course overview; lectures and exercises probabilistic modelling of uncertainty; lecture and exercises Taylor series method.
Day 1, afternoon: Computer practical Taylor series method.
Day 1, evening: Group dinner in Wageningen centre.
Day 2, morning: Lecture and exercises Monte Carlo method and quantification of uncertainty source contributions.
Day 2, afternoon: Computer practical Monte Carlo method and analysis of uncertainty source contributions.
Day 3, morning: Lecture and exercises Bayesian calibration for quantification of model structural and model parameter uncertainty.
Day 3, afternoon: Computer practical Bayesian calibration.
Day 4, morning: Lecture and exercises statistical validation and cross-validation, including spatial sampling for validation and reliability plots.
Day 4, afternoon: Computer practical statistical validation and cross-validation.
Day 5, morning: Lecture, exercises and computer practical uncertainty quantification of spatial averages.
Day 5, afternoon: Finish computer practical; course evaluation; uncertainty game; drinks and snacks.

The last 45 minutes of each afternoon (except Friday) are reserved to either continue the scheduled computer practical or apply the methods learnt to your own models and data.
On Monday evening there is a group dinner in town (cost included in course fee).

General information

Fees ¹

¹ TThe course fee includes all course materials, coffee/tea, lunches and a workshop dinner. It does not include other dinners and accommodation.
² The Early-Bird Fee applies to anyone who REGISTERS ON OR BEFORE 9 OCTOBER 2024
 

Note:

• The Early-Bird policy is such that the moment of REGISTRATION (and not payment) is leading for determining the fee that applies to you.
• Please make sure that your payment is arranged within two weeks after your registration.
• It is the participant's responsibility to make sure that he/she (or his/her secretary) completes the payment correctly and in time.

PE&RC Cancellation Conditions

• Up to 4 (four) weeks prior to the start of the course, cancellation is free of charge.
• Up to 2 (two) weeks prior to the start of the course, 50% of the participation fee will be charged.
• In case of cancellation within two weeks prior to the start of the course or no show, 100% of the participation fee will be charged. For PhD's this implies they must pay the regular fee of "All other academic participants".

Note: If you would like to cancel your registration, ALWAYS inform us and do not assume that by NOT paying the participation fee, your registration is automatically cancelled, because it isn't (and do note that you will be kept to the cancellation conditions).

More information

Prof. dr. Gerard Heuvelink
Phone: +31 (0) 317 482716
Email: gerard.heuvelink@wur.nl

Dr. Claudius van de Vijver (PE&RC)
Phone: +31 (0) 317 485116
Email: claudius.vandevijver@wur.nl

Registration

To register, please enter your details below and click "Register".