SCOPE
Input data for spatial and environmental models may have been measured in the field or laboratory, derived from remotely sensed imagery or obtained from expert elicitation. Data are also often digitized, interpolated, classified or generalized prior to submission to a model. 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, when the accuracy of the data is insufficient for the intended purpose then this may result in 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 modelling, such that they can apply these methods to their own data and models. Both attribute and positional errors are considered. Attention is also given to the effects of spatial auto- and cross-correlations on the results of an uncertainty propagation analysis and on methods to determine the relative contribution of the individual sources of uncertainty to the accuracy of the final result. The methodology is illustrated with real-world examples.
CONTENTS
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date |
9:00 - 12.15 |
13:15 - 16:00 |
16:00 - 17:00 |
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13 Dec |
lectures and exercises probabilistic modelling of uncertainty, Taylor series method |
computer practical Taylor series method |
feedback exercises and computer practical |
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14 Dec |
lecture and exercises Monte Carlo method, model error quantification |
computer practical Monte Carlo method, model error quantification |
feedback exercises and computer practical |
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15 Dec |
lecture and exercises positional uncertainty propagation |
computer practical positional uncertainty propagation |
feedback exercises and computer practical |
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16 Dec |
case: entire uncertainty propagation chain with focus on input uncertainty assessment |
feedback case |
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17-Dec |
free choice: work with own data, deepen knowledge in specific topic, discuss project with supervisors, et cetera |
feedback own data analyses |
course evaluation |
uncertainty game (with prize, drinks and snacks) |
End of Course |
GENERAL INFORMATION
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Target group: |
PhD students and researchers working with spatial models who want to know how errors in inputs propagate to model outputs. |
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Group size: |
minimum 15, maximum 25 participants |
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Course duration |
5 days |
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Language |
English |
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Prior knowledge |
Basic knowledge of statistics, GIS and spatial modelling |
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Number of credits |
1.5 ECTS |
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Course leaders |
Gerard Heuvelink & Sytze de Bruin |
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Location |
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PE&RC/SENSE PhD's with TSP |
€ 300 |
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Other PhD and staff WU |
€ 600 |
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Other participants |
€ 1000 |
Please register by sending an email to pe-office@wur.nl, providing the following information:
your name:
your email-address:
name of the course you want to participate in
status: PhD student // post-doc // else:
name of your graduate school:
if you are a member of PE&RC, whether you have an approved education plan (TSP): yes // no
name and address of research group (if applicable internal bode number):
name of department/Science Group
the address to which we can send the invoice for the course fee
Do you have any dietary requirements?
Full registration only occurs once you have provided us with the requested information as stated above. Afterwards you will receive an official registration confirmation by one of the course organizers.
For further information please contact:
Dr. Ir. Gerard Heuvelink
Tel: + 31 (0)317-486538
Email: Gerard.Heuvelink@wur.nl
Dr. Ir. Sytze de Bruin
Tel: + 31 (0)317-481830
Email: Sytze.deBruin@wur.nl
Dr. C. Van de Vijver
Tel: + 31 (0)317-485116
Email: Claudius.vandeVijver@wur.nl