Course module: Modelling and managing uncertainty in soil maps
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The course 'Modelling and managing uncertainty in soil maps' is currently under development.
Course title: | Modelling and managing uncertainty in soil maps |
Course code: | ISRIC-UNCERT |
Subject areas (Curriculum): | Statistics, Geostatistics, Soil Science |
Duration: | 1 or 2 days |
Short description: | Soil maps are not perfect, whether they are produced with traditional methods or with digital soil mapping techniques. The first part of this course addresses the accuracy assessment of soil maps by comparison with independent validation data. It explains how common accuracy measures such as map purity, mean error and root mean squared error can be estimated using sampling theory from statistics. The second part of the course focuses on the explicit modelling of soil map uncertainty using geostatistical models. These models represent the real world as a composite of a deterministic and stochastic component. Kriging uses information in point observations and covariates to reduce the stochastic component but cannot eliminate it entirely. It therefore results in probability distributions that are centered around the most likely value of the soil property or soil type, but that also characterise the uncertainty by means of the spread of the distribution. |
Moderators: | G.B.M. (Gerard) Heuvelink, T. (Tom) Hengl and B. (Bas) Kempen |
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Programme: | Module 1:
Module 2:
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Software / materials: | R base package and additional libraries; soil maps and datasets |
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