Rechnergestützte Identifikation von Böden - OPUS Bayreuth ...

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parameters which are unknown while being required (missing essential parameters). Thus, if a rule
requires the four parameters Munsell chroma, base saturation, horizon thickness and organic matter
contents while the Munsell chroma is unknown, u i = 1, z i = 4, and IMEP = 25 since one of four
required parameters is not determined. The state and/or the value of other parameters like bulk
density or Munsell hue is irrelevant for the calculation.
A IMEP of 0% means that every piece of information needed for the identification is available in
the data set. The resulting horizon is identified according to all defined parameters. Logically, a
IMEP of 100% designates a data set lacking of all essential parameters. The horizon is not
identified because the parameter constellation points out to the definition, but only because the
software found no information on whether any condition is violated. If a horizon is identified by
counting the number of uppercase letters (see chapter 3.4.3), the IMEP is set to 100%.
3.6.2 Estimation of the result quality
It is very difficult to measure or assess the result accuracy of the identification process since no
universal quantifiable scale exists which would provide the basis for measurements. Therefore we
compare the results with the expert's identifications in the data sets. The comparison can only give
a certain clue for the quality, because the soil surveyors often disagree in naming soil horizons and
the information in the data sets represents the position of only one or a few persons.
We express the similarity between the expert's and the computed result with the self-defined index
q which is composed out of the similarity of the uppercase and the lowercase letters:
- If the uppercase letters in both horizon names are equal, q is 0.6, if they are not equal, q is 0.
- If the lowercase letters in both horizons are identical in letter and order, 0.4 is added to q.
- If the lowercase letters in both horizon names have the same letters but a different order or
if they are partly equal, 0.2 is added to q.
Examples for different q are summarised in table 1. If the identification process has more than one
result, the mean value of q will be shown as the mean quality of all results.
3.7 Parameter Extraction and Definition of Linguistic Variables
The identification systems require scalable parameters, regardless of which level they operate at
(nominal, ordinal, or metric). Further requirements considered here are:
- High significance (in some cases only for special topics),
- Simple ascertainment (by observation, estimation, or measurement),
- High occurrence/frequency in soil databases.
The last point is difficult to achieve because soil databases in Germany are very heterogeneous and
often have missing values. Some information is observed only during field work and is not
recorded, except in the name of the horizon. Such identifications are unreliable due to the
subjectivity involved and they are thus generally not used for the development of the identification
system. However, in some cases the name is the only data containing detailed specifications and
their use in the development and test purposes cannot be avoided.
The parameters for the identification system were derived from the horizon definitions. Each