『Abstract
An essential component of soil mapping is classification, a process
of assigning spatial soil entities to predefined categories (classes).
However, by their nature soils exist as a continuum both in the
spatial and attribute domains and often cannot be fitted into
discrete categories without introducing errors or at least over-simplification.
One approach to mitigate this problem in digital soil mapping
is the combination of fuzzy logic-based class assignment with
a raster GIS representation model which allows the continuous
spatial variation of soils to be expressed at much greater detail
than has been achieved in conventional (analog) soil survey. However,
applications of fuzzy soil mapping face two significant challenges:
defining the central concept of a soil category and determining
the degree of membership to the central concept. Prototype category
theory is presented here as a potential solution to these difficulties.
Emerging from ideas of family resemblance, centrality and membership
gradience, and fuzzy boundaries (fuzzy set theory), prototype
category theory stresses he fact that category membership is not
homogenous and that some members are better representatives of
a category than others. A prototype can be viewed as a representation
of the category, that 1) reflects the central tendency of the
instances' properties or patterns; 2) consequently is more similar
to some category members than others; and 3) is itself realizable
but is not necessarily an instance. Based on this notion, we developed
a prototype-based approach to acquire and represent knowledge
on soil-landscape relationships and apply the knowledge in digital
soil mapping under fuzzy logic. The prototype-based approach was
applied in a case study to map soils in central Wisconsin, USA.
Our approach created maps that were more accurate in terms of
both soil series prediction and soil texture estimation than either
the traditional soil survey or a case-based reasoning approach.
Keywords: Soil map; Fuzzy logic; Cognitive theory; Prototype category
theory; GIS; SoLIM』
1. Introduction
2. Prototype theory
3. Prototype-based soil mapping
3.1. Knowledge representation and knowledge acquisition
3.2. Prototype-based inference
4. Case study
5. Results and discussion
5.1. Comparison of prototype-based inference results with
traditional soil survey map
5.2. Comparison of prototype-based inference with case-based
reasoning
6. Conclusions
Acknowledgements
References