Fuzzy reasoning versus boolean logic in land suitability assessment for maize production
1998
Van Ranst, E. | Tang, H.
Conventional methods of land evaluating use Boolean logic based on crisp sets (yes/no) and strictly defined suitability classes. They ignore the continuous nature of soil variation, which can result in a considerable loss information. Fuzzy set theory, which is a generalization of Boolean algebra to situations where data are modelled by entities whose attributes have zones of gradual transitions, rather than sharp boundaries, offers a useful alternative to the conventional methodology. Some basic principles of fuzzy set theory, and the choice of membership functions, weight values and fuzzy operators are explained. The methodology is tested by comparing observed grain maize yields in two countries in China and land indices calculated by fuzzy set theory with those obtained by conventional Boolean methods maximum limitation method and parametric approach. Critical issues in the application of fuzzy set theory to land suitability assessment and future research needs are also discussed.
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