Abstract
Present analytical functions and conventional cartographic modeling techniques in Geographic Information Systems (GIS) are based on Boolean logic, which implicitly assumes that objects in a spatial database and their attributes can be uniquely defined. The inherent constraint of the classical set theory does not allow for partial set membership conditions and imprecise information in GIS. The inadequacy of the Boolean logic for the representation and manipulation of spatial data is a major obstacle toward realistic GIS modeling. This paper demonstrates the usefulness of Zadeh's fuzzy set theory in GIS modeling for urban land evaluation. The results indicate that incorporating fuzzy set theory into GIS modeling can provide more details about the gradual transition of urban land value than the traditional cartographic modeling approach. Fuzzy GIS modeling can also reduce the information loss by obtaining membership grade for each individual land parcel. The membership function allows identification of the extent to which a particular area belongs to a valuation class based on given criteria.
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