COMPARISON OF BOOLEAN AND FUZZY CLASSIFICATION METHODS IN LAND SUITABILITY ANALYSIS BY USING GEOGRAPHICAL INFORMATION-SYSTEMS

In this paper the information content of Boolean and fuzzy-set-based approaches to the problem of analyzing land suitability for agriculture within a geographical information system (GIS) is assessed. First, the two approaches to this problem are stated and formalized in the context of land-suitability evaluation. A database comprising 642 unique areas, 7 land qualities, 13 land characteristics, and 2 crop types is defined and described. Land-use suitability ratings for two crops, wetland rice and soybean, are generated by using Boolean and fuzzy methods. Results produced by the two methods are compared in terms of their usefulness for agricultural land-use planning. The ARC/INFO vector-based GIS software package is utilized. The study area is the Cimanuk watershed in northwest Java, Indonesia.