Fuzzy set method in GIS raster to analyze the characteristics of agricultural lands

Abstract

The increasingly growing and detailed spatial data onto land resources required a precise method for the data management can be more effective. Generally, spatial data onto land resources is categorized by sharp boundary and role of every land attribute to the land suitability is equated. On the other hand, the reality of land attribute in the field varied greatly and did not have sharp boundaries also the role of each attribute towards land suitability was varying. It caused the detailed data could not be presented properly so it did not reflect the actual condition at the field. The continued approach from fuzzy set in GIS is a method that can handle such problems. This study examined land characteristics in Pangkep District using a continuous fuzzy set approach from GIS raster. The research was conducted by using exploratory method (field survey and laboratory analysis) for the review scale. The results were then analyzed using the Semantic Import Model (SIM) fuzzy set method of GIS raster. The considered value of the attribute was converted into a general membership value (0 to 1.0), according to class limits that were determined by the Agricultural Research and Development Agency criteria (2011) adapted from the FAO criteria (1976) for planned land use. The results of land characteristic analysis by continuous fuzzy set approach were divided into three groups i.e. 1) climate characteristics: rainfall, temperature, and dry month, 2) physical characteristics of soil: slope, texture, surface rock, soil depth, soil drainage, erosion hazard, and flood hazard, and 3) soil fertility characteristics: Cation Exchange Capacity (CEC), soil acidity, organic C, and salinity. The index value of each land characteristic varied from 0 (minimum) to 1.0 (maximum), according to the prospective of each land characteristics for planned land use. The results are presented in a detailed raster GIS form so it is very effective to inform and represent the actual field conditions.