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A Knowledge-based System for Evaluating Land Suitability for Crop Using Fuzzy Inference Engine
Thesis Abstract:
A land suitability evaluation is the process of assessment of the land suitability cases and the potential use of the land for agriculture. The land suitability classes describe the fitness of the land for a specified kind of land uses. A knowledge-based system for evaluating physical land suitability for 45 crops based on fuzzy inference had been developed in this research. The land suitability was evaluated by comparing crop requirement stored in the system with given climatic, topographic, wetness, physical soil, soil fertility, salinity and alkalinity, and land preparation characteristics.
The system was used to determine the limitation level and their ratings as well as the land suitability classes and the actual land suitability sub-classes from the given land characteristics data. The data can be asserted as crisp or as a fuzzy set. The land suitability classes were evaluated using the limitation method regarding the number and the intensity of limitations. The fuzzy inference method and the type of defuzzifier used were max-min and center average, respectively.
The experimental results showed that the rating of the limitation of crops can be different although the crops had the same limitation level and the same land suitability classes. The rating indicated the degree of suitability for each crop. The rating was used to determine whether the crop is appropriate to be planted on the given land area with the existing conditions. If the ratings of the limitations for the specific crop become higher, the crop becomes more suitable to be planted on the given land area with the existing conditions.