Application of Fuzzy Analytical Hierarchy Process in Land Suitability Evaluation for Faba Bean Crop

Land suitability assessment is crucial to address agricultural sustainability goals and forward future directions of managing rural landscapes. Geographic information system (GIS) and multi-criteria decision analysis (MCDA) techniques allow handling of multiple and heterogeneous factors required for land suitability evaluation. Fuzzy, analytical hierarchy process (AHP) and geographic information system (GIS) techniques were applied in the study to analyze land suitability for faba bean production in northern Ethiopia. Climate, topographic and soil data were used and transformed to a fuzzy set data. AHP was used to rank criteria based on their importance and accordingly define their weights. Weight and score of factors were integrated in GIS environment to develop land suitability index. The results indicated that 49.3% of the area fall within the moderately suitability class (S2), 24.8% in the marginally suitable range, and 25.9% of it in currently unsuitable range (N1). The area has faba bean crop production constraints related with moisture retention, structural stability, nutrient retention and availability, slope, erosion and toxicity (related to elevated CaCO3 and pH). The area is in need of soil and water management practices even though the climatic, topographic and some physical and morphological soil properties which are not flexible to be modified are still permanently influencing its production potential. Fuzzy AHP approaches are promising tools to increase accuracy and pliability of agricultural land suitability evaluation.