Land Suitability Evaluation for Cassava Production Using Integral Value Ranked Fuzzy AHP and GIS Techniques

Abstract

This study presents an improved integral value ranked Fuzzy Analytic Hierarchy Process (FAHP) and Geographic Information System (GIS) based Multi-Criteria Decision Making (MCDM) technique to help decision-makers/farmers evaluate and map suitable lands for optimum cassava production. Selected input/ suitability factors chosen from literature and experts' opinion were: pH, organic carbon, cation exchange capacity, slope, aspect, elevation, temperature, relative humidity, rain, distance from river and road. The improved integral value ranked FAHP method was used in prioritizing and assigning weights to each causative factor in the MCDM process due to its effectiveness, consistency, and ease of implementation. Land suitability maps were created using GIS techniques based on the aggregation of the various input factors and their derived weights. The outcome of the aggregation was reclassified into four classes using the standard deviation classification method (this method shows how much a feature deviates from the mean). Results obtained showed that 40% of the total area was highly suitable (S1), 36% was moderate suitability (S2), 20% was marginally suitable (S3) and 4% was not suitable (N). Results also showed that pH and organic content of the soil were the major determinants of soil suitability for cassava cultivation in the study area. This study showed the effectiveness of the proposed approach in assessing and mapping suitable areas for optimum cassava production within the study area.