Abstract
This study aims to formulate a classification model which farmers can use to determine the suitability of a land for supporting cultivation based on information about identified factors. Structured interview with farmers and agro-specialists were conducted in order to identify the factors associated with the classification of land suitability. Fuzzy membership function was used to formulate the input and output variables of the classification model for land suitability based on the risk factors identified. The model was simulated using MATLAB® R2015b -Fuzzy Logic Tool. The results showed that 7 risk factors were associated with the classification of the suitability of land for crop planting. The risk factors identified are annual rainfall, months of dry season, relative humidity, abundance of clay soil, abundance of sand soil, abundance of organic carbon and pH value of soil on land. 2 and 3 triangular membership functions were appropriate for the formulation of the linguistic variables of the factors using appropriate linguistic variables while the target suitability of land was formulated using four triangular membership functions for the linguistic variables unsuitable, fairly suitable, moderately suitable and highly suitable. 288 inferred rules were formulated using IF-THEN statements which adopted the values of the factors as antecedent and the suitability of land for planting crops as the consequent part of each rule. This study concluded that based on the assessment of information about the factors associated with the classification of land suitability a reasonable conclusion can be made about the possible use of land.
Highlights
From the beginning of time, land has been an indispensable means of livelihood for many families and countries on a large scale
The results demonstrated that when average pixel value of trees were used, the support vector machine (SVM)-based model resulted in the highest average overall classification accuracy of 89.2% for training set and 84.4% for test set
The inference engine for the fuzzy logic model was furnished by knowledge of land suitability factors and variables of land suitability elicited from the botanist
Summary
From the beginning of time, land has been an indispensable means of livelihood for many families and countries on a large scale. In developing countries like Nigeria, the use of land for farming and agricultural activities has reduced over the years owing to the unsuitability of land for farming in many regions especially in the south-south part of Nigeria due to various underlying human activities such as oil drilling and oil spillage into neighboring rivers [1]. The lack of soil classification reduces our knowledge and affects our land use decision. This difficulty is compounded by the fact that the hierarchical classifications are often built on criteria that vary greatly from one to the other. There is a need for the development of a land suitability classification model which
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