Land Suitability and Crop Pattern Model using Integrated Pollination Intelligence Algorithm and Remote Sensing

Abstract

A mathematical model for crop pattern coupled with economic and environmental factors of agricultural production constructed with remote sensing and metaheuristic based algorithm is considered in this work. The model is expected to serve as a support system for farm managers' decision making process. Geographic data showing soil properties of major cities in Benue State, Nigeria using remote sensing, was integrated to the model to obtain analyzed suitability information for selected crops. A class of modern optimization algorithms was thereafter used to find optimum cropland pattern. A net production value of $1,592,107,000.00$ was obtained by using the model compared to an initial production value of $1,364,460,000.00$ recorded in the study area. The study suggests that soil properties must be considered along side with economic factors before choosing the types of crop to be planted on a piece of land. This study has shown the efficacy of optimization tools which should be dully employed by farmers in decision making process. The data used to support the findings of this study are included within the article.