LAND SUITABILITY ANALYSIS FOR THE PRODUCTION OF COCOYAM INBENUE STATE, NIGERIA
Journal: Earth Science Malaysia (ESMY)
Author: Gelleh, I. Daniel, Okeke U. Henry, Babalogbon, B. Ayodeji, Mangut Y. Silas
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
Based on the basic principles and assumptions of FAO evaluation approach, suitability evaluation is always for a specific kind of use, meaning that different kinds of land use have different requirements. In this study, the land use suitability is specifically for the production of cocoyam in Benue State, Nigeria. This study aims to identify and delineate areas that best support the growth of cocoyam within the area. In this study, Land-Sat image of 2014 covering the study area was used to classify different land use types in ArcGIS 10.3 software, SRTM data was used to generate slope of study area, soil map of Nigeria was used, and different soil types within the study area was digitized, Multi-Criteria Evaluation was done in other to generate weightage for different factors that were used to produce the suitability map. The various factors that were used include soil, slope, and land use and the weight derived from each of the factors are 0.5, 0.3, and 0.2 respectively. Rainfall is regarded as constant in the area because of the single climatic type covering the small area. The classes established under the soil types include fluvisols, acrisols, alisols, gleysols, and nitisols, which were assigned the relative weights of 0.2667, 0.2, 0.1333, 0.0667 and 0.3333 respectively. The classes established under the slope include steep slope, strong slope, moderate slope, gentle slope, and nearly level, which were assigned the relative weights 0.0677, 0.13, 0.2, 0.27 and 0.3333 respectively and the classes established under the land-use factors include settlements, bare-surfaces, cultivated land, vegetation, and wetland, which were assigned the relative weights 0.0667, 0.13, 0.2, 0.27 and 0.3333 respectively. The result of the computation was classified into four quarters namely 0-25%, 26-50%, 51-75%, and 76-100%. The results were updated to a newly created field in the attribute data of the GIS layer containing the entire factor data used for suitability evaluation. After computation, SAVMACE sent the results into ArcGIS for symbolization and visualization.