Advancing Rice Agriculture in Nigeria through GIS and AHP

This research focused on evaluating the sutability of land for rice farming within the Kabba/Bunu local government area, Nigeria, using an integrated approach that combines the Analytic Hierarchy Process (AHP) within a Geographic Information System (GIS). The selection of key factors such as climate, soil, topography, and land use/land cover (LULC) was guided by the FAO's guidelines and expert recommendations. Through the integration of GIS-based Multi-Criteria Decision Analysis (MCDA) and the application of AHP for prioritizing these factors, we developed weighted suitability layers, culminating in the creation of a comprehensive map indicating areas optimal for rice cultivation. The land was categorized into five suitability levels: most suitable, more suitable, suitable, less suitable, and not suitable. The findings confirm the efficacy of AHP in conducting such analyses, provided the correct variables are chosen. Notably, approximately 38% of the region, primarily in the south, was identified as moderately suitable for rice cultivation.

Autorentext

James Oladimeji, with a rich background that spans over ten years in programming and advanced degrees in GIS and Computer Science, originally started with a B.Agric degree. He is presently working towards a Ph.D. at UNICAF University in Malawi and serves as an AI Engineer at Turing LLC, where his focus lies in prompt engineering for ChatGPT apps.