GIS-Based Analysis of Crop Yield Trends in Response to Climate Change Using Data-Driven Analysis Systems (DDAS) Techniques

Abstract

Climate variability poses significant challenges to crop production, particularly in vulnerable regions like Southeast Nigeria, where changing environmental conditions directly impact agricultural productivity. This study employs GIS-based analysis and Data-Driven Analysis Systems (DDAS) to assess the effects of climate variables on crop yields, focusing on temperature, rainfall, relative humidity, solar radiation, and wind factors. The objectives are to (1) analyze the Relationship Between Climate Variables and Crop Yield Trends, (2) develop Predictive Models Using GIS and DDAS Techniques, and (3) identify Climate-Sensitive Zones for Targeted Agricultural Interventions within Southeast Nigeria. Findings reveal that maximum and minimum temperatures and moderate rainfall positively influence crop yield, while high relative humidity and solar radiation have a negative impact. GIS mapping and DDAS techniques successfully highlight spatial variations and provide robust yield predictions, emphasizing their value in agricultural planning. By identifying high-risk areas, such as Abakaliki, the study provides actionable insights to develop adaptive, region-specific agricultural strategies, thereby enhancing food security and sustainable agricultural practices in Southeast Nigeria.