Application of geospatial technology and decision model in the development of improved food security index

Abstract

Most developing countries are currently experiencing a severe food security crisis. A good policy to mitigate food insecurity is dependent on accurate assessment. Therefore, an improved assessment of food situation is important in implementing food security measures. Existing food security assessments are limited in integrating localized variables, often needing more context-specific information. This study proposes a new food security index (Hybrid Food Security Index-HFSI), the Nigerian state was used as a case study. Data used include; food consumption, poverty levels, variability in food prices, inflation, climate variability data and the status of road infrastructure. The study also integrated a hybrid Multi-criteria Criteria Decision Model (MCDM) and geo-spatial technology. The geo-spatial presentation of food security across Nigeria shows that food security is generally better in the Southern part of the country than in the Northern region. Broadly, indicators' performance primarily improves from the country's North to South, which suggests that Northern states tend to be less food secure than Southern states. According to the Fuzzy-DEMATEL-ANP model, the Poverty level indicator significantly impacts the food security situation in all focused states, as it received the highest priority weight of 0.1487. The study recommends intensifying poverty alleviation programs to improve food security, and women's development programs should be prioritized. This study provides policymakers and stakeholders with evidence-based assessments to address food security challenges in Nigeria.