Abstract: Journal of Agricultural, Earth and Environmental Sciences

Abstract:
Agricultural drought represents a major environmental challenge impacting the Horn of Africa, especially So malia's Bay region. Bay, a semi-arid region dependent on rain-fed agriculture and pastoralism, is significantly susceptible to the effects of recurring droughts, which threaten food security, reduce agricultural production, and increase humanitarian disasters. The main objectives of this study were to: Analyze spatiotemporal variability in drought conditions using satellite-based indices. The research utilized essential remote sensing indices, specifical ly the Vegetation Health Index (VHI), which is derived from the Normalized Difference Vegetation Index (NDVI) and the Temperature Condition Index (TCI). Data from Landsat satellites were analyzed with GIS technologies to categorize drought severity into five classifications: Extreme, Severe, Moderate, Mild, and No Drought. The investigation encompassed the years 2014, 2016, 2018, and 2020 to assess temporal changes and spatial distri bution. The analysis was carried out using ArcGIS 10.8. The VHI results showed significant fluctuations over the study period. In 2014, severe to extreme drought covered over 54% of the region, with less than 1% unaffected. By 2016, conditions improved slightly, with mild drought covering 34% and drought-free areas rising to 12%. In 2018, drought severity escalated, with extreme drought expanding to 31%, while areas without drought declined to 7.4%. By 2020, drought conditions peaked, with over 90% of the region experiencing moderate to severe stress and only 0.3% free from drought. The findings underscore the region's vulnerability to climatic variability and the need for robust early warning systems. The study demonstrates the efficacy of GIS and remote sensing in drought monitoring, providing actionable insights for policymakers and humanitarian agencies to enhance resilience in Gedo and similar arid regions.