Integrating Spectral Vegetation Indices for Monitoring Vegetation Health and Stress in Semi-arid Ethiopia: A Case Study of Tullo District

This study offers a detailed examination of vegetation health monitoring in the Tullo District of eastern Ethiopia, underscoring the critical role of spatially explicit data in land management within semi-arid environments. Employing a multi-index remote sensing framework with Landsat 9 imagery, the research evaluates vegetation health, stress, and the risk of degradation through the analysis of six distinct spectral indices. The findings reveal considerable spatial variability in vegetation health, pinpointing regions of significant productivity and areas susceptible to degradation. This differential analysis is essential for effective environmental planning and the promotion of sustainable agricultural practices. The study also identifies strong correlations among the spectral indices, bolstering their reliability as tools for assessing vegetation conditions. Furthermore, the integration of these indices provides comprehensive insights, enhancing the understanding of ecological dynamics and informing conservation strategies. The methodology applied in this research is both scalable and cost-effective, thereby facilitating its adoption in broader contexts and regions facing similar challenges. By advancing the methodology for monitoring vegetation health, this work not only contributes to the understanding of vegetation dynamics in Ethiopia but also establishes a valuable framework that can be adapted to analogous ecosystems globally. The implications of this research are far-reaching, supporting informed decision-making in ecological restoration and land-use planning, ultimately fostering enhanced environmental stewardship in semi-arid landscapes.