Normalized Difference Vegetation Index (NDVI)

Ethiopia, like many developing countries, faces significant threat from droughts triggered by climate change. The country's heavy reliance on agriculture for production, export revenues, and employment makes it highly susceptible to climate change-induced challenges, such as frequent floods, droughts and rising temperatures. Therefore, this research aims to assess drought-prone areas in Meyo district, Borena Zone, thereby contributing to the attainment of SDG 13.1 and the creation of a more resilient and sustainable future in the face of climate change. To achieve the objective, the study employs the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) as indicators and the drought risk map was developed using weighted overlay analysis. Landsat images and rainfall datasets from December in the years 2002, 2012, and 2022 were analyzed to track changes. The result reveals a clear inverse relationship between NDVI and LST, where higher temperatures coincide with decreased NDVI values, signifying vegetation stress caused by reduced water availability. The study also highlights the deficient rainfall and high drought vulnerability in the norther and eastern parts of the study area. The provided drought risk map classifies areas into Low, Moderate, and High risk, illustrating the evolving drought scenario and it signifies increasing severity of drought risk in recent years, particularly from 2012 to 2022. The finding holds vital information for decision-makers, policymakers, and stakeholders in devising effective strategies to mitigate the adverse effect of drought and build resilience in the of climate change.

Sarhan Zerouali became fascinated with water at a young age through learning about water scarcity around the world and about traditional methods for locating groundwater. In a space applications course Sahran then learnt about space-based technologies. He is currently working on a research project on how remote sensing and other technologies can help alleviate global challenges arising from land degradation. As an aerospace engineer, Sahran has worked with various modern technologies in his work including nanosatellites, artificial intelligence, and feature extraction algorithms.

Sarhan Zerouali became fascinated with water at a young age through learning about water scarcity around the world and about traditional methods for locating groundwater. In a space applications course Sahran then learnt about space-based technologies. He is currently working on a research project on how remote sensing and other technologies can help alleviate global challenges arising from land degradation. As an aerospace engineer, Sahran has worked with various modern technologies in his work including nanosatellites, artificial intelligence, and feature extraction algorithms.