Satellite‐based hybrid drought monitoring tool for prediction of vegetation condition in Eastern Africa: A case study for Ethiopia

Abstract

AbstractAn experimental drought monitoring tool has been developed that predicts the vegetation condition (Vegetation Outlook) using a regression‐tree technique at a monthly time step during the growing season in Eastern Africa. This prediction tool (VegOut‐Ethiopia) is demonstrated for Ethiopia as a case study. VegOut‐Ethiopia predicts the standardized values of the Normalized Difference Vegetation Index (NDVI) at multiple time steps (weeks to months into the future) based on analysis of “historical patterns” of satellite, climate, and oceanic data over historical records. The model underlying VegOut‐Ethiopia capitalizes on historical climate‐vegetation interactions and ocean‐climate teleconnections (such as El Niño and the Southern Oscillation (ENSO)) expressed over the 24 year data record and also considers several environmental characteristics (e.g., land cover and elevation) that influence vegetation's response to weather conditions to produce 8 km maps that depict future general vegetation conditions. VegOut‐Ethiopia could provide vegetation monitoring capabilities at local, national, and regional levels that can complement more traditional remote sensing‐based approaches that monitor “current” vegetation conditions. The preliminary results of this case study showed that the models were able to predict the vegetation stress (both spatial extent and severity) in drought years 1–3 months ahead during the growing season in Ethiopia. The correlation coefficients between the predicted and satellite‐observed vegetation condition range from 0.50 to 0.90. Based on the lessons learned from past research activities and emerging experimental forecast models, future studies are recommended that could help Eastern Africa in advancing knowledge of climate, remote sensing, hydrology, and water resources.