Vegetation condition prediction for drought monitoring in pastoralist areas: a case study in Ethiopia

Drought monitoring, and its impact management planning, has been a challenge for decision makers mainly because of lack of reliable information and decision support tools. The main objective of the study was to develop a remote sensing-based vegetation condition drought-monitoring approach for pastoralist areas using multi-temporal and spatial resolution satellite, climate, and biophysical datasets. Twenty-four years of data (1983-2006) from 11 attributes were extracted and used for developing the prediction models. A classification and regression tree (CART) modelling technique was used to integrate and model the drought parameters. Using the CART models, drought predictio n maps were produced for 2016, and the model outputs agreed with what had been reported by government and humanitarian partners of Ethiopia. The methodology can be used for future drought monitoring and early warning for risk-based (rather than crisis-based) drought planning. Future research may improve both the spatial and administrative resolution of the model so that drought status can be determined at district levels, which will be useful for actual drought mitigation planning.