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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. [ABSTRACT FROM AUTHOR]

An inversion algorithm based on the Classification and Regression Tree (CART) has been developed to retrieve sea ice from Moderate Resolution Imaging Spectroradiometer (MODIS) images in the Bohai Sea where the sea water is characterized by a high concentration of suspended sediment in coastal areas. The inversion algorithm has been successfully applied to the sea-ice extraction from 2009 to 2012. The estimated sea ice is compared with previous studies and the comparison shows reasonable agreement. The model is further examined using sea-ice data from higher-spatial-resolution satellites, and the result indicates that the CART method is able to successfully retrieve sea ice in high sediment environments in the Bohai Sea. To comprehensively understand the working principles of the CART, a series of sensitivity studies to model input parameters such as sampling locations, the number of bands, and the effect of the thermal infrared band (TIB), was conducted. The sensitivity studies show that the CART method is easy to set up and the results are realistic. The TIB may play an important role in sea-ice inversion in turbid waters. The algorithm is also compared with a ratio-threshold segmentation (RTS) method, a common way to retrieve sea ice from satellite images in open oceans, and the comparison indicates that the algorithm developed in the present article is superior to the RTS method in high sediment environments. [ABSTRACT FROM PUBLISHER]