Drought Prediction System for Improved Climate Change Mitigation

Due to climate changes and the uncertainties in future weather conditions, research on drought monitoring information received more attention from politicians and scientists. The objective of this paper is to develop a new intelligent system concept for drought information extraction and predictions from satellite images. For the modeling experiment, this study used 24 years of data sets on selected attributes. By using these data sets, ten models were developed for predicting DroughtObjects with a one- to four-month time lag for the growing season from June to October with an accuracy rate ranging from 0.71 to 0.95. The process of the system that uses the new concept was also demonstrated on an easy-to-use graphical user interface. The output of this new concept can be developed to a full system and is helpful for extracting the freely available satellite images for drought monitoring and climate change mitigation applications at different levels of decision making.