Drought information mining from satellite images for improved climate change mitigation

Due to climate change and uncertainties in the future weather conditions, drought information mining research has got the attention of both politicians and scientists. In the past, there were limited tools available for extracting and converting the huge data available from different sources to actionable information. The objective of this article was to develop a new information extraction concept from satellite images for improved drought characterization and prediction. In this experimental analysis, a total of 11 attributes characterizing drought were identified. The regression tree models developed were found to have accuracies ranging from 0.71 to 0.95 in predicting DroughtObject. The process of the system that uses the concepts was also demonstrated on an easy-to-use graphical user interface (GUI). The output of this new concept can be developed to a full system and helpful in extracting the freely available satellite images for drought monitoring and climate change mitigation applications at different levels of decisions making.