A review of drought monitoring using remote sensing and data mining methods

Today, drought has become part of the identity as well as the fate of many countries. In fact, drought is considered among the most damaging natural disasters. The severe consequences resulting from drought affect the nature and society at different levels. Proper and efficient management is not possible without accurate prediction of drought and the identification of its various aspects. Thus, the existence of a considerable body of literature on drought monitoring. However, significant growth of remote sensing databases as will an increased amount of available data related to drought have been detected. Therefore, a more adequate approach should be developed. During the past decades, Data Mining (DM) methods have been introduced for drought monitoring. According to the best of our knowledge, a review of drought monitoring using remote sensing data and DM methods is lacking. Thereby, the purpose of this paper is to review and discuss the applications of DM methods. This paper consolidates the finding of drought monitoring, models, tasks, and methodologies.