Drought is a natural disaster which occurs in all climate regimes and causes environmental, social and economic crises. There is no universal definition for that but it is broadly defined as "severe water shortage". Assessment and monitoring of this phenomenon due to its creeping status and large spatial coverage is difficult especially using ground-based measurements. To detect drought, we need a tool that can provide information about temporal and spatial distributions of this phenomenon. Remote sensing offers considerable advantages in drought assessment and monitoring. Since the launch of satellites which is more than three decades, various remote sensing data with different temporal, spatial and spectral resolutions has been widely and successfully used in this field. The success of this technology in drought monitoring and assessment can refer to repeatability, large converge and inexpensive data that are extracted from remote sensing imagery. Also, due to the lack of meteorological data such as rainfall and temperature in remote and broad regions which is a usual case in developing countries, remote sensing can provide a valuable source of information for drought monitoring. The aim of this paper is to introduce the most widely used remote sensing techniques such as the Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Perpendicular Drought Index (PDI) and Modified Perpendicular Drought Index (MPDI) in drought studies. Because of the advantages of remotely sensed data over field measurements, information extracted from this data using remote sensing techniques can help government, non-government organizations, pastoralists and farmers to better understand the trends of drought and be more proactive in drought management.