# Reviewing the Potential of Sentinel-2 in Assessing the Drought
## 1 Introduction  
Although there is no unique definition of drought [1], the term is generally used to refer to a situation or period related to a deficiency of water for a prolonged time where the amount of rainfall is less than the potential evapotranspiration [2]. Drought occurs in both high and low rainfall regions [1]. Its severity and duration are mainly determined by the amount of recorded precipitation, the level of potential evapotranspiration, and the spatial distribution of soil types and vegetation characteristics [3]. Drought in its nature can be meteorological [4], agricultural [5], hydrological [6], or socio-economic [7, 8]. Climate change and global warming have intensified the severity and frequency of drought, especially the meteorological drought, by increasing the land surface temperature and evapotranspiration and negatively influencing the precipitation [9]. Irrespective of its classification droughs are interconnected, and one triggers another. For example, the occurrence of meteorological drought often leads to agricultural and hydrological drought [10]. It is highly essential to develop a framework for the prediction and identification of its early warnings [11, 12, 13]. The volume of research in this field shows the capability of satellite-derived information in monitoring, quantifying, modeling, and predicting the drought [14, 15]. In general, drought-related studies are mainly focused on two aspects. The first aspect is treating it as a natural disaster [16], identifying the major hotspots [17], and evaluating their negative impacts on the natural and human ecosystem [18, 19]. The second aspect gives more importance to resilience and mitigation methods to eradicate or minimize its impact [20, 21]. Drought is slow to emerge and recede, hence monitoring and quantifying this event is more complex and challenging [22; 23; 24]. Initially, the severity and the magnitude are measured based on six physical indicators such as the Palmer Drought Severity Index (PDSI), the CPC Soil Moisture Model, the Daily Streamflow Percentiles, the Percent of Normal Precipitation, the Standardized Precipitation Index [25], and the Satellite-based Vegetation Health Index [26]. Droughts can be very destructive and they are considered the costliest of all-natural events [27] and ranked top among all other natural hazards based on the gravity of their impacts on socio-economic conditions, human life, and spatial coverage [28]. Hence, to monitor and quantify the drought, an advanced mechanism is required to measure the intensity, duration [29], and spatial coverage [30]. According to the IPCC's Fifth Assessment Report, southern Europe would experience severe and longer meteorological droughts, a similar observation as that made by [PERSON] et al. 2019 [31] for the 21 st century where the hydrological droughts may become more severe as a result of increasing evapotranspiration. Agricultural drought puts stress on food production which can cause the onset of other negative impacts on economic, environmental, and social aspects. A large number of methods have been developed over the past few decades for studying agricultural drought based on precipitation, soil moisture, temperature, vegetation index, and other indicators [32; 33; 34]. Advancements in remote sensing techniques have paved the way for new developments in drought research [35; 36]. For the last few decades, there was a substantial improvement in spatial, temporal, and spectral resolutions in satellite data [37]. The Sentinel-2 can efficiently monitor and estimate the drought-driven land surface changes [38]. The Satellite-derived Perpendicular Drought Index (PDI) can be widely applied in drought analysis [39; 40]. Similarly, Sentinel-2 derived PDI was validated with the precipitation anomaly index to assess the drought conditions in the western part of Texas in the year 2017 [31]. A statistically significant negative correlation was observed between PDI and the precipitation anomaly index.