# Reviewing the Potential of Sentinel-2 in Assessing the Drought
## 3 Progress in Remote Sensing of Drought from a Climatological and Ecological Perspective
### Remote Sensing of Vegetation in Drought
#### 3.1.2 Canopy Water Content  
The canopy water content is defined as the volume of water per unit of ground area [82], a major biophysical parameter in drought monitoring [83]. The cropland canopy water content is one of the key factors in estimating agricultural drought. Satellite-based remote sensing techniques can precisely measure the variations in canopy water level at regional and field levels [84]. During the Californian drought, more than 30% of canopy water loss was estimated over 1 million ha forest [85]. [PERSON] et al. [86] proposed a novel radiative transfer inversion model for the cropland canopy water content estimation from the HLS data, minimally constrained inversion and partially constrained inversion techniques were also applied. The derived cropland canopy water content is validated with the field data and the researchers highlighted the potentiality of the HLS data and Sentinel-2 in particular for estimating the cropland canopy water content. Water stress is considered as an early warning of drought which can be identified by closely observing the vegetation characteristics. In the 2019 summer, [PERSON] et al. [87] studied the drought-induced forest fall-off in the karst plateau. To evaluate the possible drought-induced dehydration and hydraulic failure, [PERSON] et al. [87] statistically correlated the Sentinel-2 derived (NDVI and NDVI 8A, NDWI), and soil-adjusted vegetation index (SAVI) with filed measured physiological parameters such as absolute water content (AbWC), relative water content (RWC), and minimum water potential (Ymin). Among other vegetation indices, only NDWI has a significant correlation with physiological parameters and the research concludes the capabilities of NDWI as a proxy for water stress analysis. The water stresscondition over the deciduous specious during the summer dry spell was assessed using Sentinel-2 images [88]. The study underlined the importance of high spatial information obtained from the Sentinel-2 such as the moisture stress index, chlorophyll index, and simple ratio vegetation index which improved the quality of the drought assessment studies in fragile ecological regions. Sentinel-2 data was used to analyze the 2017 post-summer Mediterranean forest health conditions in contextual drought and heatwaves. Sentinel-2 derived NDVI is compared with the in situ and meteorological data for the forest damage assessment. The Manneruci and Raunkiaer methods were applied to assess the vegetation response to climatic events. It was observed that the NDVI declined, compared to the pre-event NDVI values [89]. [PERSON] et al. [90] assess the potential of the Sentinel-2 red-edge band in a gross primary productivity (GPP) estimation. Eight vegetation indices were derived from the Sentinel-2, out of which three indices are non-red edge-based. Sentinel-2 derived GPP compared with MODIS derived light-use efficiency (LUE)-based GPP data, and tower-based incident photosynthetic active radiation, carbon flux data. The research concluded that the GPP produced from the red-edge chlorophyll index coupled with incident photosynthetic active radiation (PAR\({}_{\text{in}}\)) outperformed other vegetation indices and had a higher correlation with the tower-based GPP (GPP\({}_{\text{EC}}\)). To quantify the severity of drought impacts on the forest by assessing the variations in photosynthetic activities, in 2017 [PERSON] et al. [91] compared 118 observational summer sample data with Sentinel-2 derived vegetation indices such as the NDVI, the Red edge Normalized Difference vegetation Index, and the Simple Ration Index. The observational areas are from typical Mediterranean forest environments in Italy, two broadleaf, and one evergreen forest. The research result claims Sentinel-2 derived vegetation index results are statistically best fitted with observational results.