# Status of Phenological Research Using Sentinel-2 Data: A Review
## 6 Current Developments in Using Sentinel-2 for Phenological Research
### Performance of Sentinel-2 Red-Edge Bands in Phenological Research
Sentinel-2 bands simulated from in situ spectroradiometers were also used by [PERSON] and [PERSON] (2013) [133], who reported a highly linear relationship (R\({}^{2}>\) 0.80) between the chlorophyll red-edge index (from red-edge bands 7 and 5) and the measured chlorophyll and nitrogen content of crops. The authors cited the higher sensitivity of red-edge bands due to their lower absorption by chlorophyll in the red-edge region as compared to the red band (when using NDVI data). Once operational, a study by [PERSON] et al. (2017) [134] showed that canopy chlorophyll content in maize and soybean, as estimated from field observations, matched closely to that of Sentinel-2 calculated indices using the red-edge bands. The red-edge bands were found to be much more resistant to hysteresis driven by canopy structures compared to chlorophyll estimation using NDVI, EVI and simple ratio (SR). [PERSON] et al. (2018) [135] found that atthe landscape scale, Sentinel-2 showed a high correlation of up to 0.73 with hyperspectral airborne imagery (compact airborne spectral imager (CASI)) when the latter was resampled spectrally and spatially to match that of Sentinel-2. The same study also demonstrated that, compared to NDVI or SR, the Sentinel-2 red-edge normalised vegetation index (RE-NDVI) was able to capture the greening trend most closely to that measured by field spectroscopy. [PERSON] et al. (2018) ([PERSON] et al. (2018) found that Sentinel-2 NDVI used in combination with the chlorophyll red-edge index could explain the variability in the temporal trajectory of changing vegetation conditions by about 88%. This helped establish distinct baseline conditions for monitoring vegetation health, and is therefore able to distinguish between healthy, recovering, and declining trees. Among a set of different indices evaluated in the study mentioned above (photochemical reflectance index (PRI), NDVI, transformed chlorophyll absorption index (TCARI)/soil adjusted vegetation index (OSAVI), chlorophyll red-edge and Maccioni index (Macc)), it was found that the chlorophyll red-edge had a close linear relationship with chlorophyll-a and -b. Similar observations were also made by [PERSON] et al. (2018) ([PERSON] et al., 2018), who reported an improvement of over 10% in the overall accuracy from the multi-temporal NDVI-based mapping of crops when information from the red-edge bands was also included. This study revealed that the highly coincident spectral response of winter season cropped wheat and oat in the broad visible and NIR bands of high spatial resolution WorldView-3 were only separable in the narrow bands of Sentinel-2-based red-edge and NIR. By contrast, the red-edge bands were shown by [PERSON] et al. (2017) ([PERSON] et al., 2017) to perform poorly in tracking the temporal changes in chlorophyll content in potato crops with both chlorophyll absorption and canopy scattering in the red-edge band 5 of Sentinel-2, and it is not possible to distinguish the contribution of each of the phenomena. In another study, [PERSON] et al. (2019) ([PERSON] et al., 2019) used data from several Sentinel-2 bands and indices to monitor colour changes and texture that indicate crop growth stage and crop density, respectively. The authors showed that the narrow NIR band 8a from Sentinel-2 revealed separability among crops for all growth stages, whereas the red-edge bands and other vegetation indices (i.e., triangular vegetation index (TVI), EVI, NDWI and normalised difference tillage index (NDTI)) could indicate crop separability only from the middle maturity, or mid growing season, onwards.