# Status of Phenological Research Using Sentinel-2 Data: A Review
## 6 Current Developments in Using Sentinel-2 for Phenological Research
### Further Prospects  
The current HLS dataset covers the period starting from 2013 for L30 and 2015 for S30 products, as it includes only Landsat-8 and Sentinel-2 data. To date, little work has been reported on inclusion of Landsat-5 and 7 to further extend the historic time series back in time (though data from Sentinel-2 would be lacking for the period before 2015), which could provide more than 30 years of data starting from the 1980s. A study by [PERSON] et al. (2016) [159] provides valuable insights into statistical techniques for normalising data from Landsat-5 and 7, which have different sensor characteristics. Such procedures in combination with data from high temporal frequency data from geostationary satellites (as discussed in Section 6.3) could further improve the modelling of land surface phenology.  
With the Sentinel 2-C and 2-D sensors expected to be launched in 2021, to provide continuity of the mission, data from these new satellites, combined with the existing Sentinel-2 data (A and B, provided they are still in operation) could further help resolve issues associated with cloud cover. The Sentinel-2 suite of sensors is thus expected to provide up to 15 years of freely available time series data, which will facilitate more comprehensive studies of vegetation phenology and their climatic drivers. Similarly, with Landsat 9 (that has a similar design to Landsat-8) scheduled to be launched in 2021, the success of the HLS dataset could be further extended and improved. All of these data sets are expected to improve phenological studies by overcoming existing limitations.  
In spite of the additional red-edge and SWIR bands available on the Sentinel-2 multispectral instruments with their improved vegetation species detection capabilities, there has been very little research on their efficacy to track vegetation cover and its phenology. For example, out of approximately every four papers that analyse NDVI or EVI derived from Sentinel-2 imagery, only one mentions either SWIR or the red-edge bands. However, there is a growing body of evidence that suggests that the information contained within the red-edge bands is critical for discriminating not only species but also their growth stages and health status. This review also brought to light that most Sentinel-2-based studies are concentrated on mapping crops and their seasonality. Although Sentinel 2 possesses capabilities to monitor phenological and other events across a range of different ecosystems as mentioned in this review, more attention is still needed to show enough confidence in the improved potential of Sentinel-2 in LSP studies.  
The literature analysis in this review paper found Sentinel-2-based phenology research to be mainly skewed towards croplands, with other land covers lacking similar attention amongst peer-reviewed papers. Even within the croplands, the phenological metrics, such as the SOS, POS, and EOS, are not always calculated, and the studies mostly concentrate on mapping of crop types and discriminating croplands from other land uses and land covers. Along with other information on crops, such as cropping intensity, location, health, water use and productivity, crop phenological estimates are equally critical for ensuring world food security [160]. Additionally, information on crop phenology (i.e., the cropping calendar and the dates of key growth stages) are important in the agronomic management of crops [161]. Hence, more efforts are required for testing the efficiency of Sentinel-2 data in estimating phenophases of crops.