# The Value of Sentinel-2 Spectral Bands for the Assessment of Winter Wheat Growth and Development
## 1 Introduction  
Leaf Area Index (LAI) and chlorophyll content are essential indicators of crop phenological status and condition, which can be used to support a range of precision agricultural technologies. For instance, LAI is a key biophysical parameter that quantifies plant canopy structure and function. LAI is, therefore, related to canopy-scale processes, including evapotranspiration, photosynthesis, respiration and the interception of precipitation and solar radiation [1; 2]. Consequently, past research has demonstratedthe value of LAI data for updating state variables in process-based agroecosystem models in order to improve estimates of crop yield [3; 4; 5; 6] and land-atmosphere carbon dioxide exchanges [7; 8]. On the other hand, chlorophyll is a key driver of plant light absorption and conversion to chemical energy and is, therefore, an indicator of plant health and potential gross primary productivity [9; 10]. In particular, leaf chlorophyll content is linked to leaf photosynthetic capacity via the maximum rate of carboxylation (V\({}_{\text{max}}\)). The Ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) enzyme, which relates to V\({}_{\text{max}}\) and leaf-level carbon fixation, correlates to leaf nitrogen (N) content [11]. Since leaf N also consists of chlorophyll, plant chlorophyll is strongly correlated to leaf N [12; 13; 14] including that for winter wheat [15]. LAI and chlorophyll content are important factors determining crop reflectance [11] and can, therefore, be estimated from optical Earth observation satellite sensors, which provide synoptic and repetitive coverages over large areas [16]. The retrieval of these variables from Earth observation multispectral data has extensively been carried out empirically through the statistical relationship between spectral vegetation indices (VI), typically the Normalised Difference Vegetation Index [17], to ground measurements. Although simple to apply, the development of VIs are often time-, location- and scale-specific, (i.e., leaf or canopy-scale [18]). Furthermore, VIs make simplistic assumptions about the reflectance properties of a target and typically use only two to three fixed spectral bands [19], thus under-exploiting the potential of Earth observation multispectral sensors. Alternatively, machine learning approaches have the potential to generate adaptive, robust and non-linear relationships between all spectral bands and ground measurements [20]. However, uncertainties that exist in ground measurements [11] are seldom propagated when calibrating and validating retrieval algorithms, including those involving machine learning approaches and VIs. In order to support precision agricultural management decisions, [PERSON] [21] has argued that Earth observation sensors would require spatial resolutions as fine as 20 m. Furthermore, in order to track the temporal dynamics of crop growth, observations for monitoring crop condition are required, with at least a biweekly temporal resolution [22; 23]. The recent availability of data from the European Space Agency's (ESA) Sentinel-2 dual-satellite constellation, with a spatial resolution of up to 10 m combined with an average global revisit time of 5 days and an open-access policy, could fulfil the requirements of precision agriculture [24; 25]. In contrast to previous satellite missions (including SPOT-6/7 and Landsat-8/9) the Sentinel-2 multi-spectral instrument includes measurements in two red-edge wavebands, centred at 705 and 740 nm. Observations in this red-edge region, defined as the sharp change in leaf reflectance between 680 and 750 nm [26], are particularly significant for the estimation of chlorophyll and, thus, N content [27; 28; 29; 18]. Specifically, where conventional approaches often involve combining near-infrared with red bands, the red spectra are strongly absorbed by chlorophyll, becoming saturated at intermediate to high levels [30]. The red-edge band, however, has a lower absorption by chlorophyll and a reduced saturation at higher values [31].