# The Value of Sentinel-2 Spectral Bands for the Assessment of Winter Wheat Growth and Development
## 3 Results
### Sentinel-2 Band Analysis and Responses  
Overall, the GPR model produced a high agreement with the LAI, LCC and CCC observations for all MAIA/Sentinel-2 band combinations (Figure 3). For the most explanatory band combinations, the mean R\({}^{2}\) was 0.89 and 0.83 without and with the propagated uncertainty, respectively. The model performance was greatest when estimating the CCC with the R\({}^{2}\) ranging from 0.92 (without uncertainty) to 0.86 (with uncertainty). On the basis of the standard deviations of R\({}^{2}\) and RMSE values, with the sequential band removal, the estimation uncertainty for each of the variables remained relatively stable until the successive removal of bands from the most explanatory band combinations, where error and uncertainty of these estimates sharply increased when using less than the optimum number of spectral bands.  
In comparing the GPR band selection with and without propagating observational uncertainty, it was found that without uncertainty, the number of bands included in the optimum bands was four for each variable, whereas the number of key bands varied from two to three when including uncertainty (Figure 3). The MAIA/Sentinel-2 red-edge band at 705 nm and near-infrared 783 nm band were frequently included in the most explanatory band combinations. The selected band combinations for the estimation of LAI and CCC were identical--comprising two red-edge and two near-infrared bands (705, 740, 783 and 865 nm) for the GPR models without the observational uncertainty. For the models including uncertainty, however, the two most explanatory bands selected for estimating LAI and CCC were that of the red-edge (705 nm) and near-infrared 865 nm bands only.  
For the most explanatory bands selected from the GPR framework developed with the propagated uncertainty, we analysed the sensitivity of these individual bands for estimating LAI and LCC based on the spectral responses to these two variables (Figure 4 and Table 3). The red-edge band at 705 nm showed a general exponential decrease in reflectance with increasing LAI (R\({}^{2}\) = 0.61), whereas the near-infrared band (865 nm) was characterised by a linear increase in reflectance with increasing LAI (R\({}^{2}\) = 0.67). For individual band responses to LCC, both the blue (490 nm) and green (560 nm) band reflectance exhibited a weak linear correlation (R\({}^{2}\) was 0.46 and 0.55 for the blue and green bands,  
Figure 2: Comparison of in situ non-destructive to mean destructive sample measurements acquired on three dates (25 May, 13 June and 4 July 2018) for five winter wheat trial plots, including (**a**) in situ measured Leaf Area Index (LAI) (SunScan) compared to LAI measured from destructive samples and (**b**) chlorophyll meter (soil plant analyses development (SPAD)) measured leaf chlorophyll content (LCC) compared to leaf nitrogen content measurements. Note: Fit line (black line) is defined using reduced major axis where \(y\)-axis error bars are derived from the standard deviations of non-destructive measurements and \(x\)-axis error bars represent the mean range between two destructive samples that were analysed for each plot.