## 2 Materials and Methods
### Data
#### 2.1.4 Sentinel-2 Imagery and Phenology  
The specific dates of Sentinel-2 images for 2018 were selected as those closest to the estimated phenological date (regarding GDD calculations) per zone as detailed in Table 2 and with the minimal cloud cover thresholds; the specific Sentinel-2 images used in this study are shown in Table 3. The Sentinel-2 a + b satellite constellation's combined global coverage every 5 days enables this level of phenology matching for the first time ever since its second satellite was launched in 2017.  
Sentinel-2 multispectral bands (Table 4) were downloaded from Copernicus Open Access Hub ([[https://scihub.copernicus.eu/](https://scihub.copernicus.eu/)]([https://scihub.copernicus.eu/](https://scihub.copernicus.eu/))). Despite the high 5-day temporal resolution of Sentinel-2 a + b constellation, some images were discarded due to the image-wide cloud cover areas exceeding 40%. Four Sentinel-2 tiles cover the region under study. The images were downloaded for the 2018 (15-03, 30-03, 14-04, 24-04, 09-05, 19-05, 24-05, 03-06, 18-06 and 23-06) and 2019 (15-03, 20-03, 25-03, 30-03, 09-04, 29-04, 09-05, 14-05, 08-06, 18-06 and 28-06) seasons. Images were downloaded as an LIC product and were corrected to level 2A using the Sen2 Cor tool on SNAP (Sentinel Application Platform), obtaining Bottom-Of-Atmosphere (BOA) and cirrus corrected reflectance images. Moreover, a cloud and cloud shadow mask were also applied with this tool.  
From the Sentinel-2 multispectral data bands (Table 4), the following spectral reflectance vegetation indices (VIs), which are simple mathematic combinations of spectral bands, were calculated: the chlorophyll index green (CI green) and the chlorophyll index red edge (CI red edge), related to chlorophyll content [38]; the normalized difference water index (NDWI), related to water content [39]; the modified soil-adjusted vegetation index (MSAVI) [40] and the optimized soil adjusted vegetation index (OSAVI) [41], associated with vegetation cover; and the renormalized difference vegetation index  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Montana (II)** & **Media (V)** & **Ribera Alta (VI)** \\ \hline
**Tillering** & 30-03-2018; 28-03-2019 & 03-04-2018; 29-03-2019 & 18-03-2018; 22-03-2019 \\
**Heading** & 10-05-2018; 08-05-2019 & 17-05-2018; 15-05-2019 & 26-04-2018; 29-04-2019 \\
**Ripening** & 25-06-2018; 27-06-2019 & 19-06-2018; 20-06-2019 & 05-06-2018; 06-06-2019 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Estimated phenological day of year regarding GDD average (Table 1) for the seasons analyzed (2018 and 2019).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Montana (II)** & **Media (V)** & **Ribera Alta (VI)** \\ \hline
**Tillering** & 30-03-2018; 14-04-2018 & 30-03-2018; 14-04-2018 & 15-03-2018; 30-03-2018 \\
**Heading** & 09-05-2018; 19-05-2018 & 19-05-2018; 24-05-2018 & 24-04-2018; 09-05-2018 \\
**Ripening** & 18-06-2018; 23-06-2018 & 18-06-2018; 23-06-2018 & 03-06-2018; 18-06-2018 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Closest Sentinel-2 images available to the estimated phenological dates in 2018 (Table 2), used for building the prediction model.  
(RDVI) [42], the ratio vegetation index (RVI) [43], the modified simple ration (MSR) [44], the normalized difference vegetation index (NDVI) [45], and the green normalized difference vegetation index (GNDVI) [46] sensitive to biomass (Table 5).