## 2 Methods
### Sentinel-1 Data Acquisition and Processing  
We used Google Earth Engine (GEE) [70] to process Sentinel-1 backscatter imagery with VH and VV polarizations. The Sentinel-1 ground range detected (GRD) scenes on GEE had previously been processed with ESA's Sentinel Application Platform (SNAP) toolbox (SNAP, 2021) using the processing sequence of: updating image orbit file, GRD image border noise removal, thermal noise removal, radiometric calibration, and geometric terrain correction (orthorectification). In addition to using the VH and VV backscatter imagery, we also calculated RVI by modifying the original quad-pol equation [40] to be suited for dual-pol as per [66]. We also further adapted the equation because the dual-pol modifications described in [66] included polarizations that are not present in Sentinel-1 (Table 2). To perform polarimetric decompositions on the same Sentinel-1 scenes that are processed to backscatter in GEE, we downloaded these scenes in single-look-complex (SLC) format from ESA to the calculate polarimetric parameters of entropy, anisotropy, and alpha. Polarimetric decompositions were performed in SNAP toolbox using the following sequence: image calibration, C2 matrix computation, polarimetric speckle filtering (\(5\times 5\) \begin{table}
\begin{tabular}{c c c c} \hline
**Abbreviation** & **Parameter** & **Formula** & **Citation** \\ \hline NDVI\_RE1 & Red-edge normalized difference vegetation index (B5) & & \\ \hline NDVI\_RE2 & Red-edge normalized difference vegetation index (B6) & & [59] \\ \hline NDVI\_RE3 & Red-edge normalized difference vegetation index (B7) & & \\ \hline NDRE & Normalized difference red-edge index & & [60,61] \\ \hline SR\_RE1 & Simple ratio red-edge index (B5) & & \\ \hline SR\_RE2 & Simple ratio red-edge index (B6) & & [31] \\ \hline SR\_RE3 & Simple ratio red-edge index (B7) & & \\ \hline RER & Red-edge ratio index & & [29,62] \\ \hline RTVI1 & Red-edge triangular vegetation index (B5) & & \\ \hline RTVI2 & Red-edge triangular vegetation index (B6) & & \\ \hline RTVI3 & Red-edge triangular vegetation index (B7) & & \\ \hline VARI\_RE1 & Visibly atmospherically resistant index red-edge (B5) & & [30] \\ \hline VARI\_RE2 & Visibly atmospherically resistant index red-edge (B6) & & [30] \\ \hline VARI\_RE3 & Visibly atmospherically resistant index red-edge (B7) & & [31,64,22] \\ \hline VARI\_green & Visibly atmospherically resistant index green & & [32,65,27,28] \\ \hline TVI & Triangular Vegetation index & \(0.5*[120*(\rho_{\rm NIR}-\rho_{\rm Coma})-200*(\rho_{\rm Rad}-\rho_{\rm Coma})]\) & [14,21,64] \\ \hline MTVI2 & Modified triangular vegetation index 2 & & [65,27,28] \\ \hline MCARI2 & Modified ChlorophyllM Astortion Ratio Index 2 & & [65,27,28] \\ \hline NDVI & Normalized difference vegetation index & & [31,29,20,21] \\ \hline kNDVI & Kernel normalized difference vegetation index & & [33] \\ \hline NIRV [66] & Near-infrared reflectance of vegetation index & & [32] \\ \hline SR & Simple ratio vegetation index & & [67] \\ \hline SAVI & Soil adjusted vegetation index & & [64,68] \\ \hline EVI & Enhanced vegetation index & \(2.5*(\rho_{\rm NIR}-\rho_{\rm Rad})/(1+\rho_{\rm NIR}+6*\rho_{\rm Rad}-7.5*\rho_{ \rm Thin})\) & [64,68] \\ \hline NDWI1 & Normalized difference water index (B11) & & [69] \\ \hline NDWI2 & Normalized difference water index (B12) & & [70] \\ \hline SR\_WI & Simple ratio water index & & [81] \\ \hline \end{tabular}
\end{table} 
Table 1: List of optical vegetation indices (VIs) calculated from Sentinel-2 imagery where \(\rho\) indicates reflectance of a given optical band, REx indicates a red-edge optical band (which can be either band 5, 6 or 7 depending on the index variant), and SWIRx indicates a shortwave infrared band (with band 11 or 12 depending on index variant). -Refined Lee), H-Alpha dual-pol decomposition (window size = 5), and geometric terrain correction.