## 3 Results
### Optical--Synthetic Aperture Radar (SAR) Results
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Model** & **Adj R\({}^{2}\)** & **RMSE** & **MAE** & **AICc** & **AICw** \\ \hline \multicolumn{6}{c}{**Wheat**} \\ \hline NDVI\_RE1 + Coh + \(H\) & 0.74 & 1223.24 & 770.73 & 258 & 0.63 \\ NDVI\_RE1 + Coh & 0.74 & 1226.79 & 783.74 & 259 & 0.37 \\ NDVI\_RE1 + \(H\) & 0.71 & 1263.33 & 848.04 & 280 & 0 \\ NDVI\_RE1 + VH & 0.70 & 1285.51 & 872.42 & 281 & 0 \\ NDVI\_RE1 + \(A\) & 0.70 & 1280.42 & 853.11 & 281 & 0 \\ NDVI\_RE1 + Alpha & 0.70 & 1273.26 & 854.26 & 282 & 0 \\ NDVI\_RE1 & 0.70 & 1268.34 & 865.56 & 282 & 0 \\ NDVI\_RE1 + RVI & 0.70 & 1278.49 & 870.41 & 282 & 0 \\ NDVI\_RE1 + VHVV & 0.70 & 1273.13 & 866.04 & 283 & 0 \\ NDVI\_RE1 + VV & 0.70 & 1267.58 & 865.75 & 284 & 0 \\ \hline \multicolumn{6}{c}{**Tritictale**} \\ \hline NDVI\_RE1 + Coh & 0.81 & 792.95 & 553.09 & 46 & 0.72 \\ NDVI\_RE1 + Coh + \(A\) & 0.81 & 783.8 & 542.96 & 48 & 0.28 \\ NDVI\_RE1 + \(A\) & 0.77 & 924.37 & 618.7 & 59 & 0 \\ NDVI\_RE1 + \(H\) & 0.77 & 934.07 & 621.4 & 60 & 0 \\ NDVI\_RE1 + Alpha & 0.77 & 933.43 & 623.29 & 61 & 0 \\ NDVI\_RE1 + VHVV & 0.77 & 957.74 & 627.05 & 61 & 0 \\ NDVI\_RE1 & 0.76 & 974.67 & 637.5 & 61 & 0 \\ NDVI\_RE1 + RVI & 0.76 & 904.44 & 618.24 & 62 & 0 \\ NDVI\_RE1 + VH & 0.76 & 954.15 & 634.29 & 63 & 0 \\ NDVI\_RE1 + VV & 0.76 & 980.84 & 638.24 & 63 & 0 \\ \hline \multicolumn{6}{c}{**Cereal Rye**} \\ \hline NDVI\_RE1 + VV + RVI + Coh & 0.38 & 771.81 & 596.63 & 165 & 0.75 \\ NDVI\_RE1 + Coh & 0.34 & 775.54 & 590.93 & 167 & 0.24 \\ NDVI\_RE1 + VV & 0.28 & 803.22 & 636.09 & 175 & 0 \\ NDVI\_RE1 + RVI & 0.25 & 836.67 & 653.54 & 178 & 0 \\ NDVI\_RE1 + VH & 0.25 & 800.37 & 638.94 & 178 & 0 \\ NDVI\_RE1 & 0.23 & 811.92 & 643.24 & 180 & 0 \\ NDVI\_RE1 + \(H\) & 0.22 & 811.37 & 637.39 & 181 & 0 \\ NDVI\_RE1 + VHVV & 0.23 & 811.87 & 641.96 & 181 & 0 \\ NDVI\_RE1 + Alpha & 0.22 & 815.53 & 641.43 & 182 & 0 \\ NDVI\_RE1 + \(A\) & 0.22 & 813.57 & 640.74 & 182 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Results of combined optical and synthetic aperture radar (SAR) species-specific regression models. Models combined the optical normalized difference red-edge index using band 5 (NDVI_RE1) with SAR backscatter indices (vertical-vertical (VV), vertical-horizontal (VH), VH/VV, and radar vegetation index (RVI)) and polarimetric parameters (alpha, entropy (\(H\)), anisotropy (\(A\)), InSAR coherence (Coh)), sequentially. Models were evaluated using goodness of fit (adjusted R\({}^{2}\)), root mean square error (RMSE), mean absolute error (MAE), and model fit statistics—Akaike’s information criterion for small samples (AICc ) and AIC weights (AICw). (\(\Delta\)R\({}^{2}\) = +3-9%; Table 6). We also observed small-to-moderate reductions in errors in wheat, tritticale, and rye cross-validation (\(\Delta\)RMSE = 37, 188, and 23 kg ha\({}^{-1}\); \(\Delta\)MAE = 74, 92, and 37 kg ha\({}^{-1}\), respectively). We observed that, as biomass increased, InSAR coherence decreased, a pattern that results from increased volume scattering producing return signals with a random phase (Figure 6). However, in 47 out of 573 datapoints (i.e., two April sampling dates: cereal rye = 0, tritticale = 26, wheat = 21), cover crop termination events occurred between the acquisition of the InSAR image pairs. Termination events may result in additional InSAR coherence decreases as they significantly alter the landscape structure between images in the InSAR pair. For this reason, we performed a sensitivity analysis to assess whether model statistics changed between models with or without including these 47 observations and found no substantial differences (Appendix C).