## 4 Results
### Accuracy Assessment of RFC Models
SPL RFC models generally performed better than CxQ and HPLM RFC models in most classes, including the three dominant cover types, which were corn, soybean, and grassland. However, only increases in \begin{table}
\begin{tabular}{l c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Producer’s Accuracy (\%)**} & \multicolumn{4}{c}{**User’s Accuracy (\%)**} \\ \cline{2-11}
**Land Cover** & \multicolumn{2}{c}{**ARD**} & \multicolumn{2}{c}{**HLS**} & \multicolumn{2}{c}{**ARD**} & \multicolumn{2}{c}{**HLS**} \\ \cline{2-11}  & **C1S** & **C2M** & **C1S** & **C2M** & **C1S** & **C2M** & **C1S** & **C2M** \\ \hline Corn & 94.6 & 95.7 & *** & 91.2 & 92.6 & *** & 94.8 & 95.9 & *** & 89.8 & 91.5 & *** \\ Wheat & 75.4 & 78.6 & *** & 70.2 & 74.4 & *** & 84.4 & 90.2 & *** & 82.0 & 89.1 & *** \\ Alfafla & 73.5 & 82.6 & *** & 69.3 & 79.9 & *** & 83.7 & 91.2 & *** & 79.8 & 89.6 & *** \\ Soybean & 95.4 & 96.6 & *** & 90.3 & 92.1 & *** & 93.6 & 95.2 & *** & 90.4 & 92.2 & *** \\ Other Crops & 11.2 & 50.9 & *** & 15.3 & 55.0 & *** & 35.8 & 70.2 & *** & 46.6 & 71.0 & *** \\ Water & 97.4 & 98.3 & *** & 96.2 & 98.2 & *** & 97.5 & 97.6 & *** & 96.3 & 96.9 & *** \\ Barren/Dev. & 55.1 & 60.9 & *** & 47.4 & 56.1 & *** & 77.0 & 79.0 & *** & 72.4 & 75.9 & *** \\ Forest & 87.7 & 94.0 & *** & 84.3 & 94.5 & *** & 86.7 & 91.1 & *** & 84.8 & 92.4 & *** \\ Grassland & 93.0 & 94.9 & *** & 93.6 & 96.1 & *** & 84.9 & 88.6 & *** & 85.6 & 90.4 & *** \\ Wetland & 66.8 & 79.2 & *** & 73.9 & 87.7 & *** & 74.2 & 84.4 & *** & 76.3 & 87.5 & *** \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Producer’s and user’s accuracies (in percent) of 2016 RFC models using C1S and C2M sample pools. Significance levels of the U test (C1S < C2M) across rows are indicated by ***, **, and * for p-values of less than 0.001, 0.01, and 0.05, respectively. NS stands for “not significant”. Results of the TOST equivalence tests across rows are highlighted in light blue for “not equivalent” and light yellow for “equivalent”. \begin{table}
\begin{tabular}{l c c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Producer’s Accuracy (\%)**} & \multicolumn{4}{c}{**User’s Accuracy (\%)**} \\ \cline{2-11}
**Land Cover** & \multicolumn{2}{c}{**ARD**} & \multicolumn{2}{c}{**HLS**} & \multicolumn{2}{c}{**ARD**} & \multicolumn{2}{c}{**HLS**} \\ \cline{2-11}  & **P01** & **P25** & **P01** & **P25** & **P01** & **P25** & **P01** & **P25** & **P01** & **P25** \\ \hline Corn & 94.1 & 96.2 & *** & 89.8 & 93.6 & *** & 93.0 & 96.7 & *** & 87.4 & 92.6 & *** \\ Wheat & 58.1 & 87.4 & *** & 49.6 & 85.0 & *** & 84.5 & 90.2 & NS & 80.6 & 89.0 & NS \\ Alfafla & 61.9 & 87.9 & *** & 55.0 & 86.5 & *** & 75.2 & 92.9 & NS & 69.9 & 92.0 & NS \\ Soybean & 94.6 & 96.8 & *** & 88.5 & 92.8 & *** & 92.2 & 96.1 & *** & 87.9 & 93.6 & *** \\ Other Crops & 7.1 & 48.3 & *** & 9.1 & 55.9 & *** & 7.0 & 84.7 & *** & 9.0 & 89.5 & *** \\ Water & 97.5 & 98.5 & NS & 97.0 & 97.9 & NS & 97.4 & 97.8 & NS & 96.1 & 96.8 & NS \\ Barren/Dev. & 49.6 & 64.2 & *** & 38.8 & 58.9 & *** & 72.5 & 81.7 & *** & 66.0 & 78.9 & *** \\ Forest & 86.6 & 93.4 & NS & 84.5 & 92.8 & NS & 85.3 & 91.6 & NS & 84.7 & 91.6 & NS \\ Grassland & 92.6 & 94.7 & *** & 93.7 & 95.7 & *** & 83.7 & 88.5 & *** & 84.8 & 90.1 & *** \\ Wetland & 64.8 & 77.6 & *** & 74.5 & 84.5 & *** & 72.8 & 83.5 & *** & 74.6 & 86.3 & *** \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Producer’s and user’s accuracies (in percent) of 2016 RFC models using P01 and P25 sample sizes. Significance levels of the U test (P01 < P25) across rows are indicated by ***, **, and * for p-values of less than 0.001, 0.01, and 0.05, respectively. NS stands for “not significant”. Results of the TOST equivalence tests across rows are highlighted in light blue for “not equivalent” and light yellow for “equivalent”. non-crop types were significant (Table S9). Compared to phenometrically-based models, SPL RFC models were much more accurate in barren/developed, forest, and wetland. On the other hand, CxQ and HPLM RFC models yielded higher PA/UA values for wheat and other crops.