% \begin{figure*}[ht!]
%   \begin{floatrow}
%     \ffigbox[\dimexpr0.49\textwidth\relax]{%
%       \includegraphics[width=\linewidth]{figures/susbench_figure.pdf}%
%     }{%
%       \caption{\textbf{Performance and label-efficiency of a U-Net trained on SustainBench's Farmland Parcel Delineation Dataset.} We use the standard ID split as benchmarked on in \cite{ermonsus}. Label efficiency and out-of-distribution performance reported as IoU scores averaged over five random seeds. OSM and EU-DEM-aided models match RGB-only model’s best score with 221 training images (total = 1573 images).}%
%       \label{fig:sustainbench}%
%     }

%     \hfill

%     \ffigbox[\dimexpr0.49\textwidth\relax]{%
%       \includegraphics[width=\linewidth]{figures/treecover_con.png}%
%     }{%
%       \caption{\textbf{Performance and data-efficiency of a ResNet50 trained with and without an OpenStreetMaps raster data layer as \texttt{STACK} on the USAVars dataset.} Results computed as a test $R^2$ score on the USAVars regression task for tree-cover prediction.}%
%       \label{fig:usavars_treecover}%
%     }
%   \end{floatrow}
% \end{figure*}



\begin{figure}[t]
  \centering
  \includegraphics[width=\linewidth]{figures/susbench_figure.pdf}
  \caption{\textbf{Performance and label-efficiency of a U-Net trained on SustainBench's Farmland Boundary Delineation Dataset.} We use the standard ID split as benchmarked on in \cite{ermonsus}. Label efficiency and out-of-distribution performance reported as IoU scores averaged over five random seeds. OSM and EU-DEM-aided models match RGB-only model’s best score with 221 training images (total = 1573 images).}
  \label{fig:sustainbench}
\end{figure}

\begin{figure}[h!]
  \centering
  \includegraphics[width=\linewidth]{figures/treecover_con.png}
  \caption{\textbf{Performance and data-efficiency of a ResNet50 trained with and without an OSM raster data layer as \texttt{STACK} on the USAVars treecover regression task.} Dashed lines show the performance of each input set using the full dataset (100,000 points) as training data.
  }
  \label{fig:usavars_treecover}
\end{figure}