## 3 Analyses and Results  
### Forest Distribution of Northeast China Derived from HJ-1 Images  
The confusion matrix is presented in Table 4, including user's accuracy, producer's accuracy, and overall accuracy of various forest maps in Northeast China. An overall accuracy of 0.91 \(\pm\) 0.01, with a 95% confidence interval, was obtained from the HJ-1 based forest map. The producer's accuracy and user's accuracy of forest were 0.87 \(\pm\) 0.005 and 0.89 \(\pm\) 0.02, respectively. The HJ-1 based forest map was in high accuracy. The classification accuracy of forest types was also assessed using the field validation data, indicating that the overall accuracy is approximately 0.75 \(\pm\) 0.01, with a 95% confidence interval (Table 5). The producer's accuracy and user's accuracy of deciduous broadleaf forest were the highest among all types of forest. The accuracies for shrubland and mixed forest were lower than other forest types, primarily due to the complicated mixing of different forest types and limited spatial resolution of remote sensing imagery. The forest area was estimated to be 5.0 \(\times\) 10\({}^{5}\) km\({}^{2}\) for Northeast China, accounting for 40.3% of the entire land area in the region (Figure 5a). The forested areas were dominated by deciduous broadleaf forest, which occupied 69% of the forested area, and deciduous needleleaf forest, which is 20% of the forested area. The other forest such as mixed forest, evergreen needleleaf forest, and shrubland is around 7%, 3% and 1% of the forested area, which shows a small proportion of the forest areas. The dominant tree species in Northeast China include Larix gmelinii, Korean pine, spruce, fir, birch, Mongolian oak, lime tree Huang Bo, walnut, Chinese catalpa, elm and maple tree, etc. The areas of all kinds of forest in different ecological functional zones of Northeast China are listed in Figure 6. Forests are largely distributed across mountainous terrain, including the Daxing'an Mountains, Xiaoxing'an Mountains and Changbai Mountains, with limited distribution in the low hills and plains (Figure 5a). The statistical results (Figure 6) also reveal the following order of estimated \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Data**} & \multicolumn{4}{c}{**GT Samples**} & \multirow{2}{*}{**WI**} & \multirow{2}{*}{**UA**} & \multirow{2}{*}{**PA**} & \multirow{2}{*}{**OA**} \\ \cline{3-3} \cline{5-8}  & & **Forest** & & & & & & \\ \hline \multirow{2}{*}{HJ-1 CCD} & forest & 1169 & 142 & 0.40 & 0.89 \(\pm\) 0.02 & 0.87 \(\pm\) 0.005 & \multirow{2}{*}{0.91 \(\pm\) 0.01} \\  & non-forest & 359 & 2303 & 0.60 & 0.94 \(\pm\) 0.01 & 0.92 \(\pm\) 0.005 & \\ \hline \multirow{2}{*}{MCD12Q1} & forest & 520 & 127 & 0.34 & 0.80 \(\pm\) 0.03 & 0.58 \(\pm\) 0.007 & \multirow{2}{*}{0.71 \(\pm\) 0.01} \\  & non-forest & 1008 & 2318 & 0.66 & 0.70 \(\pm\) 0.02 & 0.87 \(\pm\) 0.007 & \\ \hline \multirow{2}{*}{GlobCover} & forest & 555 & 275 & 0.36 & 0.67 \(\pm\) 0.03 & 0.56 \(\pm\) 0.008 & \multirow{2}{*}{0.69 \(\pm\) 0.02} \\  & non-forest & 973 & 2170 & 0.64 & 0.70 \(\pm\) 0.02 & 0.79 \(\pm\) 0.008 & \\ \hline \multicolumn{8}{l}{Note: GT: Ground Truth; WI: proportion of area mapped; UA: User’s Accuracy; PA: Producer’s Accuracy; OA: Overall accuracy.} \\ \end{tabular}
\end{table} 
Table 4: Confusion matrix of accuracy assessments of the three forest maps with a 95% confidence interval.