## 5 Results and Discussion
### Results of Sensitivity Analysis  
Figure 5a-c illustrates the effect of noise on SCD when it was applied to the time series with simulated land-cover changes. When noise level increased, accuracy decreased. For the change intensity, the RMSE of change date (Figure 5a) became greater from one change to three changes at noise level (represented by sigma \(\sigma\)) smaller than 0.05, but varied little across the three change intensities at noise level greater than 0.05. On the other hand, the omission errors (Figure 5c) are greater and increased more rapidly with noise for time series with intensity at one change than two or three changes. Meanwhile, the RMSE of the number of change does not show much difference among the three change intensities even when noise level increased; the variability of the RMSE for the intensity at one change is slightly larger than the other two change intensities (Figure 5b). It is noted that the simulated time series with intensity at one change consist of six change types characterized with large variability among time series and thus were more sensitive to noise, compared to the simulated time series with intensity at three changes which only represent one change type. Figure 5d shows the influence of noise on the performance of SCD when it was applied to the stable time series, assessed by the ratio of false change to the total number of stable time series for each land-cover class. For all six classes, the ratio of false change increased slightly, e.g., from 0 to 0.01-0.12, when the noise level increased from 0.01 to 0.07. The ratio of false change in the class of broadleaf deciduous forest, cropland, mixed forest and cropland mosaic (class 1, 2, 5 and 6) shows very small variation with noise. In contrast, the ratios for the class of woody savanna and permanent wetland (class 3 and 4) have great variations when the noise level is greater than 0.02. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Number of**} & \multirow{2}{*}{**Land-Cover Transitions**} & \multicolumn{2}{c}{**Time Steps**} & \multicolumn{2}{c}{**Number**} & \multirow{2}{*}{**Omission**} \\ \cline{3-3} \cline{5-7}  & & **(Sample Size)** & & & & & \\ \hline \multirow{8}{*}{1} & forest \(\rightarrow\) grassland (100) & 6.6 & 2.8 & 2.3 & 1.5 & 1.2 \\  & forest \(\rightarrow\) wetland (100) & 7.7 & 3.8 & 2.2 & 1.3 & 1.8 \\  & forest \(\rightarrow\) cropland (100) & 7.7 & 1.8 & 1.7 & 0.7 & 3.5 \\  & grassland \(\rightarrow\) wetland (100) & 8.2 & 0.5 & 2.1 & 0.8 & 4.0 \\  & grassland \(\rightarrow\) cropland (100) & 6.7 & 0.4 & 1.3 & 0.9 & 0.2 \\  & wetland \(\rightarrow\) cropland (100) & 4.6 & 1.8 & 1.9 & 1.4 & 0.5 \\  & _Overall (600)_ & _6.8_ & _1.9_ & _2.0_ & _1.1_ & _11.2_ \\ \hline \multirow{8}{*}{2} & forest \(\rightarrow\) grassland \(\rightarrow\) wetland (150) & 9.0 & -1.9 & 1.7 & 0.4 & 3.7 \\  & forest \(\rightarrow\) grassland \(\rightarrow\) cropland (150) & 7.3 & 0.5 & 1.6 & 0.7 & 1.0 \\ \cline{1-1}  & forest \(\rightarrow\)wetland \(\rightarrow\)cropland (150) & 7.5 & 0.1 & 1.8 & 0.9 & 1.3 \\ \cline{1-1}  & grassland \(\rightarrow\)wetland \(\rightarrow\)cropland (150) & 8.1 & 3.0 & 1.5 & 0.7 & 0.3 \\ \cline{1-1}  & _Overall (600)_ & _8.0_ & _0.6_ & _1.6_ & _0.7_ & _6.3_ \\ \hline \multirow{2}{*}{3} & forest \(\rightarrow\) grassland \(\rightarrow\) wetland \(\rightarrow\) & \multirow{2}{*}{7.2} & \multirow{2}{*}{0.3} & \multirow{2}{*}{1.9} & \multirow{2}{*}{0.5} & \multirow{2}{*}{7.3} \\ \cline{1-1}  & cropland (600) & & & & & \\ \hline \hline \end{tabular} Note: Time steps stands for the time of detected change in the unit of step, _i.e._, 16 days; number stands for the number of changes.  
\end{table} 
Table 3: Summary of the results for the simulated time series with changes. Figure 6 shows the smoothing effect on six accuracy indices when SCD is applied to the 244 independent time series in the sub-area.