## 3 Results and Discussion
### Study Area and Background
#### 3.1.1 Change Detection Based on the Images from 2011, 2015, and 2016
In order to further verify the efficiency of the proposed method in generating the CI, we used the same threshold strategy  
Figure 8: CI maps and 3-D plots of Region 1 based on (**a**) log-ratio (HH), (**b**) CVA, and (**c**) test statistics for the different dates of 25 June 2015 and 6 July 2016. (improved K&I) in the methods of log-ratio of single-channel SAR, CVA, and test statistics, as shown in Figure 9a-d,i and Figure 10a-d,i. As a result of the effect of speckle noise and the CI map with lower contrast, the results of log-ratio and improved K&I based on single-channel bi-temporal SAR images contain many wrong detections in some unchanged areas. The other change detection method of CVA and improved K&I results in many missed detections. Due to the high quality of the CI map obtained using the fully polarimetric information based on the test statistic, the change detection map of the test statistic and improved K&I shows a better performance. These experiments show that using the multi-temporal full polarimetric data can achieve a better change detection result than using single-channel or multi-channel data. In order to compare the effect of the threshold choice, we used the CI map based on the test statistic and the threshold methods of 5% significance level, 1% significance level, K&I, CFAR (Pfa = 0.005), and improved K&I. Among these methods of choosing the threshold, 5% and 1% significance levels and K&I result in more false alarms in the region of city and forest than improved K&I. In addition, CFAR results in more false alarms in the region of water bodies than the proposed method. The quantitative comparisons of these detection schemes shown in Tables 1 and 2 also indicate that the proposed approach shows a better performance. The proposed approach of the test statistic and improved K&I achieves the best results in all four indicators (FA (%), TE (%), OA (%), and Kappa). This confirms that the proposed method is effective and shows a significant improvement over the other methods. Figure 9: Change detection results in Region 1 between 7 December 2011 and 25 June 2015 based on the following: (**a**) log-ratio (HH) and improved K&I; (**b**) log-ratio (HV) and improved K&I; (**c**) log-ratio (VV) and improved K&I; (**d**) CVA and improved K&I; (**e**) test statistic with 5% significance level; (**f**) test statistic with 1% significance level; (**g**) test statistic and K&I; (**h**) test statistic and CFAR; (**i**) test statistic and improved K&I (the proposed method); (**j**) Ground reference (white denotes the change and black denotes the non-change). \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Method** & **FA (\%)** & **TE (\%)** & **OA (\%)** & **KAPPA** \\ \hline HH and improved K\&I & 10.49 & 11.17 & 88.83 & 0.4574 \\ HV and improved K\&I & 7.78 & 8.67 & 91.33 & 0.5292 \\ VV and improved K\&I & 8.45 & 9.31 & 90.69 & 0.5078 \\ CVA and improved K\&I & 0.67 & 7.41 & 92.59 & 0.0994 \\ Test statistic with 5\% significance level & 8.77 & 9.32 & 90.68 & 0.5204 \\ Test statistic with 1\% significance level & 6.9 & 7.82 & 92.18 & 0.5597 \\ Test statistic and K\&I & 6.16 & 7.24 & 92.76 & 0.5757 \\ Test statistic and CFAR & 5.99 & 7.32 & 92.68 & 0.5626 \\ Test statistic and improved K\&I (the proposed method) & 5.79 & 6.98 & 93.02 & 0.5827 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Performance evaluation of the change detection on East Lake between 2011 and 2015.