## 3 Results and Discussion
### Study Area and Background
#### 3.1.2 Change Detection Based on the 2015 and 2016 Images
The RGB images in Pauli basis (\(|S_{hh}-S_{vv}|\) for red, \(|S_{hv}|\) for green, and \(|S_{hh}+S_{vv}|\) for blue), and the reference data of the changed areas are shown in Figure 14.  
Figure 12: CI maps and 3-D plots of Region 2 based on (**a**) log-ratio, (**b**) CVA, and (**c**) test statistics at the different dates of 25 June 2015 and 6 July 2016. The results of the CI maps and their 3-D plots are shown by linear mapping to [0, 1] in Figure 15. Although the CI map of the log-ratio (HH) method (Figure 15a) shows a strong response in the water bodies, the contrast between the changed and unchanged areas is not obvious. Moreover, there is also a high response in the unchanged area because of the speckle noise, which impacts the accuracy of the  
Figure 14: RADARSAT-2 PolSAR images of Region 2 indicated in Figure 3, acquired on (**a**) 25 June 2015 and (**b**) 6 July 2016. (**c**) The ground-truth map (white denotes the change and black denotes the non-change). Figure 13: Change detection results in Region 2 between 25 June 2015 and 6 July 2016 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 & 6.69 & 7.97 & 92.03 & 0.5135 \\ HV and improved K\&I & 6.51 & 7.99 & 92.01 & 0.5026 \\ VV and improved K\&I & 6.37 & 7.50 & 92.50 & 0.5388 \\ CVA and improved K\&I & 1.08 & 7.36 & 92.64 & 0.0599 \\ Test statistic with 5\% significance level & 7.22 & 7.99 & 92.01 & 0.5358 \\ Test statistic with 1\% significance level & 5.37 & 6.57 & 93.43 & 0.5749 \\ Test statistic and K\&I & 4.86 & 6.19 & 93.81 & 0.5862 \\ Test statistic and CFAR & 6.70 & 7.92 & 92.08 & 0.5179 \\ Test statistic and improved K\&I (the proposed method) & 3.18 & 5.09 & 94.91 & 0.6141 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Performance evaluation of the change detection on Yanxi Lake between 2015 and 2016.  
change detection map. The CI map of the CVA method (Figure 15b) shows a weak response, which makes it difficult to distinguish the changed and unchanged areas. The proposed method (Figure 15c) shows a strong response in the water bodies corresponding to the changed parts and low values in the water bodies corresponding to the unchanged parts. Overall, the proposed method of generating the CI map is effective at accurately distinguishing changed and unchanged areas. After generating the CI maps, the change detection maps were obtained by the threshold methods of 5% significance level, 1% significance level, K&I, CFAR (Pfa = 0.005), and the proposed method. The results are shown in Figure 16, where it can be seen that the obviously changed areas can be  
Figure 15: CI maps and 3-D plots of Region 3 based on (**a**) log-ratio, (**b**) CVA, and (**c**) test statistics at the different dates of 25 June 2015 and 6 July 2016.  
easily detected by all the methods. In order to further verify the efficiency of the proposed method in generating the CI, we used the same threshold strategy (improved K&I) in the methods of log-ratio of single-channel SAR, CVA, and test statistics, as shown in Figure 16a-d,i. As a result of the speckle noise and CI map with lower contrast, the result of log-ratio and improved K&I based on single-channel bi-temporal SAR images contains many wrong detections in some unchanged areas. The other change detection method of CVA and improved K&I results in many missed detections.