## 3 Results and Discussion
### Study Area and Background
#### 3.1.1 Change Detection Based on the Images from 2011, 2015, and 2016  
The images from the three different dates display the changes associated with the construction of the new tunnel on East Lake. In order to give a detailed assessment, we separated the dataset into two groups. The first group was made up of the data from 2011 and 2015, and the second group was made up of the data from 2015 and 2016. To verify the efficiency of the proposed method, comparative experiments were designed. We compared change detection methods based on log-ratio (HH) and improved K&I, log-ratio (HV) and improved K&I, log-ratio (VV) and improved K&I, CVA and improved K&I, a test statistic with a 5% significance level, a test statistic with a 1% significance level, a test statistic and K&I, a test statistic and CFAR, and a test statistic and improved K&I (the proposed method). The results of the change detection for the first and second groups of images are shown in Figures 4 and 5, respectively. The highlighted box labeled as Region 1 is used to give a detailed assessment. The land-cover types of this area are lake, bridge, city, and forest. The size of this area is 800 \(\times\) 500 pixels, and the Pauli-RGB images are shown in Figure 6a-c.  
Figure 3: RADARSAT-2 PolSAR images acquired on (**a**) 7 December 2011, (**b**) 25 June 2015, and (**c**) 6 July 2016. Figure 4: Change detection maps of full frame between 2011 and 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). Figure 5: _Cont._  
The results of the CI maps and their 3-D plots are shown by linear mapping to [0, 1] in Figures 7 and 8, respectively. Although the CI maps of the log-ratio (HH) method (Figures 7a and 8a) show a strong response in the changed area, 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 change detection map. The CI maps of the CVA method (Figures 7b and 8b) show a weak response, which makes it difficult to distinguish the changed and decreased areas. Figure 5: Change detection maps of full frame between 2015 and 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). Figure 6: RADARSAT-2 PolSAR images of Region 1 indicated in Figure 3, acquired on (**a**) 7 December 2011, (**b**) 25 June 2015, and (**c**) 6 July 2016.  
unchanged areas. The proposed method (Figures 7c and 8c) using the fully polarimetric information also shows a strong response in the changed areas (the bridge and the edges of the water bodies). However, unlike the other methods, the proposed method shows a low response in the water bodies. Overall, the proposed method of generating the CI map is able to accurately distinguish the changed and unchanged areas. Figure 7: 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 7 December 2011 and 25 June 2015. After generating the CI maps, the change detection maps were obtained by the threshold methods of a 5% significance level, a 1% significance level, K&I, CFAR (Pfa = 0.005), and a test statistic and improved K&I (the proposed method). The results are shown in Figures 9 and 10, where it can be seen that the obvious changed areas can be easily detected by all methods.