# Quality Assessment by Region and Land Cover of Sharpening Approaches Applied to GF-2 Imagery
## 3 Results
### Quantitative Quality Assessment by Land Covers  
The segmented image and land covers from the GS pansharpened images are shown in Figure 5. The quality indices were applied only to pixels associated with a certain land cover. To evaluate the degree of quality-index preservation, the sum of the absolute change values of the quality index was calculated. A smaller sum indicated a better capability of the pansharpening method to preserve the quality index. The following analysis focuses on comparisons of the Mean, EN, MoranI, and CC values between the pansharpened images. Figure 5: _Cont._  
For preserving the Mean values (spectral analysis) of the original MS image (with regard to the percentage change), the mIHS method achieved the best result for the shrub and grassland (the sum of all four band variations was 2.0%), followed by the impervious surfaces (2.2%), sea water  
Figure 5: The segmented image and land covers. (**a**) Region 1—Urban area; (**b**) Region 2—Forest area; (**c**) Region 3—Shrub and grassland area; (**d**) Region 4—Farmland area; (**e**) Region 5—Salt pan area; (**f**) Region 6—Shrub and grassland area; (**g**) Region 7—Farmland area; (**h**) Region 8—Farmland area; (**k**) Region 9—Salt pan area; (**m**) Region 10—Salt pan area; (**n**) Region 11—Aquaculture area. (2.9%), unsown farmland (3.4%), salt water in the salt pan (3.7%), bare soil (4.1%), canal areas (4.2%), aquaculture water (10.7%), forest (11.1%), winter wheat (12.6%), and reservoir water (28.6%). The PCA method achieved the best result for the salt water in the salt pan (8.8%), followed by the canal area (11.8%), bare soil (13.6%), unsown farmland (21.5%), shrub and grassland (21.6%), impervious surface (29.9%), forest (35.9%), aquaculture water (54.4%), winter wheat (70.4%), reservoir water (96.4%), and sea water (103.2%). The CN method achieved the best result for the winter wheat (30.1%), followed by the forest (51.1%), impervious surface (52.7%), unsown farmland (59.2%), shrub and grassland (60.0%), bare soil (63.6%), salt water in the salt pan (66.8%), canal area (78.3%), sea water (87.0%), aquaculture water (110.1%), and reservoir water (132.8%). The GS method exhibited the best result for the salt water in the salt pan (5.9%), followed by the bare soil (10.7%), shrub and grassland (15.5%), unsown farmland (15.9%), impervious surface (23.7%), forest (26.5%), canal areas (33.0%), aquaculture water (47.1%), winter wheat (52.4%), reservoir water (81.7%), and sea water (85.9%). Therefore, with regard to the Mean values (spectral analysis), the mIHS was typically the best pansharpening method for all land covers, followed by the GS, PCA, and CN methods (see Figure A5 from Appendix B). For preserving the EN values, the mIHS method achieved the best result for the bare soil (the sum of all four band variations was 14.9%), followed by the impervious surface (18.3%), salt water in the salt pan (19.8%), winter wheat (24.1%), reservoir water (25.1%), aquaculture water (26.0%), unsown farmland (26.3%), shrub and grassland (31.2%), canal area (62.8%), forest (74.9%), and sea water (118.6%). The PCA method achieved the best result for the salt water in the salt pan (18.4%), followed by the aquaculture water (20.6%), bare soil (20.9%), winter wheat (32.6%), unsown farmland (37.0%), reservoir water (44.3%), impervious surface (46.8%), shrub and grassland (62.0%), canal areas (87.2%), forest (117.8%), and sea water (330.2%). The CN method achieved the best result for the salt water in the salt pan (3.4%), followed by the bare soil (6.4%), unsown farmland (16.1%), winter wheat (16.9%), aquaculture water (20.0%), impervious surface (28.6%), reservoir water (32.4%), shrub and grassland (36.3%), canal areas (56.4%), forest (92.4%), and sea water (275.9%).