# Quality Assessment by Region and Land Cover of Sharpening Approaches Applied to GF-2 Imagery
## 3 Results
### Quantitative Quality Assessment by Land Covers
The GS method achieved the best result for the bare soil (16.4%), followed by the salt water in the salt pan (16.5%), aquaculture water (18.1%), winter wheat (24.1%), unsown farmland (30.6%), reservoir water (41.2%), impervious surface (43.7%), shrub and grassland (57.9%), canal areas (80.0%), forest (114.0%), and sea water (330.3%). Therefore, with regard to preserving the EN values, for impervious surface, forest, shrub and grassland, reservoir water, and sea water, the mIHS method can achieve the best pansharpened result, and for bare soil, winter wheat, unsown farmland, canal area, and salt water in the salt pan, the CN method can achieve the best pansharpened result, and for aquaculture water, the GS method can achieve the best pansharpened result (see Figure A6 from Appendix B). Because these results could be affected by noise, they should be interpreted with caution. For preserving (with regard to the percentage change) the MoranI values (global spatial analysis) of the original MS image, the mIHS method achieved the best result for the canal areas (the sum of all four band variations was 11.0%), followed by the unsown farmland (15.4%), reservoir water (19.2%), salt water in the salt pan (19.8%), shrub and grassland (38.6%), impervious surface (38.9%), bare soil (62.3%), aquaculture water (74.3%), sea water (80.7%), forest (92.2%), and winter wheat (95.0%). The PCA method achieved the best result for the canal areas (the sum of all four band variations was 2.4%), followed by the salt water in the salt pan (22.2%), unsown farmland (24.8%), reservoir water (29.7%), impervious surface (40.3%), shrub and grassland (46.7%), aquaculture water (63.9%), bare soil (73.9%), forest (104.8%), winter wheat (113.3%), and sea water (139.9%). The CN method achieved the best result for the canal areas (the sum of all four band variations was 3.9%), followed by the salt water in the salt pan (20.6%), the unsown farmland (21.5%), reservoir water (26.9%), impervious surface (34.8%), shrub and grassland (39.1%), bare soil (67.8%), aquaculture water (68.4%), forest (94.7%), winter wheat (96.0%), and sea water (131.2%). The GS method achieved the best result for the canal areas (the sum of all four band variations was 2.8%), followed by the reservoir water (20.4%), salt water in the salt pan (21.6%), unsown farmland (23.0%), impervious surface (38.3%), shrub and grassland (43.5%), aquaculture water (63.2%), bare soil (70.9%), forest (100.5%), winter wheat (104.9%),and sea water (136.9%). Therefore, with regard to the MoranI and GearyI values, for impervious surface, the CN method can achieve the best pansharpened result, and for forest, shrub and grassland, bare soil, winter wheat, unsown farmland, reservoir water, sea water, and salt water in the salt pan, the mIHS method can achieve the best pansharpened result, and for canal area, the PCA method can achieve the best pansharpened result, and for aquaculture water, the GS method can achieve the best pansharpened result (see Figure A7 from Appendix B). For preserving the CC values between the four bands, for unsown farmland, the four pansharpening methods exhibited similar potential. The mIHS method achieved the best result for the salt water in the salt pan (the sum of the variation of the six CC values was 3.6%), followed by the unsown farmland (12.8%), bare soil (28.7%), impervious surface (128.6%), shrub and grassland (155.2%), reservoir water (207.7%), aquaculture water (220.7%), winter wheat (316.1%), canal areas (537,1%), sea water (583.1%), and forest (868.6%). The PCA method achieved the best result for the unsown farmland (12.4%), followed by the salt water in the salt pan (25.8%), bare soil (101.9%), aquaculture water (120.4%), reservoir water (189.1%), impervious surface (198.1%), shrub and grassland (216.8%), winter wheat (577.0%), canal areas (642.2%), sea water (881.3%), and forest (1022.1%).