# Quality Assessment by Region and Land Cover of Sharpening Approaches Applied to GF-2 Imagery
## 2 Materials and Methods  
### Study Area and Data  
A cloudless GF-2 image downloaded from the China Center for Resources Satellite Data and Application (CRESDA, [[http://www.cresda.com](http://www.cresda.com)]([http://www.cresda.com](http://www.cresda.com))) was used for a quality assessment of the pansharpened image. The image, which was acquired on 30 April 2016 over the city of Dongying, Shandong Province, China, includes various types of land cover, such as impervious areas, a _Robinia pseudoacacia_ plantation, shrubs and grasslands, winter wheat fields, unsown farmlands, bare soil, salt pans, aquaculture areas, rivers and canals, reservoirs, and the sea. Due to the flat terrain and the difficulty in obtaining fine resolution digital elevation model data for the research area, topographic correction was not used in this study. The PAN and MS images are displayed in Figure 1.  
Performing a quantitative quality assessment on the whole pansharpened image is time-consuming, and the redundant regions and the complementary or conflicting regions in the images often make the results of the quantitative assessment inconsistent with those of the visual analysis [28]. Moreover, some pansharpening approaches, such as the Ehlers spatial enhancement method embedded in the ERDAS Imagine Software, require large amounts of storage space and computer memory. Thus, quantitative assessments are often performed for some regions such as urban regions, rural regions, and vegetated regions, and pansharpened images are easier to display in the visualization mode. In this study, 14 regions (showed as the red square areas (400 x 400 pixels) in Figure 1) were selected for the quantitative assessment: Region 1 (urban region (the red square area labeled 1 in Figure 1b), shown in Figure 2); Region 2 (forest region, shown in Figure A1 from Appendix A); Regions 3 and 6 (shrub and grassland regions, Region 3 shown in Figure A2 from Appendix A); Regions 4, 7, and 8 (farmland regions, Regions shown in Figure A3 from Appendix A); Regions 5, 9, and 10 (salt pan \begin{table}
\begin{tabular}{c c c} \hline
**Band Name** & **Spectral Ranges (nm)** & **Spatial Resolution (m)** \\ \hline Panchromatic & 450–900 & 1 \\ Blue & 450–520 & 4 \\ Green & 520–590 & 4 \\ Red & 630–690 & 4 \\ Near-infrared (NIR) & 770–890 & 4 \\ \hline \end{tabular}
\end{table} 
Table 1: The spectrum of the Gaofen 2 (GF-2) bands. regions, Region 5 shown in Figure A4 from Appendix A), Region 11 (aquaculture region), Region 12 (reservoir area), Region 13 (canal area), and Region 14 (sea area). The quantitative assessments for the regions may be disturbed owing to the different proportions of land covers in the regions, because major differences in a land cover can be minimized by small differences in another land cover [15]. Therefore, we further analyzed the quality of the pansharpened images with regard to 11 types of land cover such as impervious surface, forest, shrub and grassland, bare soil, winter wheat, unsown farmland, canal area, salt water in the salt pan, aquaculture water, reservoir water, and sea water. The land-cover percentages for each region are presented in Table 2.