# An Optical and SAR Based Fusion Approach for Mapping Surface Water Dynamics over Mainland China
## 4 Results
### Visual Evaluation and Spatial Comparison with JRC-GSWE and GLAD-GSWD  
Surface water frequency maps were visually compared over a site dominated by aquaculture and located on the east coast of China near Haizhou Bay (Figure 8). The improved spatial detail of our algorithm is evident when compared to JRC-GSWE and GLAD-GSWD. Whilst it is possible to define the boundaries of the larger aquaculture sites in both JRC-GSWE and GLAD-GSWD, the internal divisions within these are hardly discernable at a 30 m resolution. It is only in the GRAS-SWD algorithm that it is possible to fully appreciate the richness and diversity of the aquaculture sites in this region. This is a significant advantage for counting small water features and estimating their surface water extent.  
Figure 8: Surface water frequency over aquaculture site located near Haizhou Bay on the east coast of China.  
Figure 7: Permanent and seasonal waters as proportions of the total annual maximum water extent (i.e., permanent + seasonal water).  
The issue of capturing small water bodies was explored in more depth visually and statistically in Hunan province, located in the subtropical biome in the south of China. The region is therefore relatively cloudy, and the topography is somewhat complex. Comparing the seasonal and permanent water extent shows considerable differences, with significantly more water bodies identified by GRAS-SWD both in terms of numbers and in terms of consistency, as most of the water bodies are classified as 'permanent' (Figure 9). GLAD-GSWD identifies some water features, however it appears that they are identified inconsistently, since they are classified as'seasonal'. Furthermore, some appear to be misclassifications when comparing to the Google Earth base map. JRC-GSWE identifies the least, and the large water body in the southwest is only present as a'seasonal' water feature. These differences may be due to the cloud coverage limiting optical only observations, or to their relatively smaller size proving difficult to capture at the Landsat resolution.  
To illustrate the point further, we extracted permanent water bodies with a size <0.81 ha and counted their numbers within each 10 km\({}^{2}\) grid cell for the entirety of the Hunan province administrative region (Figure 10). The 0.81 ha size threshold was chosen to be within the range of the smallest size categories in global lake inventories [82] and at the same time to respect the resolution of the evaluated SWE products, i.e., 3 \(\times\) 3 Landsat 30 m pixels (JRC-GSWE; GLAD-GSWD) vs. 9 \(\times\) 9 Sentinel 10 m pixels (GRAS-SWD).  
Figure 9: Surface water mapping by GRAS-SWD, JRC-GSWE and GLAD-GSWD over the location in Hunan province with many small water bodies. High-resolution image from Google Earth, shown as a reference.  
We found 632,081 features less than 0.81 ha with a total area of 350 km\({}^{2}\) using our algorithm. We also note that the spatial correlation of these water bodies aligns well with cropland extent, suggesting their possible importance for food production and domestic water supply. In comparison to our counts, JRC-GSWE identified only 0.2% of this number, and GLAD-GSWD even fewer at 0.1%. This significantly lower count is apparent in the figure, where less than 10 water bodies per cell were identified in nearly all grid cells by both JRC-GSWE and GLAD-GSWD (Figure 10).