# Before and After: A Multiscale Remote Sensing Assessment of the Sinop Dam, Mato Grosso, Brazil
## 3 Results
### UAS Case Study Areas and SfM-MVS Products  
In comparison to the conditions pre-flooding (Figure 2), both UAS case study areas have been substantially modified post-flooding (Figure 13). Both areas are within the lentite zone of the HPPS and now permanently covered by deeper and slow-moving water. Both the UAS photographs and Dove PS imagery acquired in February 2021 show the areas have been fully submerged in the slow-moving water. Only the tops of the trees on Ilha do Lair can be seen out of the water, while at Corredeira do Sulpicio the rapids are no longer present. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Site** & **Month** & **XCH\({}_{4}\) (ppb) (\(u\pm\sigma\))** \\ \hline HPPS lentite zone & July & 1852.5 \(\pm\) 6.8 \\ HPPS lentite zone & August & 1856.3 \(\pm\) 9.4 \\ Background region & July & 1849.8 \(\pm\) 14.2 \\ Background region & August & 1851.9 \(\pm\) 15.9 \\ Xingu National Park & July & 1807.5 \(\pm\) 10.0 \\ Xingu National Park & August & 1809.9 \(\pm\) 10.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Monthly average XCH\({}_{4}\) from TROPOMI. Figure 12: Time sequence of satellite imagery acquired monthly over the confluence of the Rio Roquete stream and Teles Pires river from prior to inundation (December 2018) to the high-water season of February 2020. Each tile is part of the monthly minimal cloud basemap mosaics produced from the PlanetScope constellation, with the exception of three single date images denoted by *. For January 2019, a single multispectral image is shown to ensure pre-inundation conditions. The 1 February 2019 image illustrates the confluence of the rivers the day after inundation began. For December 2019, a single image was chosen because it minimized cloud cover in this small area in comparison to the global mosaic. Each tile is 57.6 km\({}^{2}\) in area. For Corredeira do Sulpicio, the final ground sampling distance (GSD) of the SfM-MVS products was 2 cm. Pix4D located a median of 49,773 keypoints per photograph and a median of 7745.8 matches between neighbor photographs. The final 3D point cloud has an average point density of 584.6 pts/m\({}^{2}\). For Ilha do Lair, the GSD of the SfM-MVS products was 0.9 cm. Pix4D located a median of 51,394 keypoints per photograph and a median of 15,788.2 matches between neighbor photographs. The density of the final 3D point cloud is 7885.6 pts/m\({}^{2}\). A closer look at the Corredeira do Sulpicio illustrates the difference in scales between the high spatial resolution satellite imagery (3-5 m pixel sizes) (Figure 14a,b) and the UAS orthomosaic (Figure 14c), one of final products from the SfM-MVS workflow (Figure 8). At Ilha do Lair, the DSM shows the shallow water zone on the upstream side of the island. This site with high flow was populated by juveniles of many species, as well as smaller species foraging in the dense masses of plants. With the permanent inundation these types of habitats are covered in sediment and no longer available for the rheophile species. Figure 15 shows the Ilha do Lair 3D point cloud, DSM and vector ruggedness at different sizes pre-inundation. The fractal dimension of the Ilha do Lair triangular mesh at the original GSD of 0.9 cm was 1.99. The value of D decreased considerably to 1.09 at a resampled resolution of 20 cm and to 1.08 at a resampled resolution of 80 cm. This indicates that the greatest complexity in this habitat was found at smaller spatial scales, however, once the fine scale complexity is removed there is minimal difference between the complexities at the coarser scales. For fish such as the _Telecichla_ sp. (Figure 4) which have a small body size (\(\sim\)12 cm TL), the fine scale complexity is important because they rely on caves dug under these rocks for breeding, complex bottom structure for cover, and on microinvertebrates living in the dense mass of biocover (e.g., algae) growing on the rocks. Figure 13: Dove PS image acquired 2 February 2021 illustrating flooding of the two UAS case study areas during high water season.