# Evaluation of Satellite Imagery for Monitoring Pacific Walruses at a Large Coastal Haulout
## 3 Results
For each satellite image collected within 24 h of a UAS survey, the percent deviation was calculated as the area estimated from satellite imagery minus the area derived from the paired UAS survey, divided by the UAS survey area. Colored symbols indicate the mean percent deviation among the three observers and shaded vertical bars signify the full range of deviations. For comparison, the same deviations are plotted for UAS surveys matched to other UAS surveys (gray Xs). The plotted data are available as online Supplementary Materials. the estimates from paired UAS images. The three Sentinel-1 IW images matched to UAS surveys on the same day (<8 h) had deviations ranging from 69% to 107%, and a single same-day Sentinel-1 EW image produced a deviation exceeding 240%. Obsservers were unanimous in classifying whether each clear view satellite image (n = 195) had detectable walruses present (n = 129), with the exception of two Landsat-8 images (2020-10-13 22:38Z and 2020-10-15 20:00Z) in which only one observer identified walruses on shore. The digitized extent of aggregations varied among observers, and that variability differed substantially between the satellite missions and imaging modes, as evidenced by the increase in between-observer CV-RMSE that accompanied increasing image resolution (Table 1). Not surprisingly, the average CV-RMSE of the estimated area occupied by walruses was small for the higher resolution imagery (TerraSAR-X staring spotlight and DigitalGlobe), and large for the low-resolution imagery (Sentinel-1 EW and Landsat-8). Observer differences in aggregation size exceeded 50% of the mean size for coarse-resolution imagery types, \(\sim\)20% of the mean for moderate-resolution types, and \(\sim\)10% or less among the higher resolution types (Table 1). Not only did observers differ in estimating the area occupied by walruses, but they also differed in precisely where they delineated the aggregation boundaries. The digitized area of overlap (intersection) common to all three observers, expressed as a fraction of the total (union) area, ranged from 0.25 to 0.85 and was inversely related to image resolution (Table 1). Higher-resolution imagery types, such as TerraSAR-X and DigitalGlobe, more consistently approached a 1-to-1 intersection:union relationship (i.e., perfect 3-way spatial agreement) between observers (Figure 4). For any given imagery type, the degree of spatial consistency achieved among the observers is reflected in how closely the intersection:union \begin{table}
\begin{tabular}{c c c c c} \hline
**Satellite Sensor/Type** & **Image Sample Sizes** & **Median Days between** & **Average Observer** & **Average 3-Way Observer** \\
**(Image Resolution)** & **Year:** & **Clear-View Image** & **CV-RMSE (sd)** & **Overlap Ratio (sd)/** \\  & **Archive/Clear/Walrus** & **Revisits (IQR)** & & **Regression Slope (R\({}^{2}\))** \\ \hline Sentinel-1 EW/SAR & 2018: NA & & & \\
[1 pt] (40 m) & 2019: 8/8/6 & 12.0 (4.0) & 0.52 (0.37) & 0.43 (0.16)/ \\  & 2020: 10/10/3 & & & 0.51 (0.964) \\ Landsat-8/Optical & 2018: 11/3/2 & & & \\
[1 pt] (30 m) & 2019: 13/5/4 & 16.0 (23.5) & 0.78 (0.95) & 0.23 (0.24)/ \\  & 2020: 15/3/3 & & & 0.20 (0.364) \\ Sentinel-1 IW/SAR & 2018: 10/10/5 & & & \\
[1 pt] (10 m) & 2019: 14/14/10 & 10.5 (10.0) 1  & 0.23 (0.11) & 0.67 (0.10)/ \\  & 2020: 22/22/13 & & & 0.74 (0.990) \\ Sentinel-2/Optical & 2018: 54/17/11 & & & 0.64 (0.14)/ \\  & 2020: 52/15/12 & & & \\ PlanetScope/Optical & 2018: 134/32/23 & & & \\
[1 pt] (3.9 m) & 2019: 53/22/14 & 3.0 (4.7) & 0.16 (0.12) & 0.63 (0.10)/ \\  & 2020: 92/12/NA 2 & & & 0.68 (0.982) \\ TerraSAR-X stripmap/SAR & 2020: NA/4/4 & NA 3 & & 0.11 (0.04) & 0.75 (0.059)/ \\  & 2020: NA/12/10 & NA 3 & & 0.85 (0.032)/ \\  & 2020: 2/20 & & & 0.86 (0.999) \\ Maxar DigitalGlobe/Optical & 2018: 2/2/0 & & & 0.85 (NA)/ \\  & 2019: 1/1/1 & & & NA (NA) \\  & 2020: 1/1/NA 2 & & & \\ \hline \end{tabular}
\end{table}