We examined and interpreted all satellite imagery over our study area during our study period that were available from the following data providers, USGS Landsat-8 program, European Space Agency Copernicus Sentinel program, Deutsches Zentrum fuer Luft- und Raumfahrt TeraSAR-X program, MAXAR Digital Globe WorldView and GeoEye programs, and PlanetLabs PlanetScope program. We queried all civil satellite mission archived imagery available through the MAXAR DigitalGlobe and PlanetLabs PlanetScope archives collected over our study area during our study periods. We examined all available visible and multi-spectral GeoEye-1, LandSat-8, PlanetLabs, Sentinel-2, WorldView-1 and WorldView-2 images. We retrieved all images with less than 70% cloud cover across the study area and retained those in which we could see a clear view of the ocean beach within our study area. We examined all SAR images collected by Sentinel-1, both in the 10 m resolution VH cross-polarization and 40 m resolution HV cross-polarization. Although TeraSAR-X missions had not collected study area imagery during the first two years of our study period, TeraSAR-X program offered to collect imagery during the 2020 walrus haulout season. For this study, TeraSAR-X offered their highest resolution imagery, the "staring spotlight" that collects ~ 7.5 km x 4.6 km images with ~ 1.1 m resolution in a single polarization as well as their second highest resolution imagery, the "strip map" mode with slightly less resolution (3.5 m) but a more extensive swath width (15 km by 50 km). TeraSAR-X processed these images with the "science" orbitagraphy data to optimize ground registration, and in the radiometrically enhanced processing mode. During 2020 we examined PlanetLabs PlanetScope images to determine if the images offered a clear view of the study area, but did not obtain full resolution copies of the images for visual interpretation of walrus group presence.
We visualized each satellite image to determine whether it offered a clear view of the study area, then identified walrus groups apparent in images with clear views for all images considered, except for the 2020 PlantLabs PlanetScope images. To recognize walrus groups resting on shore, we first examined each year of each imagery type in chronological order before walruses arrived to orient ourselves with how the study area’s coastal landscape was depicted in the imagery, including how to recognize features of the barrier island such as variations in beach width, banks at the edge of the storm high-tide line, upland vegetation, as well as remnants of the historic settlements and military infrastructure. Walrus aggregations disturb beaches and upland vegetation when they gather in large numbers, churning up the soil and defecating. Occupied haulout areas are discolored by these behaviors. Because this discoloration persists when walruses are no longer present, we examined images in chronological order to recognize areas that had been recently occupied by walrus groups. We performed all visual interpretation of imagery in a desktop GIS. We visualized the Landsat, PlanetScope, and Sentinel-2 multi-spectral image bands as standard true-color red-green-blue (RGB) images, as well as false-color composites using the near infra-red, red, and green bands for the RGB channels respectively. We also examined the near infrared band individually. We visualized panchromatic imagery from GeoEye-1 as single band images. We displayed WorldView-2 multispectral images as RGB false color composites using respectively the near IR2, near IR1, and red edge bands. For each visualization we stretched each band’s color ramp from the 2nd to the 98th percentile of pixel values found within the study area, and applied brightness and contrast settings to optimize visual contrast of landscape features. If thin patchy clouds were present over the study area, we applied the image enhancement methods separately to areas with and without clouds. We classified images as having a clear view if the entire beach could be readily observed. We only retained images in our summaries that yielded a clear view.
We recognized walrus groups along the ocean-facing beach in the true-color imagery by a distinctive red-brown coloration that contrasted with the adjacent brown beach, green upland vegetation and dark brown trampled upland vegetation, or sometimes white fresh snow. We recognized walruses in the false-color imagery by similar patterns. We recognized walrus groups in the near infra-red imagery by their distinctive mid-level intensity values that contrast with lower level intensity of the adjacent beach, variable level intensity of the upland features, and bright reflectance of the breaking surf. We visualized the Sentinel-1 cross-polarization imagery as a single band image stretched from -25 to zero decibels. We visualized the TeraSar-X staring spotlight (single polarization multi-look ground range detected) normalized backscatter σ0 images by stretching the values from 1 to 512. We recognized walrus groups on the ocean-facing side of the barrier island as large contiguous clusters of pixels with very high radar backscatter that contrasted distinctly with the surrounding coastalscape.