Fischbach, Anthony S. (ORCID: 0000-0002-6555-865X) Douglas, David C. (ORCID: 0000-0003-0186-1104) 20230914 satellite maps, vector digital data, tabular digital data Pacific Walrus Coastal Haulout Occurrences Interpreted ver 1.0, September 2023 Anchorage, Alaska U.S. Geological Survey, Alaska Science Center Suggested Citation: Fischbach, A.S., Douglas, D.C., 2023. Pacific Walrus coastal haulout occurrences interpreted from satellite imagery, 2023 (ver 1.0, September 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P97NFTDU https://doi.org/10.5066/P97NFTDU U.S. Geological Survey, Alaska Science Center 2005 website Alaska Science Portal 96 Anchorage, Alaska U.S. Geological Survey, Alaska Science Center This is a link to the broader USGS Alaska Science Center research project supported by these data. Users will find a description of the research project and links to associated reports, publications, and data products. https://alaska.usgs.gov/portal/project.php?project_id=96 This data release contains maps, geospatial files, and a table of the satellite imagery types with the dates when they were collected and examined to interpret the presence of, and area occupied by, walruses at terrestrial haulouts. Estimates of the land area occupied by walruses are provided based on interpretation by experienced image reviewers. The images are from a variety of Earth observing satellite imagery sources collected over coastal areas of the Chukchi Sea (northwestern Alaska and northeastern Russia) in autumn when walruses come ashore in large numbers to rest in the absence of sea ice. Earth observing imagery sources used in this data release include (but are not limited to) optical imagery collections by: (1) the European Space Agency's Sentinel-2 mission and (2) the Plant Labs Planet Scope constellation, as well as synthetic aperture radar imagery collected by: (1) European Space Agency's Sentinel-1 mission; (2) the DLR (German Aerospace Agency) TerraSAR-X satellite (X-band), and (3) the Umbra Space satellite constellation (X-band). These data were collected and interpreted to support near real time management decisions of Pacific walruses at coastal haulouts, and to schedule collections of sub-meter-resolution X-band SAR imagery to evaluate its potential for detecting and counting walrus carcasses that occur onshore after haulouts are abandoned. The maps and haulout size estimates are considered sensitive. They are archived at the U.S. Geological Survey, Alaska Science Center (a USGS Trusted Digital Repository). At this time, only this metadata record describing the data is publicly accessible. The full set of maps and estimates will be added to this USGS public data release during the winter of 2023/2024, after walruses have left the haulout area. 20230820 20231130 observed In work As needed Chukchi Sea coast Alaska and Russia -171.7 -163.0 69.6 66.9 USGS Metadata Identifier USGS:ASC557 ISO 19115 Topic Category Biota Environment NASA GCMD Earth Science Keyword Thesaurus Animals/vertebrates Mammals Carnivores Seals/sea lions/walruses USGS CSA Biocomplexity Thesaurus Marine mammals Seasonal distribution USGS Thesaurus Wildlife Migratory species Marine ecosystems Coastal ecosystems Remote sensing Image collections Field inventory and monitoring None Satellite imagery Pinniped Walrus Pacific Walrus Odobenus rosmarus divergens USGS Geographic Names Information System (GNIS) Alaska Chukchi Sea Point Lay NGA GEOnet Names Server Russia Chukotka none Cape Serdtse-Kamen None Marine mammals Pacific Walrus Odobenus rosmarus divergens ITIS Integrated Taxonomic Information System Unknown online database online ITIS-North America Taxonomic details retrieved August 27, 2023 from the Integrated Taxonomic Information System online database https://www.itis.gov https://doi.org/10.5066/F7KH0KBK Species were identified by skilled field satellite imagery interpreters who applied methods described in Fischbach and Douglas (2021). Kingdom Animalia Subkingdom Bilateria Infrakingdom Deuterostomia Phylum Chordata Subphylum Vertebrata Infraphylum Gnathostomata Superclass Tetrapoda Class Mammalia Subclass Theria Infraclass Eutheria Order Carnivora Suborder Caniformia Family Odobenidae Genus Odobenus Species Odobenus rosmarus Walrus TSN: 180639 Subspecies Odobenus rosmarus divergens Pacific Walrus TSN: 622045 None It is requested that the authors and the USGS Alaska Science Center be cited for any subsequent publications that reference this dataset. Any reproduction of cartographic maps that include imagery from the Capella Space, DLR TerraSAR-X, Umbra Space, or Planet Labs must retain the copyright symbol and credit the respective imagery source. U.S. Geological Survey, Alaska Science Center Mailing and Physical

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Anchorage Alaska 99508 USA 907-786-7000 ascweb@usgs.gov Earth observing imagery sources used in this data release include optical imagery collections by (1) the European Space Agency's Sentinel-2 mission and (2) the Plant Labs Planet Scope constellation and synthetic aperture radar imagery collected by: (1) European Space Agency's Sentinel-1 mission; (3) the DLR (German Aerospace Agency) TerraSAR-X satellite (X-band), and (3) the Umbra Space satellite constellation (X-band). Data are satellite digital images. Users of these data may note that digitized herd locations vary with respect to an apparent coastline. The variation is due to the variable georeferencing of the various Earth observing satellite imagery. It is understood that georeferencing of satellite imagery is highly variable from image to image and the degree of this variability is expected to vary among Earth observing missions. The variability of georeferencing is expected to be greatest at study sites lacking established ground control points and or lacking high resolution mapping data, such as the case in the Russian Far East portions of the Pacific walrus range. At best, georeferenced imagery may match other imagery within meters. At worst, the authors have observed that common features in imagery may be shifted by more than one hundred meters. Although the authors recognized this problem, they did not attempt to perform post-processing georeferencing of imagery provided by the various missions. Rather, the authors worked with the imagery as it was georeferenced by each mission. The authors do not expect that the variable georeferencing will introduce substantial variation to the estimated area occupied by the walrus herds. However, because the outlines of the digitized herd may be shifted substantially away from a common referenced coastline, it is not possible to analyze the digitized herd outlines from different images for spatial overlap. Attribute values fall within expected ranges. No data were omitted. Lab A single experienced observer interpreted the satellite imagery. The observer digitized the periphery of apparent walrus groups that were comprised of at least 6 contiguous image pixels and that contrasted with the surrounding coastal landscape. The observer digitized walrus groups by hand with the use of a mouse and a desktop GIS at scale of: (a) 1:10,000 for imagery types with pixel sizes greater than 10 m, (b) 1:5,000 for imagery with pixel sizes greater than 3 m, and (c) 1:2,000 scale for imagery with pixel sizes less than 3 m. These outlines were reviewed by a second observer. If concerns were raised by the second observer, the original observer revised the outlines such that the final published digitized outline represents a consensus outline from the two experienced interpreters. Fischbach, A.S. Douglas, D.C. 2021 journal article Remote Sensing 13(21):4266 Fischbach, A.S., Douglas, D.C. 2021. Evaluation of satellite imagery for monitoring Pacific Walruses at a large coastal haulout. Remote Sensing 13(21):4266 doi:10.3390/rs13214266 https://doi.org/10.3390/rs13214266 publication 2021 publication date Fischbach and Douglas 2021 Provides method for interpretation of Earth observing imagery to determine the presence of walrus groups resting onshore. We examined and interpreted all available satellite imagery over the study area through the autumn study period, before, during and after walruses occupied the terrestrial haulout in the study area. We retrieved all available Sentinel-2 and Planet Scope optical images and retained those in which we could see a clear view of the beach at the 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. We tasked collection of Umbra (HH) Spotlight images with two-looks and one- or half-meter resolution. We tasked collection TerraSAR-X Staring Spotlight (approx. 7.5 km x 4.6 km) images with approximately 1.1 m resolution in a single polarization (HH) and had these processed with the "science" orbitography data option to optimize ground registration, and in the radiometrically enhanced processing mode. Unknown To recognize walrus groups resting on shore, we first examined imagery types 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. Walruses disturb beaches and upland vegetation when they gather in large numbers, churning up the soil and defecating. In optical imagery, 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 Sentinel-2 multi-spectral image bands as standard true-color red-green-blue (RGB) images when views were unobstructed by thin clouds and as false-color composites using the near infra-red, red, and green bands for the RGB channels respectively when thin clouds obstructed the view. 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 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. Unknown We obtained Sentinel-1 cross-polarization SAR imagery as a sigma-nought (sigma0) data product. Sigma0 is normalized with respect to the local incidence angle (i.e., terrain) so it represents the backscatter returned to the antenna from a unit area on the ground, expressed in decibels (dB) with a calibration level of 0 dB. We visualized sigma0 by stretching values from -25 to 0 and displaying them over a viridis magma color ramp to enhance geographic patterns. We recognized walrus groups on the ocean-facing side of the barrier island as large contiguous clusters of pixels with very high sigma0 that often contrasted with the surrounding coastal landscape. Unknown We visualized the TerraSar-X ellipsoid corrected single look images by stretching the single band images from the 2nd to the 98th percentile of the radar backscatter values within the study area, displayed over a viridis magma color ramp. 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 often contrasted with the surrounding coastal landscape. Unknown We visualized the TerraSar-X ellipsoid corrected single look images by stretching the single band images from the 2nd to the 98th percentile of the radar backscatter values within the study area, displayed over a viridis magma color ramp. 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 often contrasted with the surrounding coastal landscape. Unknown We visualized the Umbra Space ellipsoid corrected two-look images by stretching the single band images from the 0 to 255 of the scaled radar backscatter values within the study area, displayed over a viridis magma color ramp. 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 often contrasted with the surrounding coastal landscape. Unknown 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 often contrasted with the surrounding coastal landscape. Unknown walrus_dailySatelliteMaps_[haulout-site] Folder containing maps (JPG format) derived from a variety of Earth observing satellite imagery sources collected over coastal areas of the Chukchi Sea (northwestern Alaska and northeastern Russia) in autumn when walruses come ashore in large numbers to rest in the absence of sea ice. Filenames provide the image timestamp (in ISO8601 format using UTC) and Satellite Mission ID. File naming convention: [four digit year][two digit month][two digit day of month]T[two digit hour of day][two digit minute of hour]Z_[two character satellite mission abbreviation] Users of these data may note that digitized herd locations vary with respect to an apparent coastline. The variation is due to the variable georeferencing of the various Earth observing satellite imagery. It is understood that georeferencing of satellite imagery is highly variable from image to image and the degree of this variability is expected to vary among Earth observing missions, especially those using small satellite sensor platforms (Planet Labs and Umbra). The variability of georeferencing is expected to be greatest at study sites lacking established ground control points and or lacking high resolution mapping data, such as the case in the Russian Far East portions of the Pacific walrus range. At best, georeferenced imagery may match other imagery within meters. At worst, the authors have observed that common features in imagery may be shifted by more than one hundred meters. Although the authors recognized this problem, they did not attempt to perform post-processing georeferencing of imagery provided by the various missions. Rather, the authors worked with the imagery as it was georeferenced by each mission. The authors do not expect that the variable georeferencing will introduce substantial variation to the estimated area occupied by the walrus herds. However, because the outlines of the digitized herd may be shifted substantially away from a common referenced coastline, it is not possible to analyze the digitized herd outlines from different images for spatial overlap. Author defined Satellite Mission ID Code set of two-letter acronyms indicating the mission that collected the image. Author defined S1 European Space Agency's Copernicus Sentinel-1 mission: Synthetic Aperture Radar, C-band cross-polarized (VH), 10 m resolution. Data provider S2 European Space Agency's Copernicus Sentinel-2 mission: Optical, 10 m resolution Data provider TS Deutsches Zentrum fuer Luft- und Raumfahrt's TerraSAR-X mission: Synthetic Aperture Radar, X-band single polarization (HH), approximately 1 m resolution. Data provider US Umbra Space mission: Synthetic Aperture Radar, X-band single polarization (HH), less than or equal to 1 m resolution. Data provider PS PlanetLabs PlanetScope mission: Optical, approximately 3 m resolution Data provider walrus_dailyHauloutOutlines_[haulout-site] Folder containing geospatial polygons (in SHP and KML format) representing the outlines of walrus herds apparent in satellite imagery derived from a variety of Earth observing satellite imagery sources collected over coastal areas of the Chukchi Sea (northwestern Alaska and northeastern Russia) in autumn when walruses come ashore in large numbers to rest in the absence of sea ice. SHP polygons are geocoded in UTM Zone 3 coordinates (EPSG: 32603). Filenames provide the image timestamp (in UTC) and satellite mission ID. File naming convention: [four digit year][two digit month][two digit day of month]T[two digit hour of day][two digit minute of hour]Z_[two character satellite mission abbreviation] Author defined walrus_hauloutArea_[haulout-site].csv Table with estimates of the total land area covered by walruses and the number of walrus aggregations (groups) at the haulout as delineated by observer interpretation and digitizing of satellite images. For satellite imagery interpretation of walrus groups we identified walrus groups as contiguous clusters of pixels that met criteria for distinguishing walrus groups from the study site landscape, whereby pixel scale varied among the satellite imagery sources. Criteria for distinguishing walrus herds varied amongst the image type. For multi-spectral optical images we recognized walrus aggregations in the true-color imagery by a distinctive red brown coloration along the ocean-facing beach that contrasted with the adjacent brown beach, green upland vegetation, and dark brown trampled upland vegetation (or sometimes white fresh snow). Walruses in the false-color image composites were recognizable by similar patterns but with different contrasting colorations. We recognized walrus aggregations in the near infra-red band by distinctive mid-level intensity values that contrasted with darker levels of the adjacent beach, variable levels of the adjacent uplands, and brighter levels in the nearshore surf zone. For synthetic aperture radar images, we recognized walrus aggregations as large contiguous clusters of pixels with high radar backscatter on the ocean-facing side of the barrier island that contrasted distinctly with the surrounding coastal landscape. Presented in comma Separated Value (CSV) formatted table. For convenience, a graph (in PNG format) is provided, depicting the total land area covered by walruses on each date. Author defined Date Date and time (UTC) when the satellite image was collected. Author defined Date and time (UTC) when the satellite image was collected (YYYY-MM-DDThh:mm:ssZ). Source Name of the satellite the mission that collected the image. Author defined Sentinel-1 European Space Agency's Copernicus Sentinel-1 mission: Synthetic Aperture Radar, C-band cross-polarized (VH), 10 m resolution. Data provider Sentinel-2 European Space Agency's Copernicus Sentinel-2 mission: Optical, 10 m resolution. Data provider TerraSAR-X Deutsches Zentrum fuer Luft- und Raumfahrt's TerraSAR-X mission: Synthetic Aperture Radar, X-band single polarization (HH), approximately 1 m resolution. Data provider Umbra Umbra Space mission: Umbra Space mission: Synthetic Aperture Radar, X-band single polarization (HH), less than or equal to 1 m resolution. Data provider Planet PlanetLabs PlanetScope mission: Optical, approximately 3 m resolution. Data provider MapFile Name of the map (included in this data package) from which the haulout area was estimated. Author defined Name of the map (included in this data package) from which the haulout area was estimated. HauloutSize Land area encompassed by haulout group outlines Author defined 0 100000 Meters squared N_groups Number of haulout groups visible in each map Author defined 1 5 Count U.S. Geological Survey, Alaska Science Center Mailing and Physical

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Anchorage Alaska 99508 USA 907-786-7000 ascweb@usgs.gov The U.S. Geological Survey, Alaska Science Center is the authoritative source and distributor of these data. Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data for other purposes or on all computer systems, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. JPG, PNG, SHP, KML, CSV Data are distributed in a Zip package containing tabular data in CSV format, digital images in JPG and PNG format, geospatial data in SHP and KML format, and FGDC metadata in XML and HTML formats. Compression applied by the 7-Zip utility using the default compression level [5]. The Zip package can be decompressed and unpacked by open source or commercially available unzip tools. https://doi.org/10.5066/P97NFTDU None 20230914 U.S. Geological Survey, Alaska Science Center Mailing and Physical

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Anchorage Alaska 99508 USA 907-786-7000 ascweb@usgs.gov FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata (CSDGM) FGDC-STD-001.1-1999