Daniel Buscombe Yarran Doherty Kristen D. Splinter Sean F. Vitousek 20250405 Shoreline positions in comma separated value formats data release DOI:10.5066/P1E2JDPF Pacific Coastal and Marine Science Center, Santa Cruz, California U.S. Geological Survey Suggested Citation: Buscombe, D., Doherty, Y., Splinter, K.D., and Vitousek, S.F., 2025, Satellite-derived shorelines for the U.S. states of Oregon and Washington for the period 1984-2023, obtained using CoastSat, U.S. Geological Survey data release, https://doi.org/10.5066/P1E2JDPF. https://doi.org/10.5066/P1E2JDPF This dataset contains shoreline positions derived from available Landsat satellite imagery for two states (Oregon, and Washington) along the U.S. Pacific coast for the time period 1984 to 2023. An open-source toolbox, CoastSat (Vos and others, 2019a and 2019b), was used to classify coastal Landsat imagery and detect shorelines at the sub-pixel scale. Resulting shorelines are presented in CSV format. Significant uncertainty is associated with the locations of shorelines in extremely dynamic regions, including at the locations of river mouths, tidal inlets, capes, and ends of spits. These data are readily viewable in a text or spreadsheet editor. For technical users and researchers, data can be ingested into Global Mapper or QGIS or similar for more detailed analysis. Similar shoreline positions for North Carolina and South Carolina are available from Barnard and others, 2023 at https://doi.org/10.5066/P9W91314. Similar shoreline positions for Texas, Mississippi, Louisiana, and Florida are available from Buscombe and others, 2024 at https://doi.org/10.5066/P1WFZXDM. These data provide estimates of automatically detected coastal shoreline position for resource managers, science researchers, students, and the general public. These data can be used with geographic information systems, shoreline evolution models, or other software to assist identifying and assessing possible areas of vulnerability, along with appropriate inclusion of uncertainty. These data are not intended to be used for navigation or in lieu of definitive shoreline datasets. This data release was funded by the USGS Coastal and Marine Hazards and Resources Program. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. 1984 2023 collection years of satellite imagery used to determine shoreline positions Complete None -124.74322 -122.22177 48.51283 41.997135 USGS Metadata Identifier USGS:b2adda90-c5d0-4afd-b9d2-fc528e680921 Global Change Master Directory Hazards Planning Ocean Waves Erosion Sea Level Rise Extreme Weather ISO 19115 Topic Category Oceans ClimatologyMeteorologyAtmosphere Data Categories for Marine Planning Physical Habitats and Geomorphology USGS Thesaurus Climate Change Storms Sea-level Change Marine Realms Information Bank (MRIB) keywords sea level change waves coastal erosion None U.S. Geological Survey USGS Coastal and Marine Hazards and Resources Program CMHRP Pacific Coastal and Marine Science Center PCMSC Geographic Names Information System (GNIS) State of Oregon State of Washington No access constraints USGS-authored or produced data and information are in the public domain from the U.S. Government and are freely redistributable with proper metadata and source attribution. Please recognize and acknowledge the U.S. Geological Survey as the originator(s) of the dataset and in products derived from these data. U.S. Geological Survey, Pacific Coastal and Marine Science Center PCMSC Science Data Coordinator mailing and physical

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Santa Cruz CA 95060 831-427-4747 pcmsc_data@usgs.gov SatelliteDerivedShorelines_US_PNWcoast.png Image map showing study area for satellite derived shorelines along the Pacific Northwest coast. png The datasets were created in a Windows 11 Operating system, python 3.10. Results were output and saved as comma separated files. Daniel D. Buscombe Kilian Vos Andrea C. O’Neill Sharon Fitzpatrick Kristen Splinter Sean F. Vitousek 2024 Buscombe, D., Vos, K., O’Neill, A.C., Fitzpatrick, S.N., Splinter, K.D., and Vitousek, S.F., 2024, Satellite-derived shorelines for the U.S. Gulf Coast states of Texas, Louisiana, Mississippi, and Florida for the period 1984-2022, obtained using CoastSat, U.S. Geological Survey data release, https://doi.org/10.5066/P1WFZXDM. https://doi.org/10.5066/P1WFZXDM Patrick L. Barnard Kevin Befus Jeffrey J. Danielson Anita C. Engelstad Li H. Erikson Amy C. Foxgrover Matthew W. Hardy Daniel J. Hoover Tim Leijnse Chris Massey Robert McCall Norberto C. Nadal-Caraballo Kees Nederhoff Leonard Ohenhen Andrea C. O’Neill Kai A. Parker Manoocher Shirzaei Xin Su Jennifer A. Thomas Maarten van Ormondt Sean F. Vitousek Madison C. Yawn 2023 Barnard, P.L., Befus, K., Danielson, J.J., Engelstad, A.C., Erikson, L.H., Foxgrover, A.C., Hardy, M.W., Hoover, D.J., Leijnse, T., Massey, C., McCall, R., Nadal-Caraballo, N.C., Nederhoff, K., Ohenhen, L., O’Neill, A.C., Parker, K.A., Shirzaei, M., Su, X., Thomas, J.A., van Ormondt, M., Vitousek, S.F., Vos K., and Yawn, M.C., 2023 Future coastal hazards along the U.S. North and South Carolina coasts: U.S. Geological Survey data release, https://doi.org/10.5066/P9W91314. https://doi.org/10.5066/P9W91314 Sean Vitousek Kilian Vos Patrick L. Barnard Andrea C. O’Neill 2023 Vitousek, S., Vos, K., Barnard, P.L., and O’Neill, A.C., 2023, Projections of Shoreline Change of current and future (2005-2100) sea-level rise scenarios for the U.S. Atlantic coast, of Barnard, P.L., Befus, K., Nadal-Caraballo, N.C., Danielson, J., Engelstad, A., Erikson, L.H., Foxgrover, A.C., Hardy, M., Hoover, D., Leijnse, T., Massey, C., McCall, R., Nederhoff, K., Ohenhen, L., O'Neill, A.C., Parker, K., Shirzaei, M., Su, X., Thompson, J., van Ormondt, M., Vitousek, S., Vos, K., Yawn, M.C., 2023. Future Coastal Hazards along the U.S. Atlantic coast. U.S. Geological Survey data release, https://doi.org/10.5066/P9BQQTCI. https://doi.org/10.5066/P9BQQTCI Vos, K. Harley, M.D. Splinter, K.D. Simmons, J.A. Turner, I.L. 2019 Vos, K., Harley, M.D., Splinter, K.D., Simmons, J.A., and Turner, I.L., 2019a, Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery: Coastal Engineering, v. 150, p. 160-174. https://doi.org/10.1016/j.coastaleng.2019.04.004 Vos, K. Splinter, K.D. Harley, M.D. Simmons, J.A. Turner, I.L. 2019 Vos, K., Splinter, K.D., Harley, M.D., Simmons, J.A., and Turner, I.L., 2019b, CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery: Environmental Modelling and Software, v. 122, 104528. https://doi.org/10.1016/j.envsoft.2019.104528 Vos, K. Harley, M.D. Splinter, K.D. Walker, A. Turner, I.L. 2020 Vos, K., Harley, M.D., Splinter, K.D., Walker, A., and Turner, I.L, 2020, Beach slopes from satellite‐derived shorelines: Geophysical Research Letters, v. 47, e2020GL088365. https://doi.org/10.1029/2020GL088365 Gorelick, N. Hancher, M. Dixon, M. Ilyshechenko, S. Thau, D. Moore, R. 2017 Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore, R., 2017, Google Earth Engine: Planetary-scale geospatial analysis for everyone: Remote Sensing of Environment, v. 202, p. 18-27. https://doi.org/10.1016/j.rse.2017.06.031 Himmelstoss, E.A. Farris, A.S. Henderson, R.E. Kratzmann, M.G. Ergul, A. Zhang, O. Zichichi, J.L. Thieler, E.R. 2021 Himmelstoss, E.A., Farris, A.S., Henderson, R.E., Kratzmann, M.G., Ergul, A., Zhang, O., Zichichi, J.L., Thieler, E.R., 2021, Digital Shoreline Analysis System (version 5.1): U.S. Geological Survey software release, https://code.usgs.gov/cch/dsas. https://code.usgs.gov/cch/dsas Attribute values are estimates of shoreline position based on satellite imagery. The accuracy of this method was assessed by Vos and others (2019a), who compared data with ground-based surveys at Duck, North Carolina. In line with these estimates, authors are using a cross-shore horizontal error of 10 m (root mean square error) in most locations. In dynamic locations, including areas such as river mouths, capes, and ends of spits, uncertainty is greater, and positions should be inspected and used with care. Data have undergone QA/QC and fall within expected/reasonable ranges. Data set is considered complete for the information presented. Data are concurrent with specified transect locations. A formal accuracy assessment of the vertical positional information in the data set has either not been conducted or is not applicable. U.S. Geological Survey 2023 image online U.S. Geological Survey https://doi.org/10.5066/P9IAXOVV online database 19840101 20231231 collection years of satellite imagery Landsat imagery The archive of Landsat 5-8 satellite imagery accessed through Google Earth Engine was used to derive shoreline positions for the study area. Carrere, L. Lyard, F. Cancet, M. Guillot, A. Picot, N. 20160501 model online AVISO https://www.aviso.altimetry.fr/es/data/products/auxiliary-products/global-tide-fes/description-fes2014.html online model 20160501 Publication date FES 2014 Tide height predictions using a finite element solution model. Tidal corrections in the shoreline position were made with tide height predicted from the FES 2014 model. Set up CoastSat toolbox (Vos and others, 2019a and 2019b) for implementation along the region of interest. Toolbox set up in python 3.10 to run for geography spanning coastline for the U.S. Pacific Northwest coast, for the time period of 01 March 1984 to 31 December 2023. Beach slopes used for the tidal corrections were automatically derived from the raw satellite shorelines using the method explained by Vos and others (2020). CoastSat operates on the same transects as the CoSMoS-COAST model for the region (Vitousek and others, 2023), modified from the transects of the Digital Shoreline Analysis System (DSAS; Himmelstoss and others, 2021). The transects were grouped (including a 500 m lateral buffer) into several different bounding boxes for which the satellite imagery was extracted. The bounding boxes had an average size of 16 km2 (a maximum of 32 km2 and a minimum of 1 km2). 20240701 Ran CoastSat toolbox on Landsat imagery available through Google Earth Engine (Gorelick and others, 2017) for geography and time period of interest. Only cloudless imagery or imagery with less than 50 percent cloud cover was used. Imagery had horizontal resolution of 30 m, which was pan-sharpened to 15 m. Tidal corrections were applied using tide heights estimated from the FES 2014 Tidal model. FES 2014 Landsat imagery 20240701 Checked output to ensure quality results. These shorelines represent the automatically detected shoreline segments as identified by CoastSat (no other adjustments). The accuracy of the satellite-derived shoreline (SDS) for this area was addressed in Vos and others (2019a), who compared SDS observations with ground-based surveys at Duck, NC. They found an RMS accuracy of about 9 m (root mean square error). Lacking additional, sufficient ground-based observations for the purposes of further robust error estimates, authors use an error of 10 m (in root mean square error) for the SDS dataset. In dynamic locations, including areas such as river mouths, capes, and ends of spits, uncertainty is greater, and locations should be inspected and used with care. 20240701 Organized final extracted shorelines into comma separated files grouped by state. Originating imagery dates/times, slope, tide, and transect positions are included in files, in addition to derived shoreline positions at all transects. 20240701 point point 8239778 0.000001 0.000001 Decimal Degrees North American Datum 1983 Geodetic Reference System 80 6378137.000000 298.257222 NAVD88 (EGM2008 geoid) 0.1 meters Implicit coordinate Shoreline positions for historical period (1984-2022) for the Pacific Northwest coast, derived from satellite imagery csv file consists of shoreline positions derived from imagery of the U.S. Pacific Northwest coast. Producer Defined date date of projected data (UTC) in yyyy-mm-dd format (where yyyy is 4 digit year, mm is 2-digit month, and dd is 2-digit day). Producer defined 1984-01-01 2023-12-31 days 1 time time of projected data (UTC) in hh:MM format (where hh is 2-digit hour in 24-hour format and MM is 2-digit minutes). Producer defined 00:00 23:59 minutes 1 ID Transect along which shoreline position is derived from satellite imagery for date and time indicated. Producer Defined Sequential unique whole numbers that are automatically generated. For example, usa_WA_0038_0001, where usa stands for the United States, WA stands for the State of Washington, 0038 is the first transect identifier, and 0001 is the last number is 1. transectStart_X Starting position (longitude) of transect. Producer Defined -124.733370 -122.224945 decimal degrees 0.000001 transectStart_Y Starting position (latitude) of transect. Producer Defined 41.999010 48.510143 decimal degrees 0.000001 transectEnd_X Ending position (longitude) of transect. Producer Defined -124.743220 -122.221770 decimal degrees 0.000001 transectEnd_Y Ending position (latitude) of transect. Producer Defined 41.997130 48.512830 decimal degrees 0.000001 distance distance of derived shoreline position along transect. Producer Defined -492.02408 1224.27390 meters 0.00001 slope slope used for tidal correction of derived shoreline position Producer Defined 0.010 0.195 none 0.001 tide tide height correction (referenced to MSL) used for derived shoreline position Producer Defined -2.3479471 2.3203514 meters 0.0000001 shoreline_x Position (latitude) of shoreline derived from satellite imagery for date and time indicated. Producer Defined -124.73947 -122.224724 decimal degrees 0.000001 shoreline_y Position (longitude) of shoreline derived from satellite imagery for date and time indicated. Producer Defined 41.998660 48.510162 decimal degrees 0.000001 The first line of the csv is a header line U.S. Geological Survey U.S. Geological Survey - CMGDS mailing and physical

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Santa Cruz CA 95060 831-427-4747 pcmsc_data@usgs.gov These data are available in csv format by state. Shorelines are identified as points along transects (ID) and transect start and end points are included in the csv. 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 (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. comma-delimited text csv file for Oregon 547.9 https://doi.org/10.5066/P1E2JDPF Data can be downloaded using the Network_Resource_Name link then scrolling down to the Satellite Data section. comma-delimited text csv file for Washington 449.6 https://doi.org/10.5066/P1E2JDPF Data can be downloaded using the Network_Resource_Name link then scrolling down to the Satellite Data section. None. These data can be viewed with GIS software such as ArcGIS, Global Mapper or QGIS, or numerical processing software such as python or Matlab. 20250405 U.S. Geological Survey, Pacific Coastal and Marine Science Center PCMSC Science Data Coordinator mailing and physical

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Santa Cruz CA 95060 831-427-4747 pcmsc_data@usgs.gov Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998