Daniel D. Buscombe Joseph Burgess Kara S. Doran Sharon N. Batiste Ann E. Gibbs Rachel E. Henderson Julia L. Heslin Catherine N. Janda Mark A. Lundine Andrea C. O'Neill Joseph F. Terrano Jonathan A. Warrick Kathryn M. Weber 20250425 Shoreline vectors and settings in GeoJSON formats data release DOI:10.5066/P1NUEFDP Pacific Coastal and Marine Science Center, Santa Cruz, CA U.S. Geological Survey https://doi.org/10.5066/P1NUEFDP Daniel D. Buscombe Joseph Burgess Kara S. Doran Sharon N. Batiste Ann E. Gibbs Rachel E. Henderson Julia L. Heslin Catherine N. Janda Mark A. Lundine Andrea C. O'Neill Joseph F. Terrano Jonathan A. Warrick Kathryn M. Weber 2025 data release DOI:10.5066/P1NUEFDP Pacific Coastal and Marine Science Center, Santa Cruz, CA U.S. Geological Survey Suggested Citation: Buscombe, D., Burgess, J., Doran, K., Fitzpatrick, S., Gibbs, A., Henderson, R., Heslin, J., Janda, C., Lundine, M., O'Neill, A.C., Terrano, J., Warrick, J., and Weber, K., 2025, Satellite-derived shorelines from CoastSeg in multiple U.S. locations (1984-2023): U.S. Geological Survey data release, https://doi.org/10.5066/P1NUEFDP. https://doi.org/10.5066/P1NUEFDP This dataset contains shorelines (as vectors, where vertices are positions determined along transects) derived from available satellite imagery for multiple locations (Barter Island, Alaska; Elwha, Washington; Cape Cod, Massachusetts; Madeira Beach, Florida; and Rincon, Puerto Rico) and associated settings used to derive the data across the United States for the time period 1984 to 2023. An open-source toolbox, CoastSeg (Fitzpatrick and others, 2024a; Fitzpatrick and others, 2024b), was used to classify coastal Landsat and Sentinel imagery and detect shorelines at the sub-pixel scale, using the CoastSat (Vos and others, 2019) methodology. Shorelines are derived for multiple slope values, representing the spatial and temporal variance of slope conditions at each site. Resulting shorelines from transect-based derivation are presented in GeoJSON format. Significant uncertainty is associated with the locations of shorelines in extremely dynamic regions at all sites, including at the locations of river mouths, tidal inlets, capes, ends of spits, and adjacent to wetlands at the Barter Island site. For technical users and researchers, data can be ingested into geospatial platforms (for example, QGIS or GlobalMapper) for more detailed analysis. These data provide automatically detected estimates of coastal shoreline positions to support ongoing validation and development of automated feature detection methods, and can be used by science researchers, engineers, students, and the general public. These data can be used with geographic information systems (for example, QGIS or GlobalMapper), 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. 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 planned -143.83834890 -67.23436190 70.15710875 18.31396108 USGS Metadata Identifier USGS:1967409f-6b1d-48c6-a5e1-b137f411809a Global Change Master Directory Shorelines Shoreline mapping Beaches Erosion ISO 19115 Topic Category Oceans ClimatologyMeteorologyAtmosphere Data Categories for Marine Planning Physical Habitats and Geomorphology USGS Thesaurus image collections remote sensing Marine Realms Information Bank (MRIB) keywords coastal processes effects of coastal change shoreline erosion shoreline accretion beach coast storm erosion long term erosion remote sensing None U.S. Geological Survey USGS Coastal and Marine Hazards and Resources Program CMHRP Pacific Coastal and Marine Science Center PCMSC St. Petersburg Coastal and Marine Science Center SPCMSC Woods Hole Coastal and Marine Science Center WHCMSC Geographic Names Information System (GNIS) State of Alaska State of Washington Commonwealth of Massachusetts State of Florida Commonwealth of Puerto Rico 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 SDS_vectorfiles_and_settings_multiplelocations_1984-2023.png Image map showing study areas for satellite-derived shoreline vector files and settings in multiple locations. png This data release was funded by the USGS Coastal and Marine Hazards and Resources Program. The datasets were created in a Windows 11 Operating system, using python 3.7. Results were output and saved as comma-separated value and GeoJSON files. Fitzpatrick, S. Buscombe, D. Warrick, J.A. Lundine, M.A. Vos, K. 2024 Fitzpatrick, S., Buscombe, D., Warrick, J.A., Lundine, M.A., and Vos, K., 2024a, CoastSeg: an accessible and extendable hub for satellite-derived-shoreline (SDS) detection and mapping: Journal of Open Source Software, v. 99(99), 6683. https://doi.org/10.21105/joss.06683 Fitzpatrick, S. Buscombe, D. Warrick, J.A. Lundine, M.A. Vos, K. 2024 Fitzpatrick, S., Buscombe, D., Warrick, J.A., Lundine, M.A., and Vos, K., 2024b, CoastSeg: an accessible and extendable hub for satellite-derived-shoreline (SDS) detection and mapping: (v1.2.9). Zenodo. https://doi.org/10.5281/zenodo.12555413 https://doi.org/10.5281/zenodo.12555413 Buscombe, D. Fitzpatrick, S. 2023 Buscombe, D., & Fitzpatrick, S., 2023, CoastSeg: Beach transects and beachface slope database v1.0 (v1.0). Zenodo. https://doi.org/10.5281/zenodo.8187949 https://doi.org/10.5281/zenodo.8187949 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., 2019, 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 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 (2019), who compared data with ground-based surveys at Duck, North Carolina. In line with these estimates, a cross-shore horizontal error of 10 m (root mean square error) can be used in most locations. In dynamic locations, including areas such as river mouths, capes, ends of spits, and adjacent to wetlands in Barter Island, 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. There has not been a formal accuracy assessment of vertical position in this dataset and/or is not applicable. U.S. Geological Survey 2025 PNG image online U.S. Geological Survey https://doi.org/10.5066/P9IAXOVV online database 1984 2023 collection years of satellite imagery Landsat imagery The archive of Landsat 5 satellite imagery was accessed through Google Earth Engine and was used to derive shoreline positions for the study area. U.S. Geological Survey 2025 PNG image online U.S. Geological Survey https://doi.org/10.5066/P9C7I13B online database 1984 2023 collection years of satellite imagery Landsat imagery The archive of Landsat 7 satellite imagery was accessed through Google Earth Engine and was used to derive shoreline positions for the study area. U.S. Geological Survey 2023 image online U.S. Geological Survey https://doi.org/10.5066/P975CC9B online database 20240201 date of access Landsat 8-9 imagery The archive of Landsat 8-9 satellite imagery was used to derive shoreline positions for the study area. European Space Agency 2023 image online Copernicus https://dataspace.copernicus.eu/explore-data/data-collections/sentinel-data/sentinel-2 online database 20240201 date of access Sentinel 2 imagery The archive of Sentinel 2 satellite imagery 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/en/data/products/auxiliary-products/global-tide-fes/description-fes2014.html online model 20160501 tide height predictions using a finite element solution model FES 2014 Tidal corrections in the shoreline position were made with tide height predicted from the FES 2014 model. Gibbs, A.E. Nolan, M. Snyder, A.G. 20190226 GeoTIFF online U.S. Geological Survey https://doi.org/10.5066/P9964TKX online dataset 20240430 date of access Barter slopes beach slope data used to correct shoreline positions for tidal water levels Farris, A.S. Weber, K.M. List, J.H. 20200922 NetCDF online U.S. Geological Survey https://doi.org/10.5066/P9GWL52F online dataset 20240430 date of access Cape Cod slopes beach slope data used to correct shoreline positions for tidal water levels Stevens, A.W. Gelfenbaum, G. Warrick, J.A. Miller, I.M. Weiner, H.M. 20171208 CSV online U.S. Geological Survey https://doi.org/10.5066/F72N51GC online dataset 20240430 date of access Elwha slopes beach slope data used to correct shoreline positions for tidal water levels Brown, J.A. Birchler J.J. Thompson, D.M. Long, J.W. Seymour, A.C. 20180314 text files online U.S. Geological Survey https://doi.org/10.5066/F7T43S94 online dataset 20240430 date of access Madeira slopes beach slope data used to correct shoreline positions for tidal water levels Doran, K.S. Long, J.W. Birchler, J.J. Brenner, O.W. Hardy, M.W. Morgan, K.L.M. Stockdon, H.F. Torres, M.L. 20170805 text files online U.S. Geological Survey https://doi.org/10.5066/F7GF0S0Z online dataset 20240430 date of access Rincon slopes beach slope data used to correct shoreline positions for tidal water levels Set up CoastSeg program (Fitzpatrick and others, 2024a; Fitzpatrick and others, 2024b; Buscombe and Fitzpatrick, 2023) for each location. CoastSeg is set up using python 3.7 installed via pip into a conda environment. Regions of Interest (ROIs), transects, and reference shorelines were generated, as included in this data release. For Barter Island, ROIs were generated outside CoastSeg, using the standard CoastSeg sizes, to preserve recommended land-ocean area ratios (Vos and others, 2019) around complex coastlines. In Cape Cod, Elwha, Madeira, and Rincon, ROIs were generated within CoastSeg. Transects were generated outside CoastSeg for all locations and setup to have 30m – 140m alongshore spacing. DSAS (Himmelstoss and others, 2018) was used for Barter Island, Cape Cod, Madeira, and Rincon, to adjust transect orientation (with landward origin point) and consecutive transect labels. CoastSeg’s default reference shoreline was used in Cape Cod, Madeira Beach, and Rincon. In Barter Island and Elwha, a reference shoreline was created outside CoastSeg to reflect older shoreline positions and significant shoreline change over the observation period. These and other settings used at each site are explicitly listed in the shoreline vectors files, included in this data release. See Fitzpatrick and others (2024a, 2024b) and Vos and others (2019) for details on settings, ROIs, transects, reference shorelines, and using CoastSeg. 20230901 After initial setup of ROIs, transects, reference shorelines and settings, the CoastSeg program was run to download all available imagery for satellites (Landsat 5, 7, 8, and 9 for all locations, and also Sentinel 2 for Barter Island) between 1 January 1984 and 31 December 2023. For Barter Island, imagery collected during months when sea-ice is typically present (October – May) were removed. Landsat imagery Landsat 8-9 imagery Sentinel imagery 20240201 After all imagery was downloaded, shorelines were detected within each ROI. Initial shoreline detection images were reviewed and images with bad detections, due to clouds and weather, were manually removed from analysis and the shoreline detection process-step was repeated in CoastSeg. Output from this step included CSV and GeoJSON data for raw (not tidally corrected) shoreline positions. Landsat imagery Landsat 8-9 imagery Sentinel imagery 20240430 uncorrected shorelines Once raw, uncorrected shoreline positions were generated, tidal corrections were conducted using three different slope values (average, high and low) to show the variance of beach slope conditions at each site. Slope values were determined from in situ beach survey and elevation data. Average slope values were defined as the mean from respective datasets for Cape Cod, Elwha and Madeira Beach (Farris and others, 2020; Stevens and others, 2017; Brown and others, 2018), and high/low slope values were defined as +/- 2 standard deviations away from the mean. Because detailed slope data was not available at Barter Island for the study period, slopes at Barter Island were determined empirically from various locations across the site based on elevation data from 2014-2015 (Gibbs and others, 2019). Average, low, and high slope values were derived from the aggregate data (as mean, minimum, and maximum, respectively). Slope values were similarly determined at Rincon based on the elevation dataset from Doran and others (2018). Average/high/low slope values used for Barter Island are 0.07/0.15/0.01; values for Cape Cod are 0.13/0.201/0.061; values for Elwha are 0.125/0.15/.01; values for Madeira are 0.08/0.1596/0.033; and values for Rincon are 0.1287/0.3968/0.0211. Output from this step included tidally corrected CSV and GeoJSON shoreline positions. Tidal corrections were applied using tide heights estimated from the FES 2014 Tidal model. FES 2014 uncorrected shorelines Barter slopes Cape Cod slopes Elwha slopes Madeira slopes Rincon slopes 2024090 Output was checked to ensure quality results. In dynamic locations, including areas such as river mouths, capes, and ends of spits, uncertainty can increase, and shorelines in these locations should be inspected and used with care. 20241215 Data were packaged and prepared for data release. Data are zipped together by location and labeled according to whether the SDS are uncorrected or are tidally corrected (using average, high, or low beach slope values). GeoJSON files contain both the CoastSeg setup settings (including ROI, transects, and reference shoreline), and the output shorelines as vectors where vertices are the positions along each transect. CSV files contain the shoreline positions along each transect. 20250117 Vector 0.00000001 0.00000001 Decimal Degrees World Geodetic System 1984 (WGS84) Geodetic Reference System 80 6378137.0 298.257223563 Mean Sea Level 0.01 meters Implicit coordinate Satellite-derived shorelines and associated CoastSeg settings for historical period (1984-2023) for multiple locations GeoJSON files consist of shoreline positions (extracted shorelines) derived from imagery for multiple locations across the United States, and include reference shorelines, Regions of Interest (ROIs), transects, and other settings used in CoastSeg. Producer defined id Identification label of transects (numeric) and ROIs (alphanumeric) used in satellite derivation. IDs are only presented for transects and ROIs. Producer defined IDs of ROIs are alphanumeric and are unique to each site. IDs of transects are numeric and increase in number across each site; starting values are unique to each site. type Type of vector output presented: extracted shoreline, reference shoreline, transect, or ROI Producer defined extracted shoreline Shoreline vector is an extracted shoreline from CoastSeg for listed date. Vector vertices are from shoreline positions derived along transects. Shoreline vector is connected along consecutive transects and split if consecutive data is not present.Shoreline vector is an extracted shoreline from CoastSeg for listed date. Vector vertices are from shoreline positions derived along transects. Shoreline vector is connected along consecutive transects and split if consecutive data is not present. Producer defined reference shoreline Reference shoreline vector is the reference shoreline used in CoastSeg to identify satellite-derived shoreline positions along transects. Producer defined transect Transect vectors are transects used in CoastSeg to identify satellite-derived shoreline positions. Producer defined ROI ROI vectors are Regions of Interest (ROI) used in CoastSeg to identify areas to download imagery and identify shoreline positions. Producer defined settings Information about CoastSeg settings used in the specified ROI to derive the extracted shorelines. Producer defined Settings contains information on Landsat satellites used, date ranges, and specific settings used within CoastSeg. See Fitzgerald and others (2024a, 2024b) for details of all settings. settings: landsat collection Subfield within settings that specifies the Landsat collection sourced for satellite imagery. Producer defined CO2 Landsat Collection 2 Producer defined settings: dates Subfield within settings that details the start and end dates of imagery searched within each ROI, where date (UTC) is in yyyy-mm-dd (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 day 1 settings: months_list Subfield within settings that details the months that were searched within each ROI for imagery, where the month is identified by its numeral. Producer defined 1 12 month 1 settings: sat_list Subfield within settings that details which satellites (Landsat 5-9, Sentinel 2) were used in a search for available imagery within each ROI. Producer defined L5, L7, L8, L9, S2 Producer defined settings: cloud_thresh Subfield within settings that specifies the cloud threshold (maximum percentage of clouds in image) allowed to exist within the ROI in CoastSeg. Producer defined 0.0 1.0 fractional percentage 0.1 settings: percent_no_data Subfield within settings that specifies the bad-pixel threshold for imagery (as a fractional percentage) used in the ROI in CoastSeg. Producer defined 0.0 1.0 fractional percentage 0.1 settings: dist_clouds Subfield within settings that specifies a buffer distance from clouds to identify shorelines used in the ROI. Producer defined 0 300 meters 10 settings: output_epsg Subfield within settings that specifies the coordinate system reference for CoastSeg outputs. Producer Defined 32607 32619 EPSG projection identifer 1 settings: check_detection Subfield within settings that specifies whether the shoreline detection figures should be created in CoastSeg. Producer Defined false all identification figures are not created Producer defined settings: adjust_detection Subfield within settings that specifies whether the user should be allowed to manually modify the Modified Normalized Difference Water Index (MNDWI) threshold for detecting the shoreline for each image. False by default in CoastSeg. Producer Defined false default MNDWI threshold was not modified Producer defined settings: save_figure Subfield within settings that specifies whether figures of the shoreline detection for each image are saved. Producer Defined true detection images for each downloaded satellite image are saved Producer defined settings: min_beach_area Subfield within settings that specifies a minimum beach area/width to identify shorelines within in the ROI. Producer defined 50 6750 meters 10 settings: min_length_sl Subfield within settings that specifies a minimum shoreline length (alongshore) to identify shorelines within in the ROI. Producer defined 50 500 meters 10 settings: cloud_mask_issue Subfield within settings that specifies whether the default cloud masking algorithm is erroneously masking the shoreline. Producer Defined false default satellite-source cloud mask was used Producer defined settings: sand_color Subfield within settings that specifies sand color used for shoreline detection in the ROI. Producer Defined default default sand color is used in land classification Producer defined settings: pan_off Subfield within settings that controls whether pan-sharpening is applied to the images before shoreline detection in CoastSeg. Producer Defined False pan-sharpening was not applied Producer defined settings: max_dist_ref Subfield within settings that specifies a maximum distance to the reference shoreline to identify shorelines within in the ROI. Producer defined 100 1000 meters 10 settings: along_dist Subfield within settings that defines the maximum alongshore distance from the transect at which shoreline points are considered for calculating intersections. Producer defined 1 100 meters 5 settings: min_points Subfield within settings that defines the minimum number of shoreline points required to identify a valid shoreline intersection with the transect. Producer defined 1 5 points 1 settings: max_std Subfield within settings that defines the maximum standard deviation for the shoreline points when calculating the median intersection with the transects. Producer defined 1 15 points 0.1 settings: max_range Subfield within settings that defines the maximum range allowed for the shoreline points when calculating the median intersection with the transects. Producer defined 1 30.0 points 0.1 settings: min_chainage Subfield within settings that specifies the furthest distance landward from the transect origin that a shoreline intersection is accepted. Producer defined -100.00 0 points 0.1 settings: multiple_inter Subfield within settings that specifies how a scenario with multiple shoreline points intersecting a transect should be processed. Producer defined auto will set multiple intersection points to the furthest shoreline point (maximum distance) if the standard deviation of all the shoreline intersections is above the max_std value, otherwise it will assign these shoreline points as null. Producer defined settings: prc_multiple Subfield within settings that specifies a percentage of shoreline points that can exceed the 'max_std' setting value in 'auto' mode. If this value is exceeded, then any case where multiple shoreline points intersected the transect these intersections will be set to the max shoreline intersection point, otherwise these points will be set to null. Producer defined 0 1 points 0.1 settings: apply_cloud_mask Subfield within settings that specifies whether the cloud mask in imagery is used. Producer defined true a cloud mask in level 2 imagery is used and shorelines are identified outside this mask and any buffer distances. Producer defined false a cloud mask in level 2 imagery is not used and shorelines are identified throughout the image Producer defined settings: image_size_filter Subfield within settings that specifies whether the images were classified as bad if the image area did not meet the minimum area allowed. Producer defined true images that cover less than 40% of the ROI area are classified as bad, and only images that cover more than 40% of the ROI are used for shoreline detection Producer defined settings: drop_intersection_pts Subfield within settings that controls whether shoreline intersection points that did not land on the transect should be removed or not. False by default. Producer defined true intersection points that do not land on a transect are removed Producer defined false intersection points that do not land on a transect are kept Producer defined date Date and time of projected data (UTC) in yyyy-mm-dd HH:MM:ss format (where yyyy is 4 digit year, mm is 2-digit month, dd is 2-digit day, HH is hour in 24-hour notation, MM is minute, and ss is seconds). Producer defined 1984-01-01 00:00:00 2023-12-31 00:00:00 yyyy-mm-dd HH:MM:ss 1 Each GeoJSON file depicts shorelines (as vectors, where vertices are positions determined along transects) derived from satellite imagery and associated configuration settings and setup data used in CoastSeg to derive the shoreline positions. Files are generated for several tidal correction values, including: average slope, low slope, high slope, and no correction (no tidal correction). Files are packaged into zip files by site location (for example satellite-derived-shoreline_coastseg-vectors_BarterIsland.zip), and individual files are named for the correction (for example, coastseg_config_shorelines_averageslopecorrection_Barter.geojson is the file for Barter Island and the average slope tidal correction). 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 GeoJSON format by location. Shoreline vector vertices are derived from points along transects within each ROI, included in the file. Other configuration settings necessary to derive the shoreline positions within each ROI are included in the files. 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. GeoJSON Zip file contains Geographic JavaScript Object Notation (GeoJSON) file with spatial point locations and associated attributes for Barter Island Zip 4.2 https://doi.org/10.5066/P1NUEFDP Data can be downloaded using the Network_Resource_Name link then scrolling down to the Satellite Data section. GeoJSON Zip file contains Geographic JavaScript Object Notation (GeoJSON) file with spatial point locations and associated attributes for Cape Cod Zip 5.4 https://doi.org/10.5066/P1NUEFDP Data can be downloaded using the Network_Resource_Name link then scrolling down to the Satellite Data section. GeoJSON Zip file contains Geographic JavaScript Object Notation (GeoJSON) file with spatial point locations and associated attributes for Elwha Zip 0.96 https://doi.org/10.5066/P1NUEFDP Data can be downloaded using the Network_Resource_Name link then scrolling down to the Satellite Data section. GeoJSON Zip file contains Geographic JavaScript Object Notation (GeoJSON) file with spatial point locations and associated attributes for Madeira Beach Zip 0.1 https://doi.org/10.5066/P1NUEFDP Data can be downloaded using the Network_Resource_Name link then scrolling down to the Satellite Data section. GeoJSON Zip file contains Geographic JavaScript Object Notation (GeoJSON) file with spatial point locations and associated attributes for Rincon Zip 0.8 https://doi.org/10.5066/P1NUEFDP 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 Arc, Global Mapper or QGIS, or numerical processing software such as python or Matlab. 20250425 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