Metadata: Identification_Information: Citation: Citation_Information: Originator: Sean F. Vitousek Originator: Kilian Vos Originator: Patrick L. Barnard Originator: Andrea C. O’Neill Publication_Date: 20230128 Title: Satellite-derived shorelines for North Carolina and South Carolina (1984-2021) Geospatial_Data_Presentation_Form: Shoreline positions in Google Earth KMZ formats Series_Information: Series_Name: data release Issue_Identification: DOI:10.5066/P9W91314 Publication_Information: Publication_Place: Pacific Coastal and Marine Science Center, Santa Cruz, CA Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.5066/P9W91314 Larger_Work_Citation: Citation_Information: Originator: Patrick L. Barnard Originator: Kevin Befus Originator: Jeffrey J. Danielson Originator: Anita C. Engelstad Originator: Li H. Erikson Originator: Amy C. Foxgrover Originator: Matthew W. Hardy Originator: Daniel J. Hoover Originator: Tim Leijnse Originator: Chris Massey Originator: Robert McCall Originator: Norberto C. Nadal-Caraballo Originator: Kees Nederhoff Originator: Leonard Ohenhen Originator: Andrea C. O’Neill Originator: Kai A. Parker Originator: Manoocher Shirzaei Originator: Xin Su Originator: Jennifer A. Thomas Originator: Maarten van Ormondt Originator: Sean F. Vitousek Originator: Kilian Vos Originator: Madison C. Yawn Publication_Date: 2023 Title: Future coastal hazards along the U.S. North and South Carolina coasts Series_Information: Series_Name: data release Issue_Identification: DOI:10.5066/P9W91314 Publication_Information: Publication_Place: Pacific Coastal and Marine Science Center, Santa Cruz, CA Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.5066/P9W91314 Description: Abstract: This dataset contains shoreline positions derived from available Landsat satellite imagery for North Carolina and South Carolina for the time period of 1984 to 2021. Positions were determined using CoastSat (Vos and others, 2019a and 2019b), an open-source mapping toolbox, was used to classify coastal Landsat imagery and detect shorelines at the sub-pixel scale. To understand shoreline evolution in complex environments and operate long-term simulations illustrating potential shoreline positions in the next century (Vitousek and others, 2017, 2021), robust historical shoreline data is necessary. Satellite-derived shorelines (SDS) offer expansive shoreline observational data over large geographic and temporal scales. Resulting shorelines for the period of 1984-2021 are presented in KMZ 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 Google Earth. For best display of results, it is recommended to turn off any 3D viewing. For technical users and researchers, data can be ingested into Global Mapper or QGIS for more detailed analysis. Purpose: 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. Supplemental_Information: This data release was funded by the Additional Supplemental Appropriations for Disaster Relief Act of 2019 (H.R. 2157) for North Carolina and South Carolina. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 20200301 Ending_Date: 20230215 Currentness_Reference: project start through publication date Status: Progress: Complete Maintenance_and_Update_Frequency: None planned Spatial_Domain: Bounding_Coordinates: West_Bounding_Coordinate: -81.41555 East_Bounding_Coordinate: -75.44948 North_Bounding_Coordinate: 36.55215 South_Bounding_Coordinate: 32.03543 Keywords: Theme: Theme_Keyword_Thesaurus: USGS Metadata Identifier Theme_Keyword: USGS:4619e959-c055-4ee2-884f-3d1224f300f9 Theme: Theme_Keyword_Thesaurus: Global Change Master Directory Theme_Keyword: Hazards Planning Theme_Keyword: Ocean Waves Theme_Keyword: Erosion Theme_Keyword: Sea Level Rise Theme_Keyword: Extreme Weather Theme: Theme_Keyword_Thesaurus: ISO 19115 Topic Category Theme_Keyword: Oceans Theme_Keyword: ClimatologyMeteorologyAtmosphere Theme: Theme_Keyword_Thesaurus: Data Categories for Marine Planning Theme_Keyword: Physical Habitats and Geomorphology Theme: Theme_Keyword_Thesaurus: USGS Thesaurus Theme_Keyword: Climate Change Theme_Keyword: Storms Theme_Keyword: Sea-level Change Theme: Theme_Keyword_Thesaurus: Marine Realms Information Bank (MRIB) keywords Theme_Keyword: sea level change Theme_Keyword: waves Theme_Keyword: coastal erosion Theme: Theme_Keyword_Thesaurus: None Theme_Keyword: U.S. Geological Survey Theme_Keyword: USGS Theme_Keyword: Coastal and Marine Hazards and Resources Program Theme_Keyword: CMHRP Theme_Keyword: Pacific Coastal and Marine Science Center Theme_Keyword: PCMSC Place: Place_Keyword_Thesaurus: Geographic Names Information System (GNIS) Place_Keyword: State of South Carolina Place_Keyword: State of North Carolina Access_Constraints: None Use_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. Point_of_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey, Pacific Coastal and Marine Science Center Contact_Person: PCMSC Science Data Coordinator Contact_Address: Address_Type: mailing and physical Address: 2885 Mission Street City: Santa Cruz State_or_Province: CA Postal_Code: 95060 Contact_Voice_Telephone: 831-427-4747 Contact_Electronic_Mail_Address: pcmsc_data@usgs.gov Browse_Graphic: Browse_Graphic_File_Name: SatelliteDerivedShorelines_NC_SC.png Browse_Graphic_File_Description: Image map showing study area for the satellite derived shorelines of North and South Carolina. Browse_Graphic_File_Type: png Data_Set_Credit: This data release was funded by the Additional Supplemental Appropriations for Disaster Relief Act of 2019 (H.R. 2157) for North Carolina and South Carolina. Native_Data_Set_Environment: The datasets were created in a Windows 11 Operating system, using Matlab v2020 and python 3.7. Results were output and saved as KMZs. Cross_Reference: Citation_Information: Originator: S.F. Vitousek Originator: P.L. Barnard Originator: P.W. Limber Originator: L.H. Erikson Originator: B. Cole Publication_Date: 2017 Title: A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change Other_Citation_Details: Vitousek, S., Barnard, P.L., Limber, P., Erikson, L.H., and Cole, B., 2017, A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change, Journal of Geophysical Research: Earth Surface, v. 122, p. 782-806. Online_Linkage: https://doi.org/10.1002/2016JF004065 Cross_Reference: Citation_Information: Originator: S.F. Vitousek Originator: L. Cagigal Originator: J. Montano Originator: A. Rueda Originator: F. Mendez Originator: G. Coco Originator: P.L. Barnard Publication_Date: 2021 Title: The application of ensemble wave forcing to quantify uncertainty of shoreline change predictions Other_Citation_Details: Vitousek, S., Cagigal, L., Montaño, J., Rueda, A., Mendez, F., Coco, G., and Barnard, P. L., 2021, The application of ensemble wave forcing to quantify uncertainty of shoreline change predictions, Journal of Geophysical Research: Earth Surface, v. 126(7). Online_Linkage: https://doi.org/10.1029/2019JF005506 Cross_Reference: Citation_Information: Originator: K. Vos Originator: M.D. Harley Originator: K.D. Splinter Originator: J.A. Simmons Originator: I.L. Turner Publication_Date: 2019 Title: Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery Other_Citation_Details: 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. Online_Linkage: https://doi.org/10.1016/j.coastaleng.2019.04.004 Cross_Reference: Citation_Information: Originator: K. Vos Originator: K.D. Splinter Originator: M.D. Harley Originator: J.A. Simmons Originator: I.L. Turner Publication_Date: 2019 Title: CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery Other_Citation_Details: 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. Online_Linkage: https://doi.org/10.1016/j.envsoft.2019.104528 Cross_Reference: Citation_Information: Originator: K. Vos Originator: M.D. Harley Originator: K.D. Splinter Originator: A. Walker Originator: I.L. Turner Publication_Date: 2020 Title: Beach slopes from satellite‐derived shorelines Other_Citation_Details: 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(14). Online_Linkage: https://doi.org/10.1029/2020GL088365 Cross_Reference: Citation_Information: Originator: N. Gorelick Originator: M. Hancher Originator: M. Dixon Originator: S. Ilyshechenko Originator: D. Thau Originator: R. Moore Publication_Date: 2017 Title: Google Earth Engine: Planetary-scale geospatial analysis for everyone Other_Citation_Details: 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. Online_Linkage: https://doi.org/10.1016/j.rse.2017.06.031 Cross_Reference: Citation_Information: Originator: E.A. Himmelstoss Originator: A.S. Farris Originator: R.E. Henderson Originator: M.G. Kratzmann Originator: A. Ergul Originator: O. Zhang Originator: J.L. Zichichi Originator: R.E. Thieler Publication_Date: 2021 Title: Digital Shoreline Analysis System (version 5.1) Other_Citation_Details: Himmelstoss, E.A., Farris, A.S., Henderson, R.E., Kratzmann, M.G., Ergul, Ayhan, Zhang, Ouya, 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. Online_Linkage: https://code.usgs.gov/cch/dsas Data_Quality_Information: Attribute_Accuracy: Attribute_Accuracy_Report: 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. Logical_Consistency_Report: Data have undergone QA/QC and fall within expected/reasonable ranges. Completeness_Report: Data set is considered complete for the information presented. Positional_Accuracy: Horizontal_Positional_Accuracy: Horizontal_Positional_Accuracy_Report: Data are concurrent with specified transect locations. Vertical_Positional_Accuracy: Vertical_Positional_Accuracy_Report: N/A Lineage: Source_Information: Source_Citation: Citation_Information: Originator: U.S. Geological Survey Publication_Date: 2021 Title: Landsat imagery (from Landsat 5-8) for North Carolina and South Carolina coasts Geospatial_Data_Presentation_Form: image Publication_Information: Publication_Place: online Publisher: U.S. Geological Survey Online_Linkage: https://earthengine.google.com/ Type_of_Source_Media: online database Source_Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 19840101 Ending_Date: 20211231 Source_Currentness_Reference: ground condition Source_Citation_Abbreviation: Landsat imagery Source_Contribution: The archive of Landsat 5-8 satellite imagery accessed through Google Earth Engine was used to derive shoreline positions for the study area. Source_Information: Source_Citation: Citation_Information: Originator: Carrere, L. Originator: Lyard, F. Originator: Cancet, M. Originator: Guillot, A. Originator: Picot, N. Publication_Date: 20160501 Title: FES (Finite Element Solution) 2014, a new tidal model—Validation results and perspectives for improvements Geospatial_Data_Presentation_Form: model Publication_Information: Publication_Place: online Publisher: AVISO Online_Linkage: https://www.aviso.altimetry.fr/es/data/products/auxiliary-products/global-tide-fes/description-fes2014.html Type_of_Source_Media: online model Source_Time_Period_of_Content: Time_Period_Information: Single_Date/Time: Calendar_Date: 20160501 Source_Currentness_Reference: tide height predictions using a finite element solution model Source_Citation_Abbreviation: FES 2014 Source_Contribution: Tidal corrections in the shoreline position were made tiwth tide height predicted from the FES 2014 model. Process_Step: Process_Description: Set up CoastSat toolbox (Vos and others, 2019a and 2019b) for implementation along the region of interest. Toolbox set up in python 3.7 to run for geography spanning coastline for North Carolina and South Carolina for the time period of 01 March 1984 to 27 April 2021. The 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 transects 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). Process_Date: 20210209 Process_Step: Process_Description: 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. Source_Used_Citation_Abbreviation: FES 2014, Landsat imagery Process_Date: 20210401 Process_Step: Process_Description: 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. Process_Date: 20210915 Process_Step: Process_Description: Checked all output to ensure quality results. Process_Date: 20211216 Process_Step: Process_Description: Organized final extracted shorelines into KMZ files grouped by state, with North Carolina split into northern and southern portions for considerations of file-size constraints. Shorelines are represented as lines colored based on the date of imagery acquisition. Older shorelines are displayed in blue, and in red for newer shorelines. Process_Date: 20220110 Process_Step: Process_Description: Edits were made to correct spelling in author name. No data were changed. The metadata available from a harvester may supersede metadata bundled within a download file. Users are advised to compare the metadata date of this file to any similar file to ensure they are using the most recent version. (scochran@usgs.gov) Process_Date: 20230516 Spatial_Data_Organization_Information: Direct_Spatial_Reference_Method: Vector Point_and_Vector_Object_Information: SDTS_Terms_Description: SDTS_Point_and_Vector_Object_Type: GT-polygon composed of chains Point_and_Vector_Object_Count: 100000 Spatial_Reference_Information: Horizontal_Coordinate_System_Definition: Geographic: Latitude_Resolution: 0.000001 Longitude_Resolution: 0.000001 Geographic_Coordinate_Units: Decimal Degrees Geodetic_Model: Horizontal_Datum_Name: North American Datum 1983 Ellipsoid_Name: Geodetic Reference System 80 Semi-major_Axis: 6378137.000000 Denominator_of_Flattening_Ratio: 298.257222 Vertical_Coordinate_System_Definition: Depth_System_Definition: Depth_Datum_Name: NAVD88 Depth_Resolution: 1.0 Depth_Distance_Units: meters Depth_Encoding_Method: Implicit coordinate Entity_and_Attribute_Information: Detailed_Description: Entity_Type: Entity_Type_Label: Shoreline positions for historical period (1984-2021) for North Carolina and South Carolina, derived from satellite imagery Entity_Type_Definition: KMZ file consists of shoreline positions derived from imagery of North Carolina and South Carolina coasts. Shorelines are represented as lines colored based on the date of imagery acquisition. Older shorelines are displayed in blue, and in red for newer shorelines. Entity_Type_Definition_Source: Producer Defined Attribute: Attribute_Label: CoastSat_shoreline Attribute_Definition: Position of unique shoreline segment derived from satellite imagery for date and time indicated. Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Unrepresentable_Domain: geographic position of shoreline derived from satellite imagery. Overview_Description: Entity_and_Attribute_Overview: Shoreline positions for period 1984-2021 across North Carolina and South Carolina. Entity_and_Attribute_Detail_Citation: Shoreline positions for period 1984-2021 across North Carolina and South Carolina. The KMZ files consist of shoreline positions derived from satellite imagery. Shorelines are represented as lines colored based on the date of imagery acquisition. Older shorelines are displayed in blue, and in red for newer shorelines. Distribution_Information: Distributor: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey - CMGDS Contact_Address: Address_Type: mailing and physical Address: 2885 Mission Street City: Santa Cruz State_or_Province: CA Postal_Code: 95060 Contact_Voice_Telephone: 831-427-4747 Contact_Electronic_Mail_Address: pcmsc_data@usgs.gov Resource_Description: These data are available in KMZ format in zip files, by state. North Carolina is further divided into 2 parts (north and south) for user considerations pertaining to file size (Satellite_Derived_Shorelines_NC_north.zip, Satellite_Derived_Shorelines_NC_south.zip, and Satellite_Derived_Shorelines _SC.zip) Distribution_Liability: 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. Standard_Order_Process: Digital_Form: Digital_Transfer_Information: Format_Name: KML Format_Version_Number: Google Earth Pro (version 7.3, Google, 2017) Format_Specification: Features are in KMZ format (a zipped form of KML) and are projected in UTM Zone 17 and 18 coordinates, with horizontal datum NAD83 and vertical datum NAVD88. Format_Information_Content: The .zip file contains KMZ files for South Carolina File_Decompression_Technique: WinZip Transfer_Size: 51.4 Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: https://doi.org/10.5066/P9W91314 Access_Instructions: Data can be downloaded using the Network_Resource_Name link then scrolling down to the Satellite Data section. Digital_Form: Digital_Transfer_Information: Format_Name: KML Format_Version_Number: Google Earth Pro (version 7.3, Google, 2017) Format_Specification: Features are in KMZ format (a zipped form of KML) and are projected in UTM Zone 17 and 18 coordinates, with horizontal datum NAD83 and vertical datum NAVD88. Format_Information_Content: The .zip file contains KMZ files for North Carolina (northern part) File_Decompression_Technique: WinZip Transfer_Size: 45.9 Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: https://doi.org/10.5066/P9W91314 Access_Instructions: Data can be downloaded using the Network_Resource_Name link then scrolling down to the Satellite Data section. Digital_Form: Digital_Transfer_Information: Format_Name: KML Format_Version_Number: Google Earth Pro (version 7.3, Google, 2017) Format_Specification: Features are in KMZ format (a zipped form of KML) and are projected in UTM Zone 17 and 18 coordinates, with horizontal datum NAD83 and vertical datum NAVD88. Format_Information_Content: The .zip file contains KMZ files for North Carolina (southern part) File_Decompression_Technique: WinZip Transfer_Size: 41.5 Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: https://doi.org/10.5066/P9W91314 Access_Instructions: Data can be downloaded using the Network_Resource_Name link then scrolling down to the Satellite Data section. Fees: None. Technical_Prerequisites: These data can be viewed with Google Earth software, and other compatible GIS software such as Global Mapper or QGIS. Metadata_Reference_Information: Metadata_Date: 20230516 Metadata_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey, Pacific Coastal and Marine Science Center Contact_Person: PCMSC Science Data Coordinator Contact_Address: Address_Type: mailing and physical Address: 2885 Mission Street City: Santa Cruz State_or_Province: CA Postal_Code: 95060 Contact_Voice_Telephone: 831-427-4747 Contact_Electronic_Mail_Address: pcmsc_data@usgs.gov Metadata_Standard_Name: Content Standard for Digital Geospatial Metadata Metadata_Standard_Version: FGDC-STD-001-1998