Metadata: Identification_Information: Citation: Citation_Information: Originator: U.S. Geological Survey Publication_Date: 20240112 Title: Shorelines of the Northern California coastal region (1854-2016) used in shoreline change analysis Edition: 1 Geospatial_Data_Presentation_Form: vector digital data Series_Information: Series_Name: data release Issue_Identification: DOI:10.5066/P94J0K7Z Publication_Information: Publication_Place: Woods Hole Coastal and Marine Science Center, Woods Hole, MA Publisher: U.S. Geological Survey, Coastal and Marine Hazards and Resources Program Online_Linkage: https://doi.org/10.5066/P94J0K7Z Online_Linkage: https://www.sciencebase.gov/catalog/item/64add938d34e70357a293270 Larger_Work_Citation: Citation_Information: Originator: Meredith G. Kratzmann Originator: Amy S. Farris Originator: Emily A. Himmelstoss Publication_Date: 2024 Title: National Shoreline Change—A GIS compilation of vector shorelines and associated shoreline change data from the 1800s to 2010s for the coast of California Edition: 1.0 Geospatial_Data_Presentation_Form: vector digital data Series_Information: Series_Name: data release Issue_Identification: DOI:10.5066/P94J0K7Z Publication_Information: Publication_Place: Reston, VA Publisher: U.S. Geological Survey Other_Citation_Details: suggested citation: Kratzmann, M.G., Farris, A.S., and Himmelstoss, E.A., 2024, National Shoreline Change—A GIS compilation of vector shorelines and associated shoreline change data from the 1800s to 2010s for the coast of California: U.S. Geological Survey data release, https://doi.org/10.5066/P94J0K7Z. Online_Linkage: https://doi.org/10.5066/P94J0K7Z Online_Linkage: https://www.sciencebase.gov/catalog/item/619668d0d34eb622f69155a7 Description: Abstract: Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline data along open-ocean sandy shores of the conterminous United States and parts of Alaska and Hawaii as part of the Coastal Change Hazards programmatic focus, formerly the National Assessment of Shoreline Change project. There is no widely accepted standard for analyzing shoreline change. Existing shoreline data measurements and rate calculation methods vary from study to study and prevent combining results into state-wide or regional assessments. The impetus behind this national scale project was to develop a standardized method of measuring changes in shoreline position that is consistent from coast to coast. The goal was to facilitate the process of periodically and systematically updating the results in an internally consistent manner. In this release, three new tidal datum-based mean high water (MHW) shorelines extracted from 2009/2010/2011, 2015, and 2016 lidar elevation data are included in the analysis (coverage not necessarily continuous statewide). The full range of shoreline data is 1852 to 2016. The proxy-datum bias correction has been applied on a transect-by-transect basis to reconcile offsets between the MHW shorelines and proxy-based HWL shorelines for the entire California coastal region which is divided into three subregions: Northern California (NorCal), Central California (CenCal), and Southern California (SoCal). In the previous report (Hapke et al., 2006), the proxy-datum bias correction was only applied to regional shoreline averages. This shoreline change update for California reports proxy-datum bias corrected rates when that information was computed while extracting shoreline positions from lidar data. In areas where the methods for delineating shorelines did not include computing bias correction values, the rates are reported without that correction. The proxy-datum bias concept is explained further in Ruggiero and List (2009) and in the process steps of the metadata file associated with the transect rates. Purpose: Northern California: This dataset includes shorelines from 162 years ranging from 1854 to 2016 in Northern California's coastal region from the Oregon border to Tomales Bay. Shorelines were compiled from topographic survey sheets (T-sheets; National Oceanic and Atmospheric Administration (NOAA)), digital raster graphics (DRG) (U.S. Geological Survey (USGS)), and lidar (USGS, USGS/National Aeronautics and Space Administration (NASA), USGS/NOAA/U.S. Army Corps of Engineers (USACE) and NOAA/USACE/Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX)). Central California: This dataset includes shorelines from 164 years ranging from 1852 to 2016 in Central California's coastal region from Tomales Bay to El Capitán State Beach. Shorelines were compiled from T-sheets (NOAA), DRGs (USGS), and lidar (USGS, USGS/NASA, USGS/NOAA/USACE and NOAA/USACE/JALBTCX). Southern California: This dataset includes shorelines from 164 years ranging from 1852 to 2016 in Southern California's coastal region from El Capitán State Beach to the border with Mexico. Shorelines were compiled from T-sheets (NOAA), and lidar (USGS, USGS/NASA, USGS/NOAA/USACE and NOAA/USACE/JALBTCX). Historical shoreline positions serve as easily understood features that can be used to describe the movement of beaches through time. These data are used to calculate rates of shoreline change in support of the U.S. Geological Survey's Coastal Change Hazards programmatic focus to maintain a national scale database of shoreline positions and rates. Long-term shoreline change rates were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 5.0. DSAS uses a measurement baseline method to calculate rate-of-change statistics. Transects are cast from the reference baseline to intersect each shoreline, establishing measurement points used to calculate shoreline change rates. Supplemental_Information: Cross-referenced citations are applicable to the dataset as a whole. Additional citations are located within individual process steps that pertain specifically to the method described in that step. Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 1854 Ending_Date: 2016 Currentness_Reference: ground condition Status: Progress: Complete Maintenance_and_Update_Frequency: None planned Spatial_Domain: Bounding_Coordinates: West_Bounding_Coordinate: -124.409678 East_Bounding_Coordinate: -122.966395 North_Bounding_Coordinate: 42.009922 South_Bounding_Coordinate: 38.229678 Keywords: Theme: Theme_Keyword_Thesaurus: ISO 19115 Topic Category Theme_Keyword: geoscientificInformation Theme_Keyword: oceans Theme_Keyword: environment Theme: Theme_Keyword_Thesaurus: None Theme_Keyword: Baseline Theme_Keyword: Shoreline Theme_Keyword: Shoreline Change Theme_Keyword: Digital Shoreline Analysis System Theme_Keyword: DSAS Theme_Keyword: U.S. Geological Survey Theme_Keyword: USGS Theme_Keyword: Coastal and Marine Geology Program Theme_Keyword: CMGP Theme_Keyword: Woods Hole Coastal and Marine Science Center Theme_Keyword: WHCMSC Theme_Keyword: National Oceanic and Atmospheric Administration Theme_Keyword: NOAA Theme_Keyword: National Aeronautics and Space Administration Theme_Keyword: NASA Theme_Keyword: U.S. Army Corps of Engineers Theme_Keyword: USACE Theme_Keyword: Joint Airborne Lidar Bathymetry Technical Center of eXpertise Theme_Keyword: JALBTCX Theme_Keyword: Mean High Water Theme_Keyword: MHW Theme_Keyword: High Water Line Theme_Keyword: HWL Theme: Theme_Keyword_Thesaurus: USGS thesaurus Theme_Keyword: geospatial datasets Theme_Keyword: coastal processes Theme: Theme_Keyword_Thesaurus: USGS Metadata Identifier Theme_Keyword: USGS:64add938d34e70357a293270 Place: Place_Keyword_Thesaurus: None Place_Keyword: Pacific Coast Place_Keyword: United States Place_Keyword: North America Place_Keyword: California Place_Keyword: Northern California Place_Keyword: NorCal Place_Keyword: Central California Place_Keyword: CenCal Place_Keyword: Southern California Place_Keyword: SoCal Access_Constraints: None Use_Constraints: Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the U.S. Geological Survey as the originator of the dataset. These data are not to be used for navigation. Point_of_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Meredith G. Kratzmann Contact_Address: Address_Type: mailing and physical Address: 384 Woods Hole Road City: Woods Hole State_or_Province: MA Postal_Code: 02543-1598 Country: USA Contact_Voice_Telephone: 508-548-8700 Contact_Facsimile_Telephone: 508-457-2310 Contact_Electronic_Mail_Address: mkratzmann@contractor.usgs.gov Browse_Graphic: Browse_Graphic_File_Name: https://www.sciencebase.gov/catalog/file/get/64add938d34e70357a293270?name=BG_Norcal_shorelines.jpg&allowOpen=true Browse_Graphic_File_Description: Map view of data Browse_Graphic_File_Type: JPEG Native_Data_Set_Environment: Microsoft Windows 10 Enterprise; Esri ArcGIS 10.7.1 Cross_Reference: Citation_Information: Originator: Meredith G. Kratzmann Publication_Date: 2024 Title: National Shoreline Change—Summary Statistics of Shoreline Change From the 1800s To the 2010s for the Coast of California Series_Information: Series_Name: data report Issue_Identification: 1187 Publication_Information: Publication_Place: Reston, VA Publisher: U.S. Geological Survey Other_Citation_Details: Data report associated with data release DOI:10.5066/P94J0K7Z. Online_Linkage: https://doi.org/10.3133/dr1187 Cross_Reference: Citation_Information: Originator: Emily A. Himmelstoss Originator: Amy S. Farris Originator: Rachel E. Henderson Originator: Meredith G. Kratzmann Originator: Ayhan Ergul Originator: Ouya Zhang Originator: Jessica L. Zichichi Publication_Date: 2018 Title: Digital Shoreline Analysis System (version 5.0): U.S. Geological Survey Software Series_Information: Series_Name: software release Issue_Identification: version 5.0 Publication_Information: Publication_Place: Reston, VA Publisher: U.S. Geological Survey Online_Linkage: https://code.usgs.gov/cch/dsas/ Online_Linkage: https://doi.org/10.5066/P9VW42I0 Online_Linkage: https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas Cross_Reference: Citation_Information: Originator: Emily A. Himmelstoss Originator: Rachel E. Henderson Originator: Meredith G. Kratzmann Originator: Amy S. Farris Publication_Date: 2018 Title: Digital Shoreline Analysis System (DSAS) Version 5.0 User Guide Geospatial_Data_Presentation_Form: publication Series_Information: Series_Name: Open-File Report Issue_Identification: 20181179 Publication_Information: Publication_Place: Reston, VA Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.3133/ofr20181179 Online_Linkage: https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas Cross_Reference: Citation_Information: Originator: Cheryl J. Hapke Originator: David Reid Originator: Bruce M. Richmond Originator: Peter Ruggiero Originator: Jeff List Publication_Date: 2006 Title: National Assessment of Shoreline Change Part 3: Historical Shoreline Change and Associated Coastal Land Loss Along Sandy Shorelines of the California Coast Geospatial_Data_Presentation_Form: publication Series_Information: Series_Name: Open-File Report Issue_Identification: 2006-1219 Publication_Information: Publication_Place: Reston, VA Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.3133/ofr20061219 Cross_Reference: Citation_Information: Originator: Cheryl J. Hapke Originator: David Reid Publication_Date: 2006 Title: National Assessment of Shoreline Change: A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for the Sandy Shorelines of the California Coast Geospatial_Data_Presentation_Form: publication Series_Information: Series_Name: Open-File Report Issue_Identification: 2006-1251 Publication_Information: Publication_Place: Reston, VA Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.3133/ofr20061251 Cross_Reference: Citation_Information: Originator: Peter Ruggiero Originator: Jeffrey H. List Publication_Date: 200909 Title: Improving Accuracy and Statistical Reliability of Shoreline Position and Change Rate Estimates Geospatial_Data_Presentation_Form: publication Series_Information: Series_Name: Journal of Coastal Research Issue_Identification: vol. 255 Publication_Information: Publication_Place: n/a Publisher: Coastal Education and Research Foundation Other_Citation_Details: pp. 1069-1081 Online_Linkage: https://doi.org/10.2112/08-1051.1 Cross_Reference: Citation_Information: Originator: National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS) Publication_Date: Unknown Title: Scanned National Ocean Service (NOS) Coastal Survey Maps (also known as Topographic Survey sheets, or T-sheets) Series_Information: Series_Name: NOAA shoreline manuscripts (T-sheets) Issue_Identification: n/a Publication_Information: Publication_Place: Washington, D.C. Publisher: National Oceanic and Atmospheric Administration Online_Linkage: https://shoreline.noaa.gov/data/datasheets/t-sheets.html Cross_Reference: Citation_Information: Originator: National Oceanic and Atmospheric Administration (NOAA) Office for Coastal Management Publication_Date: Unknown Title: 1998 Spring West Coast (post El Niño) NOAA/USGS/NASA Airborne LiDAR Assessment of Coastal Erosion (ALACE) Project for the US Coastline Publication_Information: Publication_Place: Charleston, SC Publisher: NOAA Office for Coastal Management Online_Linkage: https://coast.noaa.gov/ Online_Linkage: https://coast.noaa.gov/digitalcoast/data/ Online_Linkage: https://www.fisheries.noaa.gov/inport/item/48155 Cross_Reference: Citation_Information: Originator: Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Coastal Services Center (CSC) Publication_Date: Unknown Title: 2002 NASA/USGS Airborne LiDAR Assessment of Coastal Erosion (ALACE) Project for California, Oregon, and Washington Coastlines Publication_Information: Publication_Place: Charleston, SC Publisher: NOAA's Ocean Service, Coastal Services Center (CSC) Online_Linkage: https://coast.noaa.gov/ Online_Linkage: https://coast.noaa.gov/digitalcoast/data/ Online_Linkage: https://www.fisheries.noaa.gov/inport/item/49634 Cross_Reference: Citation_Information: Originator: Kathryn M. Weber Originator: Jeffrey H. List Originator: Karen L.M. Morgan Publication_Date: 2005 Title: An operational mean high water datum for determination of shoreline position from topographic lidar data Series_Information: Series_Name: Open-File Report Issue_Identification: 2005-1027 Publication_Information: Publication_Place: Reston, VA Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.3133/ofr20051027 Cross_Reference: Citation_Information: Originator: Patrick L. Barnard Originator: Schuyler A. Smith Originator: Amy C. Foxgrover Publication_Date: 2020 Title: Mean high water (MHW) shorelines along the coast of California used to calculated shoreline change from 1998 to 2016 Series_Information: Series_Name: data release Issue_Identification: DOI:10.5066/P91QSGXF Publication_Information: Publication_Place: Reston, VA Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.5066/P91QSGXF Cross_Reference: Citation_Information: Originator: Young, Adam P. Originator: Flick, Reinhard E. Originator: Gallien, Timu W. Originator: Giddings, Sarah N. Originator: Guza, R. T. Originator: Harvey, M. Originator: Lenain, Luc Originator: Ludka, B.C. Originator: Melville, W. Kendall Originator: O'Reilly, W.C. Publication_Date: 20181105 Title: Southern California Coastal Response to the 2015–2016 El Niño Series_Information: Series_Name: Journal of Geophysical Research Issue_Identification: Earth Surface 123 Publication_Information: Publication_Place: n/a Publisher: Journal of Geophysical Research Other_Citation_Details: pp. 3069–3083 Online_Linkage: https://doi.org/10.1029/2018JF004771 Data_Quality_Information: Attribute_Accuracy: Attribute_Accuracy_Report: The data provided here are a compilation of shorelines from multiple sources, spanning >150 years. The attributes are based on the requirements of the Digital Shoreline Analysis System (DSAS) software and have gone through a series of quality assurance procedures. Logical_Consistency_Report: Adjacent shoreline segments do not overlap and are not necessarily continuous. Shorelines were quality checked for accuracy. Any slight offsets between adjacent segments due to georeferencing and digitizing error are taken into account in the uncertainty of the shoreline position, as reported in the horizontal accuracy section of this metadata file. Completeness_Report: This shoreline file is complete and contains all shoreline segments used to calculate shoreline change rates along sections of the California coastal region where shoreline position data were available. These data adequately represented the shoreline position at the time of the survey. Gaps in these data, if applicable, are a consequence of non-existing data or existing data that did not meet quality assurance standards. The digitized shoreline vectors downloaded from NOAA included attributes defining the shoreline type (attribute field name varies by file). For the open-ocean coasts, only shoreline features (Natural.Mean High Water; SPOR; 20) were retained. Other shoreline features (such as seawalls, bulkheads, manmade objects) were deleted. Positional_Accuracy: Horizontal_Positional_Accuracy: Horizontal_Positional_Accuracy_Report: The horizontal accuracy of the shoreline data varies with respect to the data source from which the shorelines were digitized, the lidar data from which the shorelines were extracted, and the time period. Shorelines prior to 1960 (T-sheets) have an estimated positional uncertainty of plus or minus 10.8 meters. DRG shorelines (1940s-1970s) have an estimated positional uncertainty of plus or minus 15 meters. Shorelines from the 1960s-1980s (T-sheets) have an estimated positional uncertainty of plus or minus 5.1 meters. The lidar shoreline from 1998/2002 has an estimated positional uncertainty of plus or minus 1.5 meters (Hapke et al., 2006). The lidar shoreline from 2009/2010/2011 has an estimated positional uncertainty of plus or minus 1.9 meters (NorCal), plus or minus 2.2 meters (CenCal), plus or minus 2.3 meters (SoCal). The lidar shoreline from 2015 (NOAA/USACE/JALBTCX) has an estimated positional uncertainty of plus or minus 4.06 meters (NorCal), plus or minus 4.06-4.35 meters (CenCal), plus or minus 4.13 meters (SoCal). The lidar shoreline from 2015 (UC San Diego) has an estimated positional uncertainty of plus or minus 0.45 meters (SoCal). The lidar shoreline from 2016 has an estimated positional uncertainty of plus or minus 0.74 meters (NorCal), plus or minus 0.72-0.74 meters (CenCal), plus or minus 0.70 meters (SoCal). More information regarding the uncertainty of these lidar shorelines is contained in the process steps of this metadata file. Crowell, M., Leatherman, S.P., and Buckley, M.K., 1991. Historical Shoreline Change: Error Analysis and Mapping Accuracy. Journal of Coastal Research: v.7, n.3, pp.839-852. Lineage: Source_Information: Source_Citation: Citation_Information: Originator: National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS) Publication_Date: Unknown Title: Scanned National Ocean Service (NOS) Coastal Survey Maps (also known as Topographic Survey sheets, or T-sheets) Online_Linkage: https://shoreline.noaa.gov/data/datasheets/t-sheets.html Type_of_Source_Media: digital data Source_Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 1852 Ending_Date: 1978 Source_Currentness_Reference: ground condition Source_Citation_Abbreviation: T-sheet shorelines Source_Contribution: T-sheets used for QA/QC of NOAA-digitized 1800s-1980s shorelines and/or used as data source to digitize shorelines. Source_Information: Source_Citation: Citation_Information: Originator: Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management Publication_Date: 201201 Title: 2009 - 2011 CA Coastal Conservancy Coastal Lidar Project Online_Linkage: https://www.coast.noaa.gov/ Online_Linkage: https://coast.noaa.gov/digitalcoast/data/ Online_Linkage: https://www.fisheries.noaa.gov/inport/item/48166 Type_of_Source_Media: digital data Source_Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 2009 Ending_Date: 2011 Source_Currentness_Reference: ground condition Source_Citation_Abbreviation: 2009-2011 lidar Source_Contribution: Lidar data that were used to extract a shoreline. Source_Information: Source_Citation: Citation_Information: Originator: National Oceanic and Atmospheric Administration (NOAA) Office for Coastal Management (OCM), U.S. Army Corps of Engineers (USACE), Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX) Publication_Date: 2018 Title: 2015 USACE NCMP Topobathy Lidar DEM: California Online_Linkage: https://inport.nmfs.noaa.gov/inport/item/51862 Online_Linkage: https://coast.noaa.gov/htdata/raster2/elevation/USACE_CA_Topobathy_DEM_2015_8482/ Type_of_Source_Media: digital data Source_Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 2015 Ending_Date: 2015 Source_Currentness_Reference: ground condition Source_Citation_Abbreviation: 2015 lidar Source_Contribution: Lidar data that were used to extract a shoreline. Source_Information: Source_Citation: Citation_Information: Originator: Flick, Reinhard E. Originator: Gallien, Timu W. Originator: Giddings, Sarah N. Originator: Guza, R. T. Originator: Harvey, M. Originator: Lenain, Luc Originator: Ludka, B.C. Originator: Melville, W. Kendall Originator: O'Reilly, W.C. Originator: Young, Adam P. Publication_Date: 20190716 Title: Data from: Southern California Coastal Response to the 2015-16 El Niño: 2015-10-06 Survey - Research Data Curation Program, UC San Diego Online_Linkage: https://doi.org/10.6075/J0F18WXQ Type_of_Source_Media: digital data Source_Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 2015 Ending_Date: 2015 Source_Currentness_Reference: ground condition Source_Citation_Abbreviation: 2015 lidar UCSD Source_Contribution: Lidar data that were used to extract a shoreline. Source_Information: Source_Citation: Citation_Information: Originator: National Oceanic and Atmospheric Administration (NOAA) Office for Coastal Management (OCM), United States Geological Survey (USGS), U.S. Army Corps of Engineers (USACE) Publication_Date: 20170412 Title: 2016 USGS Lidar DEM: West Coast El Niño (WA, OR, CA) Online_Linkage: https://inport.nmfs.noaa.gov/inport/item/48383 Online_Linkage: https://coast.noaa.gov/htdata/raster2/elevation/West_Coast_El_Nino_DEM_2016_6260/ Online_Linkage: https://coast.noaa.gov/htdata/lidar2_z/geoid12b/data/6259/supplemental/west_coast_2016_el_nino_m6259_lidar_report.pdf Type_of_Source_Media: digital data Source_Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 2016 Ending_Date: 2016 Source_Currentness_Reference: ground condition Source_Citation_Abbreviation: 2016 lidar Source_Contribution: Lidar data that were used to extract a shoreline. Process_Step: Process_Description: Data from the previously-published National Assessment of Shoreline Change study for the sandy shorelines of the California Coast (USGS Open-File Report 2006-1219 [Hapke et al., 2006] and USGS Open-File Report 2006-1251 [Hapke and Reid, 2006]) were used as the starting point for this update. Any additionally available shorelines derived from T-sheets were downloaded from NOAA's shoreline survey website: https://shoreline.noaa.gov/data/datasheets/t-sheets.html This process step and all other process steps were performed by the same person - Meredith Kratzmann, unless otherwise stated in the contact information associated with the step. Source_Used_Citation_Abbreviation: T-sheet shorelines Process_Date: 2013 Source_Produced_Citation_Abbreviation: Historical shorelines derived from T-sheets Process_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Meredith Kratzmann Contact_Address: Address_Type: Mailing and Physical Address: 384 Woods Hole Road City: Woods Hole State_or_Province: MA Postal_Code: 02543 Contact_Voice_Telephone: 508-548-8700 Contact_Facsimile_Telephone: 508-457-2310 Contact_Electronic_Mail_Address: mkratzmann@contractor.usgs.gov Process_Step: Process_Description: A quality control assessment of Digital Raster Graphic (DRG) data for Northern California and Central California was completed. DRG shorelines were included due to the lack of T-sheet data for the 1940s-1970s time period in NorCal and CenCal. No DRG shorelines are included in the SoCal dataset. DRG shorelines were edited to meet project standards (e.g., digitized headlands were not included in the dataset). These data are from the original USGS report for California shoreline change (USGS Open-File Report 2006-1219 and USGS Open-File Report 2006-1251). Process_Date: 2014 Process_Step: Process_Description: An extensive quality control assessment was conducted for all historical shoreline data to determine which of the originally published shorelines (USGS OFR 2006-1251) would be retained and which areas of California would be supplemented with the newly acquired NOAA T-sheet data. The most accurate shoreline for any given area was included in the dataset resulting in a comprehensive collection of historical shorelines from both originally compiled data (USGS OFR 2006-1251) and T-sheet derived data from NOAA. The source information is included in the attributes of the shorelines file for each subregion of California. Process_Date: 2016 Process_Step: Process_Description: The following information applies to the 2009/2010/2011 shoreline extracted from lidar data. The reference line that was used for the first National Assessments shoreline was used for this work (except for a couple of areas where there were gaps in the reference line which were filled). The reference line is made of straight segments and is roughly coast-following with points every 20 meters. At each point a profile line (or transect) is defined that is perpendicular to the reference line. A program written by Amy Farris using Matlab version 2012b loads the cloud of (x,y,z) lidar points and finds all the data points within 2 meters of each profile line. The shoreline was extrapolated from data on each of these profiles. The Matlab program described by Stockdon et al. (2002) was further developed by Laura Fauver, Jeff List and Kathy Weber at USGS. It was run on the profile data using Matlab version 2012b. This code works with one profile at a time. The code identified points located on the foreshore and fit a linear regression through them. The slope of the regression is an estimate of the slope of the foreshore. The intersection of the regression line with Mean High Water (MHW) is the calculated shoreline position. If the MHW elevation was obscured by water points, or if a data gap was present at MHW, the linear regression was simply extrapolated to the MHW elevation. The MHW values used for the three regions of California are: Northern California: Oregon/California border to Cape Mendocino 1.81 meters, Central California: Cape Mendocino to Point Buchon 1.46 meters, and Southern California: Point Buchon to U.S./Mexico Border 1.33 meters (Weber et al., 2005 and Hapke et al., 2006). The shoreline code has a graphical user interface (GUI) which plots all the data for a given profile, indicates which points were determined to be on the foreshore, plots the regression line and the calculated shoreline position. The information was visually checked and then the solution was either accepted or rejected. This manual verification process was repeated for each profile. Each lidar shoreline point has an error associated with it. This error has three components: the error due to the linear regression, the error associated with the lidar data collection system, and the error due to extrapolation (if the shoreline point was determined by extrapolation). The error due to the linear regression is simply the 95% confidence interval about the regression estimate. Sallenger et al. (2003) determined that the vertical accuracy of NASA's Airborne Topographic Mapper lidar system is about 15 centimeters. This vertical error is converted to a horizontal error using the beach slope as determined by the linear regression. The final part of the total shoreline error is the error due to extrapolation. If the shoreline point was determined by extrapolation, this error term is calculated as the amount of uncertainty in horizontal shoreline position due to the variability of the beach slope between the last point on the linear regression and the MHW elevation. These three error terms are then added in quadrature, yielding a total error for each shoreline point. Stockdon, H.F., Sallenger, A.H., List, J.H., and Holman, R.A., 2002. Estimation of Shoreline Position and Change using Airborne Topographic Lidar Data: Journal of Coastal Research, v.18, n.3, pp.502-513. Sallenger, A.H., Krabill, W., Swift, R., Brock, J., List, J., Hansen, M., Holman, R. A., Manizade, S., Sonntag, J., Meredith, A., Morgan, K., Yunkel, J.K., Frederick, E., and Stockdon, H., 2003. Evaluation of airborne scanning lidar for coastal change applications: Journal of Coastal Research, v. 19, pp. 125-133. After the shoreline code was run, the resultant shoreline was fed into another GUI for further quality checking. This GUI created a map view plot of the profile data color-coded by z values with a color jump at z = MHW so the approximate location of MHW is easily visible. The shoreline solutions were added to this plot. The shoreline data were visually scanned to look for incorrect solutions. For example the shoreline point was occasionally on the back of a barrier island or on a groin. These solutions were flagged and later removed. Small gaps on straight beaches were identified and later filled using linear interpolation but gaps at inlets or large gaps on curved beaches were not interpolated over. A visual quality check using imagery was conducted at a later stage. This datum-based shoreline is often used in conjunction with proxy-based shoreline positions. There is a recognized offset between datum-based and proxy-based shorelines, therefore the proxy-datum bias as defined by Ruggiero and List (2009) was calculated for these shorelines. The formula for the bias is based on an equation for wave run-up which depends on beach slope and the recent wave climate (specifically, wavelength and wave height). The beach slope was calculated by the shoreline code (described in a previous process step). It was averaged alongshore in 1-kilometer non-overlapping blocks. The wave climate was estimated from averages of historical data. Historical wave lengths were obtained from offshore buoys. The buoy data were downloaded from the National Buoy Data Center (https://www.ndbc.noaa.gov/). Buoys were chosen that had at least 10 years of data in at least 100 meters of water. Historical wave heights were obtained from wave information studies (WIS) stations (http://wis.usace.army.mil/). At least 10 years of data were averaged. The formula for the proxy-datum bias also needs MHW and Mean Higher High Water, which were taken from the OFR mentioned in a previous Process Step (USGS OFR 2005-1027). Ruggiero, P., and List, J.H., 2009. Improving Accuracy and Statistical Reliability of Shoreline Position and Change Rate Estimates: Journal of Coastal Research v.25, n.5, pp. 1069-1081. The output file from the shoreline code, the map-view checker and the bias code were merged and saved as an American Standard Code for Information Interchange (ASCII) text file to be loaded by DSAS. Source_Used_Citation_Abbreviation: 2009-2011 lidar Process_Date: 2013 Source_Produced_Citation_Abbreviation: ASCII text file Process_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Amy Farris Contact_Address: Address_Type: Mailing and Physical Address: 384 Woods Hole Road City: Woods Hole State_or_Province: MA Postal_Code: 02543 Contact_Voice_Telephone: 508-548-8700 x2344 Contact_Facsimile_Telephone: 508-457-2310 Contact_Electronic_Mail_Address: afarris@usgs.gov Process_Step: Process_Description: The following information applies to the 2009/2010/2011 shoreline extracted from lidar data. The ASCII file was converted into a calibrated route shapefile for use in ArcGIS by using a Python script. The script generates a point shapefile, converts it to a polyline-M file, saves the uncertainty information in an accessory dBase (.dbf) file and finally generates a calibrated route for the newly-created polyline-M file. Calibration is based on the unique and sequential profile ID value provided with the point data and stored as the M-value. This value is also stored as an attribute in the uncertainty .dbf file and is used as the common field linking the two files. The lidar data were collected in projected coordinates (WGS 84 UTM zone 10N). During the rate calculation process DSAS uses linear referencing to retrieve the uncertainty values stored in the associated table. For a detailed explanation of the method used to convert the lidar shoreline to a route, please refer to the DSAS user guide: Himmelstoss, E.A., Henderson, R.E., Kratzmann, M.G., and Farris, A.S., 2018, Digital Shoreline Analysis System (DSAS) version 5.0 user guide: U.S. Geological Survey Open-File Report 2018–1179, 110 p., https://doi.org/10.3133/ofr20181179 Source_Used_Citation_Abbreviation: ASCII text file from 2009-2011 lidar Process_Date: 2014 Source_Produced_Citation_Abbreviation: calibrated route shapefile Source_Produced_Citation_Abbreviation: accessory dBase (.dbf) file Process_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Emily Himmelstoss Contact_Address: Address_Type: Mailing and Physical Address: 384 Woods Hole Road City: Woods Hole State_or_Province: MA Postal_Code: 02543 Contact_Voice_Telephone: 508-548-8700 x2262 Contact_Facsimile_Telephone: 508-457-2310 Contact_Electronic_Mail_Address: ehimmelstoss@usgs.gov Process_Step: Process_Description: The 2009/2010/2011 lidar shoreline shapefile was then visually checked against imagery contained in Esri's World_Imagery GIS server to make sure the lidar shoreline was not interpolated through a headland or structure, for example. Attribute fields were added (based on DSAS requirements) to the attribute table and those fields were populated with the relevant information. Process_Date: 2014 Process_Step: Process_Description: The 2016 USGS Lidar DEM: West Coast El Niño (WA, OR, CA) was downloaded through NOAA's Data Access Viewer. The DEM was then imported into Esri ArcMap v10.6. The operational MHW elevation is defined as the average of the mean high tides of local tidal gauges observed over the National Tidal Datum Epoch (Weber et al., 2005). The operational MHW elevation in each analysis region (Northern, Central, and Southern California) maintained consistency with the MHW elevations defined by the National Assessment of Shoreline Change (Hapke et al., 2006). The MHW values used for the three regions of California are: Northern California: Oregon/California border to Cape Mendocino 1.81 meters, Central California: Cape Mendocino to Point Buchon 1.46 meters, and Southern California: Point Buchon to U.S./Mexico Border 1.33 meters (Weber et al., 2005 and Hapke et al., 2006). The operational MHW line was extracted from the DEM using the smoothed contour method (Farris et al., 2018) using the contour tool: Esri ArcToolbox v10.6 > 3D Analyst > Raster Surface > Contour. Tool Settings: Contour Interval= 50, Base Contour= Operational MHW elevation, Z factor= default. Next, the contour line was smoothed using ArcToolbox v10.6 > Contour Cartography Tools > Generalization > Smooth Line. The smoothing algorithm was set to PAEK, the smoothing tolerance was set to 30 meters, and all other settings within the tool were left as default. A basemap of satellite imagery was added to the ArcMap v10.6 map document, by selecting the add data icon > basemap > imagery. The smoothed contour line was then quality controlled to remove artifacts, as well as remove any contour tool interpretation of human-made infrastructure (such as jetties, piers, and sea walls). The attribute table of the shapefile was formatted according to the requirements of the DSAS version 5.0 user guide (Himmelstoss et al., 2018). Uncertainty: The uncertainty associated with each lidar-derived shoreline is comprised of the DEM vertical and horizontal uncertainty found in the metadata document of the DEM, accessible through the NOAA Data Access Viewer. It is assumed that uncertainty associated with the extraction of a MHW line from a DEM is negligible (Ruggiero et al., 2003). Using uncertainty values reported in NOAA metadata, the DEM vertical uncertainty was converted to horizontal uncertainty using the slope of the beach at the operational MHW line contour. To do this, slope maps were created from the DEMs within ArcMap v10.6 using ArcToolbox v10.6 > 3D Analyst > Raster Surface > Slope. The input raster was the 2016 USGS Lidar DEM: West Coast El Niño (WA, OR, CA). The MHW lines were converted to 50m-spaced points using XTools PRO > Feature Conversions > Convert Features to Points, in which the input feature is the final operational MHW contour line that was generated, and all of the tool parameters are left as default. The slope value of the DEM was extracted at each point, using ArcToolbox v10.6 > 3D Analyst > Functional Surface > Add Surface Information, in which the input feature class is the previously generated point file, the input surface is the previously generated slope map, ‘Z’ is selected, and all other tool parameters are left as default. The shoreline uncertainty was calculated for each region by using the point slope values to convert the vertical uncertainty of the DEM to a horizontal uncertainty. This was done using the formula 0.20/Tan([Z]*3.14159/180), in which Z is the slope at each point. The resulting values (the vertical uncertainty at each shoreline point, now in the format of horizontal uncertainty) were summed in quadrature with the original horizontal uncertainty to calculate a final uncertainty value associated with each shoreline. These uncertainty values were stored in the attribute tables of the shapefiles in meters. Citations: Barnard, P.L., Smith, S.A., and Foxgrover, A.C., 2020, California shorelines and shoreline change data, 1998-2016: U.S. Geological Survey data release, https://doi.org/10.5066/P91QSGXF Farris, A.S., Weber, K.M., Doran, K.S., and List, J.H., 2018. Comparing methods used by the U.S. Geological Survey Coastal and Marine Geology Program for deriving shoreline position from lidar data: U.S. Geological Survey Open-File Report 2018–1121, 13 p., https://doi.org/10.3133/ofr20181121 Hapke, C.J., Reid, D., Richmond, B.M., Ruggiero, P., and List, J., 2006. National assessment of shoreline change: Part 3: Historical shoreline changes and associated coastal land loss along the sandy shorelines of the California coast: U.S. Geological Survey Open-file Report 2006-1219, 72 p., https://pubs.usgs.gov/of/2006/1219/ Himmelstoss, E.A., Henderson, R.E., Kratzmann, M.G., and Farris, A.S., 2018. Digital Shoreline Analysis System (DSAS) version 5.0 user guide: U.S. Geological Survey Open-File Report 2018–1179, 110 p., https://doi.org/10.3133/ofr20181179 Ruggiero, P., Kaminsky, G., and Gelfenbaum, G., 2003. Linking Proxy-Based and Datum-Based Shorelines on a High-Energy Coastline: Implications for Shoreline Change Analyses. Journal of Coastal Research 38: 57-82. Weber, K. M., List, J. H., and Morgan, K. L. M., 2005. An Operational Mean High Water Datum for Determination of Shoreline Position from Topographic Lidar Data. U.S. Geological Survey Open-File Report 2005-1027, https://pubs.usgs.gov/of/2005/1027/index.html Source_Used_Citation_Abbreviation: 2016 lidar Process_Date: 2017 Source_Produced_Citation_Abbreviation: Shoreline derived from 2016 lidar Process_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Schuyler Smith Contact_Address: Address_Type: Mailing and Physical Address: 2885 Mission St City: Santa Cruz State_or_Province: CA Postal_Code: 95060 Contact_Voice_Telephone: 831-460-7588 Contact_Facsimile_Telephone: n/a Contact_Electronic_Mail_Address: schuylersmith@contractor.usgs.gov Process_Step: Process_Description: The 2015 USACE National Coastal Mapping Program (NCMP) Topobathy Lidar Digital Elevation Model (DEM): California was downloaded through NOAA's Data Access Viewer. The DEM was then imported into ArcGIS ArcMap v10.6. The operational MHW elevation was defined as the average of the mean high tides of local tidal gauges observed over the National Tidal Datum Epoch (Weber et al., 2005). The operational MHW elevation in each analysis region (Northern, Central, and Southern California) maintained consistency with the MHW elevations defined by the National Assessment of Shoreline Change (Hapke et al., 2006). The MHW values used for the three regions of California are: Northern California: Oregon/California border to Cape Mendocino 1.81 meters, Central California: Cape Mendocino to Point Buchon 1.46 meters, and Southern California: Point Buchon to U.S./Mexico Border 1.33 meters (Weber et al., 2005 and Hapke et al., 2006). The operational MHW line was extracted from the DEM using the smoothed contour method (Farris et al. 2018) using the contour tool: Esri ArcToolbox v10.6 > 3D Analyst > Raster Surface > Contour. Tool Settings: Contour Interval= 50, Base Contour= Operational MHW elevation, Z factor= default. Next, the contour line was smoothed using: ArcToolbox v10.6 > Contour Cartography Tools > Generalization > Smooth Line. The smoothing algorithm was set to “PAEK”, the smoothing tolerance was set to 30 meters, and all other settings within the tool were left as default. A basemap of satellite imagery was added to the ArcMap v10.6 map document, by selecting the add data icon > basemap > imagery. The smoothed contour line was then quality controlled to remove artifacts, as well as remove any contour tool interpretation of human-made infrastructure (such as jetties, piers, and sea walls). The attribute table of the shapefile was formatted according to the requirements of the Digital Shoreline Analysis System (DSAS) version 5.0 user guide (Himmelstoss et al., 2018). Uncertainty: The uncertainty associated with each lidar-derived shoreline is comprised of the DEM vertical and horizontal uncertainty found on the metadata document of the DEM, accessible through the NOAA Data Access Viewer. It is assumed that uncertainty associated with the extraction of a MHW line from a DEM is negligible (Ruggiero et al., 2003). Using uncertainty values reported in NOAA metadata, the DEM vertical uncertainty was converted to horizontal uncertainty using the slope of the beach at the operational MHW line contour. To do this, slope maps were created from the DEMs within ArcMap v10.6 using ArcToolbox v10.6 > 3D Analyst > Raster Surface > Slope. The input raster was the 2015 USACE NCMP Topobathy Lidar Digital Elevation Model. The MHW lines were converted to 50 meter-spaced points using XTools PRO > Feature Conversions > Convert Features to Points, in which the input feature is the final operational MHW contour line that was generated, and all of the tool parameters are left as default. The slope value of the DEM was extracted at each point, using ArcToolbox v10.6 > 3D Analyst > Functional Surface > Add Surface Information, in which the input feature class is the previously generated point file, the input surface is the previously generated slope map, ‘Z’ is selected, and all other tool parameters are left as default. The shoreline uncertainty was calculated for each region by using the point slope values to convert the vertical uncertainty of the DEM to a horizontal uncertainty. This was done using the formula 0.20/Tan([Z]*3.14159/180), in which Z is the slope at each point. The resulting values (the vertical uncertainty at each shoreline point, now in the format of horizontal uncertainty) were summed in quadrature with the original horizontal uncertainty to calculate a final uncertainty value associated with each shoreline. These uncertainty values were stored in the attribute tables of the shapefiles in meters. Citations: Barnard, P.L., Smith, S.A., and Foxgrover, A.C., 2020, California shorelines and shoreline change data, 1998-2016: U.S. Geological Survey data release, https://doi.org/10.5066/P91QSGXF Farris, A.S., Weber, K.M., Doran, K.S., and List, J.H., 2018. Comparing methods used by the U.S. Geological Survey Coastal and Marine Geology Program for deriving shoreline position from lidar data: U.S. Geological Survey Open-File Report 2018–1121, 13 p., https://doi.org/10.3133/ofr20181121 Hapke, C.J., Reid, D., Richmond, B.M., Ruggiero, P., and List, J., 2006. National assessment of shoreline change: Part 3: Historical shoreline changes and associated coastal land loss along the sandy shorelines of the California coast: U.S. Geological Survey Open-file Report 2006-1219, 72 p., https://pubs.usgs.gov/of/2006/1219/ Himmelstoss, E.A., Henderson, R.E., Kratzmann, M.G., and Farris, A.S., 2018. Digital Shoreline Analysis System (DSAS) version 5.0 user guide: U.S. Geological Survey Open-File Report 2018–1179, 110 p., https://doi.org/10.3133/ofr20181179 Ruggiero, P., Kaminsky, G., and Gelfenbaum, G., 2003. Linking Proxy-Based and Datum-Based Shorelines on a High-Energy Coastline: Implications for Shoreline Change Analyses. Journal of Coastal Research 38: 57-82. Weber, K. M., List, J. H., and Morgan, K. L. M., 2005. An Operational Mean High Water Datum for Determination of Shoreline Position from Topographic Lidar Data. U.S. Geological Survey Open-File Report 2005-1027, https://pubs.usgs.gov/of/2005/1027/index.html Source_Used_Citation_Abbreviation: 2015 lidar Process_Date: 2018 Source_Produced_Citation_Abbreviation: Shoreline derived from 2015 lidar Process_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Schuyler Smith Contact_Address: Address_Type: Mailing and Physical Address: 2885 Mission St City: Santa Cruz State_or_Province: CA Postal_Code: 95060 Contact_Voice_Telephone: 831-460-7588 Contact_Facsimile_Telephone: n/a Contact_Electronic_Mail_Address: schuylersmith@contractor.usgs.gov Process_Step: Process_Description: The Southern California Coastal Response to the 2015-16 El Niño: 2015-10-06 Survey Digital Elevation Model (DEM) was downloaded through the U.C. San Diego Research Data Curation Program. The DEM was then imported into ArcGIS ArcMap v10.6. The operational MHW elevation is defined as the average of the mean high tides of local tidal gauges observed over the National Tidal Datum Epoch (Weber et al., 2005). The operational MHW elevation in each analysis region (Northern, Central, and Southern California) maintained consistency with the MHW elevations defined by the National Assessment of Shoreline Change (Hapke et al., 2006). The MHW values used for the three regions of California are: Northern California: Oregon/California border to Cape Mendocino 1.81 meters, Central California: Cape Mendocino to Point Buchon 1.46 meters, and Southern California: Point Buchon to U.S./Mexico Border 1.33 meters (Weber et al., 2005 and Hapke et al., 2006). The operational MHW line was extracted from the DEM using the smoothed contour method (Farris et al., 2018) using the contour tool: Esri ArcToolbox v10.6 > 3D Analyst > Raster Surface > Contour. Tool Settings: Contour Interval= 50, Base Contour= Operational MHW elevation, Z factor= default. Next, the contour line was smoothed using: ArcToolbox v10.6 > Contour Cartography Tools > Generalization > Smooth Line. The smoothing algorithm was set to “PAEK”, the smoothing tolerance was set to 30 meters, and all other settings within the tool were left as default. A basemap of satellite imagery was added to the ArcMap v10.6 map document, by selecting the add data icon > basemap > imagery. The smoothed contour line was then quality controlled to remove artifacts, as well as remove any contour tool interpretation of human-made infrastructure (such as jetties, piers, and sea walls). The attribute table of the shapefile was formatted according to the requirements of the Digital Shoreline Analysis System (DSAS) version 5.0 user guide (Himmelstoss et al., 2018). Uncertainty: The uncertainty associated with each lidar-derived shoreline is comprised of the DEM vertical and horizontal uncertainty found on the metadata document of the DEM, accessible through the NOAA Data Access Viewer. It is assumed that uncertainty associated with the extraction of a MHW line from a DEM is negligible (Ruggiero et al., 2003). Using uncertainty values reported in NOAA metadata, the DEM vertical uncertainty was converted to horizontal uncertainty using the slope of the beach at the operational MHW line contour. To do this, slope maps were created from the DEMs within ArcMap v10.6 using ArcToolbox v10.6 > 3D Analyst > Raster Surface > Slope. The input raster was the Southern California Coastal Response to the 2015-16 El Niño: 2015-10-06 Survey Digital Elevation Model. The MHW lines were converted to 50 meter-spaced points using XTools PRO > Feature Conversions > Convert Features to Points, in which the input feature is the final operational MHW contour line that was generated, and all of the tool parameters are left as default. The slope value of the DEM was extracted at each point, using ArcToolbox v. 10.6 > 3D Analyst > Functional Surface > Add Surface Information, in which the input feature class is the previously generated point file, the input surface is the previously generated slope map, ‘Z’ is selected, and all other tool parameters are left as default. The shoreline uncertainty was calculated for each region by using the point slope values to convert the vertical uncertainty of the DEM to a horizontal uncertainty. This was done using the formula 0.20/Tan([Z]*3.14159/180), in which Z is the slope at each point. The resulting values (the vertical uncertainty at each shoreline point, now in the format of horizontal uncertainty) were summed in quadrature with the original horizontal uncertainty to calculate a final uncertainty value associated with each shoreline. These uncertainty values were stored in the attribute tables of the shapefiles in meters. Citations: Barnard, P.L., Smith, S.A., and Foxgrover, A.C., 2020, California shorelines and shoreline change data, 1998-2016: U.S. Geological Survey data release, https://doi.org/10.5066/P91QSGXF Farris, A.S., Weber, K.M., Doran, K.S., and List, J.H., 2018. Comparing methods used by the U.S. Geological Survey Coastal and Marine Geology Program for deriving shoreline position from lidar data: U.S. Geological Survey Open-File Report 2018–1121, 13 p., https://doi.org/10.3133/ofr20181121 Hapke, C.J., Reid, D., Richmond, B.M., Ruggiero, P., and List, J., 2006. National assessment of shoreline change: Part 3: Historical shoreline changes and associated coastal land loss along the sandy shorelines of the California coast: U.S. Geological Survey Open-file Report 2006-1219, 72 p., https://pubs.usgs.gov/of/2006/1219/ Himmelstoss, E.A., Henderson, R.E., Kratzmann, M.G., and Farris, A.S., 2018. Digital Shoreline Analysis System (DSAS) version 5.0 user guide: U.S. Geological Survey Open-File Report 2018–1179, 110 p., https://doi.org/10.3133/ofr20181179 Ruggiero, P., Kaminsky, G., and Gelfenbaum, G., 2003. Linking Proxy-Based and Datum-Based Shorelines on a High-Energy Coastline: Implications for Shoreline Change Analyses. Journal of Coastal Research 38: 57-82. Weber, K. M., List, J. H., and Morgan, K. L. M., 2005. An Operational Mean High Water Datum for Determination of Shoreline Position from Topographic Lidar Data. U.S. Geological Survey Open-File Report 2005-1027, https://pubs.usgs.gov/of/2005/1027/index.html Source_Used_Citation_Abbreviation: 2015 lidar UCSD Process_Date: 2019 Source_Produced_Citation_Abbreviation: Shoreline derived from 2015 lidar UCSD Process_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey Contact_Person: Schuyler Smith Contact_Address: Address_Type: Mailing and Physical Address: 2885 Mission St City: Santa Cruz State_or_Province: CA Postal_Code: 95060 Contact_Voice_Telephone: 831-460-7588 Contact_Facsimile_Telephone: n/a Contact_Electronic_Mail_Address: schuylersmith@contractor.usgs.gov Process_Step: Process_Description: The 2015 and 2016 lidar shorelines contained a very large number of vertices that caused DSAS v5.0 to run out of memory before completing casting transects. An experiment was conducted to test whether using a tool to reduce the number of vertices altered the position of the line beyond the lidar uncertainty value. The tool chosen was Simplify Line: Cartography Tools > Generalization > Simplify Line. Simplification algorithm= point remove, simplification tolerance= 0.25. DSAS (Net Shoreline Movement, NSM) was run on a sample area of the original 2016 shoreline and the reduced vertex 2016 shoreline. The difference in values between the original shoreline and the simplified shoreline clearly did not exceed the uncertainty value and therefore was deemed a reasonable solution to the problem. DSAS was able to cast transects successfully. Douglas, D. and Peucker, T., 1973. Algorithms for the reduction of the number of points required to represent a digitized line or its caricature, The Canadian Cartographer 10(2), 112–122. Process_Date: 2019 Process_Step: Process_Description: Historical shorelines were merged in Esri's ArcToolbox v10.6, Data Management Tools > General > Merge. The merged file was projected in ArcToolbox v10.6 > Data Management Tools > Projections and Transformations > Project. Parameters: input coordinate system = geographic (NAD 83); output coordinate system = UTM zone 10N (NorCal and CenCal) or UTM zone 11N (SoCal) (WGS 84); geographic transformation = NAD_1983_To_WGS_1984_1. Process_Date: 2019 Process_Step: Process_Description: Historical shorelines were merged with the lidar shorelines in ArcToolbox v10.6 > Data Management Tools > General > Merge to produce a single shoreline file for each region. The final shoreline dataset was coded with attribute fields (DATE_, Uncertainty (Uncy), Source, Source_b, Year_, Default_D, Location, DSAS_type). These fields are required by DSAS, which was used to calculate shoreline change rates. Process_Date: 2019 Process_Step: Process_Description: The shorelines file and the uncertainty table (.dbf) were imported into a personal geodatabase in ArcCatalog v10.7 by right-clicking on the geodatabase > Import (feature class for shoreline file and table for uncertainty table) for use with the DSAS v5.0 software to perform rate calculations. Process_Date: 2020 Process_Step: Process_Description: The shoreline feature class was exported from the personal geodatabase back to a shapefile in ArcCatalog v10.7 by right-clicking on the shoreline file > Export > To Shapefile (single) for publication purposes. Process_Date: 2020 Process_Step: Process_Description: The data were projected in ArcToolbox v10.7 > Data Management Tools > Projections and Transformations > Project. Parameters: input projection = UTM zone 10N WGS84 (NorCal and CenCal) or UTM zone 11N WGS84 (SoCal); output projection = geographic coordinates (WGS84); transformation = none. Process_Date: 2020 Spatial_Data_Organization_Information: Direct_Spatial_Reference_Method: Vector Point_and_Vector_Object_Information: SDTS_Terms_Description: SDTS_Point_and_Vector_Object_Type: String Point_and_Vector_Object_Count: 1112 Spatial_Reference_Information: Horizontal_Coordinate_System_Definition: Geographic: Latitude_Resolution: 0.0197395052 Longitude_Resolution: 0.0264490611 Geographic_Coordinate_Units: Decimal seconds Geodetic_Model: Horizontal_Datum_Name: WGS_1984 Ellipsoid_Name: WGS_84 Semi-major_Axis: 6378137.0 Denominator_of_Flattening_Ratio: 298.257223563 Entity_and_Attribute_Information: Detailed_Description: Entity_Type: Entity_Type_Label: Norcal_shorelines Entity_Type_Definition: Shorelines for Northern California (NorCal) used in shoreline change analysis. Entity_Type_Definition_Source: U.S. Geological Survey Attribute: Attribute_Label: FID Attribute_Definition: Internal feature number. Attribute_Definition_Source: Esri Attribute_Domain_Values: Unrepresentable_Domain: Sequential unique whole numbers that are automatically generated. Attribute: Attribute_Label: Shape Attribute_Definition: Feature geometry. Attribute_Definition_Source: Esri Attribute_Domain_Values: Unrepresentable_Domain: Coordinates defining the features. Attribute: Attribute_Label: Route_ID Attribute_Definition: Route identification value assigned to individual lidar shoreline line segments. A unique cross-shore profile identification value is stored at each vertex of the lidar route and serves as a common attribute to the shoreline uncertainty table. Attribute_Definition_Source: U.S. Geological Survey Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: 0 Enumerated_Domain_Value_Definition: Short integer field where zeros are "no data" and automatically filled in for the remaining shoreline polylines not derived from lidar. Enumerated_Domain_Value_Definition_Source: U.S. Geological Survey Attribute: Attribute_Label: DATE_ Attribute_Definition: Date of shoreline position; date of survey as indicated on source material. A default date of 07/01 was assigned to shorelines where only the year was known (month and day unknown). Using July, the mid-point month of the calendar year, minimizes the potential offset to the actual shoreline date by a maximum of six months. Attribute_Definition_Source: U.S. Geological Survey Attribute_Domain_Values: Unrepresentable_Domain: Date of the shoreline in mm/dd/yyyy Attribute: Attribute_Label: Year_ Attribute_Definition: Four digit year of shoreline Attribute_Definition_Source: U.S. Geological Survey Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1854 Range_Domain_Maximum: 2016 Attribute: Attribute_Label: Uncy Attribute_Definition: Estimate of shoreline position uncertainty. Actual shoreline position is within the range of this value (plus or minus, meters). The historic shoreline uncertainty values incorporate measurement uncertainties associated with mapping methods and materials for historical shorelines, the geographic registration of shoreline position, and shoreline digitizing. The lidar shoreline position uncertainty values for the 2009/2010/2011 lidar are stored in the associated _uncertainty.dbf file. Uncertainty for the other lidar shorelines is described in the process steps of this metadata file. Attribute_Definition_Source: U.S. Geological Survey Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0.74 Range_Domain_Maximum: 15 Attribute: Attribute_Label: Source Attribute_Definition: Agency that provided shoreline feature or the data source used to digitize shoreline feature. Attribute_Definition_Source: U.S. Geological Survey Attribute_Domain_Values: Unrepresentable_Domain: Character string of length 25 Attribute: Attribute_Label: Source_b Attribute_Definition: Type of data used to create shoreline. Attribute_Definition_Source: U.S. Geological Survey Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: lidar Enumerated_Domain_Value_Definition: Light detection and ranging (lidar). Enumerated_Domain_Value_Definition_Source: U.S. Geological Survey Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: T or TP with number Enumerated_Domain_Value_Definition: NOAA/NOS topographic survey sheet (T- or TP-sheet) with associated registry number. Enumerated_Domain_Value_Definition_Source: U.S. Geological Survey Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: DRG Enumerated_Domain_Value_Definition: Digital Raster Graphic (DRG) with associated USGS quadrangle name. Enumerated_Domain_Value_Definition_Source: U.S. Geological Survey Attribute: Attribute_Label: Default_D Attribute_Definition: Differentiates between shorelines that have known month and day attributes and those that use the default value of 07/01 when only the year is known. Attribute_Definition_Source: U.S. Geological Survey Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: 0 Enumerated_Domain_Value_Definition: Shoreline month and day are known. Enumerated_Domain_Value_Definition_Source: U.S. Geological Survey Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: 1 Enumerated_Domain_Value_Definition: Shoreline month and day are unknown and default value of 07/01 was used. Enumerated_Domain_Value_Definition_Source: U.S. Geological Survey Attribute: Attribute_Label: DSAS_type Attribute_Definition: Shoreline type field used to specify the datum to which the shoreline is referenced. It is a required field when proxy-based and datum-based shorelines are combined to compute rates in DSAS. Attribute_Definition_Source: U.S. Geological Survey Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: MHW Enumerated_Domain_Value_Definition: Mean High Water (datum-based shoreline). Enumerated_Domain_Value_Definition_Source: U.S. Geological Survey Attribute_Domain_Values: Enumerated_Domain: Enumerated_Domain_Value: HWL Enumerated_Domain_Value_Definition: High Water Line (proxy-based shoreline). Enumerated_Domain_Value_Definition_Source: U.S. Geological Survey Attribute: Attribute_Label: Shape_Leng Attribute_Definition: Length of shoreline in meter units (UTM zone 10N WGS84). Attribute_Definition_Source: U.S. Geological Survey, Woods Hole Science Center Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 12.904541 Range_Domain_Maximum: 677283.583384 Overview_Description: Entity_and_Attribute_Overview: The entity and attribute information provided here describes the tabular data associated with the dataset. Please review the individual attribute descriptions for detailed information. Entity_and_Attribute_Detail_Citation: U.S. Geological Survey Distribution_Information: Distributor: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey - ScienceBase Contact_Address: Address_Type: mailing and physical address Address: Federal Center, Building 810, MS 302 City: Denver State_or_Province: CO Postal_Code: 80225 Country: USA Contact_Voice_Telephone: 1-888-275-8747 Contact_Electronic_Mail_Address: sciencebase@usgs.gov Resource_Description: The dataset contains polyline shorelines (SHP and other shapefile components), browse graphic, and the FGDC CSDGM metadata. 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 for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. Although these data have been processed successfully on a computer system at the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. The USGS or the U.S. Government shall not be held liable for improper or incorrect use of the data described and/or contained herein. Standard_Order_Process: Digital_Form: Digital_Transfer_Information: Format_Name: Shapefile Format_Version_Number: ArcGIS 10.7 Format_Specification: Esri polyline shapefile Format_Information_Content: These files (.cpg, .dbf, .prj, .sbn, .sbx, .shp, .html, and .shx) are a collection of files with a common filename prefix and must be downloaded and stored in the same directory. Together they are the components of the shapefile and include FGDC CSDGM-compliant metadata in HTML format. Transfer_Size: 1.97 Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: https://doi.org/10.5066/P94J0K7Z Network_Resource_Name: https://www.sciencebase.gov/catalog/file/get/64add938d34e70357a293270 Network_Resource_Name: https://www.sciencebase.gov/catalog/item/64add938d34e70357a293270 Access_Instructions: The first link is to the USGS publication page, the second link downloads all the data on the landing page, and the third link is to the dataset landing page. Fees: None Technical_Prerequisites: These data are available in a polyline shapefile format. The user must have software to read and process the data components of a shapefile. Metadata_Reference_Information: Metadata_Date: 20240112 Metadata_Contact: Contact_Information: Contact_Person_Primary: Contact_Person: Meredith G. Kratzmann Contact_Organization: U.S. Geological Survey Contact_Address: Address_Type: mailing and physical address Address: 384 Woods Hole Road City: Woods Hole State_or_Province: MA Postal_Code: 02543-1598 Country: USA Contact_Voice_Telephone: 508-548-8700 Contact_Facsimile_Telephone: 508-457-2310 Contact_Electronic_Mail_Address: whsc_data_contact@usgs.gov Contact_Instructions: The metadata contact email address is a generic address in the event the person is no longer with USGS. Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata Metadata_Standard_Version: FGDC-STD-001-1998 Metadata_Time_Convention: local time