U.S. Geological Survey
20210929
Shorelines of the Florida panhandle (FLph) coastal region used in shoreline change analysis
1.0
vector digital data
data release
DOI:10.5066/P9J3CVN4
Woods Hole Coastal and Marine Science Center, Woods Hole, MA
U.S. Geological Survey, Coastal and Marine Hazards and Resources Program
https://doi.org/10.5066/P9J3CVN4
https://www.sciencebase.gov/catalog/item/614a7c3bd34e0df5fb9756d8
Meredith G. Kratzmann
Amy S. Farris
Kathy M. Weber
Rachel E. Henderson
Emily A. Himmelstoss
2021
USGS National Shoreline Change: A GIS compilation of Updated Vector Shorelines (1800s - 2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts
1.0
vector digital data
data release
DOI:10.5066/P9J3CVN4
Reston, VA
U.S. Geological Survey
suggested citation: Kratzmann, M.G., Farris, A.S., Weber, K.M., Henderson, R.E., and Himmelstoss, E.A., 2021, USGS National Shoreline Change: A GIS compilation of Updated Vector Shorelines (1800s - 2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts: U.S. Geological Survey data release, https://doi.org/10.5066/P9J3CVN4
https://doi.org/10.5066/P9J3CVN4
https://www.sciencebase.gov/catalog/item/612cf2a3d34e40dd9c08844b
During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The U.S. Geological Survey (USGS) Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion along the southeast US coastline and implications for vulnerability to future storms.
Shoreline positions were compiled prior to and following Hurricane Irma along the sandy shorelines of the Gulf of Mexico and Atlantic coasts of Florida and the coast of Georgia. Shoreline positions from the mid-1800s through 2018 were used to update the shoreline change rates for Florida and Georgia using the Digital Shoreline Analysis System (DSAS) software. The shoreline positions and updated shoreline change rates provide actionable information to homeowners, coastal communities, and managers of public and private properties to improve resiliency for long-term hazards.
Georgia (GA):
The Georgia dataset includes shorelines from 161 years ranging from 1855 to 2016. Shorelines were compiled from topographic survey sheets (T-sheets; National Oceanic and Atmospheric Administration (NOAA)) and lidar (USGS/NOAA/National Aeronautics and Space Administration (NASA), NOAA/U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP)/Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX)).
Florida east coast (FLec): border with GA to Key Biscayne
The FLec dataset includes shorelines from 166 years ranging from 1851 to 2017. Shorelines were compiled from topographic survey sheets (T-sheets; NOAA, NOAA/Florida Department of Environmental Protection (FLDEP)), aerial photographs (FLDEP/USGS), and lidar data (USGS/NASA, USACE/Federal Emergency Management Agency (FEMA), NOAA/USACE NCMP).
Florida west coast (FLwc): Anclote Key to Barefoot Beach
The FLwc dataset includes shorelines from 159 years ranging from 1858 to 2017. Shorelines were compiled from topographic survey sheets (T-sheets; NOAA, NOAA/FLDEP), aerial photographs (FLDEP/USGS), and lidar data (USGS/NASA, USACE/FEMA, NOAA/USACE NCMP).
Florida panhandle (FLph): Bald Point State Park to the Alabama border
The FLph dataset includes shorelines from 163 years ranging from 1855 to 2018. Shorelines were compiled from topographic survey sheets (T-sheets; NOAA, NOAA/FLDEP), aerial photographs (FLDEP), and lidar data (USGS/NASA, USACE/FEMA, NOAA/USACE NCMP).
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 and short-term shoreline change rates were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 5. 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.
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.
1855
2018
ground condition
None planned
-87.555300
-84.333249
30.397156
29.585579
ISO 19115 Topic Category
geoscientificInformation
oceans
environment
None
Baseline
Shoreline
Shoreline Change
Digital Shoreline Analysis System
DSAS
U.S. Geological Survey
USGS
Coastal and Marine Geology Program
CMGP
Woods Hole Coastal and Marine Science Center
WHCMSC
National Oceanic and Atmospheric Administration
NOAA
National Aeronautics and Space Administration
NASA
U.S. Army Corps of Engineers
USACE
Joint Airborne Lidar Bathymetry Technical Center of eXpertise
JALBTCX
Florida Department of Environmental Protection
FLDEP
Federal Emergency Management Agency
FEMA
Mean High Water
MHW
High Water Line
HWL
USGS thesaurus
geospatial datasets
coastal processes
USGS Metadata Identifier
USGS:614a7c3bd34e0df5fb9756d8
None
Atlantic Coast
Gulf Coast
United States
North America
Georgia
Florida
None
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.
U.S. Geological Survey
Meredith G. Kratzmann
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700
508-457-2310
mkratzmann@contractor.usgs.gov
https://www.sciencebase.gov/catalog/file/get/614a7c3bd34e0df5fb9756d8?name=BG_FLph_shorelines.jpg
Map view of data
jpg
Microsoft Windows 10 Enterprise; Esri ArcGIS 10.7.1
Meredith G. Kratzmann
2022
U.S. Geological Survey National Shoreline Change: Summary Statistics for Updated Vector Shorelines (1800s - 2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts
Data Report
1156
Reston, VA
U.S. Geological Survey
Data Report associated with this data release: Kratzmann, M.G., Farris, A.S., Weber, K.M., Henderson, R.E., and Himmelstoss, E.A., 2021, USGS national shoreline change-A GIS compilation of updated vector shorelines (1800s - 2010s) and associated shoreline change data for the Georgia and Florida Coasts: U.S. Geological Survey data release, https://doi.org/10.5066/P9J3CVN4.
https://doi.org/10.3133/dr1156
Emily A. Himmelstoss
Amy S. Farris
Rachel E. Henderson
Meredith G. Kratzmann
Ayhan Ergul
Ouya Zhang
Jessica L. Zichichi
2018
Digital Shoreline Analysis System (version 5): U.S. Geological Survey Software
software release
version 5
Reston, VA
U.S. Geological Survey
Current version of software at time of use was 5.1
https://doi.org/10.5066/P9VW42I0
https://code.usgs.gov/cch/dsas/
https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas
Emily A. Himmelstoss
Rachel E. Henderson
Meredith G. Kratzmann
Amy S. Farris
2018
Digital Shoreline Analysis System (DSAS) Version 5.0 User Guide
publication
Open-File Report
20181179
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20181179
https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas
Emily Himmelstoss
Meredith Kratzmann
E. Robert Thieler
2017
National Assessment of Shoreline Change: A GIS compilation of Updated Vector Shorelines and Associated Shoreline Change Data for the Southeast Atlantic Coast
Data release
doi:10.5066/F74X55X7
Reston, VA
U.S. Geological Survey
https://doi.org/10.5066/F74X55X7
Emily Himmelstoss
Meredith Kratzmann
E. Robert Thieler
2017
National Assessment of Shoreline Change: A GIS compilation of Updated Vector Shorelines and Associated Shoreline Change Data for the Gulf of Mexico Coast
Data release
doi:10.5066/F78P5XNK
Reston, VA
U.S. Geological Survey
https://doi.org/10.5066/F78P5XNK
Emily Himmelstoss
Meredith Kratzmann
E. Robert Thieler
2017
National assessment of shoreline change — Summary statistics for updated vector shorelines and associated shoreline change data for the Gulf of Mexico and Southeast Atlantic coasts
Open-File Report
2017-1015
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20171015
Robert A. Morton
Tara L. Miller
2005
National Assessment of Shoreline Change: Part 2 Historical Shoreline Changes and Associated Coastal Land Loss along the U.S. Southeast Atlantic Coast
Open-File Report
2005-1401
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20051401
Tara L. Miller
Robert A. Morton
Asbury H. Sallenger
2005
The National Assessment of Shoreline Change: A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for the U.S. Southeast Atlantic Coast
Open-File Report
2005-1326
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20051326
Robert A. Morton
Tara L. Miller
Laura J. Moore
2004
National Assessment of Shoreline Change: Part 1 Historical Shoreline Changes and Associated Coastal Land Loss along the U.S. Gulf of Mexico
Open-File Report
2004-1043
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20041043
Tara L. Miller
Robert A. Morton
Asbury H. Sallenger
Laura J. Moore
2004
The National Assessment of Shoreline Change: A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for the U.S. Gulf of Mexico
Open-File Report
2004-1089
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20041089
Peter Ruggiero
Jeffrey H. List
200909
Improving Accuracy and Statistical Reliability of Shoreline Position and Change Rate Estimates
publication
Journal of Coastal Research
vol. 255
n/a
Coastal Education and Research Foundation
pp. 1069-1081
https://doi.org/10.2112/08-1051.1
Amy S. Farris
Kathryn M. Weber
Kara S. Doran
Jeffrey H. List
2018
Comparing methods used by the U.S. Geological Survey Coastal and Marine Geology Program for deriving shoreline position from lidar data
Open-File Report
2018–1121
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20181121
National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS)
Unknown
Scanned National Ocean Service (NOS) Coastal Survey Maps (also known as Topographic Survey sheets, or T-sheets)
NOAA shoreline manuscripts (T-sheets)
n/a
Washington, D.C.
National Oceanic and Atmospheric Administration
https://shoreline.noaa.gov/data/datasheets/t-sheets.html
Kathryn M. Weber
Jeffrey H. List
Karen L.M. Morgan
2005
An operational mean high water datum for determination of shoreline position from topographic lidar data
Open-File Report
2005-1027
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20051027
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.
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.
This shoreline file is complete and contains all shoreline segments used to calculate shoreline change rates along sections of the Florida panhandle (FLph) coastal region where shoreline position data were available. These data adequately represented the shoreline position at the time of the survey. Remaining 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.
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. Georgia and Florida: Shorelines prior to 1960 (T-sheets) have an estimated positional uncertainty of plus or minus 10.8 meters. Shorelines from the 1960s-1980s (T-sheets) have an estimated positional uncertainty of plus or minus 5.1 meters. Shorelines from the 1950s-1970s (FLDEP, air photos) have an estimated positional uncertainty of plus or minus 3.2 meters. See below for average estimated uncertainty values for shorelines extracted from lidar. All lidar shorelines new to the FL/GA dataset have uncertainty recorded on a segment-by-segment basis in the attribute table (i.e., all except 1998/2001 and 1999 which are from data releases doi:10.5066/F74X55X7 and doi:10.5066/F78P5XNK, 2017). See the Uncy field in the shoreline attribute table for individual values.
GEORGIA (GA; average estimated positional uncertainty of lidar shorelines):
1999 = plus or minus 4.4 meters
2006 = plus or minus 3.2 meters
2010 = plus or minus 4.2 meters
2016 = plus or minus 5.5 meters
FLORIDA EAST COAST (FLec; average estimated positional uncertainty of lidar shorelines):
1999 = plus or minus 2.8 meters
2006 = plus or minus 1.9 meters
2009 = plus or minus 1.8 meters
2010 = plus or minus 2.7 meters
2016 = plus or minus 2.8 meters
2017 = plus or minus 2.9 meters
FLORIDA WEST COAST (FLwc; average estimated positional uncertainty of lidar shorelines):
1998 = plus or minus 1.7 meters
2010 = plus or minus 2.2 meters
2015 = plus or minus 2.0 meters
2017 = plus or minus 2.2 meters
FLORIDA PANHANDLE (FLph; average estimated positional uncertainty of lidar shorelines):
1998/2001 = plus or minus 1.4 meters
2010 = plus or minus 2.6 meters
2015 = plus or minus 1.7 meters
2016 = plus or minus 1.0 meters
2018 = plus or minus 2.7 meters
National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS)
Unknown
Scanned National Ocean Service (NOS) Coastal Survey Maps (also known as Topographic Survey sheets, or T-sheets)
https://shoreline.noaa.gov/data/datasheets/t-sheets.html
digital data
1851
1980
ground condition
T-sheet shorelines
T-sheets used for QA/QC of NOAA-digitized 1800s-1980s shorelines and/or used as data source to digitize shorelines.
National Oceanic and Atmospheric Administration (NOAA), U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA)
20000101
1998 Fall Gulf Coast NOAA/USGS/NASA Airborne LiDAR Assessment of Coastal Erosion (ALACE) Project for the US Coastline
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/48152
digital data
1998
1998
ground condition
1998 gulf coast lidar
Lidar data that were used to extract a shoreline.
National Oceanic and Atmospheric Administration (NOAA), U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA)
20000101
Fall 1999 East Coast NOAA/USGS/NASA Airborne LiDAR Assessment of Coastal Erosion (ALACE) Project for the US Coastline
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/48158
digital data
1999
1999
ground condition
1999 east coast lidar
Lidar data that were used to extract a shoreline.
U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA)
2009
2001 USGS/NASA Airborne Topographic Mapper (ATM) Lidar: Coastal Alabama, Florida, Louisiana, Mississippi, Texas
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/50098
digital data
2001
2001
ground condition
2001 gulf coast lidar
Lidar data that were used to extract a shoreline.
U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP)/Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX)
20061114
2006 US Army Corps of Engineers (USACE) East Coast Topo/Bathy Mapping Project for Florida, Georgia and South Carolina
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/50057
digital data
2006
2006
ground condition
2006 east coast lidar
Lidar data that were used to extract a shoreline.
U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP)/Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX)
2018
2009 USACE NCMP Topobathy Lidar: Florida Atlantic Coast
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/54218
digital data
2009
2009
ground condition
2009 FL Atlantic Coast lidar
Lidar data that were used to extract a shoreline.
U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP)/Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX)
2017
2010 US Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX) Southeast Lidar: Florida, Georgia, South Carolina, North Carolina
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/50093
digital data
2010
2010
ground condition
2010 Southeast coast lidar
Lidar data that were used to extract a shoreline.
U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP)/Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX)
2018
2010 USACE NCMP Topobathy Lidar: Florida Gulf Coast
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/54215
digital data
2010
2010
ground condition
2010 FL Gulf coast lidar
Lidar data that were used to extract a shoreline.
U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP)/Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX)
201109
2010 US Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) Topobathy Lidar: Alabama Coast and Florida Gulf Coast
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/50083
digital data
2010
2010
ground condition
2010 AL/FL Gulf coast lidar
Lidar data that were used to extract a shoreline.
U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP)/Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX)
20161215
2015 USACE NCMP Topobathy Lidar: Florida Gulf Coast
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/49720
digital data
2015
2015
ground condition
2015 FL Gulf coast lidar
Lidar data that were used to extract a shoreline.
U.S. Army Corps of Engineers (USACE)/Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX)
20170215
2016 USACE Post-Matthew Topobathy Lidar: Southeast Coast (VA, NC, SC, GA and FL)
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/49616
digital data
2016
2016
ground condition
2016 Southeast coast lidar
Lidar data that were used to extract a shoreline.
U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP)/Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX)
20161215
2016 USACE NCMP Topobathy Lidar: Florida East Coast
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/49722
digital data
2016
2016
ground condition
2016 FL east coast lidar
Lidar data that were used to extract a shoreline.
U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP)/Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX)
20170913
2016 USACE NCMP Topobathy Lidar: Gulf Coast (AL, FL, MS, TX)
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/49738
digital data
2016
2016
ground condition
2016 Gulf coast lidar
Lidar data that were used to extract a shoreline.
U.S. Army Corps of Engineers (USACE), Federal Emergency Management Agency (FEMA)
20171002
2017 USACE FEMA Topobathy Lidar: Florida East Coast, Florida Keys, and Collier County (Post Hurricane Irma)
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/49723
digital data
2017
2017
ground condition
2017 FL east coast lidar
Lidar data that were used to extract a shoreline.
U.S. Army Corps of Engineers (USACE), Federal Emergency Management Agency (FEMA)
20181108
2018 USACE FEMA Post-Michael Topobathy Lidar: Florida Panhandle
https://www.coast.noaa.gov/
https://coast.noaa.gov/digitalcoast/data/
https://www.fisheries.noaa.gov/inport/item/54682
digital data
2018
2018
ground condition
2018 FL panhandle lidar
Lidar data that were used to extract a shoreline.
Data from the previously-published National Assessment of Shoreline Change study for the sandy shorelines of the Gulf of Mexico and Southeast Atlantic Coasts (USGS Open-File Report 2004-1089 and USGS Open-File Report 2005-1326) as well as the update reports (doi:10.5066/F74X55X7 and doi:10.5066/F78P5XNK, both in 2017) were used as the starting point for this update which includes several new lidar shorelines for Georgia and Florida. The previously published lidar shorelines are from 1998, 1999, and 2001.
T-sheet shorelines
1998 gulf coast lidar
1999 east coast lidar
2001 gulf coast lidar
2019
U.S. Geological Survey
Meredith Kratzmann
Mailing and Physical
384 Woods Hole Road
Woods Hole
MA
02543
508-548-8700
508-457-2310
mkratzmann@contractor.usgs.gov
A profile method was used to extract the operational MHW shoreline from the lidar point cloud data utilizing the Matlab-based approach (Matlab version 2019b) described in Farris and others (2018). Elevation values for the height of MHW were obtained from Weber and others (2005). The profile method used a coast-following reference line with 20-meter spaced profiles. All lidar data points that were within 1 meter of each profile line were associated with that profile. All processing was done on the 2-meter-wide profiles, working on a single profile at a time. For each profile, a linear regression was fit through data points on the foreshore and the regression was evaluated at the MHW elevation to yield the cross-shore position of the MHW shoreline. If there was a data gap at MHW or if the MHW elevation was obscured by water points, the linear regression was simply extrapolated to the MHW elevation. For each profile, the foreshore beach slope was defined as the slope of the regression line.
Each MHW shoreline point that was extracted using this profile method has an uncertainty associated with it. This uncertainty includes three components: 1) the 95% confidence interval on the linear regression estimate of the shoreline position; 2) a 15 cm vertical error in the raw lidar data that was converted into a horizontal error using the beach slope; and 3) the uncertainty due to extrapolation (if the shoreline was determined using extrapolation). These three components of uncertainty were added in quadrature to yield a total error for each shoreline point.
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
Weber, K.M., List, J.H., 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://doi.org/10.3133/ofr20051027
Lidar shorelines were extracted by Amy Farris, Kathy Weber, Zehao Xue, and Marie Bartlett of the USGS from 2015 through 2020 using the method described in this step.
2006 east coast lidar
2009 FL Atlantic Coast lidar
2010 Southeast coast lidar
2010 FL Gulf coast lidar
2010 AL/FL Gulf coast lidar
2015 FL Gulf coast lidar
2016 Southeast coast lidar
2016 FL east coast lidar
2016 Gulf coast lidar
2017 FL east coast lidar
2018 FL panhandle lidar
2020
GA 2006 lidar shoreline
FLec 2006 lidar shoreline
FLec 2009 lidar shoreline
GA 2010 lidar shoreline
FLec 2010 lidar shoreline
FLwc 2010 lidar shoreline
FLph 2010 lidar shoreline
FLwc 2015 lidar shoreline
FLph 2015 lidar shoreline
GA 2016 lidar shoreline
FLec 2016 lidar shoreline
FLph 2016 lidar shoreline
FLec 2017 lidar shoreline
FLph 2018 lidar shoreline
U.S. Geological Survey
Amy Farris
Mailing and Physical
384 Woods Hole Road
Woods Hole
MA
02543
508-548-8700 x2344
508-457-2310
afarris@usgs.gov
The lidar shoreline shapefiles were then visually checked against imagery contained in Esri's World_Imagery GIS server to make sure the shoreline was not interpolated through a headland or structure, for example. Attribute fields were added (based on DSAS requirements described in the DSAS v5 User Guide) to the attribute table and those fields were populated with the relevant information.
This process step and all other process steps were performed by the same person - Meredith Kratzmann.
2020
U.S. Geological Survey
Meredith Kratzmann
Mailing and Physical
384 Woods Hole Road
Woods Hole
MA
02543
508-548-8700
508-457-2310
mkratzmann@contractor.usgs.gov
Historical (1800s-1980s) and previously published lidar shorelines (1998/2001, 1999) were merged with the new lidar shorelines (2006-2018) in ArcToolbox v10.7 > Data Management Tools > General > Merge to produce a single shoreline file for each region.
2020
The shorelines file was imported into a personal geodatabase in ArcCatalog v10.7 by right-clicking on the geodatabase > Import (feature class) for use in the DSAS v5 software to perform rate calculations.
2020
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.
2020
The data were projected in ArcToolbox v10.7 > Data Management Tools > Projections and Transformations > Project. Parameters: input projection = UTM zone 16N WGS84; output projection = geographic coordinates (WGS84); transformation = none.
2021
Updated the cross-reference information with regards to the related Data Report (20220427). The metadata available from a harvester may supersede metadata bundled with the dataset. Compare the metadata dates to determine which metadata file is most recent.
20220427
U.S. Geological Survey
VeeAnn A. Cross
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
(508) 548-8700 x2251
508-457-2310
vatnipp@usgs.gov
Vector
String
630
0.0197395052
0.0264490611
Decimal seconds
WGS_1984
WGS_84
6378137.0
298.257223563
FLph_shorelines
Shorelines for Florida panhandle (FLph) used in shoreline change analysis.
U.S. Geological Survey
FID
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Feature geometry.
Esri
Coordinates defining the features.
DATE_
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.
U.S. Geological Survey
Date of the shoreline in mm/dd/yyyy
Uncy
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.
U.S. Geological Survey
0.91
12.5
Source
Agency that provided shoreline feature or the data source used to digitize shoreline feature.
U.S. Geological Survey
Character string of length 25
Source_b
Type of data used to create shoreline.
U.S. Geological Survey
lidar
Light detection and ranging (lidar).
U.S. Geological Survey
T or TP with number
NOAA/NOS topographic survey sheet (T- or TP-sheet) with associated registry number.
U.S. Geological Survey
aerials (or army survey, orthophoto, pl. survey) with letters and numbers
FLDEP aerial photo with associated registry information.
U.S. Geological Survey
H- with number, letters and numbers
FLDEP-sourced hydrographic survey (H-sheet) with associated registry information.
U.S. Geological Survey
Year_
Four digit year of shoreline
U.S. Geological Survey
1855
2018
Default_D
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.
U.S. Geological Survey
0
Shoreline month and day are known.
U.S. Geological Survey
1
Shoreline month and day are unknown and default value of 07/01 was used.
U.S. Geological Survey
Location
Location of shoreline with respect to wave energy exposure. An open ocean coast is directly exposed to ocean waves and is typically characterized by higher wave energy. A sheltered coast is not directly exposed to ocean waves and is characterized by lower wave energy. This shoreline dataset includes only open ocean locations.
U.S. Geological Survey
open ocean
Shoreline on a coast with open ocean wave exposure.
U.S. Geological Survey
Shape_Leng
Length of shoreline in meter units (UTM zone 16N WGS84).
U.S. Geological Survey, Woods Hole Science Center
8.173243
76429.983931
DSAS_type
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.
U.S. Geological Survey
MHW
Mean High Water (datum-based shoreline).
U.S. Geological Survey
HWL
High Water Line (proxy-based shoreline).
U.S. Geological Survey
ATTRIBUTE
Additional notation regarding source of shoreline data.
U.S. Geological Survey
Character string of length 50
The entity and attribute information provided here describes the tabular data associated with the dataset. Please review the individual attribute descriptions for detailed information.
U.S. Geological Survey
U.S. Geological Survey - ScienceBase
mailing and physical address
Federal Center, Building 810, MS 302
Denver
CO
80225
USA
1-888-275-8747
sciencebase@usgs.gov
The dataset contains polyline shorelines (SHP and other shapefile components), browse graphic, and the FGDC CSDGM metadata.
Neither the U.S. Government, the Department of the Interior, nor the USGS, nor any of their employees, contractors, or subcontractors, make any warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe on privately owned rights. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the USGS in the use of these data or related materials. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), and have been processed successfully on a computer system at the 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. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Shapefile
ArcGIS 10.7
Esri polyline shapefile
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.
2
https://doi.org/10.5066/P9J3CVN4
https://www.sciencebase.gov/catalog/file/get/614a7c3bd34e0df5fb9756d8
https://www.sciencebase.gov/catalog/item/614a7c3bd34e0df5fb9756d8
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.
None
These data are available in a polyline shapefile format. The user must have software to read and process the data components of a shapefile.
20220427
Meredith G. Kratzmann
U.S. Geological Survey
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700
508-457-2310
mkratzmann@contractor.usgs.gov
FGDC Content Standards for Digital Geospatial Metadata
FGDC-STD-001-1998
local time