U.S. Geological Survey
20210929
Long-term shoreline change rates for the Florida east coast (FLec) coastal region using the Digital Shoreline Analysis System version 5
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/614a7c15d34e0df5fb9756d4
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 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.
Long-term (~150 years) shoreline change rates for the Florida east coast (FLec) (border with GA to Key Biscayne) coastal region are included in this dataset. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate based on available shoreline data for Florida east coast (FLec). A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline, establishing measurement points which provide location and time information used to calculate rates of change. This dataset consists of shoreline change rates stored as a new transect layer.
2021
publication date
None planned
-81.443927
-80.028514
30.701708
25.664117
ISO 19115 Topic Category
oceans
geoscientificInformation
environment
None
Shoreline
Historical Shoreline
Long-term shoreline change rate
Short-term shoreline change rate
Shoreline change rate
Erosion
Accretion
Linear Regression Rate
LRR
End point rate
EPR
Proxy-Datum bias
PDB
Transect
Digital Shoreline Analysis System
DSAS
U.S. Geological Survey
USGS
Coastal and Marine Geology Program
CMGP
Woods Hole Coastal and Marine Science Center
WHCMSC
USGS Thesaurus
geospatial datasets
coastal processes
USGS Metadata Identifier
USGS:614a7c15d34e0df5fb9756d4
None
Atlantic Coast
Gulf Coast
United States
North America
Georgia
Florida
None
These data were automatically generated using the DSAS v5 software applications. 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/614a7c15d34e0df5fb9756d4?name=BG_FLec_transects_rates_LT.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
2018-1179
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
The attributes of this dataset are based on the field requirements of the Digital Shoreline Analysis System and were automatically generated by the software during the generation of the transect layer or during the calculation of shoreline change rates performed by the software.
These data were generated using DSAS v5. The transects automatically generated by the software were visually inspected along with the shoreline data prior to rate calculations. Sometimes transect positions were manually edited within a standard ArcMap edit session to adjust the position at which an individual transect intersected the shorelines to better represent an orthogonal position to the general trend of the coast over time.
This dataset contains the transects automatically generated by the DSAS software application that were used to calculate long-term shoreline change rates for the region. Additional transects may have been generated but did not meet the required number of shorelines or time period requirements.
The uncertainty of the linear regression rate is estimated by the elements LR2, LSE and LCI90. See the attribute definition of each for more information.
Transect features generated in a personal geodatabase using DSAS v5 for long-term rate calculations. Transects truncate at the landwardmost shoreline intersection.
Long-term rate calculation parameters used: baseline layer=FLec_baseline, baseline group field=NULL, baseline=offshore, transect spacing=50 meters, search distance=2000 meters, smoothing distance=1200 meters, land direction=left, shoreline intersection=seaward, clip to extent=checked, File produced=FLec_transects.
For additional details on parameters, please see the DSAS help file distributed with the DSAS software, or visit the USGS website at: https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas
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
Some transects were manually edited or deleted in an edit session using standard editing tools in ArcMap v10.7.
2020
Shoreline intersects and rate calculations performed for long-term rates with and without bias. Parameters Used: shoreline layer=FLec_shorelines, shoreline date field=DATE_, shoreline uncertainty field name=Uncy, the default accuracy=15 meters, shoreline intersection=seaward, stats calculations=LRR, shoreline threshold=3, confidence interval=90%. File produced (FLec)= FLec_transects_rates_20201124_205641.
2020
The rate feature classes were exported to shapefiles in ArcMap v10.7 by right-clicking the transect layer > data > export data. File renamed FLec_transects_rates_LT.
2020
The exported rate shapefiles were projected in Esri's ArcToolbox (v10.7) > Data Management Tools > Projections and Transformations > Project. Parameters: input projection - UTM zone 17N (WGS84); output projection - geographic coordinates (WGS84); transformation = none.
2020
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
11695
0.0000001
0.0000001
Decimal degrees
WGS_1984
WGS_1984
6378137.0
298.257223563
FLec_transects_rates_LT.shp
Transects were automatically generated by DSAS at a 90 degree angle to the user-specified baseline using a smoothing algorithm to maintain roughly parallel transects that are orthogonal with respect to the baseline. These attributes are for long-term rates in Florida east coast (FLec).
U.S. Geological Survey
FID
Internal feature number used as a unique identifier of an object within a table primarily used in shapefiles.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Feature geometry.
Esri
Coordinates defining the features.
TransectID
A unique identification number for each transect. Values may not increment sequentially alongshore.
U.S. Geological Survey
Sequential unique whole numbers that are automatically generated.
BaselineID
Unique identification number of the baseline segment. If BaselineID=0 no transects will be generated. Used by DSAS to determine transect ordering alongshore if multiple baseline segments exist.
U.S. Geological Survey
1
unlimited
TransOrder
Assigned by DSAS based on ordering of transects along the baseline. Used to allow user to sort transect data along the baseline from baseline start to baseline end.
U.S. Geological Survey
0
unlimited
Azimuth
Assigned by DSAS to record the azimuth of the transect measure in degrees clockwise from North. If a transect position has been adjusted during the editing process, the azimuth value in the attribute table is updated automatically.
U.S. Geological Survey
0
360
degrees
ShrCount
Number of shorelines used to compute shoreline change metrics.
U.S. Geological Survey
3
unlimited
SHAPE_Leng
Length of feature in meter units (UTM zone 17N, WGS 84)
Esri
0
unlimited
LRR
A linear regression rate-of-change statistic was calculated by fitting a least-squares regression line to all shoreline points for a particular transect. Any shoreline points that are referenced to HWL were adjusted by the proxy-datum bias distance (meters) along the transect to correct for the offset between proxy-based HWL and datum-based MHW shorelines. The best-fit regression line is placed so that the sum of the squared residuals (determined by squaring the offset distance of each data point from the regression line and adding the squared residuals together) is minimized. The linear regression rate is the slope of the line. The rate is reported in meters per year with positive values indicating accretion and negative values indicating erosion.
U.S. Geological Survey
Decimal values may be positive or negative, which is used to indicate landward (negative) or seaward (positive) direction from baseline origin. Reported in meters per year.
NB_LRR
A linear regression rate-of-change statistic as described in the attribute LRR but without the proxy-datum bias applied. NB=no bias.
U.S. Geological Survey
Decimal values may be positive or negative, which is used to indicate landward (negative) or seaward (positive) direction from baseline origin. Reported in meters per year.
LR2
The R-squared statistic, or coefficient of determination, is the proportion of variance in the data that is explained by a regression. It is a dimensionless index that ranges from 1.0 to 0.0 and measures how successfully the best-fit line accounts for variation in the data. The smaller the variability of the residual values around the regression line relative to the overall variability, the better the prediction (and closer the R-squared value is to 1.0).
U.S. Geological Survey
0
1
NB_LR2
The R-squared statistic, or coefficient of determination, as described in the attribute LR2 but for NB (no bias) rates.
U.S. Geological Survey
0
1
LSE
This quantity is the standard error of the regression, also known as the standard error of the estimate. To calculate it, the distance between each data point and the regression line is calculated. These distances are squared then summed. The sum is divided by the number of data point minus two. The square root is taken of the result.
U.S. Geological Survey
Positive decimal values in meters.
NB_LSE
The standard error as described in the attribute LSE but for NB (no bias) rates.
U.S. Geological Survey
Positive decimal values in meters.
LCI90
The standard error of the slope with confidence interval describes the uncertainty of the reported rate. The LRR rates are determined by a best-fit regression line for the shoreline data at each transect. The slope of this line is the reported rate of change (in meters/year). The confidence interval (LCI) is calculated by multiplying the standard error (also called the standard deviation) of the slope by the two-tailed test statistic at the user-specified 90 percent confidence. This value is often reported in conjunction with the slope to describe the confidence of the reported rate. For example: LRR = 1.2 LCI90 = 0.7 could be reported as a rate of 1.2 (+/-) 0.7 meters/year.
U.S. Geological Survey
Positive decimal values in meters.
NB_LCI90
The 90 percent confidence interval as described in the attribute LCI90 but for NB (no bias) rates.
U.S. Geological Survey
Positive decimal values in meters.
The entity and attribute information provided here describes the tabular data associated with long-term (greater than 50 years, and typically closer to 100 years) shoreline change rates, as well as rates that incorporate the known unidirectional offset between proxy-based high water line features and datum-based mean high water line features (the proxy-datum bias), and rates that did not have the necessary information to correct for this offset (no bias). Please review the individual attribute descriptions for detailed information. All calculations for length are in meter units and were based on the UTM zone 17N WGS 84 projection. This region, Florida east coast, has two shapefiles describing rates: long-term (LT) and short-term (ST).
U.S. Geological Survey
U.S. Geological Survey - ScienceBase
mailing and physical address
Federal Center, Building 810, MS 302
Denver
CO
880225
USA
1-888-275-8747
sciencebase@usgs.gov
The dataset contains the polyline rates of shoreline change data, (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.
no compression applied
0.86
https://doi.org/10.5066/P9J3CVN4
https://www.sciencebase.gov/catalog/file/get/614a7c15d34e0df5fb9756d4
https://www.sciencebase.gov/catalog/item/614a7c15d34e0df5fb9756d4
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