U.S. Geological Survey
2019
Long-term and short-term shoreline change rates for the coastal region north of Boston, Massachusetts calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.0
1.0
vector digital data
data release
DOI:10.5066/P9RRBEYK
Woods Hole Coastal and Marine Science Center, Woods Hole, MA
U.S. Geological Survey, Coastal and Marine Geology Program
https://doi.org/10.5066/P9RRBEYK
https://www.sciencebase.gov/catalog/item/5c644dc7e4b0fe48cb372955
Emily A. Himmelstoss
Amy S. Farris
Kathryn M. Weber
Rachel E. Henderson
2019
Massachusetts Shoreline Change Project, 2018 Update: A GIS Compilation of Shoreline Change Rates Calculated Using Digital Shoreline Analysis System Version 5.0, With Supplementary Intersects and Baselines for Massachusetts
1.0
vector digital data
data release
DOI:10.5066/P9RRBEYK
Reston, VA
U.S. Geological Survey
suggested citation: Himmelstoss, E.A., Farris, A.S., Weber, K.M., and Henderson, R.E., 2019, Massachusetts shoreline change project, 2018 update–A GIS compilation of shoreline change rates calculated using Digital Shoreline Analysis System version 5.0, with supplementary intersects and baselines for Massachusetts: U.S. Geological Survey data release, https://doi.org/10.5066/P9RRBEYK
https://doi.org/10.5066/P9RRBEYK
https://www.sciencebase.gov/catalog/item/5be5857ce4b0b3fc5cf8c6ca
The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color aerial orthoimagery and 2007 topographic lidar datasets obtained from the National Oceanic and Atmospheric Administration's Ocean Service, Coastal Services Center. This 2018 data release includes rates that incorporate two new mean high water (MHW) shorelines for the Massachusetts coast extracted from lidar data collected between 2010 and 2014. The first new shoreline for the State includes data from 2010 along the North Shore and South Coast from lidar data collected by the U.S. Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of Expertise. Shorelines along the South Shore and Outer Cape are from 2011 lidar data collected by the U.S. Geological Survey's (USGS) National Geospatial Program Office. Shorelines along Nantucket and Martha’s Vineyard are from a 2012 USACE Post Sandy Topographic lidar survey. The second new shoreline for the North Shore, Boston, South Shore, Cape Cod Bay, Outer Cape, South Cape, Nantucket, Martha’s Vineyard, and the South Coast (around Buzzards Bay to the Rhode Island Border) is from 2013-14 lidar data collected by the (USGS) Coastal and Marine Geology Program. This 2018 update of the rate of shoreline change in Massachusetts includes two types of rates. Some of the rates include a proxy-datum bias correction, this is indicated in the filename with “PDB”. The rates that do not account for this correction have “NB” in their file names. The proxy-datum bias is applied because in some areas a proxy shoreline (like a High Water Line shoreline) has a bias when compared to a datum shoreline (like a Mean High Water shoreline). In areas where it exists, this bias should be accounted for when calculating rates using a mix of proxy and datum shorelines. This issue is explained further in Ruggiero and List (2009) and in the process steps of the metadata associated with the rates. This release includes both long-term (~150 years) and short term (~30 years) rates. Files associated with the long-term rates have “LT” in their names, files associated with short-term rates have “ST” in their names.
This dataset describes the long-term (~150 years) and short-term (~30 years) shoreline change rates for the coastal region north of Boston, MA. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.0, an ArcGIS extension developed by the U.S. Geological Survey. Long-term and short-term rates of shoreline change were calculated using a linear regression rate based on available shoreline data. 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 are then used to calculate rates. This dataset consists of shoreline change rates calculated with DSAS v5.0 and stored as a new transect layer. Original measurement transects are cast by DSAS from the baseline to intersect shoreline vectors, and the intersect data provide location and time information used to calculate rates of change.
2014
ground condition of the most recent shoreline these rates are based on
None planned
-70.991087
-70.590412
42.875167
42.343497
USGS Metadata Identifier
USGS:5c644dc7e4b0fe48cb372955
ISO 19115 Topic Category
oceans
geoscientificInformation
None
Esri polyline shapefile
Shoreline
Historical Shoreline
long-term
short-term
Shoreline Change Rate
Erosion
Accretion
Linear Regression Rate
LRR
Baseline
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
Massachusetts Office of Coastal Zone Management
USGS Thesaurus
geospatial datasets
coastal processes
None
Atlantic Coast
United States
New England
Massachusetts
North Shore
None
These data were automatically generated using the DSAS v5.0 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
Emily A. Himmelstoss
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700
508-547-2310
ehimmelstoss@usgs.gov
https://www.sciencebase.gov/catalog/file/get/5c644dc7e4b0fe48cb372955/?name=NorthShore_rates_browse.png
Map view of data
png
Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.5.0.6491
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 5.0): U.S. Geological Survey Software
software release
version 5.0
Reston, VA
U.S. Geological Survey
https://code.usgs.gov/cch/dsas/
https://doi.org/10.5066/P9VW42I0
https://woodshole.er.usgs.gov/project-pages/DSAS/
Emily A. Himmelstoss
Rachel E. Henderson
Meredith G. Kratzmann
Amy S. Farris
2018
DSAS v5.0 user guide
publication
Open-File Report
2018-1179
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20181179
https://woodshole.er.usgs.gov/project-pages/DSAS/
E.R. Thieler
T.L. Smith
Julia Knisel
D.W. Sampson
2013
Massachusetts Shoreline Change Mapping and Analysis Project, 2012 Update
publication
Open-File Report
2012-1189
Reston, VA
U.S. Geological Survey
http://pubs.usgs.gov/of/2012/1189/
Emily A. Himmelstoss
Amy S. Farris
Kathryn M. Weber
2018
Massachusetts Shoreline Change Project: A GIS Compilation of Vector Shorelines for the 2018 update
DOI:10.5066/P9O7S72B
data release
DOI:10.5066/P9O7S72B
Reston, VA
U.S. Geological Survey, Coastal and Marine Geology Program
https://doi.org/10.5066/P9O7S72B
https://www.sciencebase.gov/catalog/item/5bcde5dce4b0f0758fc178d0
https://www.sciencebase.gov/catalog/file/get/5bcde5dce4b0f0758fc178d0
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
ppg. 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 v5.0. 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 shoreline change rates for the region. Additional transects may have been generated but did not intersect the minimum requirement of three shorelines. Shoreline change rates data is provided where there are available shorelines to compute change metrics.
The uncertainty of the linear regression rate is estimated by the elements LR2, LSE and LCI90_0. See the attribute definition of each for more information.
Explanation of the methods used to delineate shoreline features that are a part of this update for the Massachusetts Office of Coastal Zone Management Shoreline Change Project: This data release computes both long- and short-term rates of shoreline change, and depending on the available data may include shorelines referenced to mean high water (MHW) or a proxy-based high water line (HWL). The new data recently published as part of this update are from Himmelstoss and others (2018), these shorelines were combined with data from previous assessments most recently compiled in Smith and others (2013). Shoreline data were merged into a single feature class for a region after all input files were projected to UTM zone 19N coordinates and confirmed to have the same attribute names needed for use in DSAS. MHW shorelines are datum-based and in the case of the shorelines used here, were extracted from lidar data using a profile method, whenever possible, or a contour method. Profile open-ocean coast: datum-based mean high water (MHW) shoreline. The elevation of MHW was obtained from Weber and others (2005). These data have an associated uncertainty table that provides the horizontal uncertainty associated with the shoreline, a proxy-datum bias value describing the unidirectional horizontal offset between the MHW shoreline and the historical proxy-based high water line (HWL) shorelines, and the uncertainty associated with the calculated proxy-datum bias value. For more information about the proxy-datum bias, see Ruggiero and List (2009). These shorelines are polyline-M shapefiles. Profile not open-ocean: datum-based mean high water (MHW) shoreline. Since Weber and others (2005) only covers open-ocean coast, all MHW elevations for these data come from NOAA's vdatum (version 3.8; https://vdatum.noaa.gov/). These data have an associated uncertainty table that provides the horizontal uncertainty associated with the shoreline. These shorelines are polyline-M shapefiles. Contour method: this method is used along sections of the coast that were too crenulated for the profile method. The elevation of MHW was used from Weber and others, 2005 when available. In areas not covered by Weber and others (2005), NOAA's vdatum (version 3.8; https://vdatum.noaa.gov/) is used to determine MHW. Once this value is determined, the contour line of that value is extracted from the DEM surface in the area of interest. These shorelines are polyline shapefiles. Most of the historical shorelines from Smith and others (2013) are proxy-based historical shorelines. Vector shorelines digitized from georegistered T-sheets using standard editing tools in ArcMap provide a proxy-based high water line (HWL) feature that is not tidally-referenced. Individually these shorelines are stored as polyline shapefiles. In previous analyses these data were published as a merged file with profile method data extracted from lidar. Therefore the published data are all polyline-M, but the historic HWL shorelines contain no linear referencing. Visually identified HWL-type proxy shorelines are virtually never coincident with datum-based MHW-type shorelines. In fact, HWL shorelines are almost universally estimated to be higher (landward) on the beach profile than MHW shorelines. Not accounting for this offset will cause shoreline change rates to be biased toward slower shoreline retreat, progradation rather than retreat, or faster progradation than in reality (for the typical case where datum-based MHW shorelines are more recent data than the proxy-based HWL shoreline dates). The Digital Shoreline Analysis System software used to compute rates has an option to indicate when proxy-based and datum-based shorelines are present and uses linear referencing to retrieve the information on bias and uncertainty stored in the DBF table associated with the profile method shorelines and correct for the proxy-datum bias offset. This process step and all subsequent process steps were performed by the same person: Emily A. Himmelstoss.
2016
Emily A. Himmelstoss
U.S. Geological Survey
Geologist
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02540
508-548-8700
ehimmelstoss@usgs.gov
Transect features generated in a personal geodatabase using DSAS v5.0.20180213.1225. Parameters Used: baseline layer=NorthShore_baseline, baseline group field=NULL, transect spacing=50 meters, search distance=1000 meters, land direction=right, shoreline intersection=seaward, File produced = NorthShore_transects. For additional details on these parameters, please see the DSAS help file distributed with the DSAS software, or visit the USGS website at: https://woodshole.er.usgs.gov/project-pages/DSAS/
2018
Some transects were manually edited for length, moved, or deleted in an edit session using standard editing tools in ArcMap v10.5.1
2018
Shoreline intersects and rate calculations performed for long-term rates with bias. Parameters Used: shoreline layer=NorthShore_LT_shorelines, shoreline date field=DSAS_date, shoreline uncertainty field name=Uncy, the default accuracy=4.4 meters, shoreline intersection=seaward, stats calculations=[LRR], shoreline threshold=3, confidence interval=90%. Files produced = NorthShore_PDB_LT_rates_20180522_115445, NorthShore_PDB_LT_intersect_20180522_115445.
2018
Shoreline intersects and rate calculations performed for long-term rates without bias. Parameters Used: shoreline layer=NorthShore_LT_shorelines, shoreline date field=DSAS_date, shoreline uncertainty field name=Uncy, the default accuracy=4.4 meters, shoreline intersection=seaward, stats calculations=[LRR], shoreline threshold=3, confidence interval=90%. Files produced = NorthShore_NB_LT_rates_20180518_102615, NorthShore_NB_LT_intersect_20180518_102615.
2018
Shoreline intersects and rate calculations performed for short-term rates with bias. Parameters Used: shoreline layer=NorthShore_ST_shorelines, shoreline date field=DSAS_date, shoreline uncertainty field name=Uncy, the default accuracy=4.4 meters, shoreline intersection=seaward, stats calculations=[LRR], shoreline threshold=3, confidence interval=90%. Files produced = NorthShore_PDB_ST_rates_20180522_120358, NorthShore_PDB_ST_intersect_20180522_120358.
2018
Shoreline intersects and rate calculations performed for short-term rates without bias. Parameters Used: shoreline layer=NorthShore_ST_shorelines, shoreline date field=DSAS_date, shoreline uncertainty field name=Uncy, the default accuracy=4.4 meters, shoreline intersection=seaward, stats calculations=[LRR], shoreline threshold=3, confidence interval=90%. Files produced = NorthShore_NB_ST_rates_20180518_104252, NorthShore_NB_ST_intersect_20180518_104252.
2018
The rate feature classes were exported to shapefiles in ArcMap v10.5 by right-clicking the transect layer > data > export data.
2018
The exported rate shapefiles were projected in Esri's ArcToolbox (v10.5) > Data Management Tools > Projections and Transformations > Project. Parameters: input projection - UTM zone 19N (WGS84); output projection - geographic coordinates (WGS84); transformation = none.
20180919
Added keywords section with USGS persistent identifier as theme keyword.
20200810
U.S. Geological Survey
VeeAnn A. Cross
Marine Geologist
Mailing and Physical
384 Woods Hole Road
Woods Hole
MA
02543-1598
508-548-8700 x2251
508-457-2310
vatnipp@usgs.gov
Vector
String
2217
0.0000001
0.0000001
Decimal degrees
WGS_1984
WGS_1984
6378137.0
298.257223563
NorthShore_PDB_LT_rates.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 where bias has been applied and shapefiles will have LT for long-term and PDB for proxy-datum bias in filename.
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
GroupID
This optional field is a way to aggregate transects on the basis of physical variations alongshore (for example, tidal inlets, change in coastal type, or hard stabilization features). This value was assigned by the user as an attribute to a baseline segment and results in a group average being reported in the DSAS summary text file.
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
TCD
The Total Cumulative Distance (TCD) is the measure in meters along shore from the start of the baseline segment with an ID=1, and measured sequentially alongshore to the end of the final baseline segment
U.S. Geological Survey
0
unlimited
SHAPE_Leng
Length of feature in meter units (UTM zone 19N, 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.
LR2
The R-squared statistic, or coefficient of determination, is the percentage 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
LSE
The predicted (or estimated) values of y (the distance from baseline in meters) are computed for each shoreline point by using the values of x (the shoreline date) and solving the equation for the best-fit regression line (y=mx+b). The standard error is also called the standard deviation.
U.S. Geological Survey
Positive decimal values in meters.
LCI90_0
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.
NorthShore_NB_LT_rates.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 where bias has not been applied and shapefiles will have LT for long-term and NB for no bias in filename.
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
GroupID
This optional field is a way to aggregate transects on the basis of physical variations alongshore (for example, tidal inlets, change in coastal type, or hard stabilization features). This value was assigned by the user as an attribute to a baseline segment and results in a group average being reported in the DSAS summary text file.
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
TCD
The Total Cumulative Distance (TCD) is the measure in meters along shore from the start of the baseline segment with an ID=1, and measured sequentially alongshore to the end of the final baseline segment
U.S. Geological Survey
0
unlimited
SHAPE_Leng
Length of feature in meter units (UTM zone 19N, 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.
LR2
The R-squared statistic, or coefficient of determination, is the percentage 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
LSE
The predicted (or estimated) values of y (the distance from baseline in meters) are computed for each shoreline point by using the values of x (the shoreline date) and solving the equation for the best-fit regression line (y=mx+b). The standard error is also called the standard deviation.
U.S. Geological Survey
Positive decimal values in meters.
LCI90_0
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.
NorthShore_PDB_ST_rates.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 short-term rates where bias has been applied and shapefiles will have ST for short-term and PDB for proxy-datum bias in filename.
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
GroupID
This optional field is a way to aggregate transects on the basis of physical variations alongshore (for example, tidal inlets, change in coastal type, or hard stabilization features). This value was assigned by the user as an attribute to a baseline segment and results in a group average being reported in the DSAS summary text file.
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
TCD
The Total Cumulative Distance (TCD) is the measure in meters along shore from the start of the baseline segment with an ID=1, and measured sequentially alongshore to the end of the final baseline segment
U.S. Geological Survey
0
unlimited
SHAPE_Leng
Length of feature in meter units (UTM zone 19N, WGS 84)
Esri
0
unlimited
meters
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.
LR2
The R-squared statistic, or coefficient of determination, is the percentage 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
LSE
The predicted (or estimated) values of y (the distance from baseline in meters) are computed for each shoreline point by using the values of x (the shoreline date) and solving the equation for the best-fit regression line (y=mx+b). The standard error is also called the standard deviation.
U.S. Geological Survey
Positive decimal values in meters.
LCI90_0
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.
NorthShore_NB_ST_rates.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 short-term rates where bias has not been applied and shapefiles will have ST for short-term and NB for no bias in filename.
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.
TransectIDr
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
GroupID
This optional field is a way to aggregate transects on the basis of physical variations alongshore (for example, tidal inlets, change in coastal type, or hard stabilization features). This value was assigned by the user as an attribute to a baseline segment and results in a group average being reported in the DSAS summary text file.
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
TCD
The Total Cumulative Distance (TCD) is the measure in meters along shore from the start of the baseline segment with an ID=1, and measured sequentially alongshore to the end of the final baseline segment
U.S. Geological Survey
0
unlimited
SHAPE_Leng
Length of feature in meter units (UTM zone 19N, WGS 84)
Esri
0
unlimited
meters
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.
LR2
The R-squared statistic, or coefficient of determination, is the percentage 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
LSE
The predicted (or estimated) values of y (the distance from baseline in meters) are computed for each shoreline point by using the values of x (the shoreline date) and solving the equation for the best-fit regression line (y=mx+b). The standard error is also called the standard deviation.
U.S. Geological Survey
Positive decimal values in meters.
LCI90_0
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.
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) and short-term (approximately 30 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 19N WGS 84 projection. This region has four shapefiles describing rates; long-term with bias, long-term without bias, short-term with bias, and short-term without bias.
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 in XML and TEXT format
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 10.5
Esri polyline shapefile
These files (.cpg, .dbf, .prj, .sbn, .sbx, .shp, .shp, .xml, 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.
no compression applied
2
https://www.sciencebase.gov/catalog/file/get/5c644dc7e4b0fe48cb372955
https://www.sciencebase.gov/catalog/item/5c644dc7e4b0fe48cb372955
https://doi.org/10.5066/P9RRBEYK
The first link downloads all the data on the landing page, the second link is to the dataset landing page, and the third link is to the main landing page of the data release.
WMS
1.3.0
Web Mapping Services 1.3.0
https://www.sciencebase.gov/catalogMaps/mapping/ows/5c644dc7e4b0fe48cb372955?service=wms&request=getcapabilities&version=1.3.0
https://www.sciencebase.gov/catalog/item/5c644dc7e4b0fe48cb372955
https://doi.org/10.5066/P9RRBEYK
The first link is for the Web Mapping Services, the second link is to the dataset landing page, and the third link is to the main landing page of the data release.
WFS
1.0.0
Web Feature Services 1.0.0
https://www.sciencebase.gov/catalogMaps/mapping/ows/5c644dc7e4b0fe48cb372955?service=wfs&request=getcapabilities&version=1.0.0
https://www.sciencebase.gov/catalog/item/5c644dc7e4b0fe48cb372955
https://doi.org/10.5066/P9RRBEYK
The first link is for the Web Feature Services, the second link is to the dataset landing page, and the third link is to the main landing page of the data release.
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.
20200810
Emily A. Himmelstoss
U.S. Geological Survey
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700
508-457-2310
ehimmelstoss@usgs.gov
FGDC Content Standards for Digital Geospatial Metadata
FGDC-STD-001-1998
local time