Maritza Barreto-Orta
Loderay Bracero-Marrero
Nias Hernández-Montcourt
Rubén Maldonado-González
Emily A. Himmelstoss
20211117
1970s Shorelines for Vieques and Culebra, Puerto Rico
vector digital data
Woods Hole Coastal and Marine Science Center, Woods Hole, MA
U.S. Geological Survey, Coastal and Marine Geology Program
https://doi.org/10.5066/P9SEUAHC
https://www.sciencebase.gov/catalog/item/6140c006d34e1449c5d5ff3f
Maritza Barreto-Orta
Loderay Bracero-Marrero
Nias Hernández-Montcourt
Rubén Maldonado-González
Emily A. Himmelstoss
Julia L. Heslin
20211130
A GIS Compilation of Vector Shorelines and Shoreline Classification for Puerto Rico from 1970 and 2010
1
vector digital data
data release
doi:10.5066/P9SEUAHC
Reston, VA
U.S. Geological Survey
suggested citation: Bracero-Marrero, L., Barreto-Orta, M., Hernández-Montcourt, N., Maldonado-González, R., Himmelstoss, E.A., Heslin, J.L. 2021, A GIS Compilation of Vector Shorelines and Shoreline Classification for Puerto Rico from 1970 and 2010: U.S. Geological Survey data release, https://doi.org/10.5066/P9SEUAHC
https://doi.org/10.5066/P9SEUAHC
https://www.sciencebase.gov/catalog/item/610ae914d34ef8d70568fba9
The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas most susceptible to erosion or accretion. These data can help coastal managers understand which areas of the coast are vulnerable to change.
This data release and other associated products represent an expansion of the USGS national-scale shoreline database to include Puerto Rico and its islands, Vieques and Culebra. The United States Geological Survey (USGS) in cooperation with the Coastal Research and Planning Institute of Puerto Rico (CoRePI, part of the Graduate School of Planning at the University of Puerto Rico, Rio Piedras Campus) has derived and compiled a database of historical shoreline positions using a variety of methods. These shorelines are used to measure the rate of shoreline change over time.
The shoreline data in this data release were digitized from georeferenced photographs, using the high-water line, ground water exit point, wet-dry line and instantaneous water line as specified in the shoreline type description of the data and attribute section of the metadata. This data release also provides a detailed classification of the coast from aerial photo interpretations. These data are used in conjunction with other compiled shorelines provided in complementary data releases to calculate rates of shoreline change.
19640101
19780829
ground condition
None planned
-65.5781
-65.2211
18.3590
18.0807
ISO 19115 Topic Category
geoscientificInformation
oceans
environment
USGS Thesaurus
coastal processes
geospatial datasets
None
UPR
University of Puerto Rico
University of Puerto Rico Graduate School of Planning
Coastal Research and Planning Institute of Puerto Rico
USGS
U.S. Geological Survey
Coastal and Marine Geology Program
Woods Hole Coastal and Marine Science Center
WHCMSC
DSAS
Digital Shoreline Analysis System
Shoreline
Historical Shorelines
Shoreline Change
Shoreline Classification
High Water Line
HWL
Wet/Dry Line
WDL
Instantaneous Water Line
Groundwater Exit
Aerial Photos
Hurricane Maria
Hurricane Irma
USGS Metadata Identifier
USGS:6140c006d34e1449c5d5ff3f
None
United States
Atlantic Coast
Caribbean
Puerto Rico
Vieques
Culebra
None.
Users must be aware of these conditions and bear responsibility for the appropriate use of the information with respect to possible errors, scale, resolution, rectification, positional accuracy, development methodology, time period, environmental and climatic conditions and other circumstances specific to these data. The user should refer to the accompanying metadata notes for a description of the data and data development procedures.
The data herein, including but not limited to geographic data, tabular data, analytical data, electronic data structures or files, are provided "as is" without warranty of any kind, either expressed or implied, or statutory, including, but not limited to, the implied warranties or merchantability and fitness for a particular purpose.
Maritza Barreto-Orta
Coastal Research and Planning Institute of Puerto Rico (CoRePI-PR), Graduate School of Planning, UPR-RP
Principal Investigator
mailing and physical
Station 1001
San Juan
Puerto Rico
00925
Puerto Rico
787764000, ext. 85118 or 85119
maritza.barreto@upr.edu; coastal.planning@upr.edu
https://www.sciencebase.gov/catalog/file/get/6140c006d34e1449c5d5ff3f?name=PR_1970_ViequesCulebra_Shoreline_Classification.jpg
Map view of data
JPEG
"Shoreline mapping, change estimation and forecasting for the coast of Puerto Rico impacted by Hurricanes Irma and Maria" Grant awarded to the Graduate School of Planning, University of Puerto Rico, Rio Piedras Campus (UPR-RP) by the Woods Hole Coastal and Marine Science Center of the United States Geological Survey (USGS). Maritza Barreto-Orta, Principal Investigator, Graduate School of Planning; Loderay I.M. Bracero-Marrero, Research Assistant Lead Nias Hernández-Montcourt, Research Assistant; Rubén O. Maldonado-González, Research Assistant. Woods Hole Coastal and Marine Science Center, USGS: Emily Himmelstoss, Project Manager; Rachel Henderson, Researcher IV; Julia Heslin, Geographer.
Esri ArcGIS Desktop 10.7.1
Elizabeth H. Boak
Ian L. Turner
2005
Shoreline Definition and Detection: A Review
publication
Journal of Coastal Research
vol. 214
West Palm Beach, FL, USA
Coastal Education and Research Foundation
https://bioone.org/journals/journal-of-coastal-research/volume-2005/issue-214/03-0071.1/Shoreline-Definition-and-Detection-A-Review/10.2112/03-0071.1.full
Peter Ruggiero
Meredith G. Kratzmann
Emily A. Himmelstoss
David Reid
Jonathan Allan
George Kaminsky
2013
National Assessment of Shoreline Change - Historical Shoreline Change Along the Pacific Northwest Coast
publication
Open-File Report
2012-1007
Reston, VA, USA
U.S. Geological Survey
https://doi.org/10.3133/ofr20121007
Mary Jean Pajak
Stephen Leatherman
2002
The High Water Line as Shoreline Indicator
publication
Journal of Coastal Research
Vol. 18, No. 2
Coconut Creek, FL, USA
Coastal Education and Research Foundation
https://journals.flvc.org/jcr/article/view/81276
B.J. Hudson
1980
Anthropogenic Coasts
publication
Geography
Vol. 65, No. 3
Sheffield, UK
Geographical Association
http://www.jstor.org/stable/40569272
Aileen Aponte
2019
Guía de Estructuras Costeras Duras (2019): "A Guide for Coast Hard Structures"
publication
This guide was created for the Coastal Research and Planning Institute of Puerto Rico (CoRePI-PR), Graduate School of Planning, UPR-RP.
M.A. Hampton
G.B. Griggs
2004
Formation, Evolution, and Stability of Coastal Cliffs – Status and Trends
publication
Professional Paper
1693
Reston, VA, USA
U.S. Geological Survey
https://pubs.usgs.gov/pp/pp1693/
A.M. Williams
R.A. Feagin
2010
Sargassum and Beach Erosion: Potential Costs and Benefits for Coastal Managers
publication
Working Paper
N/A
College Station, TX, USA
Spatial Sciences Laboratory, Department of Ecosystem Science & Management, Texas A&M University
https://tamug-ir.tdl.org/handle/1969.3/29002
U.S. Army Corps of Engineers
2002
Coastal Engineering Manual
publication
Engineer Manual
1110-2-1100
Washington, DC, USA
U.S. Army Corps of Engineers
https://www.publications.usace.army.mil/USACE-Publications/Engineer-Manuals/u43544q/434F415354414C/
Julia L. Heslin
Rachel E. Henderson
Emily A. Himmelstoss
20211130
Historical Shorelines for Puerto Rico from 1901 to 1987
publication
data release
DOI:10.5066/P9CLXCEG
Reston, VA
U.S. Geological Survey
https://www.sciencebase.gov/catalog/item/60cb7627d34e86b938a3a1b0
Julia L. Heslin
Rachel E. Henderson
Emily A. Himmelstoss
20211130
A GIS Compilation of Vector Shorelines for Puerto Rico from 2015 to 2018
publication
data release
DOI:10.5066/P9AZYW74
Reston, VA
U.S. Geological Survey
https://www.sciencebase.gov/catalog/item/610abe37d34ef8d70568937a
Rachel E. Henderson
Julia L. Heslin
Emily A. Himmelstoss
20211130
Puerto Rico Shoreline Change: A GIS Compilation of Shorelines, Baselines, Intersects, and Change Rates using the Digital Shoreline Analysis System version 5.1
publication
data release
DOI:10.5066/P9FNRRN0
Reston, VA
U.S. Geological Survey
https://www.sciencebase.gov/catalog/item/61255b87d34e40dd9c03f390
Quality Control (Q/C) was a key part of the project. This Q/C was applied to the shoreline digitization process and classification. ArcGIS Online and Desktop tools were used. Once the digitization process was completed by areas (Vieques and Culebra), the Q/C was started.
A web map was created called “Digitalization Q/C USGSUPR.” This map included two editable layers. These layers were designated to the principal investigator and research assistant. The principal investigator edited the layer directly in ArcGIS Online, while the lead research assistant used mostly ArcGIS Pro. Both layers were synced regardless of the editing environment.
The Q/C was conducted clockwise around the islands. Different sources were used as a reference to classify the shoreline. Also, for this project, the elevation was used to calculate the slope. The slope calculation proved to be a valuable layer, especially on rocky coasts, in particular - where rocky, cliff areas were classified as forest.
Google Earth and Google Maps were used to understand the ground condition. However, this evaluation was conducted with caution since the ground photos were not the same year as our aerial photos. Additionally, the location of stores, hotels, and other land cover helped to determine the type of activities in the coastal area. Finally, the temporal photography tool from Google Earth allowed us to compare aerial and satellite photography through time to better understand the shoreline dynamics. This method was also used with caution since sometimes the photos are not placed in the right location.
The research assistants in charge of digitization added this layer into their ArcGIS Pro project in order to see the Q/C comments and apply the edits as needed. There was frequent clarification and communication between the principal investigator and the lead research assistant. Once the Q/C was applied and discussed, these lines were classified as “Final” in the “Revisions/Doubts” field.
After this process was conducted, the principal investigator reviewed the digitization and added new feedback. The research assistants corrected the lines if needed.
Topology rules were tested for each feature class polyline. Topology rules:
Must Not Overlap (Line)
Must Not Intersect (Line)
Must Not have Dangles (Line)
Must Not Self Overlap (Line)
Must Not Self Intersect (Line)
This shoreline includes the shoreline feature for Puerto Rico's Vieques and Culebra municipalities.
For the 1970 shoreline, we accounted for the following errors in meters:
1) Georeferencing (RMSE): 0.82; 2) Digitizing error: 2.00; 3) Uncertainty HWL: 3.00. We calculated the total error by: first, squaring each of the errors, summing all of the squared errors, and finally, taking the square root of the sum. The total horizontal error for this shoreline is 3.7 meters.
United States Geological Survey (USGS)
20181212
2015-2017 USGS Lidar DEM Puerto Rico
raster digital data
Charleston, SC
NOAA Office for Coastal Management
https://chs.coast.noaa.gov/htdata/raster2/elevation/PR_USGS_DEM_2015_8654/
Digital
20160126
20170316
ground condition
2015-2017 USGS Lidar DEM Puerto Rico
DEM was used to calculate the slope for this project in order to assign the CLIFF classification.
National Centers for Coastal Ocean Science
20011201
Benthic Habitat Mapping in Puerto Rico and the U.S. Virgin Islands
vector digital data
Charleston, SC
NOAA Coastal Services Center
https://products.coastalscience.noaa.gov/collections/benthic/e95usvi_pr/
6000
Digital
19990101
20011101
ground condition
2000-2002 Benthic Habitat
This layer helped to understand the shoreline granulometry and other features to classify the shoreline.
National Centers for Coastal Ocean Science
20170214
C-CAP Land Cover, Puerto Rico, 2010
raster digital data
Charleston, SC
NOAA's Ocean Service, Office for Coastal Management
https://coast.noaa.gov/htdata/raster1/landcover/bulkdownload/hires/pr/
Digital
2010
ground condition
Puerto Rico Land Cover 2010
Information to corroborate the classification of the lines shoreline. This layer was especially useful in the vegetation classification.
United States Army Corps of Engineers
20080217
2006-2007 USACE NCMP ADS40 8 Bit Color Infrared Imagery: Puerto Rico
remote-sensing image
Charleston, SC
NOAA Office of Coastal Management
https://chs.coast.noaa.gov/htdata/raster1/imagery/PuertoRico_CIR_2007_393/
Digital
20061101
20070331
ground condition
2006-2007 Orthophoto
Images used to digitize the shoreline of 2006 where 2010 images were not available.
Puerto Rico Highway Administration, Office of Photogrammetry
2020
1964-1978 Culebra Aerial Images Puerto Rico Highway Administration, Commonwealth
remote-sensing image
20000
Digital
19640119
19780829
ground condition
Culebra and Vieques Aerial Images
Aerial images used to digitize the 1970 shoreline after geometric corrections were performed.
Images were collected from the Puerto Rico Highway Authority, Photogrammetry Office.
The images were georeferenced in ArcGIS Pro to extract the shoreline positions. Aerial images were purchased from the Puerto Rico Highway Authority. For Culebra, we received a total of 13 images. For Vieques, we received 33 images. The timeframe of the images is from 1964, 1972, and 1978. The scale of all the images was 1:20,000. The 2006-2007 orthophotos were used as reference. The ground control points (GCPs) for each image used varied according to the transformation method used: first order polynomial, second order polynomial, and spline. After the rectifications were completed, we checked each of the images for quality control.
A geodatabase (GDB) was created to mask or clip the images to the area of interest and create the final mosaic. The clipping of the images was done to erase black areas, labeled areas or undesired coverage improves the quality of the mosaics.
To best classify the images, different datasets were used as reference: land cover and benthic areas. Also, the DEM was collected to calculate the slope. This helped to identify cliff areas in the classification.
GROUND CONTROL POINTS AND ROOT MEAN SQUARE ERROR (RMSE)
The main control points were streets, highways, and bridges. However, on some occasions, some rocky features were used in areas where no anthropogenic structures were found. Also, due to bombing in Vieques and Culebra, another reliable source to rectify the images was the army bombarding target points, especially along the Vieques coast. To select the control points, the map scale in ArcGIS Pro was zoomed in between 1:100 and 1:500.
A total of four points were selected per image in most cases. These points were well-distributed across the image. In other cases, more points were used due to the image quality. A maximum RMSE of 4.0 was achieved for each image.
All GCPs in text files were saved individually for backup and reference purposes. All images were exported as “.tif” before being added into the GDB.
TRANSFORMATION
Different raster transformations were used to accomplish the best quality possible; these include first order polynomial, second order polynomial, and spline. Different transformations were applied based on the number of available GCPs.
REVISIONS
The rectifications were revised several times to achieve the best possible RMSE while ensuring the aerial image matched closely with the reference orthophotos. The GCPs and different transformations were tested for the aerial images individually.
MOSAIC CREATION
Once all the images were rectified and the best images were chosen, we mosaicked the images. First, an individual GDB was created for Vieques and Culebra. All images were inserted in the GDB.
Each of the images was masked before creating the final mosaics. By creating a mask of the images, we eliminated the black borders and labels on the photos. For these purposes, a polygon was created in the desired area to cut the image and the image was exported to a different GDB to create the mosaics. Once all images were clipped by the mask, the mosaic process was started.
Culebra Mosaic
As mentioned, several attempts were conducted to create the final mosaics. For Culebra, all the rectified images were used. In some cases, the images were clipped twice to improve the quality of the transformation.
For Culebra, the VORONOI transformation was chosen. After testing other methods, the Voronoi transformation was optimal as it divides the images into different sections and analyzes the similarity in each of the images to construct the final mosaics. Therefore, the seamlines inside the mosaic dataset was created using the Voronoi effect (see Build Seamlines: https://pro.arcgis.com/en/pro-app/2.6/tool-reference/data-management/build-seamlines.htm).
Due to technical limitations with the software, we created first the mosaic using the Voronoi and merged the resulting image with a small section that was not being exported from the original mosaic (see Create Mosaic Dataset: https://pro.arcgis.com/en/pro-app/latest/help/data/imagery/creating-mosaic-datasets-wf.htm; and Merge: https://pro.arcgis.com/en/pro-app/latest/arcpy/image-analyst/merge.htm). We collected each image RMSE and averaged these values to establish a final RMSE for the whole mosaic of 0.8309.
Vieques Mosaic
Vieques aerial images mosaic was approached differently. In this case, each image was analyzed and were organized in a certain order using the field “ZOrder.” The ZOrder field is automatically included in the mosaic dataset and gives the user the ability to control the display order of the images. Most of the images were organized from west to east. We collected each image RMSE and averaged these values to establish a final RMSE for the whole mosaic of 0.804.
2006-2007 Orthophoto
Culebra and Vieques Aerial Images 1964-1978
20200101
Aerial Images Mosaics Vieques and Culebra 1970
Coastal Research and Planning Institute of Puerto Rico (CoRePI-PR), Graduate School of Planning, UPR-RP.
Loderay Bracero Marero
Research Assistant Lead
mailing and physical
Station 1001
San Juan
Puerto Rico
00925
Puerto Rico
787764000, ext. 85118 or 85119
loderay.bracero@upr.edu; coastal.planning@upr.edu
A single GDB and feature class was created in ArcGIS Pro to digitize the 1970s shoreline for Vieques and Culebra Shoreline. Shoreline types (SHORE_TYPE) and descriptions (SHORE_DESC) were used to increase the quality of the shoreline classification.
For the 1970s shoreline, 1964, 1972 and 1978 aerial images were used. The total shoreline digitized per year was: 1964 (2%), 1972 (49%) and 1978 (49%).
To best classify the shoreline, different datasets were used as reference: land cover and benthic areas. Also, the DEM was collected to calculate the slope. This helped to identify cliff areas in the classification. The land cover and the benthic areas were used to understand the shoreline areas.
The digitizing scale was at 1:500 and visualization of 1:1000. The digitization was conducted clockwise. The digitized line was continuous line with their respective exceptions (rocky barrier, sand bars, etc.). When digitizing the type of beach coast ("Beach"), the high-water line (HWL) will be used as a proxy (Boak and Turner, 2005). If the HWL is not visible, the shoreline proxies will be digitized following this order: Wet/Dry Line or Run Up Maxima, Groundwater Exit, Instantaneous Line.
To merge the digitization and avoid overlaps, transition line features were made when each person finished their assigned classification.
Digitization Decisions: Summary
The main requirement to classify the shoreline features was to answer the question: “What is in contact with the highest water level?” Using this information, the shoreline was digitized as beach, concrete forms, vegetation, and others described in the attribute information. However, the variability of Vieques and Culebra's coasts do not make it possible to answer this question with a single answer for each type of coastline. Therefore, some decisions were taken to homogenize the digitization of Vieques and Culebra. One of the goals was to digitize a continuous line describing the coastal areas and the shoreline. Some exceptions were considered when digitizing rocky barriers, vegetation formations in the ocean such as mangroves, and rock formations off the coast. This summary was generated mainly from the inconsistencies that were found during the digitization process.
Beach
High Water Line
In beaches with coarser grain size, the HWL was defined following the line of sediment accumulated along the beach. For this analysis, the benthic layers (2000-2002 Benthic Habitat) helped to identify features like coral reefs and understand the granulometry of the beach. When bluff areas were seen, the HWL was digitized in the color contrast between the bluff and beach berm. If the HWL was not visible, areas with shadows were classified as “No Visibility>Shadows”
When the HWL was not visible, and sand accumulation was seen in the shoreline, other proxies were digitized: instantaneous line, wet/dry line, or groundwater exit point. For beaches with terrigenous sand, the HWL was identified by the highest contrast between wet and dry areas.
Tombolo sand formations were digitized using the instantaneous line or HWL indicators if visible.
When sargasso was present, the continuous line of sargasso accumulated around the last highest tide mark was digitized, avoiding sargasso deposited by a storm or extreme event.
Rocky
The coast is characterized as rocky when water is observed to impact the rock. The instantaneous lines were digitized in the Rocky formation.
The DEM for 2015-2017 was used to calculate the slope in the coastal areas in order to classify the cliff areas. Areas with a slope greater than 40 degrees digitized as “CLIFF.” However, some cells between "cliff" areas could be 20 degrees. In cliff areas where the instantaneous line was seen on the ocean side, the area was digitized as "Bare Land" with a description of "Rocky land." For the shoreline type of "Rocky," the area can have a description of "Cliff," "Bare Land” or "Rocky Barrier."
Rocky areas off the coast within a 300 meters buffer of the shoreline were digitized as “Bare Land” or “Cliff.”
The slope information and Google Earth were used to help distinguish the vegetated shoreline amongnst rocky areas.
Rocky Barriers
The rocky barriers were identified as areas where rocky land and sandy beaches were divided by water. This feature was classified as a reference for further shoreline change analysis. To identity rocky barriers, the benthic layers helped to identify features like coral reefs. Pocket beaches mostly between rocky areas were mostly digitized using the instantaneous line proxy.
Anthropogenic
Marina areas like boating docks were digitized up to 500 meters inland of the shoreline area.
Tourism areas were classified using other sources such as Puerto Rico Land Cover 2010. When no information was available, the concrete forms were classified as “Housing.”
Vegetation
To classify the vegetation, the land cover classification was followed.
In small sandy areas around mangroves, the HWL was digitized to capture sand accumulation.
No Visibility
Palms trees or shadows created by them were classified as “Shadows.” In cases where areas mostly shadows were present, even small sections of the HWL were digitized if visible. If the HWL or any other indicator was not visible, it was classified as "Other." When no orthophoto was available, the area was classified as "Not Surveyed."
In areas where the HWL was not visible, but sand accumulation was seen, other proxies were digitized: instantaneous line, wet/dry line, or groundwater exit point.
Hard Structures
When multiple hard structures were seen, it was classified as “Multiple Structures.” For example, when mitigation structures and construction filling areas were seen, it was classified as “Multiple Structures." Rip-rap covered by water was also digitized if visible.
Other Considerations
River mouth areas were digitized up to 500 meters inland and where some of the water or vegetation connect the shoreline area.
The sandy areas around the river mouth were digitized as HWL.
If a continuous beach was seen along the river mouth areas, the river mouth was not digitized.
2015-2017 USGS Lidar DEM Puerto Rico
2000-2002 Benthic Habitat
Puerto Rico Land Cover 2010
2009-2010 USACE NCMP 4 Band Bit Imagery
2006-2007 Orthophoto
Culebra and Vieques Aerial Images 1964-1978
20200101
Shoreline Vieques and Culebra 1970 feature class
Coastal Research and Planning Institute of Puerto Rico (CoRePI-PR), Graduate School of Planning, UPR-RP.
Loderay Bracero Marrero
Research Assistant Lead
mailing and physical
Station 1001
San Juan
Puerto Rico
00925
Puerto Rico
787764000, ext. 85118 or 85119
loderay.bracero@upr.edu; coastal.planning@upr.edu
The geodatabase was transferred to USGS for final processing steps. The geodatabase feature class was exported as a shapefile (ArcToolbox >> Conversion >> To Shapefile >> Feature Class to Shapefile (multiple)), ensuring that the "Transfer field domain descriptions" was checked in the Environment Settings.
A "YEAR" field was added and calculated based on the IMG_DATE field so shorelines could be easily grouped by year.
Finally, the shapefile was projected (ArcToolbox >> Data Management >> Projections and Transformations >> Project) to WGS 1984 using the Puerto_Rico_To_NAD_1983 + Puerto_Rico_to_WGS_1984_4 geographic transformation.
Shoreline Vieques and Culebra 1970 feature class
2021
Shoreline_Puerto_Rico_Vieques_Culebra_1970.shp
Julia L. Heslin
U.S. Geological Survey, Woods Hole Coastal and Marine Science Center
Geographer
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02543
USA
508-457-2262
jheslin@usgs.gov
Vector
String
1392
0.0198254372
0.0207098977
Decimal seconds
WGS_1984
WGS_84
6378137.0
298.257223563
Shoreline_Puerto_Rico_Vieques_Culebra_1970.shp
Table containing attribute information associated with the data set.
Producer Defined
FID
Internal feature number.
ESRI
Sequential unique whole numbers that are automatically generated.
Shape
Feature geometry.
ESRI
Coordinates defining the features.
USER
Person who digitized the shoreline section.
Producer Defined
NIAS HERNANDEZ MONTCOURT
Person who digitized the line section.
Producer defined
RUBEN O. MALDONADO GONZALEZ
Person who digitized the line section.
Producer defined
LODERAY BRACERO MARRERO
Person who digitized the line section.
Producer defined
SHORE_TYPE
The shoreline general category. A subtype or description was created for each category.
Producer Defined
BEACH
Unconsolidated sediment deposit (sand and gravel)Komar, P. 1998. Beach Processes and Sedimentation: Prentice Hall, second edition, p.25
Producer defined
ROCKY
Rocky features including rocky outcrop (volcanic/sedimentary and/or metamorphic), eolianite and/or beach rock formations.
Producer defined
VEGETATION
Shoreline type that includes wetlands, mangrove, forests, pasture, among other vegetation.
Producer defined
HARD STRUCTURE
Mitigation structure placed on the shoreline, both formal and informal structures.
Producer defined
ANTHROPOGENIC
Any type of anthropogenic structure build-up in the coast. This may range from small to large structures.
Producer defined
NO VISIBILITY
This item was used to identify areas where the classification was not possible to perform. Example: presence of clouds.
Producer defined
SHORE_DESC
This a more detailed classification of the coast. In this field, the shoreline proxies are identified.
"SHORE_DESC" further classifies "SHORE_TYPE."
Producer Defined
HIGH WATER LINE
Change in color or shade of the beach sand. For panchromatic images, the higher contrast seen between the wet and dry. It is visually determined as a change in tone left by the maximum runup from a preceding high tide, leaving a contrast between dry and wet sand. The HWL was digitized in the pocket beach. It should not be confused with storm and/or swell lines. The intersection of the land with the water surface at an elevation of high water. (Boak and Turner, 2005).
Producer defined
WET/DRY LINE OR RUN UP MAXIMA
The line between the dry and wet zones seaward of the High Water Line (HWL).
Producer defined
GROUNDWATER EXIT
Darker area created after the wave has broken and returns to the water.
Producer defined
INSTANTANEOUS LINE
Where a wave breaks; often observed as a foaming mass of water.
Producer defined
CLIFF
Areas with a slope greater than 40 degrees is considered "Cliff." However, some cells between these values might be 20 degrees (Hampton and Griggs, 2004, p. 1).
Producer defined
BARE LAND
Exposed rock, inland or on the coastline with little or no vegetation cover with a low slope.
Producer defined
ROCKY BARRIER
Exposed rock in the form of a barrier limiting the entry of water completely. It can be found on the shore, nearshore and/or offshore.
Producer defined
MANGROVE
All vegetation that was classified in the 2010 Puerto Rico Land Cover C-CAP layer, as Estuarine Forested Wetland or Estuarine Emergent Wetland was classified as "Mangrove" here (Puerto Rico Land Cover C-CAP 2010 (2017)). At least 300 meters inland was digitized.
Producer defined
FOREST/SHRUB
Shrub: a shrub smaller than a tree and can be found individually on the coast. Forest: large area covered by trees and other vegetation. Name of the classification in the Land Cover layer: Scrub/Shrub and Upland Forest (Puerto Rico Land Cover C-CAP 2010 (2017)).
Producer defined
PALUSTRINE
An area with little vegetation, such as grass, seen on the shoreline, especially around river mouths. Name of the classification in the Land Cover layer: Palustrine Forested Wetland Areas (Puerto Rico Land Cover C-CAP 2010 (2017)).
Producer defined
SEAWALL
It is a massive structure built of concrete to protect the shoreline from wave activity, and its own weight provides the stability it requires to prevent it from sliding (USACE, 2002; Aponte, 2019).
Producer defined
BREAKWATER
These are mostly built with concrete or rocks. Their location, mainly, is parallel to the coastline. They are also used to protect the infrastructure (residences, stores, etc.) from the force of the waves and to widen the beach width (Aponte, 2019).
Producer defined
RIP-RAP
Rocks, mostly round, placed in a linear fashion for the purpose of protecting structures near the coast, considered formal mitigation structures and informal constructions through the coastline (Aponte, 2019).
Producer defined
BULKHEADS
Vertical retaining walls used to support or prevent the soil from sliding into the sea (USACE, 2002; Aponte 2019).
Producer defined
HOUSING
Houses close to the shoreline. Interpreted from aerial photos and Google Earth.
Producer defined
TRANSPORTATION
Roads (primary, secondary, tertiary), ramps, entrances or exits for boats or pipelines. Interpreted from aerial photos and Google Earth.
Producer defined
TOURISM
Spaces used for recreation and/or as a center of attraction. They can be boardwalks, squares near the coast, lookout points, etc. Interpreted from aerial photos and Google Earth.
Producer defined
PIERS
Bridges for pedestrians, cars, and boats. Interpreted from aerial photos and Google Earth.
Producer defined
MARINAS
Space designed for parking boats. Usually contains docks, bridges, and boats. Interpreted from aerial photos and Google Earth.
Producer defined
SHADOWS
Shadows generated by the presence of trees, houses and other types of structures. Usually, you can see that the shadow is created by a structure and not by the image itself.
Producer defined
CLOUDS
Presence of clouds at the time the aerial image was taken. These clouds limit the visualization completely and impedes the digitizing process.
Producer defined
BRIGHTNESS
The photo is too bright. The coast looks extremely white and the contrasts do not improve the quality.
Producer defined
NOT SURVEYED
Area was not surveyed by the dataset used, meaning no aerial photo was available.
Producer defined
OTHER
Any other reason not considered in the previous classifications where the shoreline was not visible.
Producer defined
IMG_REF
Images used to digitize the shoreline.
Producer Defined
Mosaic Culebra Aerial Images 1964, 1972
Years when air photo survey was conducted
Producer defined
Mosaic Vieques Aerial Images 1972, 1978
Years when air photo survey was conducted
Producer defined
IMG_DATE
Date of the image. A month and day of January 1 was assigned for those images that no exact date was found.
Producer Defined
01/19/1964
08/29/1978
AREA_COVERED
Geographical area in which the shoreline lies.
Producer Defined
Vieques
Island to the east of Puerto Rico
Producer defined
Culebra
Island to the east of Puerto Rico
Producer defined
UNCY
Uncertainty value for the shoreline derived from the Georeferencing error (RMSE), the digitization error, and HWL position error.
Producer Defined
3.70
3.70
YEAR
The year of the shoreline taken from the IMG_DATE field.
Producer Defined
1964
1978
U.S. Geological Survey - ScienceBase
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Shapefile
ArcGIS 10.7
ESRI Polyline Shapefile
Dataset contains the shapefile, browse graphic, and CSDGM metadata.
31.0
https://doi.org/10.5066/P9SEUAHC
https://www.sciencebase.gov/catalog/file/get/6140c006d34e1449c5d5ff3f
https://www.sciencebase.gov/catalog/item/6140c006d34e1449c5d5ff3f
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.
N/A
20211117
Julia L. Heslin
U.S. Geological Survey, Woods Hole Coastal and Marine Science Center
Geographer
mailing and physical
384 Woods Hole Road
Woods Hole
MA
02543
USA
508-457-2262
508-457-2310
jheslin@usgs.gov
Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998