Kevián A. Pérez-Valentín Maritza Barreto-Orta Legna M. Torres-García David Carrión Brittany Ubinas Samiris Suleimán Bianca Rodríguez 20260626 vector digital data Kevián A. Pérez-Valentín Maritza Barreto-Orta Legna M. Torres-García David Carrión Brittany Ubinas Samiris Suleimán Bianca Rodríguez 20260626 U.S. Geological Survey data release doi:10.5066/P13R6R7K St. Petersburg, Florida U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center https://doi.org/10.5066/P13R6R7K These geospatial datasets correspond to the extraction of elements and their attributes related to the shoreline and back beach of eleven (11) municipalities in the northwest and north coasts of Puerto Rico (Rincón, Aguadilla, Isabela, Hatillo, Arecibo, Dorado, Vega Baja, Carolina, Loíza, Río Grande, and Luquillo). These data were generated as part of the "U.S. Geological Survey (USGS) Development of Coastal Change Capacity in Puerto Rico" project (Cooperative Agreement G23AC00551-02). Cartographic information is organized into eight data types for the purpose of analysis and monitoring of changes along selected municipalities of the northwest and north coast of Puerto Rico. The "Federal Emergency Management Agency-University of Puerto Rico at Río Piedras (FEMA-UPRRP) Post-María Beach Assessment" project, which the Coastal Research and Planning Institute of Puerto Rico (CoRePI-PR) team published in 2021 (FEMA-4339-DR-PR Grant No. 4339-0007p), served as the baseline for the creation of these datasets. This dataset modifies the techniques established by Barreto and others (2021), which integrates high-resolution image analysis, field data collection, and an assessment of the pre-existing conditions of the beaches using Geographic Information Systems (GIS) (FEMA-4339-DR-PR Grant No. 4339-0007p). The data types are as follows: 1) shoreline, 2) back beach, 3) beach edges, 4) beach polygons, and 5) beach transects (5-meters), 6) beach transects 2018 vs. 2022–2023, 7) lost transects and 8) beach displacement. In addition to providing shapefiles (.shp) with this data release, these data are packaged into a file geodatabase (.gdb) and ArcGIS Pro Map Package file (.mpkx) for enhanced visualization of the data. This dataset provides a rigorous approach to the acquisition, extraction, and processing of geospatial data related to the coastal changes on the Puerto Rico North Coast. The dataset supports the systematic classification and analysis of coastal types and geomorphic variability using aerial images from 2018, 2022, and 2023 (Barreto and others, 2021). The subtypes and domains presented in this data release enhance the accuracy of shoreline classification and coastal change analysis, leading to a better understanding of shoreline features, geomorphic changes, and environmental dynamics. These datasets include information on coastal shoreline displacement (using high water line as a proxy). This information was extracted from high-resolution aerial images from 2018 and 2022–2023 period. The source aerial imagery from 2018 [Barreto and others, CoRePI-PR, unpublished data] and the imagery from 2022–2023 [Pérez-Valentín, CoRePI-PR, unpublished data] used in this study are not publicly available. 20180701 20231231 ground condition Complete None planned -67.2711728 -65.6688773 18.5154982 18.2965845 USGS Metadata Identifier USGS:c9b95c04-d742-4073-a591-939f548e4c55 ISO 19115 Topic Categories biota environment geoscientificInformation inlandWaters oceans planningCadastre structure USGS Thesaurus erosion shoreline accretion coastal processes hurricanes geospatial analysis geospatial datasets None back beach back beach type Digital Shoreline Analysis System DSAS shoreline shoreline type environment edges beach coastal infrastructure Hurricane Fiona Geographic Names Information System (GNIS) Commonwealth of Puerto Rico Island of Puerto Rico Aguadilla Arecibo Carolina Dorado Hatillo Isabela Loíza Luquillo Rincón Vega Baja Río Grande None 2018 2022 2023 No access constraints. Please see 'Distribution Information' for details. These data are marked with a Creative Commons CC0 1.0 Universal License. These data are in the public domain and do not have any use constraints. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. Graduate School of Planning of the Río Piedras Campus of the University of Puerto Rico Kevián Augusto Pérez-Valentín Research Assistant mailing and physical

10 Ave. Universidad STE 1001

San Juan Puerto Rico 00925-2530 USA (787)764-0000 kevian.perez@upr.edu In collaboration with the USGS St. Petersburg Coastal and Marine Science Center (SPCMSC), this dataset was produced by a team of researchers and research assistants from the Graduate School of Planning and the Environmental Science Department of the University of Puerto Rico, Río Piedras Campus (UPR-RP). Listed below are the team members who worked on the digitization process: Principal investigator: Maritza Barreto-Orta (UPR-RP) Investigator: Kevián A. Pérez-Valentín (UPR-RP) Project Director: Legna Torres-García (USGS) Project administrator: Wilma González and Vanessa Villanueva Graduate Research Assistants (Graduate School of Planning at the University of Puerto Rico): Samiris Suleimán, Brittany Ubinas, and David Carrión Undergraduate Research Assistants (Environmental Science Department at the University of Puerto Rico): Bianca Rodríguez The 2018 (CoRePI_2018_Imagery) and 2022–2023 aerial imagery (CoRePI_Drone_Field_Images_2022_2023) data are not publicly available (owing to restrictions of proprietary interest) from the Coastal Research and Planning Institute of Puerto Rico (CoRePI-PR). Contact the CoRePI-PR for further information. This work was supported by supplemental funds from the Extending Government Funding and Delivering Emergency Assistance Act (Public Law 117-43). Environment as of metadata creation: Microsoft® Windows® 11 Enterprise (version 23H2); ESRI® ArcGIS Pro (version 3.6.1) and ESRI® Field Maps; Digital Shoreline Analysis System (DSAS) version 5.1; Microsoft® Word® Microsoft 365 MSO (Version 2511). Maritza Barreto Rafael Méndez Tejeda Nahir Cabrera Valeria Bonano Elizabeth Díaz Kevián Pérez Aurelio Castro 20211231 Número Especial Erosión Costera y Dinámica Litoral No. 1 (2021) Online Revista Geográfica De Chile Terra Australis https://doi.org/10.23854/07199562.2021571esp.Barreto29 After completing digitization, a quality assurance and quality control (QA/QC) process was carried out by two GIS analysts and coastal experts to validate the classified subtypes and domains used in the datasets. Please see the process steps for more information. No formal logical accuracy tests were conducted. Dataset is considered complete for the information presented, as described in the abstract. The information presented in this data release were validated with field visits, drone images taken during the 2022–2023 period, and global positioning system (GPS) data collected across the 11 coastal municipalities [Pérez-Valentín, CoRePI-PR, unpublished data]. The dataset was generated using a combination of tracing method, free hand tool, and field validation. The following topology rules were used in the digitization process to describe the relationship within and across all feature classes: Must Not Overlap, Must Not Intersect, Must Not Have Dangles, Must Not Self Overlap, and Must Not Self Intersect. Some transects may have positional accuracy variations due to differences in image resolution. For the 11 coastal municipalities that were the subject of the study, the average digitization error was 1.20 meters (m). Each municipality's digitization error was: Continuous orthophoto coverage of Carolina-Loíza: 2.96 m; Continuous orthophoto coverage of Aguadilla-Isabela: 1.33 m; Arecibo: 1.25 m; Dorado: 1.44 m; Hatillo: 1.25 meters Geometric Similarity Analysis of Isabela (0.68 m), Loíza (0.60 m), and Río Grande and Luquillo (1.06 m), Rincón (1.07 m) and Vega Baja (1.24). The similarity between the 2018 and 2022–2023 calibration polygons from was evaluated using the Jaccard Similarity Index (JSI), calculated as the ratio between the area of intersection and the area of the unions of the polygons (Jaccard Similarity Index = Intersection Area/Union Area). The JSI measures spatial overlap over time using polygons, where values closer to 1 represent greater spatial agreement, where lower values indicate positional and spatial discrepancies. Calibration polygons are historical or permanent structures that were established in both images. This index calculates the degree of overlap or similarity between the two polygons increases with the index value's proximity to 1, indicating less geometric distortion between layers. In comparison to 2018, the 2022–2023 polygons' Jaccard Similarity Index was 0.8217, or 82.17% similarity across all images under study. Emily A. Himmelstoss Rachel E. Henderson Amy S. Farris Meredith G. Kratzmann Marie K. Bartlett A. Ergul J. McAndrews R. Cibaj J. L. Zichichi E. Robert Thieler 20211010 5.1 software Reston, VA U.S. Geological Survey https://doi.org/10.5066/P13WIZ8M software 20211010 publication date DSAS Digital Shoreline Analysis System (DSAS) was not used to generate beach transects or calculate shoreline change rates. Instead, this dataset employed an adapted version of the Net Shoreline Movement (NSM) equation developed by USGS (Himmelstoss and others, 2021), which calculates the total movement (meters) between two shoreline positions. Perpendicular transects were generated between the shorelines of July 2018 and the 2022–2023 period. Transect selection was established at 5 meters distance where both shorelines were present. Transects with no net shoreline movement due to the presence of anthropogenic structures or coastal cliffs were discarded. Coastal areas that underwent transitions from beach to rocky coasts and in which net shoreline movement was documented regardless of the coastal type were considered as an element of analysis. M. Barreto A. Castro N. Cabrera E. Díaz K. Pérez M. López L. Santiago R. Méndez Unpublished remote-sensing imagery University of Puerto Rico, San Juan, Puerto Rico Coastal Research and Planning Institute of Puerto Rico (CoRePI-PR) (HMGP) FEMA-4339-DR-PR Subgrantee Number 4339-0007P Not available digital orthophoto imagery 20180701 ground condition CoRePI_2018_Imagery High-resolution aerial imagery acquired in 2018. The imagery was used as the baseline dataset for shoreline digitization and beach polygon mapping. Source_Restrictions: The 2018 aerial imagery data are not publicly available (owing to restrictions of proprietary interest) from the Coastal Research and Planning Institute of Puerto Rico (CoRePI-PR). Contact the CoRePI-PR for further information. Kevián A. Pérez Valentín Unpublished remote-sensing imagery University of Puerto Rico, San Juan, Puerto Rico Coastal Research and Planning Institute of Puerto Rico (CoRePI-PR) Not available digital imagery 20220101 20231231 ground condition CoRePI_Drone_Field_Images_2022_2023 Drone imagery repository, field imagery, and data were collected using ESRI® Field Maps from 2022–2023 by Kevián A. Pérez Valentín, researchers and research assistants as part of ongoing coastal monitoring efforts conducted by the CoRePI-PR. These images were used for field validation and for interpretation purposes only. The imagery is for internal use of CoRePI-PR and is not published. Contact the CoRePI-PR for further information. National Centers for Coastal Ocean Science (NCCOS) 20170727 vector digital data Online National Oceanic and Atmospheric Administration (NOAA) https://coastalscience.noaa.gov/project/benthic-habitat-mapping-puerto-rico-virgin-islands/ shapefile 2000 2002 ground condition benthic habitat map Cartographic source for validating the presence and identification of natural structures in Puerto Rico. IMAGE DATA COLLECTION AND DIGITIZATION: This dataset modifies the techniques established by Barreto and others (2021), which integrates GIS, high-resolution image analysis, field data collection, and an assessment of the pre-existing conditions of the beaches. The digitization process was carried out using high-resolution aerial imagery by researchers from the CoRePI-PR and undergraduate and graduate students from the University of Puerto Rico, Río Piedras Campus from the Graduate School of Planning and Environmental Science Department. The digitization scale used was 1:500, and the Ground Sample Distance (GSD) of the high-resolution aerial photos taken during the 2022–2023 timeframe was 15 centimeters (cm). Images from July 2018 and the January 2022–March 2023 timeframe were used for the calibration process (Barreto and others, 2021). During this period, Hurricane Fiona impacted Puerto Rico. Historical buildings or structures that were present in both datasets were recognized in each image. In order to determine the margin of error between the 2018 photos and the 2022–2023 mosaics, more than 200 homogeneous objects (permanent structures, etc.) were also identified and digitized using the calibration reference structures as a guide and/or through photointerpretation. To enhance precision, and maintain methodological consistency with Barreto and others (2021), objects located too close to one another were not included, as their spatial proximity increase uncertainty in feature delineation. Whenever feasible, a minimum distance of two kilometers (km) was maintained. Field validation was performed using drones, GPS, and ESRI® Field Maps (Barreto and others, 2021). Each image featured a minimum of one structure per municipality. Priority for digitization was given to structures that had not changed over time. Every object was shown at a 1:1000 scale and digitized at the same scale as the coastline (1:500). The differences between one polygon's endpoints (at least four corners) and its matching polygon were measured using the "measure distance" tool in ArcGIS Pro 3.6.1. For each year, a polygon was drawn using the "create" and "edit" tools, producing two polygons: July 2018 was represented by the first polygon. January 2022–March 2023 was represented by the second polygon. July 2018 polygon's vertices, designated A, B, C, and D, were measured clockwise using the "measurement" tool. The January 2022–March 2023 polygon's vertices were designated A', B', C', and D'. CoRePI_2018_Imagery CoRePI_Drone_Field_Images_2022_2023 2023 SHORELINE: In this dataset, a coastal type classification was developed as part of the digitalization process to characterize the geomorphic and geological diversity of the Puerto Rican shoreline. The main coastal types include: 1) Alluvial (shorelines mainly associated with river mouths and minor alluvial systems); 2) Anthropogenic structures (coastal protective hard structures and/or residential structures in the shoreline); 3) Beach (shoreline composed of unconsolidated sand and/or gravel material at the high water line); 4) Rocky (shoreline segments composed of consolidated geological material). This coastal type employs the wet/dry zone as the primary indicator for digitization in rocky shorelines; 5) Vegetation (for this shoreline, the maximum extent of the closed canopy was used as an indicator). Additionally, two (2) complementary categories were incorporated to facilitate the digitization workflow: 6) Not Surveyed (applied to segments not present in the aerial imagery under study; these shorelines were validated with field data); and 7) Undefined (used to categorize shorelines that could not be classified into the main coastal types due to indistinct geomorphological or geological features resulting from shadows, cloud cover, or poor image quality). After completing the digitization process, a QA/QC process was carried out by two GIS analysts and coastal experts to validate the classified subtypes and domains. Identification and classification of natural structures were identified using photointerpretation, field inspections, and a benthic habitat map from NOAA NCCOS (2017). If the feature could not be classified using these methods, it was designated as "Undefined". benthic habitat map 2025 North_Coast_Puerto_Rico_Shoreline_2022_2023 BACK BEACH: In this dataset, the term 'back beach' refers to the zone of the subaerial beach that delineates the physical boundary in an aerial image between the unconsolidated sand, coastal vegetation, rocks, coastal cliffs, coastal bluffs, compacted sand, dirt roads, dunes, and/or structures of anthropogenic origin (Barreto and others, 2021). The back beach categories include (1) Compacted sand/dirt road/unpaved road, (2) Dunes, (3) Infrastructure, (4) Mitigation Hard Structures, (5) Riverine/Bar, (6) Road, (7) Rock, (8) Vegetation, (9) Undefined, and (10) Other. The visual limit of these categories in an aerial image was used as a proxy for the back beach indicator, representing the limit of the subaerial beach. 2025 North_Coast_Puerto_Rico_Back_Beach_2022_2023 BEACH EDGES: This dataset defines beach edges as the lateral boundary that allows the back beach to be joined with the shoreline and edges (Barreto and others, 2021). This facilitated the creation of the beach polygon by linking these three features. The resulting vector polygon is a representation of the subaerial beach system for the study period (2022–2023). The principal edge categories include (1) Tombolo, (2) Infrastructure, (3) Rock, (4) Sand, (5) Vegetation, (6) Mitigation Hard Structure, (7) Road, (8) Riverine/Bar, (9) Dune, and (10) Other. Additionally, a complementary beach edge category was incorporated to facilitate the digitization workflow: (11) Undefined (used to categorize beach edges that could not be classified into the main coastal types). For these data, all beach edges were validated using field data, and therefore 'Undefined' was not used. 2025 North_Coast_Puerto_Rico_Beach_Edges_2022_2023 BEACH POLYGON: The beach polygon is the result of merging three features: the shoreline, back beach, and beach edges. North_Coast_Puerto_Rico_Shoreline_2022_2023 North_Coast_Puerto_Rico_Back_Beach_2022_2023 North_Coast_Puerto_Rico_Beach_Edges_2022_2023 2025 North_Coast_Puerto_Rico_Beach_Polygon_2022_2023 2018–2022 TO 2023 TRANSECTS AND LOST TRANSECTS: Transects from July 2018, initially produced by DSAS (Himmelstoss and others, 2021), in a prior study (CoRePI-PR, 2021; FEMA-4339-DR-PR Grant No. 4339-0007p). These transects were used to assess erosion and/or accretion throughout the 2022–2023 period. The transects lost to erosion were studied from this layer. A point layer was created from these transects, North_Coast_Puerto_Rico_Lost_Transects_20182022_2023. North_Coast_Puerto_Rico_Lost_Transects_20182022_2023 2025 EROSION/ACCRETION BEACH TRANSECTS: This data release also contains coastal change data (measured erosion or accretion) from July 2018 to 2022–2023. The July 2018 transects were generated using DSAS (Himmelstoss and others, 2021) published in a previous study (Barreto and others, 2021). The first dataset, North_Coast_Puerto_Rico_Beach_Width_Transects_5m_Interval_2022_2023, was created by generating a reference line parallel to the beach polygon dataset (North_Coast_Puerto_Rico_Beach_Polygon_2022_2023) to follow the natural geometry of the beach. This line was drawn parallel to the maximum extent of the beach polygon. QA/QC was carried out to ensure that each line marking the maximum extent of the beach followed the orientation of the coast. Then, perpendicular transects were generated along the reference line using the "Generate Transects Along Lines" geoprocessing tool, at a 5-meter spacing. This 5-m transect dataset was used as an input to generate the North_Coast_Puerto_Rico_Beach_Erosion_Accretion_Transects_2018_2022_2023 dataset. DSAS 2025 North_Coast_Puerto_Rico_Beach_Erosion_Accretion_Transects_2018_2022_2023 North_Coast_Puerto_Rico_Beach_Beach_Width_Transects_5m_Interval_2022_2023 BEACH DISPLACEMENT: This dataset used an adapted version of the Net Shoreline Movement (NSM) equation developed by the USGS, which calculated the total movement between two shoreline positions (Himmelstoss and others, 2021). Perpendicular transects were generated between the shorelines of July 2018 and the 2022–2023 period. Transect selection was established at 5 meters distance where both shorelines were present. Transects with no net shoreline movement due to the presence of anthropogenic structures or coastal cliffs were discarded. These transects were necessary for calculating two metrics: Net Shoreline Movement (NSM) - the total movement of the shoreline between 2018 and the period 2022–2023; and Direction of Shoreline Displacement - the directional change of the shoreline between the two timeframes. The shoreline displacement was evaluated across four representative domains based on the photointerpretation of imagery. The domains include: 1) Inland Displacement (represents the landward movement of the shoreline, measured in meters, from sea to land); 2) Seaward Displacement (represents the outward movement of the shoreline toward the sea); 3) Structure Displacement (represents the seaward displacement caused by coastal structures; these structures may include formal mitigation structures, informal mitigation structures, or residential/commercial infrastructure); 4) Vegetation Displacement (represents shoreline displacement caused by changes in the vegetation canopy; the limit of coastal vegetation and forests was digitized to serve as an indicator of the shoreline). North_Coast_Puerto_Rico_Beach_Width_Transects_5m_Interval_2022_2023 2025 North_Coast_Puerto_Rico_Beach_Displacement_2018_vs_2022_2023 GEODATABASE AND MAP PACKAGE CREATION: The eight shapefiles created in the previous process steps were imported into a file geodatabase as a feature class and added to a blank map in an ArcGIS Pro Map Package (.mpkx) for inclusion in this data release. The symbology used for these features adapts the color scheme recommendations in the U.S. Geological Survey's Federal Geographic Data Committee (FGDC) Digital Cartographic Standard for Geologic Map Symbolization (https://doi.org/10.3133/tm11A2). For further information regarding the dataset's classification definitions (fields and domains), please refer to the Data Dictionary document accompanying this data release. 2025 North_Coast_Puerto_Rico_Shoreline_Analysis_2022_2023.gdb North_Coast_Puerto_Rico_Shoreline_Analysis_2022_2023.mpkx North_Coast_Puerto_Rico_Shoreline_Analysis_Data_Dictionary.docx Graduate School of Planning of the Río Piedras Campus of the University of Puerto Rico Kevián Augusto Pérez Valentín Research Assistant mailing

10 Ave. Universidad STE 1001

San Juan Puerto Rico 00925-2530 USA (787)764-0000 kevian.perez@upr.edu Vector State Plane Coordinate System 1983 NAD 1983 StatePlane Puerto Rico Virgin Isl FIPS 5200 (Meters) 0.9999825 -66.43333333333334 17.83333333333333 200000.0 200000.0 coordinate pair 0.0001 0.0001 meters D North American 1983 GRS 1980 6378137.0 298.257222101 North_Coast_Puerto_Rico_Shoreline_Analysis_2022_2023.zip: This zip file contains 8 shapefiles related to the shoreline and back beach of 11 municipalities in the northwest and north coasts of Puerto Rico. In addition to providing shapefiles with this data release, these data are packaged into feature classes stored in a file geodatabase (North_Coast_Puerto_Rico_Shoreline_Analysis_2022_2023.gdb) and ArcGIS Pro Map Package file (North_Coast_Puerto_Rico_Shoreline_Analysis_2022_2023.mpkx) for enhanced visualization of the data. For further information regarding the dataset's classification definitions (fields and domains), please refer to the Data Dictionary document accompanying this data release (North_Coast_Puerto_Rico_Shoreline_Analysis_Data_Dictionary.docx). The entity and attribute information were generated by the individual and/or agency identified as the originator of the dataset. Please review the rest of the metadata record for additional details and information. U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center USGS SPCMSC Data Management mailing and physical

600 4th Street South

Saint Petersburg FL 33701 United States 727-502-8000 gs-g-spcmsc_data_inquiries@usgs.gov North_Coast_Puerto_Rico_Back_Beach_2022_2023.shp, North_Coast_Puerto_Rico_Beach_Edges_2022_2023.shp, North_Coast_Puerto_Rico_Beach_Polygon_2022_2023.shp, North_Coast_Puerto_Rico_Beach_Erosion_Accretion_Transects_5m_Interval_2022_2023.shp, North_Coast_Puerto_Rico_Shoreline_2022_2023.shp, North_Coast_Puerto_Rico_Beach_Displacement_2018_vs_2022_2023.shp, North_Coast_Puerto_Rico_Beach_Erosion_Accretion_Transects_2018_2022_2023.shp, North_Coast_Puerto_Rico_Lost_Transects_2018_2022_2023.shp, North_Coast_Puerto_Rico_Shoreline_Analysis_2022_2023.gdb, North_Coast_Puerto_Rico_Shoreline_Analysis_2022_2023.mpkx, and North_Coast_Puerto_Rico_Shoreline_Analysis_Data_Dictionary.docx Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. shapefile, file geodatabase (Esri), ArcGIS Pro Map Package, comma-delimited text https://coastal.er.usgs.gov/data-release/doi-P13R6R7K/data/North_Coast_Puerto_Rico_Shoreline_Analysis_2022_2023.zip None 20260626 U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center USGS SPCMSC Data Management mailing and physical

600 4th Street South

Saint Petersburg FL 33701 United States 727-502-8000 gs-g-spcmsc_data_inquiries@usgs.gov Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998