North Puerto Rico Shoreline Analysis 2022–2023

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'.

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".

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.

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.

BEACH POLYGON: The beach polygon is the result of merging three features: the shoreline, back beach, and beach edges.

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.

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.

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).

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.