Historic shoreline positions for Rincon, Puerto Rico 1936-2006 (shorelines.shp)

This process step describes the methods used to digitize shoreline positions for the following years: 1963, 1971, 1974, 1977, 1987 and 1989. Seven sets of near-vertical, overlapping aerial photographs were used to obtain historical shoreline positions. The data included sets of photography from 1950 as well but was discarded after determining that the original input data were flawed. All have a nominal scale of 1:20,000, were flown during winter months, and except the 1987 set which used natural color film, were taken in black and white.
A ground control network for the air photos was developed by identifying a number of common features on most or all of the photograph sets. Stable reference features such as buildings and road intersections were identified and their approximate locations marked on a U.S. Geological Survey (USGS) 7.5-minute topographic map. The points were then precisely located in the field and a more specific, stable target (e.g., a building comer, sidewalk, etc.) identifiable on the photographs was surveyed using a differential Global Positioning System (GPS) receiver. The points used in this study are accurate horizontally within 3 m and vertically to within about 6 m.
Once the basic control network was established, a suite of pass points (common points appearing on two or more photos for which precise geographic information is unknown) was identified to provide further relative control for the photos within each time series. To provide a very "tight" control network and permit greater photogrammetric accuracy, the photo sets for each date included frames that were well inland from the shoreline.
The air photos were digitized using a 12x lighted magnifying loupe to aid in identification of the fiducial reference marks around the photo border, ground control points, pass points, and the shoreline. The wet/dry line on the beach, the reference feature used in the field surveys described below, was used to delineate the shoreline in each photo. The wet/dry line is the most frequently used shoreline for digitizing because it is easily identified by the tonal difference between wet and dry sand. Where available, camera system calibration data were used to correct the photographs for film distortion and assess the magnitude of lens distortion. The National Ocean Service's General Integrated Analytical Triangulation (GIANT) aerotriangulation program was used to solve simultaneously for the camera position and angular orientation parameters for the air photos. GIANT was also used to remove atmospheric refraction effects from the aerotriangulation solution. Statistical output from GIANT indicated an accuracy of +4 m for the air photo-derived shoreline locations.
The camera parameters for each photo were used to compute a single-ray intersection solution for the digitized shoreline points. A geographic coordinate system based on the WGS84 ellipsoid was used in shoreline position calculations for consistency with the GPS control point surveys and the field shoreline surveys. The output shoreline position data files for each photo were imported into separate overlays (one for each year of photography) in Maplnfo TM, a Macintosh®-based Geographic Information System (GIS), and joined to adjacent photo data to form a continuous shoreline.

This process step describes the methods used to digitize shoreline positions for the following years: 1936, 1983, and 1987. Aerial photographs were scanned into digital format (.tif) at 600 dpi. The 2004 True Color Orthoimages (U.S. Army Corps of Engineers) were used as a reference for the creation of Ground Control Points (GCPs) to geometrically correct all aerial photographs. No RMS error greater than 0.03 was used. A Direct Linear Transform (DLT) model was utilized. All photographs were re-sampled to 1-meter pixel resolution using nearest neighbor re-sampling. Three image mosaics, one for each survey year, were created (1936, 1983 and 1987). Cutlines were manually created following general linear features. Areas of overlap were feathered by a distance of 10-meters. All images were histogram matched to decrease variability between images

This process step describes the methods used to digitize shoreline positions for the following years: 1994, 2005 and 2006. Field surveys of wet/dry shoreline positions were conducted on 24 August 1994, 06 December 2005, and 05-06 December 2006. These surveys utilized a backpack-mounted GPS receiver logging positions at 5- second intervals as the backpacker walked along the wet/dry line. The wet/dry line is the most frequently used shoreline for digitizing because it is easily identified by the tonal difference between wet and dry sand. The data were differentially corrected in real-time in the field. Further post-processing yielded a positioning accuracy of 2-3 m. The GPS data were imported directly into the GIS for display with the shorelines obtained from the photographs.

The final shoreline file for each year was coded with 6 attribute fields (ID, Type, Date, Descr, Source, and Accuracy) required for the Digital Shoreline Analysis System (DSAS), which was used to calculate shoreline change rates.

The metadata was edited to remove errors as well as update some information. Edits include updating the citation section with the DOI link and a slight modification to the dataset title, added the USGS Thesaurus, added keywords section with USGS persistent identifier as theme keyword, replaced distribution liability with FSP statement. Other unrequired blank fields were deleted, duplicate entries within a field were deleted, required empty elements were fixed with “information unavailable from original metadata”. The metadata date (20070222), but not the contact (except email and contact instructions) was updated. The metadata available from a harvester may supersede metadata available from the publication. Compare the metadata dates to determine which metadata file is most recent. The metadata available from a harvester may supersede metadata available from the publication. Compare the metadata dates to determine which metadata file is most recent.