Erika E. Lentz

Geologic Evidence for Onshore Sediment Transport from the Inner Continental Shelf: Fire Island, New York

ABSTRACT Schwab, W.C.; Baldwin, W.E.; Hapke, C.J.; Lentz, E.E.; Gayes, P.T.; Denny, J.F.; List, J.H., and Warner, J.C., 2013. Geologic evidence for onshore sediment transport from the inner continental shelf: Fire Island, New York. Sediment budget analyses along the south shore of Fire Island, New York, have been conducted and debated in the scientific and coastal engineering literature for decades. It is well documented that a primary component of sediment transport in this system is directed alongshore from E to W, but discrepancies in volumetric sediment budget calculations remain. An additional quantity of sand, averaging about 200,000 m3/y is required to explain the growth of the western segment of the barrier island, a prograding spit. Littoral sediment derived from updrift erosion of the coast, addition of beach nourishment fill, and onshore transport of inner continental shelf, shoreface sediments, or both have all been proposed as potential sources of the additional sediment needed to balance the sediment budget deficit. Analysis of high-resolution seafloor mapping data collected in 2011, including seismic reflection profiles and inteferometric sonar acoustic backscatter and swath bathymetry; comparison with seafloor mapping data collected in 1996–1997; and shoreline change analysis from 1933 to 2011 support previous suggestions that the inner-shelf Holocene sedimentary deposit is a likely source to resolve this sediment budget discrepancy.

A Review of Sediment Budget Imbalances along Fire Island, New York: Can Nearshore Geologic Framework and Patterns of Shoreline Change Explain the Deficit?

Abstract Sediment budget analyses conducted for annual to decadal timescales report variable magnitudes of littoral transport along the south shore of Long Island, New York. It is well documented that the primary transport component is directed alongshore from east to west, but relatively little information has been reported concerning the directions or magnitudes of cross-shore components. Our review of budget calculations for the Fire Island coastal compartment (between Moriches and Fire Island Inlets) indicates an average deficit of 217,700 m3/y. Updrift shoreline erosion, redistribution of nourishment fills, and reworking of inner-shelf deposits have been proposed as the potential sources of additional sediment needed to rectify budget residuals. Each of these sources is probably relevant over various spatial and temporal scales, but previous studies of sediment texture and provenance, inner-shelf geologic mapping, and beach profile comparison indicate that reworking of inner-shelf deposits is the source most likely to resolve budget discrepancies over the broadest scales. This suggests that an onshore component of sediment transport is likely more important along Fire Island than previously thought. Our discussion focuses on relations between geomorphology, inner-shelf geologic framework, and historic shoreline change along Fire Island and the potential pathways by which reworked, inner-shelf sediments are likely transported toward the shoreline.

UAS-SfM for Coastal Research: Geomorphic Feature Extraction and Land Cover Classification from High-Resolution Elevation and Optical Imagery

The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy.