Application of Airborne LIDAR for Seacliff Volumetric Change and Beach-Sediment Budget Contributions

Young, Adam P.; Ashford, Scott A.

doi:10.2112/05-0548.1

Cited by 144 publications

(83 citation statements)

References 11 publications

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“…These two processes are observed to play an important role in controlling how the seacliffs contribute sediments to the OLC, whereas the composition of the cliffs (grain size) determines whether the failed material will remain on the beach. This research, along with current findings by others (Haas, 2005;Young and Ashford, 2006), illustrates the significance of these geological features for coastal resource management. The establishment of a baseline dataset in the region provides insight for quantifying changes based on longerterm geomorphological impacts from climate events (e.g., El Niño and/or sea level rise).…”

Section: Discussionsupporting

confidence: 82%

“…Through sediment provenance (Haas, 2005) and airborne lidar data (Young and Ashford, 2006;Young et al, 2009a), 50% or more of the sand supplied to the beach is estimated to be sourced from the seacliffs. This estimate is in marked contrast to the established paradigm that rivers in the OLC supply the majority of sand to the beach system with the cliffs being a minor source (Brownlie and Taylor, 1981;Inman and Jenkins, 1999).…”

Section: Study Areamentioning

confidence: 99%

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Morphological Expressions of Coastal Cliff Erosion Processes in San Diego County

Johnstone

Raymond

Olsen

et al. 2016

Journal of Coastal Research

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Section: Discussionsupporting

confidence: 82%

Section: Study Areamentioning

confidence: 99%

Morphological Expressions of Coastal Cliff Erosion Processes in San Diego County

Johnstone

Raymond

Olsen

et al. 2016

Journal of Coastal Research

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“…In contrast to the methods used in these studies, airborne Light Detection And Ranging (LiDAR) scanning enables short term mapping of small objects and surfaces with very little texture and contrast and offers new applications for coastal erosion studies. White and Wang (2003) and Young and Ashford (2006) used repeat airborne LiDAR data to estimate volumetric erosion and sediment pathways of non-permafrost coasts. Jones et al (2013) demonstrated suitability of airborne LIDAR data for landscape changes of arctic coastal lowlands, including volumetric changes due to coastal erosion.…”

Section: Introductionmentioning

confidence: 99%

Coastal erosion and mass wasting along the Canadian Beaufort Sea based on annual airborne LiDAR elevation data

et al. 2017

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Erosion of permafrost coasts has received increasing scientific attention since 1990s because of rapid land loss and the mobilisation potential of old organic carbon. The majority of permafrost coastal erosion studies are limited to time periods from a few years to decades. Most of these studies emphasize the spatial variability of coastal erosion, but the intensity of inter-annual variations, including intermediate coastal aggradation, remains poorly documented. We used repeat airborne Light Detection And Ranging (LiDAR) elevation data from 2012 and 2013 with 1 m horizontal resolution to study coastal erosion and accompanying mass-wasting processes in the hinterland. Study sites were selected to include different morphologies along the coast of the Yukon Coastal Plain and on Herschel Island. We studied elevation and volume changes and coastline movement and compared the results between geomorphic units. Results showed simple uniform coastal erosion from low coasts (up to 10 m height) and a highly diverse erosion pattern along coasts with higher backshore elevation. This variability was particularly pronounced in the case of active retrogressive thaw slumps, which can decrease coastal erosion or even cause temporary progradation by sediment release. Most of the extremes were recorded in study sites with active slumping (e.g. 22 m of coastline retreat and 42 m of coastline progradation). Coastline progradation also resulted from the accumulation of slope collapse material. These occasional events can significantly affect the coastline position on a specific date and can affect coastal retreat rates as estimated in long term by coastline digitalisation from air photos and satellite imagery. These deficiencies can be overcome by short-term airborne LiDAR measurements, which provide detailed and high-resolution information about quickly changing elevations in coastal areas.

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“…Vantage points, coverage, and access can be limited in ground-based surveys due to variable terrain, vegetation, and habitat sensitivity, and storm impacts can compound access issues through erosion, overwash, or breaching, making direct measurements difficult. Although there are remote sensing techniques that can alleviate many of the ground-based limitations (e.g., airborne lidar and satellite imagery) [16], the platforms and data are expensive or provide coverage at an unsuitable temporal or spatial resolution for small-scale site-specific observation [17]. As a result, areas of interest are often surveyed using multiple techniques to assess change over a range of timescales [18].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2017

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Abstract: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.

show abstract

Application of Airborne LIDAR for Seacliff Volumetric Change and Beach-Sediment Budget Contributions

Cited by 144 publications

References 11 publications

Morphological Expressions of Coastal Cliff Erosion Processes in San Diego County

Morphological Expressions of Coastal Cliff Erosion Processes in San Diego County

Coastal erosion and mass wasting along the Canadian Beaufort Sea based on annual airborne LiDAR elevation data

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

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