Florida and US East Coast Beach Change Metrics Derived from LiDAR Data Utilizing ArcGIS Python Based Tools

Robertson, Quin; Dunkin, Lauren M.; Dong, Zhifei; Wozencraft, Jennifer M.; Zhang, Keqi

doi:10.1007/978-3-319-58304-4_12

Cited by 9 publications

(4 citation statements)

References 9 publications

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“…The framework for feature extraction is based in GIS using a set of transects that circumnavigate Lake Michigan (Figure 4). The framework is implemented with the JALBTCX Toolbox (Figure 5), which is a toolbox available for Esri ArcGIS Pro that provides a standard workflow for the development of shoreline baselines and transects, and the extraction of coastal engineering metrics including nearshore geomorphology features, shoreline change, beach volume quantities and engineering resilience metrics (Robertson et al 2017). Additional inputs for bluff extraction include a smoothing parameter, a cross-shore limit, a bluff percent slope minimum, and a minimum bluff elevation.…”

Section: Jalbtcx Toolboxmentioning

confidence: 99%

Geomorphic feature extraction to support the Great Lakes Restoration Initiative’s sediment budget and Geomorphic Vulnerability Index for Lake Michigan

Sylvester¹,

Spurgeon²,

McGill³

et al. 2023

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Section: Jalbtcx Toolboxmentioning

confidence: 99%

Geomorphic feature extraction to support the Great Lakes Restoration Initiative’s sediment budget and Geomorphic Vulnerability Index for Lake Michigan

Sylvester¹,

Spurgeon²,

McGill³

et al. 2023

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“…In addition, the time series of ALB datasets can successfully support accurate change detection analysis in this difficult environment [ 99 ].…”

Section: Use Of Lidar Bathymetrymentioning

confidence: 99%

The Use of Green Laser in LiDAR Bathymetry: State of the Art and Recent Advancements

Szafarczyk

Toś

2022

Sensors

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Bathymetric LiDAR technology is a technology used for simultaneous data acquisition regarding the morphology of the bottom of water reservoirs and the surrounding coastal zone, realized from the air, e.g., by plane or drone. Contrary to the air topographic LiDAR, which uses an infrared wavelength of 1064 nm, bathymetric LiDAR systems additionally use a green wavelength of 532 nm. The green laser can penetrate the water, which makes it possible to measure the depth of shallow water reservoirs, rivers, and coastal sea waters within three Secchi depths. This article presents the theoretical basis for the construction of a green laser. Against the background of other methods of measuring the bottom of water reservoirs, the technology using waves from the visible light range is presented in detail in the assessment of the bottom morphology of shallow water reservoirs. The possibilities of using green laser in lidar bathymetry implemented in particular in non-navigable regions are shown. The results of the researchers’ work on river processes (erosion, sedimentation), design of stream restoration, determination of morphometric parameters of the riverbed, as well as assessment of the topography of the marine coastal bottom zones are summarized. The development direction of lidar bathymetry is discussed.

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“…USGS developed a method to extract the dune crest, dune toe, shoreline position and mean beach slope from three-dimensional LiDAR data (Stockdon et al 2012;Doran et al 2015). The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has also developed a toolbox to process LiDAR data in terms of transects and shorelines (Robertson et al 2018). Similarly, we developed a Python-based ArcGIS toolset to extract the beach morphologic features from various data sources such as LiDAR data and field measurements, and calculate resilience parameters and CRI.…”

Section: Beach Morphologic Feature Extractionmentioning

confidence: 99%

Quantifying Beach and Dune Resilience Using the Coastal Resilience Index

Elko¹,

Robertson²,

Rosati³

2018

Int. Conf. Coastal. Eng.

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US Army Corps of Engineers Coastal Storm Risk Management (CSRM) projects have reduced coastal vulnerability and helped communities anticipate and mitigate toward improved resilience. This study proposes the Coastal Resilience Index (CRI) to quantify storm damage reduction benefits due to beach restoration projects in the context of resilience. The CRI considers metrics of the beach and dune system and disturbance factors such as storm surge and waves, using five non-dimensional factors: Protective Elevation (PE), Volume Density (VD), Protective Width (PW), Crest Freeboard (CF) and wave run-up (WR). The CRI is the summation of these five non-dimensional factors. This study developed a geographic information systems (GIS) based tool to automatically extract morphologic features from historic profiles and profiles extracted from LiDAR data to quantify beach resilience over time.

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Florida and US East Coast Beach Change Metrics Derived from LiDAR Data Utilizing ArcGIS Python Based Tools

Cited by 9 publications

References 9 publications

Geomorphic feature extraction to support the Great Lakes Restoration Initiative’s sediment budget and Geomorphic Vulnerability Index for Lake Michigan

Geomorphic feature extraction to support the Great Lakes Restoration Initiative’s sediment budget and Geomorphic Vulnerability Index for Lake Michigan

The Use of Green Laser in LiDAR Bathymetry: State of the Art and Recent Advancements

Quantifying Beach and Dune Resilience Using the Coastal Resilience Index

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