Application of the AMBUR R package for spatio-temporal analysis of shoreline change: Jekyll Island, Georgia, USA

Jackson, Chester W.; Alexander, Clark; Bush, David M.

doi:10.1016/j.cageo.2011.08.009

Cited by 88 publications

(59 citation statements)

References 5 publications

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“…DSAS has been used to analyze changes in shoreline position in a range of coastal systems, including sandy beaches (Thieler and Danforth 1994;Morton et al 2005;Esteves et al 2009), coastline cliffs (Addo et al 2008;Brooks and Spencer 2010), estuarine and lagoon boundaries (Cowart et al 2010;Kuleli 2010), and coastal wetlands (Borrelli 2009;Gorokhovich and Leiserowiz 2012). The more recently developed AMBUR (Analyzing Moving Boundaries Using R) software has also been shown to be useful for quantifying shoreline change (Jackson et al 2012;Eulie et al 2013).…”

Section: Introductionmentioning

confidence: 98%

Rates and Forcing of Marsh Edge Erosion in a Shallow Coastal Bay

McLoughlin

Wiberg

Safak

et al. 2014

Estuaries and Coasts

105

113

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Salt marshes can experience a significant land loss through erosion and retreat of their perimeter edges. Rates of shoreline change between 1957 and 2007 were determined for four salt marshes in a Virginia coastal bay using aerial photographs and the Digital Shoreline Analysis System (DSAS). High average rates of lateral erosion of 1.0-1.6 m year −1 were found at three marshes, while the edge of the fourth marsh, along the mainland edge of the bay, remained stable. Erosion rates were temporally consistent during the 50-year period at the three eroding sites, although there was a significant spatial variation in rates of change along the length of the edges at these sites. A simple parametric wave model and the SWAN (Simulating WAves Nearshore) spectral wave model were used to calculate incident wave energy flux along the marsh boundaries at each of the sites. Values of wave energy flux agreed fairly well between the two models but are sensitive to the manner in which wave energy flux is calculated. A stronger relationship was found between wave energy flux and volumetric erosion rates along the marsh edges than with lateral erosion rates. This is an important consideration when examining the effects of future sea level rise on marsh loss.

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Section: Introductionmentioning

confidence: 98%

Rates and Forcing of Marsh Edge Erosion in a Shallow Coastal Bay

McLoughlin

Wiberg

Safak

et al. 2014

Estuaries and Coasts

105

113

View full text Add to dashboard Cite

show abstract

“…The AMBUR software improves on previous shoreline analysis tools by providing functions for new transects casting techniques, detailed output from statistical analyses, generation of summary reports and graphics, and shoreline position forecasting [23]. It analyses shoreline change by capturing the positions of each historical shoreline along transects and measure changes that occur along each transect using advanced statistical analysis [22].…”

Section: Introductionmentioning

confidence: 99%

“…It analyses shoreline change by capturing the positions of each historical shoreline along transects and measure changes that occur along each transect using advanced statistical analysis [22]. AMBUR provides a collection of scripts to assist with the shoreline change analysis taking advantage of R's statistical, graphical and geospatial capabilities [23]. It allows users to choose any commercial or open source GIS software for editing, preparing and viewing shape files.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Volta Delta Shoreline Change

Addo¹

2015

J Coast Zone Manag

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Journal of Coastal Zone Management AbstractShorelines fronting deltas evolve in their quest to achieve equilibrium state. Such activities have encountered the increasing human development in deltaic regions and resulted in the destruction of the environment and resources. This paper discusses the shoreline evolution trends of the Volta Delta in Ghana. The shoreline was divided into four sections based on the orientation and human interventions. Data sources for the study included satellite imageries of 1986, 1991, 2001, 2004 and 2013. Trends were statistically analysed using the AMBUR software. It emerged that the 27 years period under study, the shoreline is accreting at an average rate of about 0.53 m/yr. Section one is accreting at a rate of about 0.136 m/yr; section two is accreting a rate of about 1.703 m/yr; section three is accreting at a rate of about 2.126 m/yr; while section four is eroding at a rate of about 3.703 m/yr. This observation is significant because the area has been reported by previous studies to be eroding at a rate of about 8 m/yr. Accretion of the three sections can be explained by the presence of the Keta sea defense project (KSDP) and the shoreline orientation which influences the breaking pattern of swell waves that approach the shore. The observed development of sediment build-up will influence the sediment regime along the eastern Ghana and Togo coastal areas. There is the need to develop a systematic sub-regional coastal monitoring activity to effectively manage the coastal systems in the two countries.

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“…Oceanfront shoreline dynamics were compared using the line shared by supratidal and intertidal and then analyzed using AMBUR [28]. AMBUR is similar to the Digital Shoreline Analysis System (DSAS) [29] where the difference in two shorelines are compared at equally spaced transects and the rate of change (erosion or accretion) is calculated [28]. Movement/migration of dune features was calculated by using the "Detect Feature Change" and "Near" tools in ArcMap [30] in order to measure the distance between features through time.…”

Section: Temporal Change Analysismentioning

confidence: 99%

An Automated Model to Classify Barrier Island Geomorphology Using Lidar Data and Change Analysis (1998–2014)

2018

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Abstract:Previous research has documented the usefulness of Lidar data to derive a variety of topographic products (e.g., DEM, DTM, canopy and forest structure, and urban infrastructure). Lidar has been used to map coastal environments and geomorphology; however, there is no comprehensive model to derive coastal geomorphology. Therefore, the purpose of this project was to build on existing research and develop an automated modeling approach to classify coastal geomorphology across barrier islands. The model was developed and tested at four sites in North Carolina including two undeveloped and two developed islands. Barrier island geomorphology is shaped by natural coastal processes, such as storms and longshore sediment transport, as well as human influences, such as beach nourishment and urban development. The model was developed to classify ten geomorphic features over four time-steps from 1998 to 2014. Model results were compared to compute change through time and derived the rate and direction of feature movement. Tropical storms and hurricanes had the most influence in geomorphic change and movement. On the developed islands, there was less influence of storms due to the inability of features to move because of coastal infrastructure. From 2005 to 2010, beach nourishment was the dominant influence on developed beaches because this activity ameliorated the natural tendency for an island to erode. Understanding how natural and anthropogenic processes influence barrier island geomorphology is critical to predicting an island's future response to changing environmental factors such as sea-level rise. The development of an automated model enables it to be replicated in other locations where policy makers and coastal managers may use this information to make development and conservation decisions.

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Application of the AMBUR R package for spatio-temporal analysis of shoreline change: Jekyll Island, Georgia, USA

Cited by 88 publications

References 5 publications

Rates and Forcing of Marsh Edge Erosion in a Shallow Coastal Bay

Rates and Forcing of Marsh Edge Erosion in a Shallow Coastal Bay

Assessment of the Volta Delta Shoreline Change

An Automated Model to Classify Barrier Island Geomorphology Using Lidar Data and Change Analysis (1998–2014)

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