3-D Morphological Change Analysis of a Beach with Seagrass Berm Using a Terrestrial Laser Scanner

Corbí, Hugo; Riquelme, Adrián; Megías-Baños, Clara; Abellán, Antonio

doi:10.3390/ijgi7070234

Cited by 20 publications

(11 citation statements)

References 44 publications

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“…digital elevation models (DEM) (Eisemann et al, 2018). However, high levels of uncertainty are inherent in the calculations derived through this method, as surface heights between transects are interpolated, and are often derived by multiplying profile end areas by the transect separation distance (Cantrill and Kruimel, 2013;Corbí et al, 2018;Shrestha et al, 2005). Nevertheless, transect-based methods are still frequently used in many studies and by coastal management bodies (especially for cliff retreat calculations (Young, 2018)); they have also been combined with methods such as linear regression (Appeaning Addo et al, 2008).…”

Section: Geomorphological Change Detection (Gcd)mentioning

confidence: 99%

“…It is common for C2C comparisons to involve the use of tailored scripts and task specific algorithms; many past studies have utilised Matlab for this (Kromer et al, 2017;Michoud et al, 2015;Williams et al, 2018). Examples of software used for point cloud data based GCD include Polyworks (Michoud et al, 2015), Cyclone (Corbí et al, 2018), and CloudCompare (Corbí et al, 2018;Lague et al, 2013;Leyland et al, 2017). The M3C2 algorithm developed specifically for C2C comparisons (Section 1.2.5), now comes complete with the software CloudCompare, as a plugin ("M3C2 (Plugin)", 2018).…”

Section: Software Selectionmentioning

confidence: 99%

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The application of data innovations to geomorphological impact analyses in coastal areas: An East Anglia, UK, case study

Rumson

Hallett

Brewer

2019

Ocean & Coastal Management

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Rapidly advancing surveying technologies, capable of generating high resolution bathymetric and topographic data, allow precise measurements of geomorphological change and deformation. This permits great accuracy in the characterisation of volumetric change, sediment and debris flows, accumulations and erosion rates. However, such data can be utilised inadequately by coastal practitioners in their assessments of coastal change, due to a lack of awareness of the appropriate analytical techniques and the potential benefits offered by such data-driven approaches. This was found to be the case for the region of East Anglia, UK, which was analysed in this study. This paper evaluates the application of innovative geomorphological change detection (GCD) techniques for analysis of coastal change. The first half of the paper contains an extensive review of GCD methods and data sources used in previous studies. This leads to the selection and recommendation of an appropriate methodology for calculation of volumetric GCD, which has been subsequently applied and evaluated for 14 case study sites in East Anglia. This has involved combining open source point cloud datasets for broad spatial scales, covering an extended temporal period. The results comprise quantitative estimates of volumetric change for selected locations. This allows estimation of the sediment budgets for each stretch of coastline focused upon, revealing fluctuations in their rates of change. These quantitative results were combined with qualitative outputs, such as visual representations of change and we reveal how combining such methods assists identification of patterns and impacts linked to specific events. The study demonstrates how high-resolution point cloud data, which is now readily available, can be used to better inform coastal management practices, revealing trends, impacts and vulnerability in dynamic coastal regions. The results also indicate heterogeneous impacts of events, such as the 2013 East Coast Storm Surge, across the study area of East Anglia.

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Section: Geomorphological Change Detection (Gcd)mentioning

confidence: 99%

Section: Software Selectionmentioning

confidence: 99%

The application of data innovations to geomorphological impact analyses in coastal areas: An East Anglia, UK, case study

Rumson

Hallett

Brewer

2019

Ocean & Coastal Management

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“…In contrast, airborne, mobile, or terrestrial lidar systems are capable of collecting elevation data in a wide range of coastal environments, and their use has become increasingly common in recent years [14][15][16][17]. In coastal areas, lidar scanners have been used to produce both large-scale coastal maps [18,19] as well as small-scale high resolution scans of nearshore morphology [20][21][22]. Additionally, lidar scanners are capable of providing returns off both the ground and the water surface, allowing for the assessment of beach and dune morphology (e.g., [20][21][22][23][24][25]) as well as wave transformation and water surface elevation in the swash and inner surf-zones [26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Continuous Coastal Monitoring with an Automated Terrestrial Lidar Scanner

O’Dea

Brodie

Hartzell

2019

JMSE

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This paper details the collection, geo-referencing, and data processing algorithms for a fully-automated, permanently deployed terrestrial lidar system for coastal monitoring. The lidar is fixed on a 4-m structure located on a shore-backing dune in Duck, North Carolina. Each hour, the lidar collects a three-dimensional framescan of the nearshore region along with a 30-min two-dimensional linescan time series oriented directly offshore, with a linescan repetition rate of approximately 7 Hz. The data are geo-referenced each hour using a rigorous co-registration process that fits 11 fixed planes to a baseline scan to account for small platform movements, and the residual errors from the fit are used to assess the accuracy of the rectification. This process decreased the mean error (defined as the magnitude of the offset in three planes) over a two-year period by 24.41 cm relative to using a fixed rectification matrix. The automated data processing algorithm then filters and grids the data to generate a dry-beach digital elevation model (DEM) from the framescan along with hourly wave runup, hydrodynamic, and morphologic statistics from the linescan time series. The lidar has collected data semi-continuously since January 2015 (with gaps occurring while the lidar was malfunctioning or being serviced), resulting in an hourly data set spanning four years as of January 2019. Examples of data products and potential applications spanning a range of spatial and temporal scales relevant to coastal processes are discussed.

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“…It can measure wild range target and are convenient compared with other methods, e.g., real time response and digital model building, low cost, better mobility, can operate in dark, and determine physical and chemical composition by the reflecting laser wavelanth [27]. Comparing the classical methods using in erosion research, such as erosion pins and sediment traps [28][29][30], high spatial-resolution topography data obtained from airborne LiDAR and terrestrial scanning LiDAR (TLS) provide precise and detailed landscape changes, e.g., terrain analysis [31], landslide [32][33][34][35], rockfall [36][37][38], beach erosion [39], channel erosion [40][41][42], and slope erosion [43][44][45][46]. This research is helpful for studying the geomorphological processes in a certain spatial scale where traditional tools can hardly reach, and provide more evidence of landscape evolution.…”

Section: Introductionmentioning

confidence: 99%

Application for Terrestrial LiDAR on Mudstone Erosion Caused by Typhoons

2019

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Storms are important agents for shaping the Earth’s surface and often dominate the landscape evolution of mudstone areas, by rapid erosion and deposition. In our research, we used terrestrial scanning LiDAR (TLS) to detect surface changes in a 30 m in height, 60 m in width mudstone slope. This target slope shows the specific erosion pattern during extreme rainfall events such as typhoons. We investigate two major subjects: (1) how typhoon events impact erosion in the target slope, and (2) how rills develop on the hillslopes during these observation periods. There were three scans obtained in 2011, and converted to two observation periods. The permanent target points (TP) method and DEMs of differences were used to check the accuracy of point cloud. The results showed that the average erosion rate was 5 cm during the dry period in 2011. Following the typhoons, the erosion rate increased 1.4 times to 7 cm and was better correlated with the increase in the rainfall intensity than with general precipitation amounts. The hillslope gradient combined with rainfall intensity played a significant role in the geomorphic process. We found that in areas with over 75° gradients with larger rainfall intensity showed more erosion that at other gradients. The gradient also influenced the rill development, which occurred at middle and low gradients but not at high gradients. The rills also created a transition zone for erosion and deposition at the middle gradient where a minimal change occurred.

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3-D Morphological Change Analysis of a Beach with Seagrass Berm Using a Terrestrial Laser Scanner

Cited by 20 publications

References 44 publications

The application of data innovations to geomorphological impact analyses in coastal areas: An East Anglia, UK, case study

The application of data innovations to geomorphological impact analyses in coastal areas: An East Anglia, UK, case study

Continuous Coastal Monitoring with an Automated Terrestrial Lidar Scanner

Application for Terrestrial LiDAR on Mudstone Erosion Caused by Typhoons

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