Monitoring coastal change using terrestrial LiDAR

Hobbs, Peter; Gibson, Andy; Jones, Lee; Pennington, Catherine; Jenkins, Gareth; Pearson, Stephen; Freeborough, Katy

doi:10.1144/sp345.12

Cited by 20 publications

(19 citation statements)

References 7 publications

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“…They prefer to use the isohypse at the highest tidal position (datum-based shoreline) as it would be more reliable for beach profile changes. This 3D information is normally obtained by GNSS mapping (Global Navigation Satellite System) [9,10], LiDAR [11][12][13][14] or TLS [15] (Terrestrial Laser Scanner). These 3D resources may offer high accuracy data: up to 5 cm (horizontal and vertical) on differential GNSS surveys; and up to 10 cm (horizontal) and 20 cm (vertical) depending on each of the LiDAR flight demands.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Accuracy of Automatically Extracted Shorelines on Microtidal Beaches from Landsat 7, Landsat 8 and Sentinel-2 Imagery

et al. 2018

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This paper evaluates the accuracy of shoreline positions obtained from the infrared (IR) bands of Landsat 7, Landsat 8, and Sentinel-2 imagery on natural beaches. A workflow for sub-pixel shoreline extraction, already tested on seawalls, is used. The present work analyzes the behavior of that workflow and resultant shorelines on a micro-tidal (<20 cm) sandy beach and makes a comparison with other more accurate sets of shorelines. These other sets were obtained using differential GNSS surveys and terrestrial photogrammetry techniques through the C-Pro monitoring system. 21 sub-pixel shorelines and their respective high-precision lines served for the evaluation. The results prove that NIR bands can easily confuse the shoreline with whitewater, whereas SWIR bands are more reliable in this respect. Moreover, it verifies that shorelines obtained from bands 11 and 12 of Sentinel-2 are very similar to those obtained with bands 6 and 7 of Landsat 8 (−0.75 ± 2.5 m; negative sign indicates landward bias). The variability of the brightness in the terrestrial zone influences shoreline detection: brighter zones cause a small landward bias. A relation between the swell and shoreline accuracy is found, mainly identified in images obtained from Landsat 8 and Sentinel-2. On natural beaches, the mean shoreline error varies with the type of image used. After analyzing the whole set of shorelines detected from Landsat 7, we conclude that the mean horizontal error is 4.63 m (±6.55 m) and 5.50 m (±4.86 m), respectively, for high and low gain images. For the Landsat 8 and Sentinel-2 shorelines, the mean error reaches 3.06 m (±5.79 m).

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Section: Introductionmentioning

confidence: 99%

Assessing the Accuracy of Automatically Extracted Shorelines on Microtidal Beaches from Landsat 7, Landsat 8 and Sentinel-2 Imagery

et al. 2018

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“…However, limiting the incidence angle is not always practical in field settings and field-testing the effects of positional error may be necessary before analyzing the data. Many researchers seek to minimize incidence angles by increasing the elevation of the scanner, by mounting the instrument atop very large or telescoping tripods, atop a stabilized vehicle, or from scaffolding Hobbs et al 2010;Pietro et al 2008) (Fig. 3.2).…”

Section: Field Surveys and Scanner Setupmentioning

confidence: 99%

“…When scanning larger geographic extents, relying on relativistic reference targets between adjacent scans often results in cumulative errors, manifested in final surface models as irregular geometries and overall slopes that do not well represent the actual scanned area (Pietro et al 2008;Hobbs et al 2010;Olsen et al 2010). Scanning permanent benchmarks embedded in concrete by the surveyor may improve merging statistics, but also may be difficult to install and/or maintain in dynamic coastal settings.…”

Section: Field Surveys and Scanner Setupmentioning

confidence: 99%

Terrestrial Laser Scanner Surveying in Coastal Settings

O’Neal

2014

Remote Sensing and Modeling

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Over the last decade, there has been a proliferation of commercially available tripod-mounted Terrestrial Laser Scanner (TLS) systems that use the phase difference or the time-of-flight of emitted pulses of light to rapidly acquire high-density topographic and surface reflectance data. These TLS systems have been well received in the Earth science community because of their ability to collect 10 2 -10 5 measurements per second of azimuth, zenith, distance, intensity, and surface color data at distances ranging from 10 0 to 10 3 m. A TLS instrument's portability, ease of use, and rate of data collection opens the possibility of collecting detailed topographic data at sites where such surveys may not have been possible before. The application of TLS data to current Earth sciences research has allowed us to better understand of the character, timing, rates, and spatial scales of different processes that have been difficult, if not impossible, to evaluate using traditional survey techniques. However, the successes achieved with TLS systems in certain projects may result in unrealistic expectations regarding the density and quality of data that can reasonably be achieved in different settings. This chapter seeks to orient potential or experienced TLS users to its applicability in above-water coastal settings. An emphasis is placed on providing insight into both the variety of current research using TLS data, as well as the compromises in spatial resolution that necessarily arise from field conditions and survey design.

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“…Terrestrial LIDAR works by measuring the relative distance, elevation and azimuthal angles between the laser scanner and landslide and, when georeferenced with differential GPS (dGPS), a 3-D surface model can be generated (Hobbs et al 2002;Rowlands et al 2003). Analysis of repeated scans over regular time intervals can accurately determine, for example, the nature of the landslide processes (Hobbs et al 2010). A high resolution digital camera mounted onto the scanner enables coloured point-clouds, textured triangulated surfaces or orthophotos with depth information to be captured.…”

Section: Repeat Terrestrial Lidar and Dgps Surveysmentioning

confidence: 99%

Mapping a Nation’s Landslides: A Novel Multi-Stage Methodology

Evans

Pennington

Jordan

et al. 2013

Landslide Science and Practice

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Through combining new technologies and traditional mapping techniques, the British Geological Survey (BGS) has developed a novel, multi-stage methodology for landslide mapping. 3-D aerial photograph interpretation, variable-perspective 3-D topographic visualisation and field mapping with digital data capture are being used to map the UK's landslides. The resulting ESRI ArcGIS polygons are published on BGS 1:50,000 geological maps and as digital data products. Data collected during mapping are also uploaded directly into the National Landslides Database maintaining a systematic, nationally-uniform landslide inventory. Repeat monitoring of selected landslides using terrestrial LIDAR and dGPS allows the database to be frequently updated and the proactive Landslide Response Team means that new landslide events can be mapped within days, if not hours, of their occurrence. The long-term aim is to apply this methodology throughout the UK, providing a wealth of data for scientific research and hazard assessment. This methodology is also suitable for application in an international context.

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Monitoring coastal change using terrestrial LiDAR

Cited by 20 publications

References 7 publications

Assessing the Accuracy of Automatically Extracted Shorelines on Microtidal Beaches from Landsat 7, Landsat 8 and Sentinel-2 Imagery

Assessing the Accuracy of Automatically Extracted Shorelines on Microtidal Beaches from Landsat 7, Landsat 8 and Sentinel-2 Imagery

Terrestrial Laser Scanner Surveying in Coastal Settings

Mapping a Nation’s Landslides: A Novel Multi-Stage Methodology

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