Measuring bluff erosion part 1: terrestrial laser scanning methods for change detection

Day, Stephanie S.; Gran, Karen B.; Belmont, Patrick; Wawrzyniec, Tim F.

doi:10.1002/esp.3353

Cited by 54 publications

(57 citation statements)

References 31 publications

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“…Jaboyedoff et al, 2012;Barnhart and Crosby, 2013) and investigating Earth surface processes (e.g. Schürch et al, 2011;Montreuil et al, 2013;Day et al, 2013). In these applications, TLS data usually need to be transformed into an external coordinate system for data fusion or the derivation of surface movement.…”

Section: : Introductionmentioning

confidence: 99%

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Error in target-based georeferencing and registration in terrestrial laser scanning

Fan

Smethurst

Atkinson

et al. 2015

Computers & Geosciences

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Terrestrial laser scanning (TLS) has been used widely for various applications, such as measurement of movement caused by natural hazards and Earth surface processes. In TLS surveying, registration and georeferencing are two essential steps, and their accuracy often determines the usefulness of TLS surveys. So far, evaluation of registration and georeferencing errors has been based on statistics obtained from the data processing software provided by scanner manufacturers. This paper demonstrates that these statistics are incompetent measures of the actual registration and georeferencing errors in TLS data and, thus, should no longer be used in practice. To seek a suitable replacement, an investigation of the spatial pattern and the magnitude of the actual registration and georeferencing errors in TLS data points was undertaken. This led to the development of a quantitative means of estimating the registrationor georeferencing-induced positional error in point clouds. The solutions proposed can aid in the planning of TLS surveys where a minimum accuracy requirement is known, and are of use for subsequent analysis of the uncertainty in TLS datasets.

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Section: : Introductionmentioning

confidence: 99%

“…This approach has also widely been adopted by researchers (e.g. Barnhart andCrosby, 2013, Lague et al, 2013;Montreuil et al, 2013;Day, et al, 2013). They are single and spatial uniform statistics per point cloud.…”

Section: : Introductionmentioning

confidence: 99%

Error in target-based georeferencing and registration in terrestrial laser scanning

Fan

Smethurst

Atkinson

et al. 2015

Computers & Geosciences

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“…Meter-and sub-meter-scale time-varying processes, often derived from TLS, have been quantified in the response of point bar and bank morphodynamics (Lotsari et al, 2014) and in the formation of micro-topography due to feedbacks with biota (e.g., Roering et al, 2010;Harman et al, 2014). Examples of larger scale change detection applications, typically ALS-derived, include measuring changes in stream channel pathways resulting from Holocene climate change and anthropogenic activities (e.g., Day et al, 2013;Kessler et al, 2012;James et al, 2012;Belmont et al, 2011), rates of change in migrating sand dunes (Pelletier, 2013), the influence of lithology and climate on hillslope form (e.g., Marshall and Roering, 2014;Hurst et al, 2013;Perron et al, 2008;West et al, 2014), and channel head formation (e.g., Pelletier et al, 2013;Pelletier and Perron, 2012;Perron and Hamon, 2012). Automated tools to identify geomorphic features (e.g., floodplains, terraces, landslides) and transitional zones (e.g., hillslope-to-valley, floodplain-tochannel) have been used in conjunction with high-resolution elevation data sets from lidar, including Geonet 2.0 (Passalacqua et al, 2010), ALMTools (Booth et al, 2009), and TerrEX (Stout and Belmont, 2014).…”

Section: Advances In Geomorphology Using Lidarmentioning

confidence: 99%

Laser vision: lidar as a transformative tool to advance critical zone science

Harpold

Marshall

Lyon

et al. 2015

Hydrol. Earth Syst. Sci.

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Abstract. Observation and quantification of the Earth's surface is undergoing a revolutionary change due to the increased spatial resolution and extent afforded by light detection and ranging (lidar) technology. As a consequence, lidar-derived information has led to fundamental discoveries within the individual disciplines of geomorphology, hydrology, and ecology. These disciplines form the cornerstones of critical zone (CZ) science, where researchers study how interactions among the geosphere, hydrosphere, and biosphere shape and maintain the "zone of life", which extends from the top of unweathered bedrock to the top of the vegetation canopy. Fundamental to CZ science is the development of transdisciplinary theories and tools that transcend disciplines and inform other's work, capture new levels of complexity, and create new intellectual outcomes and spaces. Researchers are just beginning to use lidar data sets to answer synergistic, transdisciplinary questions in CZ science, such as how CZ processes co-evolve over long timescales and interact over shorter timescales to create thresholds, shifts in states and fluxes of water, energy, and carbon. The objective of this review is to elucidate the transformative potential of lidar for CZ science to simultaneously allow for quantification of topographic, vegetative, and hydrological processes. A review of 147 peer-reviewed lidar studies highlights a lack of lidar applications for CZ studies as 38 % of the studies were focused in geomorphology, 18 % in hydrology, 32 % in ecology, and the remaining 12 % had an interdisciplinary focus. A handful of exemplar transdisciplinary studies demon- Published by Copernicus Publications on behalf of the European Geosciences Union. 2882 A. A. Harpold et al.: Laser vision: lidar as a transformative toolstrate lidar data sets that are well-integrated with other observations can lead to fundamental advances in CZ science, such as identification of feedbacks between hydrological and ecological processes over hillslope scales and the synergistic co-evolution of landscape-scale CZ structure due to interactions amongst carbon, energy, and water cycles. We propose that using lidar to its full potential will require numerous advances, including new and more powerful open-source processing tools, exploiting new lidar acquisition technologies, and improved integration with physically based models and complementary in situ and remote-sensing observations. We provide a 5-year vision that advocates for the expanded use of lidar data sets and highlights subsequent potential to advance the state of CZ science.

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“…Guarnieri et al (2009) carried out research into the retrieval of small-relief marsh morphology from TLS, and found that the vegetation-induced uncertainty was in the order of a few centimetres. Day et al (2013) investigated the use of TLS for measuring bluff erosion and discussed the effect of ground vegetation in this application. Pirotti et al (2013) investigated the use of a multi-return terrestrial laser scanner in measuring vegetated ground, and proposed a work-flow for identifying ground points and deriving digital terrain and surface models.…”

Section: Introductionmentioning

confidence: 99%

The effect of short ground vegetation on terrestrial laser scans at a local scale

Fan

Powrie

Smethurst

et al. 2014

ISPRS Journal of Photogrammetry and Remote Sensing

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Terrestrial laser scanning (TLS) can record a large amount of accurate topographical information with a high spatial accuracy over a relatively short period of time. These features suggest it is a useful tool for topographical survey and surface deformation detection. However, the use of TLS to survey a terrain surface is still challenging in the presence of dense ground vegetation. The bare ground surface may not be illuminated due to signal occlusion caused by vegetation. This paper investigates vegetation-induced elevation error in TLS surveys at a local scale and its spatial pattern. An open, relatively flat area vegetated with dense grass was surveyed repeatedly under several scan conditions. A total station was used to establish an accurate representation of the bare ground surface. Localhighest-point and local-lowest-point filters were applied to the point clouds acquired for deriving vegetation height and vegetation-induced elevation error, respectively. The effects of various factors (for example, vegetation height, edge effects, incidence angle, scan resolution and location) on the error caused by vegetation are discussed. The results are of use in the planning and interpretation of TLS surveys of vegetated areas.

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Measuring bluff erosion part 1: terrestrial laser scanning methods for change detection

Cited by 54 publications

References 31 publications

Error in target-based georeferencing and registration in terrestrial laser scanning

Error in target-based georeferencing and registration in terrestrial laser scanning

Laser vision: lidar as a transformative tool to advance critical zone science

The effect of short ground vegetation on terrestrial laser scans at a local scale

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