The successful application of Airborne LiDAR Bathymetry surveys using latest technology

Parker, H. C.; Sinclair, Mark

doi:10.1109/oceans-yeosu.2012.6263588

Cited by 19 publications

(8 citation statements)

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“…The water surface in topobathymetric lidar surveys are most often detected from NIR lidar data and are simultaneously collected along with the green lidar data (Collin et al, 2012;Guenther et al, 2000;Parker and Sinclair, 2012;Wang and Philpot, 2007). However, detecting the water surface and generating a DWSM based on the green lidar data alone provides a potential to perform topobathymetric surveys with just one sensor, thus optimizing the survey costs as well as data handling and storage.…”

Section: Performance Of the Water Surface Detection Methodsmentioning

confidence: 99%

“…Often, the water surface is detected and modelled from simultaneous collection of green and NIR lidar measurements, where the green laser reflects from the seabed and the NIR laser reflects from the air-water interface, and the NIR laser data are then used to detect and model the water surface (Allouis et al, 2010;Collin et al, 2008;Guenther, 2007;Parker and Sinclair, 2012). The use of NIR lidar data for water surface detection has been applied in several studies.…”

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confidence: 99%

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Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment

Andersen

Gergely

Al-Hamdani

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. The transition zone between land and water is difficult to map with conventional geophysical systems due to shallow water depth and often challenging environmental conditions. The emerging technology of airborne topobathymetric light detection and ranging (lidar) is capable of providing both topographic and bathymetric elevation information, using only a single green laser, resulting in a seamless coverage of the land-water transition zone. However, there is no transparent and reproducible method for processing green topobathymetric lidar data into a digital elevation model (DEM). The general processing steps involve data filtering, water surface detection and refraction correction. Specifically, the procedure of water surface detection and modelling, solely using green laser lidar data, has not previously been described in detail for tidal environments. The aim of this study was to fill this gap of knowledge by developing a step-by-step procedure for making a digital water surface model (DWSM) using the green laser lidar data. The detailed description of the processing procedure augments its reliability, makes it user-friendly and repeatable. A DEM was obtained from the processed topobathymetric lidar data collected in spring 2014 from the Knudedyb tidal inlet system in the Danish Wadden Sea. The vertical accuracy of the lidar data is determined to ±8 cm at a 95 % confidence level, and the horizontal accuracy is determined as the mean error to ±10 cm. The lidar technique is found capable of detecting features with a size of less than 1 m 2 . The derived high-resolution DEM was applied for detection and classification of geomorphometric and morphological features within the natural environment of the study area. Initially, the bathymetric position index (BPI) and the slope of the DEM were used to make a continuous classification of the geomorphometry. Subsequently, stage (or elevation in relation to tidal range) and a combination of statistical neighbourhood analyses (moving average and standard deviation) with varying window sizes, combined with the DEM slope, were used to classify the study area into six specific types of morphological features (i.e. subtidal channel, intertidal flat, intertidal creek, linear bar, swash bar and beach dune). The developed classification method is adapted and applied to a specific case, but it can also be implemented in other cases and environments.

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Section: Performance Of the Water Surface Detection Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment

Andersen

Gergely

Al-Hamdani

et al. 2017

Hydrol. Earth Syst. Sci.

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“…Following the success of near-infrared LiDAR in mapping terrestrial systems, topobathymetric airborne LiDARs, including the NASA Experimental Advanced Airborne Research LiDAR (EAARL) (McKean et al, 2009b), the Optech Scanning Hydrographic Operational Airborne LiDAR System (SHOALS) (Hilldale and Raff, 2007), the Coastal Zone Mapping and Imaging Lidar (CZMIL) (Tuell et al, 2010), the Laser Airborne Depth Sounder (LADS) Mk II and Mk 3 (Parker and Sinclair, 2012), the Riegl VQ-820-G (Mandlburger et al, 2011), the Optech Aquarius (Fernandez-Diaz et al, 2014), the Teledyne Optech Titan TopoBathy Sensor (Fernandez-Diaz et al, 2016) and Leica Aquatic Hydrography AB (AHAB) Chiroptera II and HawkEye II and III (Quadros, 2013), have recently been applied to stream systems (McKean et al, 2009a). All of these systems use a green wavelength laser, which has very low absorbance in water, rather than the near-infrared to map submerged topography (McKean et al, 2009a).…”

Section: Introductionmentioning

confidence: 99%

Mapping river bathymetries: Evaluating topobathymetric LiDAR survey

Tonina

McKean

Benjankar

et al. 2018

Earth Surf Processes Landf

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Advances in topobathymetric LiDARs could enable rapid surveys at sub‐meter resolution over entire stream networks. This is the first step to improving our knowledge of riverine systems, both their morphology and role in ecosystems. The Experimental Advanced Airborne Research LiDAR B (EAARL‐B) system is one such topobathymetric sensor, capable of mapping both terrestrial and aquatic systems. Whereas the original EAARL was developed to survey littoral areas, the new version, EAARL‐B, was also designed for riverine systems but has yet to be tested. Thus, we evaluated the ability of EAARL‐B to map bathymetry and floodplain topography at sub‐meter resolution in a mid‐size gravel‐bed river. We coupled the EAARL‐B survey with highly accurate field surveys (0.03 m vertical accuracy and approximately 0.6 by 0.6 m resolution) of three morphologically distinct reaches, approximately 200 m long 15 m wide, of the Lemhi River (Idaho, USA). Both point‐to‐point and raster‐to‐raster comparisons between ground and EAARL‐B surveyed elevations show that differences (ground minus EAARL‐B surveyed elevations) over the entire submerged topography are small (root mean square error, RMSE, and median absolute error, M, of 0.11 m), and large differences (RMSE, between 0.15 and 0.38 m and similar M) are mainly present in areas with abrupt elevation changes and covered by dense overhanging vegetation. RMSEs are as low as 0.03 m over paved smooth surfaces, 0.07 m in submerged, gradually varying topography, and as large as 0.24 m along banks with and without dense, tall vegetation. EAARL‐B performance is chiefly limited by point density in areas with strong elevation gradients and by LiDAR footprint size (0.2 m) in areas with topographic features of similar size as the LiDAR footprint. © 2018 John Wiley & Sons, Ltd.

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“…LiDAR depth data [28] were collected by Fugro LADS (Kidman Park, SA) with their Mark II instrument, in a survey conducted for WA Transport in April 2009 off the coast of Western Australia from Two Rocks to Cape Naturaliste, see Table 1. The LiDAR waveform data were processed by Fugro Pty Ltd. to create depth maps, by measuring the time difference between LiDAR pulses returned from the surface of the water and the seafloor.…”

Section: Lidar Bathymetrymentioning

confidence: 99%

Depth from Satellite Images: Depth Retrieval Using a Stereo and Radiative Transfer-Based Hybrid Method

et al. 2018

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Satellite imagery is increasingly being used to provide estimates of bathymetry in near-coastal (shallow) areas of the planet, as a more cost-effective alternative to traditional methods. In this paper, the relative accuracy of radiative-transfer and photogrammetric stereo methods applied to World View 2 imagery are examined, using LiDAR bathymetry and towed video as ground truth, and it is demonstrated, with a case study, that these methods are complementary; where one method might have limited accuracy, the other method often has improved accuracy. The depths of uniform, highly-reflective (sand) sea bed are better estimated with a radiative transfer-based method, while areas where there is high visual contrast in the scene, as identified by using a local standard deviation measure, are better estimated using the photogrammetric technique. In this paper, it is shown that a hybrid method can give a potential improvement in accuracy of more than 50% (from 2.84 m to 1.38 m RMSE in the ideal case) compared to either of the two methods alone. Metrics are developed that can be used to characterize regions of the scene where each technique is superior, realizing an improved overall depth accuracy over either method alone of between 16.9% and 19.7% (demonstrating a realised RMSE of 2.36 m).

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The successful application of Airborne LiDAR Bathymetry surveys using latest technology

Cited by 19 publications

References 0 publications

Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment

Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment

Mapping river bathymetries: Evaluating topobathymetric LiDAR survey

Depth from Satellite Images: Depth Retrieval Using a Stereo and Radiative Transfer-Based Hybrid Method

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