Comparison of remote sensing based approaches for mapping bathymetry of shallow, clear water rivers

Kasvi, Elina; Salmela, Jouni; Lotsari, Eliisa; Kumpula, T.; Lane, Stuart N.

doi:10.1016/j.geomorph.2019.02.017

Cited by 122 publications

(94 citation statements)

References 43 publications

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“…The authors of [51] provide a comparison of remote sensing methods for mapping bathymetry of shallow, clear water rivers. Their work mainly focuses on echo sounding and SfM-based techniques.…”

Section: Comparison and Accuracy Evaluation Studiesmentioning

confidence: 99%

Concept and Performance Evaluation of a Novel UAV-Borne Topo-Bathymetric LiDAR Sensor

Mandlburger

Pfennigbauer²,

Schwarz³

et al. 2020

Remote Sensing

100

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We present the sensor concept and first performance and accuracy assessment results of a novel lightweight topo-bathymetric laser scanner designed for integration on Unmanned Aerial Vehicles (UAVs), light aircraft, and helicopters. The instrument is particularly well suited for capturing river bathymetry in high spatial resolution as a consequence of (i) the low nominal flying altitude of 50-150 m above ground level resulting in a laser footprint diameter on the ground of typically 10-30 cm and (ii) the high pulse repetition rate of up to 200 kHz yielding a point density on the ground of approximately 20-50 points/m 2 . The instrument features online waveform processing and additionally stores the full waveform within the entire range gate for waveform analysis in post-processing. The sensor was tested in a real-world environment by acquiring data from two freshwater ponds and a 500 m section of the pre-Alpine Pielach River (Lower Austria). The captured underwater points featured a maximum penetration of two times the Secchi depth. On dry land, the 3D point clouds exhibited (i) a measurement noise in the range of 1-3 mm; (ii) a fitting precision of redundantly captured flight strips of 1 cm; and (iii) an absolute accuracy of 2-3 cm compared to terrestrially surveyed checkerboard targets. A comparison of the refraction corrected LiDAR point cloud with independent underwater checkpoints exhibited a maximum deviation of 7.8 cm and revealed a systematic depth-dependent error when using a refraction coefficient of n = 1.36 for time-of-flight correction. The bias is attributed to multi-path effects in the turbid water column (Secchi depth: 1.1 m) caused by forward scattering of the laser signal at suspended particles. Due to the high spatial resolution, good depth performance, and accuracy, the sensor shows a high potential for applications in hydrology, fluvial morphology, and hydraulic engineering, including flood simulation, sediment transport modeling, and habitat mapping.Remote Sens. 2020, 12, 986 2 of 28 UAV-based 3D data acquisition was first accomplished using light-weight camera systems, where advancements in digital photogrammetry and computer vision-enabled automatic data processing workflows for the derivation of dense 3D point clouds based on Structure-from-Motion (SfM) and Dense Image Matching (DIM). Due to advancements in UAV-platform technology and ongoing sensor miniaturization, today compact LiDAR sensors are increasingly integrated on both multi-copter and fixed-wing UAVs, enabling 3D mapping with unprecedented spatial resolution and accuracy. The tackled applications include topographic mapping, geomorphology, infrastructure inspection, environmental monitoring, forestry, and precision farming. While UAV-borne laser scanning (ULS) can already be considered state-of-the-art for mapping tasks above the water table, UAV-based bathymetric LiDAR still lacks behind, mainly due to payload restrictions.The established techniques for mapping bathymetry are single-or multi-beam echo sounding (SBES/MBES), incl...

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Section: Comparison and Accuracy Evaluation Studiesmentioning

confidence: 99%

Concept and Performance Evaluation of a Novel UAV-Borne Topo-Bathymetric LiDAR Sensor

Mandlburger

Pfennigbauer²,

Schwarz³

et al. 2020

Remote Sensing

100

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“…A very important additional feature of image-based seabed mapping is that a permanent record of other features is obtained in the coastal region, such as tidal levels, coastal dunes, benthic communities, marine litter, rock platforms, and beach erosion [2]. These benefits are especially evident in the coastal zones of up to 10 m depth, in which most of the economic activities are concentrated, even though many alternatives for bathymetry have been reported recently [3]. Hence, this dynamically changing zone is prone to accretion or erosion and is an area in need of further methodological development, since there are no robust and cost-effective solutions for seamless underwater and overwater mapping tasks.…”

Section: Introductionmentioning

confidence: 99%

Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters

et al. 2020

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Although aerial image-based bathymetric mapping can provide, unlike acoustic or LiDAR (Light Detection and Ranging) sensors, both water depth and visual information, water refraction poses significant challenges for accurate depth estimation. In order to tackle this challenge, we propose an image correction methodology, which first exploits recent machine learning procedures that recover depth from image-based dense point clouds and then corrects refraction on the original imaging dataset. This way, the structure from motion (SfM) and multi-view stereo (MVS) processing pipelines are executed on a refraction-free set of aerial datasets, resulting in highly accurate bathymetric maps. Performed experiments and validation were based on datasets acquired during optimal sea state conditions and derived from four different test-sites characterized by excellent sea bottom visibility and textured seabed. Results demonstrated the high potential of our approach, both in terms of bathymetric accuracy, as well as texture and orthoimage quality.

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“…However, there is no “perfect technique,” with factors such as cost, scale, and repeatability all playing an important role in determining the most appropriate method for a user (Figure ). Many of the methods used have been thoroughly reviewed and can be used to inform researchers for deployment and processing, for example, UAV imagery (Westoby et al, ), TLS (Telling, Lyda, Hartzell, & Glennie, ), ALS (Hofle & Rutzinger, ), ADCP (Muste et al, ), and MBES (Jha, Mariethoz, & Kelly, ), as well as comparing between methods for bathymetric modelling (Kasvi, Salmela, Lotsari, Kumpula, & Lane, ). However, the aim of this review is not to provide a methodological overview but rather to evaluate the range of applications and how each approach can enhance our understanding of the river corridor.…”

Section: River Corridor Remote Sensingmentioning

confidence: 99%

Remote sensing of river corridors: A review of current trends and future directions

Tomsett

Leyland

2019

River Research & Apps

112

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River corridors play a crucial environmental, economic, and societal role yet also represent one of the world's most dangerous natural hazards, making monitoring imperative to improve our understanding and to protect people. Remote sensing offers a rapidly growing suite of methods by which river corridor monitoring can be performed efficiently, at a range of scales and in difficult environmental conditions. This paper aims to evaluate the current state and assess the potential future of river corridor monitoring, whilst highlighting areas that require further investigation. We initially review established methods that are used to undertake river corridor monitoring, framed by the context and scales upon which they are applied. Subsequently, we review cutting edge technologies that are being developed and focussed around unmanned aerial vehicle and multisensor system advances. We also "horizon scan" for future methods that may become increasingly prominent in research and management, citing examples from within and outside of the fluvial domain. Through review of the literature, it has become apparent that the main gap in fluvial remote sensing lies in the trade-off between resolution and scales. However, prioritising process measurements and simultaneous multisensor data collection is likely to offer a bigger advance in understanding than purely from better surveying methods alone. Challenges regarding the legal deployment of more complex systems, as well as effectively disseminating data into the science community, are amongst those that we propose need addressing. However, the plethora of methods currently available means that researchers and monitoring agencies will be able to identify suitable techniques for their needs.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Comparison of remote sensing based approaches for mapping bathymetry of shallow, clear water rivers

Cited by 122 publications

References 43 publications

Concept and Performance Evaluation of a Novel UAV-Borne Topo-Bathymetric LiDAR Sensor

Concept and Performance Evaluation of a Novel UAV-Borne Topo-Bathymetric LiDAR Sensor

Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters

Remote sensing of river corridors: A review of current trends and future directions

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