Iron Age Shipwrecks in Deep Water off Ashkelon, Israel

Ballard, Robert D.; Stager, Lawrence E.; Master, Daniel M.; Yoerger, D.; Mindell, David A.; Whitcomb, Louis L.; Singh, Hanumant; Piechota, Dennis

doi:10.2307/4126241

Cited by 132 publications

(73 citation statements)

References 17 publications

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“…For example, sub-bottom profilers (SBP) have been employed to delineate lake bathymetry and sediment sublayers (Lin et al, 2009). Sidescan sonar (SSS) has been used to illustrate surficial sediment textures (Huvenne et al, 2002), sedimentary bedforms (Shawab et al, 1996) and objects such as shipwrecks over lake or sea floors (Ballard et al, 2002). Through successive surveys, changes of the lake floor and sublayer structures can thereby be determined, and the erosion or deposition patterns over lake bottoms are revealed (Nitsche et al, 2004).…”

Section: Methodsmentioning

confidence: 99%

Response of bottom sediment stability after carp removal in a small lake

Lin

2013

Ann. Limnol. - Int. J. Lim.

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-This study combined several features of acoustic and electromagnetic (EM) waves-based devices including sub-bottom profiler (SBP), side-scan sonar (SSS) and ground penetrating radar (GPR), and in situ sediment data to study responses of bottom sediments after carp removal in Lake Wingra. In 2007, i.e., before carp removal, macrophytes only grew to a water depth of 2 m. Meanwhile, GPR data showed no visible sublayer in vegetated regions, while SBP data revealed a loose and fluffy sediment layer in unvegetated regions, easily affected by wave or current motions. The field data showed that suspended sediment concentrations (SSC) were much greater in unvegetated regions than those in vegetated regions during a one-day wind event, and the resuspended sediments could remain suspended in the water column for two days. In 2009, i.e., after more than half (51%) of carp were removed, the fluffy sediment layer recognized by SBP became thinner or even disappeared, and both SBP and SSS results showed that submerged macrophytes started growing in deeper water. In situ sediment data presented that bulk sediment density and critical shear stress became greater, and bottom sediments consolidated and were harder to be resuspended. Secchi depth collected between 2008 and 2010 was greater than that in the previous 10 years, indicated clearer water state. In short, the fluffy sediment layer because of carp activities may be the main source for suspended sediments to deteriorate water quality. Removal of carp is crucial for stabilizing bottom sediment and improving water clarity in this small lake.

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Section: Methodsmentioning

confidence: 99%

Response of bottom sediment stability after carp removal in a small lake

Lin

2013

Ann. Limnol. - Int. J. Lim.

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“…Underwater vehicles are commonly outfitted with vision sensors for biological [133,145], geological [66,153,174,175], and archaeological [5,144,178] survey needs. As such, they have become standard equipment onboard submersibles.…”

Section: Visually-based Methodsmentioning

confidence: 99%

“…A précis of the diverse mission scenarios for which they are being deployed includes hydrothermal vents and spreading ridges [153,[174][175][176], chemical plume mapping [47,66], studies of biodiversity [133], underwater forensics [69,89,148], deep-water archeology [5,144,178], and the monitoring of coral reefs [145]. Fig.…”

Section: Motivationmentioning

confidence: 99%

Large-area visually augmented navigation for autonomous underwater vehicles

Eustice¹

2005

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This thesis describes a vision-based, large-area, simultaneous localization and mapping (SLAM) algorithm that respects the low-overlap imagery constraints typical of autonomous underwater vehicles (AUVs) while exploiting the inertial sensor information that is routinely available on such platforms. We adopt a systems-level approach exploiting the complementary aspects of inertial sensing and visual perception from a calibrated pose-instrumented platform. This systems-level strategy yields a robust solution to underwater imaging that overcomes many of the unique challenges of a marine environment (e.g., unstructured terrain, low-overlap imagery, moving light source).Our large-area SLAM algorithm recursively incorporates relative-pose constraints using a view-based representation that exploits exact sparsity in the Gaussian canonical form. This sparsity allows for efficient O(n) update complexity in the number of images composing the view-based map by utilizing recent multilevel relaxation techniques. We show that our algorithmic formulation is inherently sparse unlike other feature-based canonical SLAM algorithms, which impose sparseness via pruning approximations. In particular, we investigate the sparsification methodology employed by sparse extended information filters (SEIFs) and offer new insight as to why, and how, its approximation can lead to inconsistencies in the estimated state errors. Lastly, we present a novel algorithm for efficiently extracting consistent marginal covariances useful for data association from the information matrix.In summary, this thesis advances the current state-of-the-art in underwater visual navigation by demonstrating end-to-end automatic processing of the largest visually navigated dataset to date using data collected from a survey of the RMS Titanic (path length over 3 km and 3100 m 2 of mapped area). This accomplishment embodies the summed contributions of this thesis to several current SLAM research issues including scalability, 6 degree of freedom motion, unstructured environments, and visual perception.

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“…In terms of attenuation, sonar is by far the preferred sensor for surveying the ocean seafloor [3], and imaging sonars in particular are a popular alternative to underwater cameras. Recent work related to imaging sonars has focused on the registration problem, where two overlapping images are geometrically matched.…”

Section: A Related Workmentioning

confidence: 99%

Building 3D mosaics from an Autonomous Underwater Vehicle, Doppler velocity log, and 2D imaging sonar

Ozog

Troni

Kaess

et al. 2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-This paper reports on a 3D photomosaicing pipeline using data collected from an autonomous underwater vehicle performing simultaneous localization and mapping (SLAM). The pipeline projects and blends 2D imaging sonar data onto a large-scale 3D mesh that is either given a priori or derived from SLAM. Compared to other methods that generate a 2D-only mosaic, our approach produces 3D models that are more structurally representative of the environment being surveyed. Additionally, our system leverages recent work in underwater SLAM using sparse point clouds derived from Doppler velocity log range returns to relax the need for a prior model. We show that the method produces reasonably accurate surface reconstruction and blending consistency, with and without the use of a prior mesh. We experimentally evaluate our approach with a Hovering Autonomous Underwater Vehicle (HAUV) performing inspection of a large underwater ship hull.

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Iron Age Shipwrecks in Deep Water off Ashkelon, Israel

Cited by 132 publications

References 17 publications

Response of bottom sediment stability after carp removal in a small lake

Response of bottom sediment stability after carp removal in a small lake

Large-area visually augmented navigation for autonomous underwater vehicles

Building 3D mosaics from an Autonomous Underwater Vehicle, Doppler velocity log, and 2D imaging sonar

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