Bathymetric mapping by means of remote sensing: methods, accuracy and limitations

Gao, Jay

doi:10.1177/0309133309105657

Cited by 327 publications

(235 citation statements)

References 30 publications

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“…Analytical modeling of bathymetry is based on the characteristics of propagation of light in the water column. An analytical model is based on number of optical properties of water, such as the attenuation coefficient and backscattering are required as input parameter [7]. The flow radiative transfer model is a commonly used analytical model and it requires the input of the spectral signatures of suspended and dissolved materials, and bottom reflectance [13].…”

Section: Bathymetric Measurements Using Optical Rsmentioning

confidence: 99%

“…RS allows modeling of bathymetry at spatial scales that are impossible to achieve with traditional methods. Bathymetry can be estimated using RS by using several techniques, each having its own depth detection capability, accuracy/error/precision, strengths/advantages, drawbacks and best application environment [7]. The two broad categories used in remote sensing for deriving bathymetry information are active RS methods and passive RS methods.…”

Section: Introductionmentioning

confidence: 99%

“…It is the time drift Table 1. Types of non-imaging and imaging systems with their strengths and limitations (source: modified from Gao [7] of the returned radiation pulses from the object at the sensed spots, which is eventually used to produce bathymetric information. However, this method is limited by the coarse bathymetric sampling interval and high cost.…”

Section: Introductionmentioning

confidence: 99%

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A Synoptic Review on Deriving Bathymetry Information Using Remote Sensing Technologies: Models, Methods and Comparisons

Jawak¹,

Vadlamani²,

Luis³

2015

ARS

114

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This paper discusses the bathymetric mapping technologies by means of satellite remote sensing (RS) with special emphasis on bathymetry derivation models, methods, accuracies, advantages, limitations, and comparisons. Traditionally, bathymetry can be mapped using echo sounding sounders. However, this method is constrained by its inefficiency in shallow waters and very high operating logistic costs. In comparison, RS technologies present efficient and cost-effective means of mapping bathymetry over remote and broad areas. RS of bathymetry can be categorised into two broad classes: active RS and passive RS. Active RS methods are based on active satellite sensors, which emit artificial radiation to study the earth surface or atmospheric features, e.g. light detection and ranging (LIDAR), polarimetric synthetic aperture radar (SAR), altimeters, etc. Passive RS methods are based on passive satellite sensors, which detect sunlight (natural source of light) radiation reflected from the earth and thermal radiation in the visible and infrared portion of the electromagnetic spectrum, e.g. multispectral or optical satellite sensors. Bathymetric methods can also be categorised as imaging methods and non-imaging methods. The non-imaging method is elucidated by laser scanners or LIDAR, which measures the distance between the sensor and the water surface or the ocean floor using a single wave pulse or double waves. On the other hand, imaging methods approximate the water depth based on the pixel values or digital numbers (DN) (representing reflectance or backscatter) of an image. Imaging methods make use of the visible and/or near infrared (NIR) and microwave radiation. Imaging methods are implemented with either analytical modelling or empirical modelling, or by a blend of both. This paper presents the development of bathymetric mapping technology by using RS, and discusses the state-of-the-art S. D. Jawak et al. 148bathymetry derivation methods/algorithms and their implications in practical applications.

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Section: Bathymetric Measurements Using Optical Rsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Synoptic Review on Deriving Bathymetry Information Using Remote Sensing Technologies: Models, Methods and Comparisons

Jawak¹,

Vadlamani²,

Luis³

2015

ARS

114

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“…Such information is also critical for port facility management and dredging operation [Gao, 2009]. Bathymetric data are significant to all ocean management decisions, such as identifying living and nonliving ocean resources, responding to extreme events, spatial planning, and geohazard assessment [Lucieer et al, 2016].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Effective Swath Width for Dual-Head Multibeam Echosounder

Grządziel

Wąż

2016

Annual of Navigation

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Many surveying companies and maritime institutions are now using multibeam systems for their operations, either offshore or in coastal and inland waters. Since the time the first multibeam echosounder appeared (late 1970s) the technology has advanced enormously. Modern systems now boast far greater angular coverage (typically 120º-150º) and form hundreds of beams. Dual-head multibeam systems can potentially cover the entire sector (180º) underneath the ship. However surveyors must be aware that the outer beams of these acoustic systems return the most errors causing that the effective swath width is shorter than what the manufacturers declare. The paper presents the methods of estimating of effective (usable) swath width of dual-head multibeam echosounder EM 3002D. Results of the hydrographic survey performed by the polish navy survey ship ORP 'Arctowski' have been showed in the article.

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“…Mapping underwater features as rocks, sandy areas, sediments accumulation and coral reefs needs up to date water depths information [2], [3]. Water depths data are essential also for accomplishing sustainable management [4], bathymetric information constitutes a key element hydrological modeling, flooding estimation and degrading or sediments removing [5], [6]. Manuscript received November 25, 2014; revised April 27, 2015.…”

mentioning

confidence: 99%

Bathymetry Determination from High Resolution Satellite Imagery Using Ensemble Learning Algorithms in Shallow Lakes: Case Study El-Burullus Lake

Mohamed¹,

Negm²,

Zahran³

et al. 2016

IJESD

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Abstract-Determination of bathymetric information is key element for near off shore activities and hydrological studies such as coastal engineering applications, sedimentary processes and hydrographic surveying. Remotely sensed imagery has provided a wide coverage, low cost and time-effective solution for bathymetric measurements. In this paper a methodology is introduced using Ensemble Learning (EL) fitting algorithm of Least Squares Boosting (LSB) for bathymetric maps calculation in shallow lakes from high resolution satellite images and water depth measurement samples using Eco-sounder. This methodology considered the cleverest sequential ensemble that assigns higher weights as Boosting for those training sets that are difficult to fit. The LSB ensemble using reflectance of Green and Red bands and their logarithms from Spot-4 satellite image was compared with two conventional methods; the Principal Component Analysis (PCA) and Generalized Linear Model (GLM). The retrieved bathymetric information from the three methods was evaluated using Echo Sounder data. The LSB fitting ensemble resulted in RMSE of 0.15m where the PCA and GLM yielded RMSE of 0.19m and 0.18m respectively over shallow water depths less than 2m. The application of the proposed approach demonstrated better performance and accuracy compared with the conventional methods.Index Terms-Bathymetry, PCA, GLM, least square boosting. I. INTRODUCTIONAccurate bathymetric information is so important for costal science applications, shipping navigations and environmental studies of marine areas [1]. Mapping underwater features as rocks, sandy areas, sediments accumulation and coral reefs needs up to date water depths information [2], [3]. Water depths data are essential also for accomplishing sustainable management [4], bathymetric information constitutes a key element hydrological modeling, flooding estimation and degrading or sediments removing [5], [6]. Manuscript received November 25, 2014; revised April 27, 2015. The work was supported by Mission Department, Egyptian Ministry of Higher Education (MoHE), Egypt-Japan University of Science and Technology (E-JUST) and partially supported by JSPS "Core-to-Core Program, B. Asia-Africa Science Platforms".H. Mohamed and Abdelazim Negm are with the Environmental Engineering Department, School of Energy and Environmental Engineering, Egypt-Japan University of Science and Technology, Alexandria, Egypt (e-mail: hassan.mohamed@ejust.edu.eg, negm@ejust.edu.eg).M. Zahran is with the Department of Geomatics Engineering, Faculty of Engineering at Shoubra, Benha University, Egypt (e-mail: mohamed.zahran01@feng.bu.edu.eg).O. Saavedra is with the Department of Civil Engineering, Tokyo Institute of Technology, Oookayama, Meguro, Tokyo, Japan. He is also with E-JUST, Egypt (e-mail: saavedra.o.aa@m.titech.ac.jp).Sonar remains the primary method for obtaining discreet water depth measurements with high accuracy [7]. Single beam sonar on survey vessel can acquire single point depths along sparsely surveying scan lines up to 50...

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Bathymetric mapping by means of remote sensing: methods, accuracy and limitations

Cited by 327 publications

References 30 publications

A Synoptic Review on Deriving Bathymetry Information Using Remote Sensing Technologies: Models, Methods and Comparisons

A Synoptic Review on Deriving Bathymetry Information Using Remote Sensing Technologies: Models, Methods and Comparisons

Estimation of Effective Swath Width for Dual-Head Multibeam Echosounder

Bathymetry Determination from High Resolution Satellite Imagery Using Ensemble Learning Algorithms in Shallow Lakes: Case Study El-Burullus Lake

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