Modelling bathymetry by inverting satellite altimetry data: A review

Calmant, Stéphane; Baudry, Nicolas

doi:10.1007/bf00286073

Cited by 37 publications

(26 citation statements)

References 46 publications

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“…Despite initial reports stating that it was impossible to derive reliable bathymetry from satellite altimeter (Keating et al, 1984;Watts and Ribe, 1984), Dixon et al (1983) were the first to demonstrate its feasibility using real data. Several algorithms and methods to estimate and predict bathymetry from the gravitational field have since been developed (reviewed in Calmant andBeaudry, 1996 andSmith, 2001). However, it remains a complex process (Calmant and Beaudry, 1996) that still requires acoustic data for calibration (Smith and Sandwell, 1997).…”

Section: Discussionmentioning

confidence: 99%

A review of marine geomorphometry, the quantitative study of the seafloor

Lecours

Dolan

Micallef

et al. 2016

Hydrol. Earth Syst. Sci.

179

120

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Abstract. Geomorphometry, the science of quantitative terrain characterization, has traditionally focused on the investigation of terrestrial landscapes. However, the dramatic increase in the availability of digital bathymetric data and the increasing ease by which geomorphometry can be investigated using geographic information systems (GISs) and spatial analysis software has prompted interest in employing geomorphometric techniques to investigate the marine environment. Over the last decade or so, a multitude of geomorphometric techniques (e.g. terrain attributes, feature extraction, automated classification) have been applied to characterize seabed terrain from the coastal zone to the deep sea. Geomorphometric techniques are, however, not as varied, nor as extensively applied, in marine as they are in terrestrial environments. This is at least partly due to difficulties associated with capturing, classifying, and validating terrain characteristics underwater. There is, nevertheless, much common ground between terrestrial and marine geomorphometry applications and it is important that, in developing marine geomorphometry, we learn from experiences in terrestrial studies. However, not all terrestrial solutions can be adopted by marine geomorphometric studies since the dynamic, fourdimensional (4-D) nature of the marine environment causes its own issues throughout the geomorphometry workflow. For instance, issues with underwater positioning, variations in sound velocity in the water column affecting acousticbased mapping, and our inability to directly observe and measure depth and morphological features on the seafloor are all issues specific to the application of geomorphometry in the marine environment. Such issues fuel the need for a dedicated scientific effort in marine geomorphometry.This review aims to highlight the relatively recent growth of marine geomorphometry as a distinct discipline, and offers the first comprehensive overview of marine geomorphometry to date. We address all the five main steps of geomorphometry, from data collection to the application of terrain attributes and features. We focus on how these steps are relevant to marine geomorphometry and also highlight differences and similarities from terrestrial geomorphometry. We conclude with recommendations and reflections on the future of marine geomorphometry. To ensure that geomorphometry is used and developed to its full potential, there is a need to increase awareness of (1) marine geomorphometry amongst scientists already engaged in terrestrial geomorphometry, and of (2) geomorphometry as a science amongst marine scientists with a wide range of backgrounds and experiences.

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Section: Discussionmentioning

confidence: 99%

A review of marine geomorphometry, the quantitative study of the seafloor

Lecours

Dolan

Micallef

et al. 2016

Hydrol. Earth Syst. Sci.

179

120

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“…Several algorithms are developed to derive bathymetric predictions from satellite altimeter. The most popular methods are: 1) the one-dimensional inversion of satellite tracks using linear approximation of the transfer function [9] [48] [49], 2) the one-dimensional adjustment of synthetic and satellite tracks [50], 3) the geometrical analysis of satellite tracks [51], 4) the two-dimensional inversion of geoid anomalies [52], and 5) the two-dimensional inversion of satellite data and the merging with conventional geophysical measurements [10] [53] [54].…”

Section: Bathymetric Measurements Using Altimetrymentioning

confidence: 99%

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

Jawak¹,

Vadlamani²,

Luis³

2015

ARS

109

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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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“…At present, a continuous time series of sea surface topography is being maintained by Jason-2 (LAMBIN et al 2010) and, additionally, by Jason-1, Cryosat-2 and HY-2. Altimetry can be utilised to produce sea floor bathymetry data through application of inversion algorithms (DIXON et al 1983;BAUDRY and CALMANT 1991;CALMANT and BAUDRY 1996) based on the fact that depth influences local gravity. The description of the problem may be summarised as follows: ''depth variations of the seafloor can be considered as height variations of mass elements the density Dq of which is given by the contrast between rock and sea water densities' ' (CALMANT and BAUDRY 1996).…”

Section: Global Bathymetrymentioning

confidence: 99%

“…Altimetry can be utilised to produce sea floor bathymetry data through application of inversion algorithms (DIXON et al 1983;BAUDRY and CALMANT 1991;CALMANT and BAUDRY 1996) based on the fact that depth influences local gravity. The description of the problem may be summarised as follows: ''depth variations of the seafloor can be considered as height variations of mass elements the density Dq of which is given by the contrast between rock and sea water densities' ' (CALMANT and BAUDRY 1996). This concept was used by HAXBY et al (1983) andHAXBY (1985) who first produced a global map of the marine gravity field.…”

Section: Global Bathymetrymentioning

confidence: 99%

“…There are a few procedures that allow us to invert satellite altimetric data to sea floor topography data, and the development of these methods was initiated by DIXON et al (1983). A review of more advanced approaches was presented by CALMANT and BAUDRY (1996). SMITH and SANDWELL (1997) produced a global digital bathymetric map of the oceans with a horizontal resolution of 2 arc-minutes by combining high-resolution marine gravimetry from Geosat and ERS-1 with carefully validated ship-borne depth soundings.…”

Section: Global Bathymetrymentioning

confidence: 99%

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Use of Remotely-Derived Bathymetry for Modelling Biomass in Marine Environments

Wieczorek

Niedzielski

Godbold

et al. 2013

Pure Appl. Geophys.

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Abstract-The paper presents results on the influence of geometric attributes of satellite-derived raster bathymetric data, namely the General Bathymetric Charts of the Oceans, on spatial statistical modelling of marine biomass. In the initial experiment, both the resolution and projection of the raster dataset are taken into account. It was found that, independently of the equal-area projection chosen for the analysis, the calculated areas are very similar, and the differences between them are insignificant. Likewise, any variation in the raster resolution did not change the computed area. Although the differences were shown to be insignificant, for the subsequent analysis we selected the cylindrical equal area projection, as it implies rectangular spatial extent, along with the automatically derived resolution. Then, in the second experiment, we focused on demersal fish biomass data acquired from trawl samples taken from the western parts of ICES Sub-area VII, near the sea floor. The aforementioned investigation into processing bathymetric data allowed us to build various statistical models that account for a relationship between biomass, sea floor topography and geographic location. We fitted a set of generalised additive models and generalised additive mixed models to combinations of trawl data of the roundnose grenadier (Coryphaenoides rupestris) and bathymetry. Using standard statistical techniquessuch as analysis of variance, Akaike information criterion, root mean squared error, mean absolute error and cross-validation-we compared the performance of the models and found that depth and latitude may serve as statistically significant explanatory variables for biomass of roundnose grenadier in the study area. However, the results should be interpreted with caution as sampling locations may have an impact on the biomass-depth relationship.

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Modelling bathymetry by inverting satellite altimetry data: A review

Cited by 37 publications

References 46 publications

A review of marine geomorphometry, the quantitative study of the seafloor

A review of marine geomorphometry, the quantitative study of the seafloor

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

Use of Remotely-Derived Bathymetry for Modelling Biomass in Marine Environments

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