Assessment of different models for bathymetry calculation using SPOT multispectral images in a high-turbidity area: the mouth of the Guadiana Estuary

Periodic calculation of coastal bathymetries can show the evolution of geomorpholo- gical features in active areas such as mesotidal estuary mouths. Bathymetries in shallow coastal areas have been addressed mainly by two technologies, lidar and optical remote sensing. Lidar provides good accuracy, but is an expensive technique, requiring planned flights for each region and dates of interest. Optical remote sensing acquires images periodically but its results are limited by water turbidity. Here we use a lidar bathymetry to compare different bathymetry computation methods using a SPOT optical image from a nearby date. Three statistical models (green-band, PCA correlations, and GLM) were applied to obtain mathematical expressions to estimate bathymetry from that image: all gave errors lower than 1 m in an area with depths ranging from 0 to 6 m. These algorithms were then applied to images from three different dates, correcting the effects caused by different tidal and atmospheric condi- tions. We show how this allows the study of morphological changes. We discuss the accuracy obtained with respect to the reference bathymetry (0.9 m on average, but less than 0.5 m in low-turbidity areas), the effects of the turbidity on our estimations, and compare both with previously published results. The results show that this approach is effective and allows identification of known features of coastal dynamics, and thus it would be an important step towards short-term bathymetry monitoring based on optical satellite remote sensing.Ministerio de Ciencia e Innovación CSO2010-15807Consejería de Innovación, Ciencia y Empresa P10-RNM-620

Radar sounding using the Cassini altimeter waveform modeling and Monte Carlo approach for data inversion observations of Titan's seas

Recently, the Cassini RADAR has been used as a sounder to probe the depth and constrain the composition of hydrocarbon seas on Saturn's largest moon, Titan. Altimetry waveforms from observations over the seas are generally composed of two main reflections: the first from the surface of the liquid and the second from the seafloor. The time interval between these two peaks is a measure of sea depth, and the attenuation from the propagation through the liquid is a measure of the dielectric properties, which is a sensitive property of liquid composition. Radar measurements are affected by uncertainties that can include saturation effects, possible receiver distortion, and processing artifacts, in addition to thermal noise and speckle. To rigorously treat these problems, we simulate the Ku-band altimetry echo received from Titan's seas using a two-layer model, where the surface is represented by a specular reflection and the seafloor is modeled using a facet-based synthetic surface. The simulation accounts for the thermal noise, speckle, analog-to-digital conversion, and block adaptive quantization and allows for possible receiver saturation. We use a Monte Carlo method to compare simulated and observed waveforms and retrieve the probability distributions of depth, surface/subsurface intensity ratio, and subsurface roughness for the individual double-peaked waveform of Ligeia Mare acquired by the Cassini spacecraft in May 2013. This new analysis provides an update to the Ku-band attenuation and results in a new estimate for its loss tangent and composition. We also demonstrate the ability to retrieve bathymetric information from saturated altimetry echoes acquired over Ontario Lacus in December 2008

On the effect of random errors in gridded bathymetric compilations

We address the problem of compiling bathymetric data sets with heterogeneous coverage and a range of data measurement accuracies. To generate a regularly spaced grid, we are obliged to interpolate sparse data; our objective here is to augment this product with an estimate of confidence in the interpolated bathymetry based on our knowledge of the component of random error in the bathymetric source data. Using a direct simulation Monte Carlo method, we utilize data from the International Bathymetric Chart of the Arctic Ocean database to develop a suitable methodology for assessment of the standard deviations of depths in the interpolated grid. Our assessment of random errors in each data set are heuristic but realistic and are based on available metadata from the data providers. We show that a confidence grid can be built using this method and that this product can be used to assess reliability of the final compilation. The methodology as developed here is applied to bathymetric data but is equally applicable to other interpolated data sets, such as gravity and magnetic data

Automatic Processing of High-Rate, High-Density Multibeam Echosounder Data

Multibeam echosounders (MBES) are currently the best way to determine the bathymetry of large regions of the seabed with high accuracy. They are becoming the standard instrument for hydrographic surveying and are also used in geological studies, mineral exploration and scientific investigation of the earth\u27s crustal deformations and life cycle. The significantly increased data density provided by an MBES has significant advantages in accurately delineating the morphology of the seabed, but comes with the attendant disadvantage of having to handle and process a much greater volume of data. Current data processing approaches typically involve (computer aided) human inspection of all data, with time-consuming and subjective assessment of all data points. As data rates increase with each new generation of instrument and required turn-around times decrease, manual approaches become unwieldy and automatic methods of processing essential. We propose a new method for automatically processing MBES data that attempts to address concerns of efficiency, objectivity, robustness and accuracy. The method attributes each sounding with an estimate of vertical and horizontal error, and then uses a model of information propagation to transfer information about the depth from each sounding to its local neighborhood. Embedded in the survey area are estimation nodes that aim to determine the true depth at an absolutely defined location, along with its associated uncertainty. As soon as soundings are made available, the nodes independently assimilate propagated information to form depth hypotheses which are then tracked and updated on-line as more data is gathered. Consequently, we can extract at any time a “current-best” estimate for all nodes, plus co-located uncertainties and other metrics. The method can assimilate data from multiple surveys, multiple instruments or repeated passes of the same instrument in real-time as data is being gathered. The data assimilation scheme is sufficiently robust to deal with typical survey echosounder errors. Robustness is improved by pre-conditioning the data, and allowing the depth model to be incrementally defined. A model monitoring scheme ensures that inconsistent data are maintained as separate but internally consistent depth hypotheses. A disambiguation of these competing hypotheses is only carried out when required by the user. The algorithm has a low memory footprint, runs faster than data can currently be gathered, and is suitable for real-time use. We call this algorithm CUBE (Combined Uncertainty and Bathymetry Estimator). We illustrate CUBE on two data sets gathered in shallow water with different instruments and for different purposes. We show that the algorithm is robust to even gross failure modes, and reliably processes the vast majority of the data. In both cases, we confirm that the estimates made by CUBE are statistically similar to those generated by hand

UBathy: a new approach for bathymetric inversion from video imagery

A new approach to infer the bathymetry from coastal video monitoring systems is presented. The methodology uses principal component analysis of the Hilbert transform of video images to obtain the components of the wave propagation field and their corresponding frequency and wavenumber. Incident and reflected constituents and subharmonics components are also found. Local water depth is then successfully estimated through wave dispersion relationship. The method is first applied to monochromatic and polychromatic synthetic wave trains propagated using linear wave theory over an alongshore uniform bathymetry in order to analyze the influence of different parameters on the results. To assess the ability of the approach to infer the bathymetry under more realistic conditions and to explore the influence of other parameters, nonlinear wave propagation is also performed using a fully nonlinear Boussinesq-type model over a complex bathymetry. In the synthetic cases, the relative root mean square error obtained in bathymetry recovery (for water depths 0.75m¿h¿8.0m) ranges from ~1% to ~3% for infinitesimal-amplitude wave cases (monochromatic or polychromatic) to ~15% in the most complex case (nonlinear polychromatic waves). Finally, the new methodology is satisfactorily validated through a real field site video.Postprint (published version

MAGSAT investigation of crustal magnetic anomalies in the eastern Indian Ocean

Crustal magnetic anomalies in a region of the eastern Indian Ocean were studied using data from NASA's MAGSAT mission. The investigation region (0 deg to 50 deg South, 75 to 125 deg East) contains several important tectonic features, including the Broken Ridge, Java Trench, Ninetyeast Ridge, and Southeast Indian Ridge. A large positive magnetic anomaly is associated with the Broken Ridge and smaller positive anomalies correlate with the Ninetyeast Ridge and western Australia. Individual profiles of scalar data (computed from vector components) were considered to determine the overall data quality and resolution capability. A set of MAGSAT ""Quiet-Time'' data was used to compute an equivalent source crustal magnetic anomaly map of the study region. Maps of crustal magnetization and magnetic susceptibility were computed from the equivalent source dipoles. Gravity data were used to help interpretation, and a map of the ratio of magnetization to density contrasts was computed using Poisson's relation. The results are consistent with the hypothesis of induced magnetization of a crustal layer having varying thickness and composition

Airborne laser bathymetry for documentation of submerged archaeological sites in shallow water

Knowledge of underwater topography is essential to the understanding of the organisation and distribution of archaeological sites along and in water bodies. Special attention has to be paid to intertidal and inshore zones where, due to sea-level rise, coastlines have changed and many former coastal sites are now submerged in shallow water. Mapping the detailed inshore topography is therefore important to reconstruct former coastlines, identify sunken archaeological structures and locate potential former harbour sites. However, until recently archaeology has lacked suitable methods to provide the required topographical data of shallow underwater bodies. Our research shows that airborne topo-bathymetric laser scanner systems are able to measure surfaces above and below the water table over large areas in high detail using very short and narrow green laser pulses, even revealing sunken archaeological structures in shallow water. Using an airborne laser scanner operating at a wavelength in the green visible spectrum (532 nm) two case study areas in different environmental settings (Kolone, Croatia, with clear sea water; Lake Keutschach, Austria, with turbid water) were scanned. In both cases, a digital model of the underwater topography with a planimetric resolution of a few decimeters was measured. While in the clear waters of Kolone penetration depth was up to 11 meters, turbid Lake Keutschach allowed only to document the upper 1.6 meters of its underwater topography. Our results demonstrate the potential of this technique to map submerged archaeological structures over large areas in high detail providing the possibility for systematic, large scale archaeological investigation of this environment

Use of remotely-derived bathymetry for modelling biomass in marine environments

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 techniques—such 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

Scattering statistics of rock outcrops: Model-data comparisons and Bayesian inference using mixture distributions

The probability density function of the acoustic field amplitude scattered by the seafloor was measured in a rocky environment off the coast of Norway using a synthetic aperture sonar system, and is reported here in terms of the probability of false alarm. Interpretation of the measurements focused on finding appropriate class of statistical models (single versus two-component mixture models), and on appropriate models within these two classes. It was found that two-component mixture models performed better than single models. The two mixture models that performed the best (and had a basis in the physics of scattering) were a mixture between two K distributions, and a mixture between a Rayleigh and generalized Pareto distribution. Bayes' theorem was used to estimate the probability density function of the mixture model parameters. It was found that the K-K mixture exhibits significant correlation between its parameters. The mixture between the Rayleigh and generalized Pareto distributions also had significant parameter correlation, but also contained multiple modes. We conclude that the mixture between two K distributions is the most applicable to this dataset.Comment: 15 pages, 7 figures, Accepted to the Journal of the Acoustical Society of Americ