The impressive growth of the aviation industry and the number of flights entail several environmental repercussions, such as increased aircraft noise emissions. With the worrying number of complaints from the communities around airports comes also the distrust in numerical models used for aircraft noise prediction. In this study, we compare the ‘Dutch aircraft noise model’ predictions to measured values from the NOise MOnitoring System (NOMOS) around Amsterdam Airport Schiphol between 2012 and 2018. While the model underestimates aircraft noise in 2012, the model prediction improved throughout the years. We observe a decreasing trend of measured aircraft-related L_den values of 0.6dB(A)/year (a total of 3.6dB(A) over the investigation period), although the total number of flight movements increased during the observation time. We propose that a change in fleet mix, as well as the implementation of Noise Abatement Procedures at Schiphol Airport, fuelled this trend.

@en

Realistic predictions of the contribution of the uncertainty sources affecting the quality of the bathymetric measurements prior to a survey is of importance. To this end, models predicting these contributions have been developed. The objective of the present paper is to assess the performance of the bathymetric uncertainty prediction model for Phase Difference Bathymetric Sonars (PDBS) which is an interferometric sonar. Two data sets were acquired with the Bathyswath-2 system with a frequency of 234 kHz at average water depths of around 26 m and 8 m with pulse lengths equal to 0.0555 ms and 0.1581 ms, respectively. The comparison between the bathymetric uncertainties derived from the measurements and those predicted using the current model indicates a relatively good agreement except for the across-track distances close to the nadir. The performance of the prediction model can be improved by modifying the term addressing the effect of footprint shift, i.e., spatial decorrelation, on the bottom due to fact that at a given time the footprints seen by different receiving arrays are slightly different@en

The sound speed provides insight in ocean properties, as it depends on depth, temperature and salinity. Here, we propose a method to invert sound speed profiles (SSPs) from multibeam echosounder (MBES) measurements, providing a SSP for every ping. Using erroneous SSPs results in a mismatch in the estimated bathymetry between overlapping swaths. The SSP is estimated by minimizing this mismatch using Differential Evolution. In this work, SSPs are described using empirical orthogonal functions (EOFs), which are obtained from historical SSPs. As a proof-of-concept, we apply the inversion on a simulated MBES survey, where the synthetically generated SSPs are fully described by 3 EOFs. The inverted SSPs deviate 1 m/s from the correct profiles. In the case of actual SSPs, more EOFs are possibly required. The number of required EOFs to get an accurate estimate of the SSP is assessed by using SSPs acquired in the North Sea. Results show that including only 2 EOFs is sufficient to accurately estimate the SSP, although larger deviations up to 3 m/s were found. In this paper, we demonstrated the potential of the proposed method to invert SSPs from MBES measurements, which can provide information about the vertical structure of the water column. @en

Detailed information about the sea and river bed is of high importance for a large number of applications, such as marine geology, coastal engineering, safe navigation and offshore construction. Acoustic remote sensing techniques have become extremely attractive for obtaining bathymetry measurements and for mapping the sediment properties, due to their high coverage capabilities and relatively low costs. Among the available tools for remotely mapping the seafloor, the MultiBeam EchoSounder (MBES) belongs to the state-of-the-art technology enabling acquisition of high resolution measurements of bathymetry within a relatively short time period. Despite the widespread use of MBESs for hydrographic operations and the considerable efforts devoted to optimize these operations, the existing knowledge with regard to the measurement capabilities of the MBES is lacking in some respects. This can lead to an unreliable and inaccurate representation of the seafloor and/or unrealistic estimates of the measurement uncertainties. Moreover, realistic pre-survey predictions of the contribution of the various uncertainty sources affecting the quality of the bathymetric measurements is of importance to ensure sufficient accuracy of the soundings and a correct interpretation of the sediment properties. This thesis thus aims at bringing the insight of the MBES measurement capabilities to a new stage by addressing these issues. The contribution of this thesis to the field of MBES bathymetric mapping is to bring the knowledge of the MBES measurements capabilities to a stage such that hydrographic operations are optimized. This leads to a reliable and accurate representation of the bottom and a realistic expectation of the associated uncertainties. Optimizing hydrographic operations is accomplished by correcting the systematic errors (if present), using a realistic depth uncertainty prediction model and addressing proper distribution of the soundings while ensuring low uncertainties of the measurement. These issues allow for realistic bathymetry maps and need to be accounted for in survey planning. @en

Realistic predictions of the contribution of the various sources affecting the quality of the bathymetric measurements prior to a survey are of importance to ensure sufficient accuracy of the soundings. To this end, models predicting these contributions have been developed. The objective of the present paper is to assess the performance of the bathymetric uncertainty prediction model for modern Multi-Beam Echo-Sounder (MBES) systems. Two datasets were acquired at water depths of 10m and 30m with three pulse lengths equaling 27 μs, 54 μs, and 134 μs in the Oosterschelde estuary (The Netherlands). The comparison between the bathymetric uncertainties derived from the measurements and those predicted using the current model indicated a relatively good agreement except for the most outer beams. The performance of the uncertainty prediction model improved by accounting for the most recent insights into the contributors to the MBES depth uncertainties, i.e., the Doppler effect, baseline decorrelation (accounting for the pulse shape), and the signal-to-noise ratio.

@en

Multi-frequency multibeam backscatter (BS) has indicated, in particular for fine sediments, the potential for increasing the discrimination between different seabed environments. Fine sediments are expected to have a varying signal penetration within the frequency range of modern multibeam echosounders (MBESs). Therefore, it is unknown to what extent the multispectral MBES data represent the surface of the seabed or different parts of the subsurface. Here, the effect of signal penetration on the measured multi-frequency BS and bathymetry is investigated. To this end, two multi-frequency datasets (90 to 450 kHz) were acquired with an R2Sonic 2026 MBES, supported by ground-truthing, in the Vlietland Lake and Port of Rotterdam (The Netherlands). In addition, a model to simulate the MBES bathymetric measurements in a layered medium is developed. The measured bathymetry difference between the lowest (90 kHz) and highest frequency (450 kHz) in areas with muddy sediments reaches values up to 60 cm dependent on the location and incident angle. In spatial correspondence with the variation in the depth difference, the BS level at the lowest frequency varies by up to 15 dB for the muddy sediments while the BS at the highest frequency shows only small variations. A comparison of the acoustic results with the ground-truthing, geological setting and model indicates that the measured bathymetry and BS at the different frequencies correspond to different parts of the seabed. However, the low-frequency BS cannot be directly related to a subsurface layer because of a significant sound attenuation in the upper layer. The simulation of the MBES bottom detection indicates that the bathymetry measured at the highest and lowest frequency can be used to determine the thickness of thin layers (20 cm). However, with an increasing layer thickness, the bottom detection becomes more sensitive to the incident angle and small variations in the sediment properties. Consequently, an accurate determination of the layer thickness is hampered. Based on this study, it is highly recommended to analyze multi-frequency BS in combination with the inter-frequency bathymetry difference to ensure a correct interpretation and classification of multi-frequency BS data.

@en

Methods for gridding multibeam echo sounder (MBES) measurements to equidistant grids are proposed as alternatives to the shallowest measured depth, which is affected by outliers. The approaches considered use a combination of mean and standard deviation of soundings and the regression coefficient from the best fitted plane. These methods along with mean and shallowest depths were applied to two surveyed areas. Two issues were found to be of importance, that is, a proper distribution of soundings and low uncertainties in the depth measurements. Improper sampling excludes using the method employing regression coefficients. For flat areas, the shallowest measured depth was found to be highly influenced by measurement uncertainties, counteracted when using the mean depth. However, the mean depth underestimates the shallowest depth for areas with slopes. When correcting the mean depth for standard deviation, the effect of slopes is accounted for while the influence of measurement uncertainties is decreased compared to shallowest measured depth. Since the uncertainties are dependent on beam angle, depth, and measurement equipment, these issues need to be accounted for in survey planning.

@en

Nowadays Multi-Beam Echo-Sounder (MBES) systems are used for obtaining information of the sea/river bed bathymetry and sediment composition. For the latter, use is usually made of the backscatter strength and depth derivatives, such as depth residuals. However, the depth derivatives are affected by the uncertainties inherent to the MBES varying with the sensors used, survey configuration and operational environment. Although models are available for the vertical uncertainty prediction, the question is how well these models can capture the estimated uncertainties of real observations. The present contribution addresses this issue by comparing the measured with modelled depth uncertainty accounting for the most recent insights of the error contributors. Data was acquired in water depths of around 2m, 10m and 30m with pulse lengths of 27 μs, 54 μs and 134 μs in the Oosterschelde estuary, the Netherlands, enabling the assessment of depth and pulse length dependence of the uncertainties. In general, the predicted and measured uncertainties are in the same order of magnitude. With increasing depth the discrepancy between the modelled and measured uncertainties increases. The effect of changing pulse length is found to be captured by the model, except for the angles close to nadir. The most dominant contributors to the vertical uncertainty are those induced by the angle of impact and range measurements. These contributors thus require further investigation to obtain a more realistic estimate of the vertical uncertainties.@en

In this contribution a method for correcting bathymetric measurements affected by inaccurate water column sound speed profiles (SSPs) is presented. The method exploits the redundancy in the multibeam echosounder measurements obtained from the overlap of adjacent swaths by minimizing the difference between depths along overlapping swaths. Two optimization methods are used, i.e., Differential Evolution (DE) and Gauss-Newton (GN). While DE inverts for the sound speed by minimizing the depth variation, GN inverts for both bathymetry and sound speed by minimizing the squared sum of the differences between the modeled and measured travel times. The inversion method assumes a constant SSP in the water column. Applying the method to a salt wedge survey area with large variations in the water column sound speed indicates a good agreement between the original depth measurements and those derived after the inversion with the mean and standard deviation of the depth differences equaling 0.009m and 0.024m, respectively. This indicates that even with a simple parametrization of the sound speed in the water column, the correct bathymetry can be derived from the inversion. The SSP inversion method is also applied to an area with existing refraction artefacts. It corrects the bathymetry and reduces the mean and standard deviation of the depth standard deviation by a factor of around 2.75 compared to the case where the measured SSPs were used. Furthermore, the SSP inversion method neither manipulates the existing morphology nor introduces artificial bathymetric features in the areas where such refraction artefacts are not present. Considering constant SSPs, both DE and GN give almost identical results with GN being faster. However, GN is less flexible with regards to varying sound speed parameterizations.

@en

Nowadays Multi-Beam Echo-Sounder (MBES) derived bathymetry is used for a large range of applications. However, these measurements are affected by the uncertainties inherent to the MBES. Since the development of the depth uncertainty prediction model, MBES systems have been improved noticeably. The present contribution addresses the importance of modifying the vertical uncertainty prediction model based on the most recent insights of the error contributors.The received signal is affected by a Doppler frequency shift due to the constant movement of the MBES. This induces an error on the beamsteering which is not corrected for by the manufacturer, and hence its contribution is a first-order effect. The phenomenon of baseline decorrelation is encountered in the MBES interferometry step in which the full MBES receiving array is divided into two sub-arrays and the phase difference of the signals arriving at these sub-arrays is determined. The slightly different angular directions of the two received signals together with the finite signal footprint reduces the coherence between them, leading to a deterioration in the precision of the MBES derived depth.In this contribution, we compare the predictions for the bathymetric uncertainty with and without accounting for the Doppler effect and baseline decorrelation with the uncertainties estimated from real observations. To this end, data was acquired with EM2040c dual head MBES (manufactured by Kongsberg) with the center frequency of 300 kHz in water depths of around 2 m, 10 m and 30 m with pulse lengths of 27 μs, 54 μs and 134 μs in Oosterschelde estuary, the Netherlands. In general, the predicted and measured uncertainties are in the same order of magnitude. It is seen that the contribution of the Doppler effect increases with depth and beam angle and, if not accounted for, can potentially lead to an underestimation of the total vertical uncertainty budget. Including the contribution of the baseline decorrelation improves the agreement between the modeled and measured uncertainties for the beams close to nadir.@en

In this contribution bathymetric uncertainties induced by the use of frequency modulated (FM) signals for multi-beam-echo-sounder (MBES) measurements are quantified and their relevance for MBES bathymetric uncertainty predictions is assessed. When switching to FM, the quality of depth measurements can get deteriorated due to the Doppler effect and baseline decorrelation. The uncertainty due to the former is divided into second-order (imperfectness of the Doppler-range correction) and first-order (effect on beamsteering) effects. The latter also holds for continuous wave (CW) signals. Here, situations of relevance for measurements in the continental shelf and ship dynamics associated to rough and calm sea-states are considered, and the vertical uncertainty induced by the above sources is quantified. The influence of the Doppler effect depends on the sea state, but is found to potentially have a significant contribution to the MBES error budget for both FM and CW [nearly 82% (rough) and 68% (calm) of the total uncertainty]. The effect of baseline decorrelation depends on the actual pulse shape. For the specifications investigated, vertical uncertainties induced by this source are predicted to be larger for FM than that of CW. This is confirmed by a comparison between the modelled and measured effect on depth uncertainties when switching to FM.@en

Reliable information about the seafloor and river-bed bathymetry is of high interest for a large number of applications. A Multi-Beam echo sounder (MBES) system is able to produce high-resolution bathymetry data at relatively small cost. These measurements, providing a depth for each beam and every ping, are processed to obtain a more ordered structure, such as a grid. Most approaches for assigning a depth to the centre of a cell (in a grid) use the shallowest or the mean depth in each cell. However, while the grid derived from the mean depth might be too deep compared to the shallowest depth, using the shallowest depth approach can result in an artificially shallow grid, affected by outliers. This paper introduces a number of alternatives to the current methods by combining the mean depth with statistical properties derived from the point cloud of the MBES data. In addition, the possibility of assigning a depth based on the regression coefficients of each cell is considered. The methods introduced have been tested on data acquired in different survey areas. The resulting grids have been compared to their shallowest and mean counterparts to obtain a better understanding of their advantages and limitations.@en

In a world of high precision sensors, one of the few remaining challenges in multibeam echosounding is that of refraction-based uncertainty. A poor understanding of oceanographic variability or a poor choice of equipment can lead directly to poor quality bathymetric data. Post-processing software tools have existed for some time to allow data processors to correct for these artifacts. These tools typically involve the manual review of soundings and manual adjustment of a small set of parameters to achieve the desired correction. Though there are a number of commercial solutions currently available, they all have the same inherent weaknesses: (1) they are manual, thus time-consuming, (2) they are subjective, thus not repeatable, (3) they require expert training and thus are typically only usable by experienced personnel. QPS and the Technical University of Delft, The Netherlands (TU Delft) have worked together to implement an algorithm to address these issues in QPS’ post-processing software, Qimera. The algorithm, the TU Delft Sound Speed Inversion, works by taking advantage of the overlap between survey lines, harnessing the power of redundancy of the multiple observations. For a given set of pings, the algorithm simultaneously estimates sound speed corrections for the chosen pings and their neighbors by computing a best-fit solution that minimizes the mismatch in the areas of overlap between lines. This process is repeated across the entire spatial area, allowing for an adaptive solution that responds to changes in oceanographic conditions. This process is completely automated and requires no operator interaction or data review. The algorithm is also physics-based in that it honors the physics of acoustic ray bending. For accountability, the algorithm preserves the output of the inversion process for review, vetting, adjustment, and reporting. In this paper, we briefly explain how the algorithm works in simple terms. We also explore two data sets that cover differing oceanographic conditions, seabed morphologies, and survey line planning geometries in order to establish some early guiding principles on how far the algorithm can be pushed for performance. @en

The most recent generation multi-beam echosounders (MBES) allows to transmit Frequency Modulated (FM) signals, in addition to the more conventional Continuous Wave (CW) pulses. In this contribution, the effect of using these FM pulses for bathymetric measurements is investigated. Advantage of using FM signals is that measurements can be taken at long ranges, due to the use of long pulse lengths combined with matched filtering at reception. However, it is found that using FM pulses results sometimes in a loss of the quality of the depth measurements. An important contributor to the errors when using FM signals is the Doppler frequency shift of the received signal, inducing errors in the matched filtering and beamsteering. The latter, however, also holds when using CW signals. A second contributor is the baseline decorrelation, resulting from not having an infinitely small footprint. Due to the larger pulse lengths of the FM signals, also the footprint is larger and consequently the effect of baseline decorrelation is more pronounced for FM signals. Here, we consider a situation of relevance for measurements in the Dutch North Sea (water depth of 50 m and ship dynamics corresponding to a typical winter season sea state). For this case, the uncertainty induced by the Doppler frequency shift, both for CW and FM signals, is found to contribute significantly to the MBES total error budget. The effect of baseline decorrelation depends fully on the signal shape and parameters. @en

The second reprocessing of all GPS data gathered by the Analysis Centers of IGS was conducted in late 2013 using the latest models and methodologies. Improved models of antenna phase center variations and solar radiation pressure in JPL’s reanalysis are expected to significantly reduce errors. In an earlier work, JPL estimates of position time series, termed first reprocessing campaign, were examined in terms of their spatial and temporal correlation, power spectra, and draconitic signal. Similar analyses are applied to GPS time series at 89 and 66 sites of the second reanalysis with the time span of 7 and 21 years, respectively, to study possible improvements. Our results indicate that the spatial correlations are reduced on average by a factor of 1.25. While the white and flicker noise amplitudes for all components are reduced by 29–56 %, the random walk amplitude is enlarged. The white, flicker, and random walk noise amount to rate errors of, respectively, 0.01, 0.12, and 0.09 mm/yr in the horizontal and 0.04, 0.41 and 0.3 mm/yr in the vertical. Signals reported previously, such as those with periods of 13.63, 14.76, 5.5, and 351.4 / n for n=1,2,…,8
n=1,2,…,8 days, are identified in multivariate spectra of both data sets. The oscillation of the draconitic signal is reduced by factors of 1.87, 1.87, and 1.68 in the east, north and up components, respectively. Two other signals with Chandlerian period and a period of 380 days can also be detected.@en

Knowing the morphology and sediment composition of the seabed is of high importance for various applications. In this contribution, the repeatability of acoustic seafloor classification (ASC) results obtained from MBES backscatter value is investigated. The unsupervised classification algorithm based on Principal Component Analysis has been applied to the MBES backscatter acquired in the Cleaver Bank, Netherlands Continental Shelf, during five different surveys with two vessels. In general, there is good repeatability between surveys demonstrating the potential of using backscatter for marine environmental monitoring. To increase the discrimination performance the so-called depth residuals can be used. These are derived from the bathymetric measurements and considered to be representative for the sediment roughness. The challenge is that the small-scale depth variations are not solely dependent on the sediment roughness but also on the intrinsic uncertainties inherent to the MBES system. An A-Priori Multibeam Uncertainty Simulation Tool (AMUST) has been developed to predict the depth errors induced by various contributors. Correcting the measured depths for these uncertainties, as predicted by AMUST, theoretically provides information about the actual sediment roughness and this should improve the ASC algorithms. This was first tested on a MBES data set from Shallow Survey Conference Plymouth, 2015. It was shown that for the water depth of 20 m the standard deviation of the depth measurements was in agreement with AMUST predictions indicating a smooth seafloor, however, discrepancies between the predictions and real measurements occurred for the water depth of 8 m which is an indication of roughness or morphological features. This indicates the necessity of knowledge about the uncertainties when the objective is to derive the sediment roughness from MBES measurements. @en