Ocean Wave Imaging Research Articles

Wave height measurement scheme using wave detector based on convolutional neural network and PPM calculator with ocean wave images

The measurement of wave height is essential for weather analysis, safe navigation of ships, and ship design. This study proposes a low-cost and direct method for measuring wave height using ocean wave images. The proposed scheme comprises a Wave Detector based on Convolutional Neural Networks that takes two-dimensional ocean images as input, and a PPM Calculator that measures the size of an object in the image. The study explains the configuration and implementation of the Wave Detector and the basic principle of the PPM surface generating method for the PPM Calculator, with support from ground experiments. The proposed scheme is validated using two types of wave height measurement sensors and three types of real ocean images for the Wave Detector, as well as two rounds of ground experiments for the PPM Calculator.The results show that the wave height values measured by the proposed scheme are highly consistent with the values from the measurement sensors.

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SAR Imaging Algorithm of Ocean Waves Based on Optimum Subaperture.

Synthetic Aperture Radar (SAR) is widely applied to the field of ocean remote sensing. Clear SAR images are the basis for ocean information acquisitions, such as parameter retrieval of ocean waves and wind field inversion of the ocean surface. However, the SAR ocean images are usually blurred, which seriously affects the acquisition of ocean information. The reasons for the wave blurring in SAR images mainly include the following two aspects. One is that when SAR observes the ocean, the motion of ocean waves will have a greater impact on imaging quality. The other is that the ocean’s surface is seriously decorrelated within the integration time. In order to obtain clear SAR images of ocean waves, a SAR imaging algorithm of ocean waves based on the optimum subaperture is proposed, aiming at the above two aspects. The optimum focus setting of the ocean waves is calculated, drawing support from the azimuth phase velocity of the dominant wave. The optimum subaperture is further calculated according to the proposed new evaluation, namely, F. Finally, according to the optimum focus setting and the optimum subaperture, the dominant wave is refocused, and a clear SAR image of the dominant wave can be obtained. The proposed algorithm was applied to airborne L-band and P-band SAR data. Furthermore, the proposed algorithm was compared with present methods, and the results sufficiently demonstrated the effectiveness and superiority of the proposed algorithm.

Numerical Simulation of SAR Image for Sea Surface

Based on the simulated signal, a numerical simulation method of synthetic aperture radar (SAR) imaging for time-varying sea surfaces is proposed, which is helpful to study the SAR imaging mechanism of time-varying sea surfaces so as to better extract ocean wave parameters from SAR images. Not only are the modulation of ocean waves, speckle noise, and temporal decorrelation of the small-scale waves considered, but the velocity bunching (VB) effect caused by the motion of large-scale waves is also effectively added to the simulation of the SAR echo signal. To verify the reliability of the simulation method, the simulated SAR images using the parameters of the RADARSAT-2 SAR, the corresponding wind wave information measured by an in-situ buoy, and the reanalysis wave spectra have been compared with the actual RADARSAT-2 SAR images. The comparisons demonstrate that the characteristics of simulated SAR images, such as the intensity distribution and the image spectra, are consistent with those of actual RADARSAT-2 SAR images. Based on the numerical simulation method proposed by us, SAR images of ocean waves for different marine environments and radar platform parameters are simulated. The imaging results indicate that the texture feature of the wind waves would be severely damaged due to the VB effect, while the texture of swells in the simulated SAR images may not be damaged or even becomes clearer. From the simulated SAR image spectrum, it can be found that the azimuth wavenumber is cut off when the VB effect is considered in the simulation process, and the azimuth cut-off wavelength increases with the range-to-velocity ratio.

A simulator of Synthetic Aperture Radar (SAR) image spectra: the applications on oceanswell waves

ABSTRACT The Synthetic Aperture Radar (SAR) carried on-board satellites yields invaluable data of global wave spectra since the early 1990s, with several satellites in orbit at present and more launches scheduled in the near future. However, the retrieval of wave information from SAR images constitutes a complex set of procedures. In this context, we have presented here a methodology to simulate SAR image spectra of ocean swell waves. SAR simulators are important tools for the implementation and evaluation of wave spectra retrieval schemes. The one proposed here is based on the Hasselmann Transform whose Modulation Transfer Functions (MTF’s) account for the main physical processes involved in the imaging of ocean waves. A detailed description of its structure is provided. Through several test cases, we highlight some particularities of the relationship between SAR image spectra and wave spectra. We have evaluated the impact of the parameters settings and input information on the retrieval process, pinpointing possible shortcomings. The results indicated that useful information about the processes involved in the imaging of ocean swells can be derived from the SAR simulator.

Wave Monitoring Based on Improved Convolution Neural Network

Kang, L., 2019. Wave monitoring based on improved convolution neural network. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 186–190. Coconut Creek (Florida), ISSN 0749-0208.As human's marine activities, such as marine aquaculture, ocean shipping and coastal facilities construction, flourished world-widely, it is required to monitor the ocean wave dynamics timely and accurately. In this paper, a convolutional neural network (CNN)method was presented to assist the classification of ocean wave. Then it was compared with other traditional models in terms of accuracy and speed. Firstly, the performance of different CNN models was evaluated and the best one was improved with the idea of network in network. Then the best hyper parameters corresponding to the improved model were acquired. Finally, the performance of improved CNN model was compared with that of traditional models on a test database of 26536 image cases. The rate of correct identification in the proposed model is 96.23%, similarly to that of ResNet-152 (97.85%), and it take the least execution times. Overall, this method could be used for near-real-time wave monitoring by efficient classification of ocean wave images.

Estimation of Significant Wave Height of Near-Range Traveling Ocean Waves Using Sentinel-1 SAR Images

Synthetic aperture radar (SAR) is a valuable tool to observe many oceanographic parameters of the ocean surface. The significant wave height (H s or SWH), defined as the mean wave height of the highest one-third of waves, can be estimated using indirect relations between SAR-derived and the actual ocean wave spectra. However, multilook SAR imaging of ocean surface waves is highly affected by degraded azimuthal resolution and the random shift of scattered elements as the waves propagate off the SAR range direction. Therefore, the azimuthal displacement is found to be very low when near-range travelling ocean waves with narrow band spectrum are imaged. In this study, an improved algorithm is developed to directly estimate the significant wave height of ocean waves that propagate in the near-range direction using SARSAR imagery. The slope of the NRCS with respect to the radar wave incidence angle is derived from SAR images using an iterative scheme. A total of 69 SAR images from Sentinel-1A and 1B from 2016 to 2017, acquired near Hawaii, and in situ wave data from nearby National Data Buoy Center buoys are used to estimate H s and validate the improved algorithm. Results show that the algorithm performs well in estimating SWH under low to moderate wind forcing conditions (4-10 ms -1 ). The accuracy of the SWH estimation decreases under high-wind-speed and wind-wave-dominant conditions.

Application of Velocity Bunching Model to Estimate Wave Height of Ocean Waves using Multiple Synthetic Aperture Radar Data

ABSTRACT Yang, C.-S. and Ouchi, K., 2017. Application of velocity bunching model to estimate wave height of ocean waves using multiple synthetic aperture radar data. In: Lee, J.L.; Griffiths, T.; Lotan, A.; Suh, K.-S., and Lee, J. (eds.), The 2nd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 79, pp. 94–98. Coconut Creek (Florida), ISSN 0749-0208. The purpose of this study is to investigate the images of ocean waves produced by synthetic aperture radar (SAR) through the image modulations based on the normalized radar cross section (NRCS) and wave orbital motions, leading to the estimation of ocean wave height. The former is known as the tilt or NRCS modulation and the latter as velocity bunching. In general, the dominant contribution to the image modulation of range travelling waves is the NRCS modulation, and that of azimuth travelling waves is the velocity bunching mechanism. In this study, these two wave imaging mechanisms are investigated using the airborne Pi-SAR...

4-D imaging of the short scale ocean waves using a slit streak tube imaging Lidar

A flash Lidar system based on a slit streak tube receiver has been developed and its functionality demonstrated for oceanographic and coastal measurements. Especially, the slit Streak Tube Imaging Lidar (STIL) can image the short scale sea-wave because of its high frame rate and good 4-D (3-D range+1-D intensity) image quality. From the range information supplied by STIL, accuracy of sea-wave height measurement is about centimeter level. In the paper, we calculate the echo power so that STIL carried by plane can image the ocean surface. Measurements of the short scale surface wave fields in the Yellow Sea and Bohai Sea are analyzed and discussed. We experimentally demonstrate that STIL can detect the short scale surface waves with high resolution.

Study of Wave Group Velocity Estimation From Inhomogeneous Sea-Surface Image Sequences by Spatiotemporal Continuous Wavelet Transform

In this paper, a new image processing technique is introduced for the analysis of consecutive ocean wave images by spatiotemporal continuous wavelet transform (STCWT) using the Morlet wavelet as the mother wavelet. This technique, which has been adapted to give a full time–frequency and spatiofrequency representation of ocean surface waves from remotely captured wave image sequences, provides more detailed information from wave-field measurements than the traditional Fourier transform (FT) method. A series of numerical simulations of wave image sequences was analyzed to justify the algorithm and to present quantitative theoretical results on the propagation of ocean waves for normal incidence, diffraction, reflection, and shoaling in coastal areas. The comparisons of these estimates to simulated conditions for several wave parameters show that the wavelet theory is applicable to the identification of wave spectra from inhomogeneous sea-surface image sequences.

A semiempirical algorithm for SAR wave height retrieval and its validation using Envisat ASAR wave mode data

Many synthetic aperture radar (SAR) wave height retrieval algorithms have been developed. However, the wave height retrievals from most existing methods either depend on other input as the first guess or are restricted to the long wave regime. A semiempirical algorithm is presented, which has the objective to estimate the wave height from SAR imagery without any prior knowledge. The proposed novel algorithm was developed based on the theoretical SAR ocean wave imaging mechanism and the empirical relation between two types of wave period. The dependency of the proposed model on radar incident and wave direction was analyzed. For Envisat advanced synthetic aperture radar (ASAR) wave mode data, the model can be reduced to the simple form with two input parameters, i.e., the cutoff wavelength and peak wavelength of ocean wave, which can be retrieved from SAR imagery without any prior knowledge of wind or wave. Using Envisat ASAR wave mode data and the collocated buoy measurements from NDBC, the semiempirical algorithm is validated and compared with the Envisat ASAR level 2 products. The root-mean-square-error (RMSE) and scatter index (SI) in respect to the in situ measurements are 0.52 m and 19% respectively. Validation results indicate that, for Envisat ASAR wave mode data, the proposed method works well.

Ocean remotely sensed image analysis using two-dimensional continuous wavelet transforms

Ocean remote sensing is a useful way to obtain ocean wave information. Due to possible inhomogeneities from remotely sensed images, the current work proposes issues concerning ocean wave image analysis using the two-dimensional continuous wavelet transforms (2-D CWTs) to calculate local wave image spectra from inhomogeneous images. To optimize the algorithm of the 2-D CWT for wave image analysis, this work explores ideal parameter values for the wavelet function. The current study also analyses the limits of spatial image resolution and wave image size. After implementing the 2-D CWT on satellite and X-band radar images, this study presents local image spectra and ocean wave information from all the ocean images. These local image spectra reveal the phenomenon of wave refraction and wave nonlinearity nearshore. Compared to real wave spectra, the wavelet spectra present accurate results to describe local wave features in the spatial frequency domain.

Quantification of non-homogeneity from ocean remote-sensing images using two-dimensional continuous wavelet transforms

In this study, a two-dimensional continuous wavelet transform is applied to quantify the non-homogeneity from remote-sensing wave images. Our study shows that the non-homogeneity index, which is proposed here, is capable of identifying the degree of non-homogeneity from the wave-field images. However, the influence from the edges of the wave-field image should be considered in analysis. The calculated results from the simulated wave fields and from the natural wave-field images reveal that the non-homogeneity index is influenced by the bathymetry inside the area of the ocean-wave image. It conforms to the character of the natural wave non-homogeneity. After discussing the wave characteristics from the wave-field image with a high non-homogeneity index, an inhomogeneous algorithm is recommended for obtaining accurate and reasonable wave results from the wave image.

Remote sensing of ocean waves by along‐track interferometric synthetic aperture radar

A new wave retrieval method for the Along‐Track Interferometric Synthetic Aperture Radar (AT‐InSAR) phase image is presented. The new algorithm, named parametric retrieval algorithm (PRA), uses the full nonlinear mapping relations. It differs from previous retrieval algorithms in that it does not require a priori information about the sea state or the wind vector from scatterometer data. Instead, it combines the observed AT‐InSAR phase spectrum and assumed wind vector to estimate the wind sea spectrum. The method has been validated using several C‐band and X‐band HH‐polarized AT‐InSAR observations collocated with spectral buoy measurements. In this paper, X‐band and C‐band HH‐polarized AT‐InSAR phase images of ocean waves are first used to study AT‐InSAR wave imaging fidelity. The resulting phase spectra are quantitatively compared with forward‐mapped in situ directional wave spectra collocated with the AT‐InSAR observations. Subsequently, we combine the parametric retrieval algorithm (PRA) with X‐band and C‐band HH‐polarized AT‐InSAR phase images to retrieve ocean wave spectra. The results show that the ocean wavelengths, wave directions, and significant wave heights estimated from the retrieved ocean wave spectra are in agreement with the buoy measurements.

Oceanographic Applications of SAR Remote Sensing

This paper provides a comprehensive review of the use of synthetic aperture radar for oceanographic applications. It summarizes the current state of the art, covering research and operational aspects of the various applications: ocean wave imaging, solitary waves, ocean currents, sea floor topography, oil spill detection, ship and wake detection, wind speed and direction as well as other wind related phenomena. The extensive references throughout the review can serve as starting point for a more intensive study of the ocean by novice and expert alike.

Numerical simulation and validation of ocean waves measured by an Along-Track Interferometric Synthetic Aperture Radar

A new nonlinear integral transform of ocean wave spectra into Along-Track Interferometric Synthetic Aperture Radar (ATI-SAR) image spectra is described. ATI-SAR phase image spectra are calculated for various sea states and radar configurations based on the nonlinear integral transform. The numerical simulations show that the slant range to velocity ratio (R/V), significant wave height to ocean wavelength ratio (H-s/lambda), the baseline (2B) and incident angle (theta) affect ATI-SAR imaging. The ATI-SAR imaging theory is validated by means of Two X-band, HH-polarized ATI-SAR phase images of ocean waves and eight C-band, HH-polarized ATI-SAR phase image spectra of ocean waves. It is shown that ATI-SAR phase image spectra are in agreement with those calculated by forward mapping in situ directional wave spectra collected simultaneously with available ATI-SAR observations. ATI-SAR spectral correlation coefficients between observed and simulated are greater than 0.6 and are not sensitive to the degree of nonlinearity. However, the ATI-SAR phase image spectral turns towards the range direction, even if the real ocean wave direction is 30 degrees. It is also shown that the ATI-SAR imaging mechanism is significantly affected by the degree of velocity bunching nonlinearity, especially for high values of R/V and H-s/lambda.

SAR imaging and hydrodynamic analysis of ocean bottom topographic waves

The satellite synthetic aperture radar (SAR) images display wave‐like patterns of the ocean bottom topographic features at the south outlet of Taiwan Strait (TS). Field measurements indicate that the most TS water body is vertically stratified. However, SAR imaging models available were developed for homogeneous waters. Hence explaining SAR imaging mechanisms of bottom features in a stratified ocean is beyond the scope of those models. In order to explore these mechanisms and to determine the quantitative relations between the SAR imagery and the bottom features, a two‐dimensional, three‐layer ocean model with sinusoidal bottom topographic features is developed. Analytical solutions and inferences of the momentum equations of the ocean model lead to the following conditions. (1) In the lower layer, the topography‐induced waves (topographic waves hereafter) exist in the form of stationary waves, which satisfy a lower boundary resonance condition σ = kC0, here σ is an angular frequency of the stationary waves, k is a wavenumber of bottom topographic corrugation, and C0 is a background current speed. (2) As internal waves, the topographic waves may propagate vertically to the upper layer with an unchanged wavenumber k, if a frequency relation N3 < σ < N2 is satisfied, here N2 and N3 are the Brunt‐Wäisälä frequencies of middle layer and upper layer, respectively. (3) The topographic waves are extremely amplified if an upper layer resonance condition is satisfied. The SAR image of topographic waves is derived on the basis of current‐modulated small wave spectra. The results indicate that the topographic waves on SAR images have the same wavelength of bottom topographic corrugation, and the imagery brightness peaks are either inphase or antiphase with respect to the topographic corrugation, depending on a sign of a coupling factor. These theoretical predictions are verified by field observations. The results of this study provide a physical basis for quantitative interpretation of SAR images of bottom topographic waves in the stratified ocean.

Parameterized first-guess spectrum method for retrieving directional spectrum of swell-dominated waves and huge waves from SAR images

A method to retrieve ocean wave spectra from SAR images, named Parameterized First-guess Spectrum Method (PFSM), was proposed after interpretation of the theory to ocean wave imaging and analysis of the drawbacks of the retrieving model generally used. In this method, with additional information and satellite parameters, the separating wave-number is first calculated to determine the maximum wave-number beyond which the linear relation can be used. The separating wave-number can be calculated using the additional information on wind velocity and parameters of SAR satellite. And then the SAR spectrum can be divided into SAR spectrum of wind wave and of swell according to the result of separating wave-number. The portion of SAR spectrum generated by wind wave, is used to search for the most suitable parameters of ocean wind wave spectrum, including propagation direction of ocean wave, phase speed of dominating wave and the angle spreading coefficient. The swell spectrum is acquired by directly inversing the linear relation of ocean wave spectrum to SAR spectrum given the portion of SAR spectrum generated by swell. We used the proposed method to retrieve the ocean wave spectrum from ERS-SAR data from the South China Sea and compared the result with altimeter data. The agreement indicates that the PFSM is reliable.

A Second Order Lagrangian Model for Irregular Ocean Waves

Synthetic aperture radar (SAR) imaging of ocean waves involves both the geometry and the kinematics of the sea surface. However, the traditional linear wave theory fails to describe steep waves, which are likely to bring about specular reflection of the radar beam, and it may overestimate the surface fluid velocity that causes the so-called velocity bunching effect. Recently, the interest for a Lagrangian description of ocean gravity waves has increased. Such an approach considers the motion of individual labeled fluid particles and the free surface elevation is derived from the surface particles positions. The first order regular solution to the Lagrangian equations of motion for an inviscid and incompressible fluid is the so-called Gerstner wave. It shows realistic features such as sharper crests and broader troughs as the wave steepness increases. This paper proposes a second order irregular solution to these equations. The general features of the first and second order waves are described, and some statistical properties of various surface parameters such as the orbital velocity, slope, and mean curvature are studied.

Comparison of the two-dimensional directional wave spectra retrieved from spaceborne synthetic aperture radar images using the MPI scheme against directional buoy measurements

Spaceborne Synthetic Aperture Radar (SAR) is to date the only source of two-dimensional directional wave spectra with continuous and global coverage when operated in the so-called SAR Wave Mode (SWM). Since the launch in 1991 of the first European Remote Sensing Satellite ERS-1, and more recently with ENVISAT, millions of SWM imagettes containing detailed spectral information are now available in quasi-real time. This huge amount of directional wave data has opened up many exciting possibilities for the improvement of our knowledge of the dynamics of ocean waves. However, the retrieval of wave spectra from SAR images is not a trivial exercise due to the nonlinearities involved in the mapping mechanism. In this paper we review the main features of the SAR ocean wave imaging mechanisms and give a detailed description of the Max-Planck Institut (MPI) retrieval algorithm which is running operationally at the European Centre for Medium-Range Weather Forecasts (ECMWF). Some examples of retrieved spectra are compared against directional buoy measurements obtained in deep water in the South Atlantic and against WAM spectra. The main characteristics of the MPI retrieval scheme are discussed and some of its deficiencies and strengths are identified.