Conference Agenda

In this paper, we review the main research work and results in the first phase of our dragon-4 project from kick-off to the mid-term. The contents of this paper include the following three parts: 1) multi-source altimetry data fusion and marine application, 2) sea ice freeboard retrieval by Cryosat-2, 3) Sea surface salinity algorithm based on combined active/passive microwave imagers.

In altimetry marine application, a multi-source satellite crossover data comparison of Sentinel-3 SRAL, HY-2A RA and Jason-2 altimeter were conducted, and the accuracy of the sea surface height of Sentinel-3 SRAL altimeter was analyzed. For the capabilities of the new satellite altimeter data to detect mesoscale eddies, the data fusion of multi-source satellite altimetry including Sentinel-3 and Jason-2/3 and the comparison of mesoscale eddies detection using these fusion data are carried out for the different satellite combinations. The mesoscale eddies observation abilities of Sentinel-3 SRAL were summarized.

In sea ice freeboard retrieval, a new method called Bézier curve fitting (BCF) that can simulate the CryoSat-2 SAR-mode waveform is developed for the retrieval of surface elevation of both sea ice and leads. We apply this method for optimizing the retracking procedure. The results of the retracking procedure for the algorithm was validated using data of the Operation IceBridge (OIB) airborne mission. The mean absolute differences between freeboard values retrieved from CS-2 and OIB data were 9.5 and 13.8 cm when using the proposed method. This suggests that the sea ice freeboard data obtained from our proposed BCF method has a high accuracy.

In the study of SSS retrieval, based on the combined active/passive observations of the L-band microwave radiometer and scatterometer onboard Aquarius, a method to retrieval the sea surface salinity under the rainy conditions is developed and validated. The L-band GMFs (Geophysical Model Functions) are developed and the radiation feature of the rough sea surface is analyzed. The dependence of the sea surface emissivity (sensitive to both roughness and freshening) on the backscatter (only sensitive to roughness) is obtained and the rain-induced roughness is corrected. The method is applied to the salinity retrieval under rain. The retrieval results (SSS_rc) are compared with HYCOM data corrected by RIM (Rain Impact Model). The standard deviation of SSS_rc is about 0.5 psu and the bias of SSS_rc shows no clear dependence on the rain rate.

Ocean mesoscale eddies transport properties such as heat, salt and nutrients around the ocean with typical horizontal scales of less than 100 km and timescales on the order of a month. Eddies are important in supplying nutrients to coastal zones and the surface ocean where plankton blooms may result.

Mesoscale eddies can be detected through satellite altimetry technique due to depressions formed as they spin. Traditionally, those measurements have been retrieved through satellite with the Low Resolution Mode (LRM) which allowed a limited resolution and distance to the coast. Now thanks to the constant advance, those limitations have been reduced, allowing a better resolution and consequently obtaining data where before it was not possible, thanks to the new satellites generation (Cryosat-2, Sentinel-3 and Sentinel-6) with Synthetic Aperture Radar (SAR) mode.

This presentation will show the results obtained with the in-house isardSAT SAR ocean retracker [RD-1 and RD-2], using CryoSat-2 L1B data over Bohai Sea region. To do so, an analysis of the precision has been carried out on the geophysical retrievals (Sea Surface Height, Sea Wave Height and sigma0) obtained against the ones on ESA L2. This retracker is able to fit ocean-like surfaces as well as more specular-like responses, expected when getting close to the coast, thanks to an additional fitting parameter related to the surface roughness (Mean-Squared Slopes). Some pre-processing stage is required to choose the proper portion of the waveform related to the surface beneath the track, especially when getting close to the coast due to land contamination. DEM/geoid supported retracking operation is exploited in this case.

On further stages the same analysis will be repeated with Sentinel-3 data since the 1.5 years data only became available recently.

References:

[RD-1] E. Makhoul, M. Roca, C. Ray, R. Escolà, and A. Garcia-Mondéjar, “Evaluation of the precision of different Delay-Doppler Processor (DDP) algorithms using CryoSat-2 data over open ocean”, accepted for publication in Advances in Space Research.

[RD-2] Q. Gao, E. Makhoul, M. J. Escorihuela, M. Zribi, and P. Quintana-Segui, “Comparision of Retrackers’ performances over inland water bodies”, in Geophysical Research Abstracts, vol. 20, EGU2018-14298, 2018, EGU General Assembly 2018.

Oceanic mesoscale eddy is an important mesoscale dynamic process in the global ocean, and it is one of the research hotspots in physical oceanography. Mesoscale eddies play an important role in ocean circulation, material and energy transport and other marine dynamics and marine biochemical processes in the global ocean. Mesoscale eddies usually have a spatial scale of tens to hundreds of kilometers and a time scale of more than ten days to several months. Conventional in situ observations make it difficult to achieve complete observations of mesoscale eddies. Satellite altimetry is the important means of mesoscale eddies detection. Multi-source satellite altimetry data fusion provides abundant data for the global mesoscale eddies detection. ESA launched sentinel-3 satellites equipped with Synthetic Aperture Radar Altimeters (SRAL) on February 16, 2016, which provides new data sources for the detection of mesoscale eddies in global ocean.

In this study, the northwestern Pacific Ocean of Kuroshio region is selected as the experimental area and the mesoscale eddies observation abilities of Sentinel-3 SRAL are analyzed, including the independent detection abilities of Sentinel-3 SRAL and the improvement of mesoscale eddies detection abilities by data fusion with other satellite altimetry data. Firstly, Jason-2 altimeter is taken as the reference and Sentinel-3 SRAL data are compared with Jason-2 at the crossover of each other. Then the data of Sentinel-3 SRAL are corrected and uniformed based on their comparisons at the crossovers. The uniformed Sentinel-3 SRAL data are mapped by the spatial-temporal objective analysis method to the sea level anomaly grid data. The mapping errors are analyzed by the comparisons between the grid data and the Jason-2 along track data. The independent detection abilities of Sentinel-3 SRAL are analyzed by the comparison between the grid data and the AVISO MSLA data. On the other hand, through the multi-satellite data fusion of different combinations of Sentinel-3 altimeter and other satellite altimeter such as Jason-2/3, the mesoscale eddies detection was performed based on the merged sea level anomaly data, and the addition of Sentinel-3 SRAL data for the improvements of mesoscale eddies detection abilities by multi-satellite altimeters are concluded. Based on the above analysis, the mesoscale eddies observation abilities of Sentinel-3 SRAL are summarized.

During the last decade the radar altimetry has entered in its golden age as demonstrated by the different number of missions (Jason-2/-3, CryoSat-2, Saral/Altika, Sentinel-3) currently operating and the forthcoming ones (Sentinel-6). The relatively new operational synthetic aperture radar (SAR) mode in CryoSat-2 and Sentinel-3 missions, opens a new paradigm in the capabilities that can offer an altimetric radar mission. In this line, a scientific proposal within the DRAGON-4 tries to exploit the lessons learned from classical 2-D SAR focusing to evaluate the imaging-like capability of delay-Doppler altimetric radar mounted on Sentinel-3 over coastal areas. In this way, the altimetric product gets closer to the conventional SAR imaging data, but in the altimeter case a “strip-like” image is obtained compared to the classical 2D SAR image.

Conventional delay-Doppler processor (DDP) coherently integrates a series of pulses to provide specific Doppler beams focused to a specific location, which after being correctly aligned (compensating for the slant-range variation, among others) provide several looks that can be incoherently averaged, increasing the performance in terms of geophysical retrieval (increasing the signal-to-noise ratio-SNR). The fully focused DDP moves one step ahead and intends to coherently integrate such information to get an even higher along-track resolution with an improved SNR and the available number of beams.

In order to achieve such imaging capability, the azimuth or along-track phase modulation needs to be compensated for. The relative movement between the scene and the satellite creates a chirp-like modulation in the along-track dimension (quadratic phase response), and so an azimuth compression needs to be performed (once range migration has been compensated) to obtain a fully focused SAR strip, analogous to the well-known range compression (where a specific chirp pulse is compressed).

The main objective of the scientific proposal within the DRAGON-4 is to evaluate the potential capabilities offered by the state-of-the-art Sentinel-3 operational synthetic aperture radar (SAR) mode, when extending the delay-Doppler processing (DDP) to a fully focused DDP (FF-DDP) altimetric operation. This will confer the SAR altimetric product a very high resolution (in the order of 0.6 m) of great interest for Coastal Altimetry (being able to get closer to the coastline), providing much higher number of looks that can be averaged to improve the altimetric performance as anticipated by Raney in [RD-1]:

• Development of an efficient fully focused SAR altimetric processor

• Validation of the processor’s chains using point-like target (transponder)

• Evaluation of the capabilities of the fully focused SAR over coastal regions in Chinese seas

The core of this presentation is to show the preliminary investigations carried out in the development of such innovative processor (FF-DDP), pointing out the specificities of such processing compared to the conventional DDP. The initial implemented processing chain will be described, showing preliminary tests on simulated point-targets. ESA Sentinel-6 simulated data will be exploited as testbed, since the flexibility of the Sentinel-6 interleaved mode allows to emulate different acquisition configurations (potentially simulating a closed burst operation, similar to Sentinel-3 or CryoSat-2 modes) and how this may impact the final results.

References:

[RD- 1] Curlander, John C., and Robert N. McDonough. Synthetic aperture radar. New York, NY, USA: John Wiley & Sons, 1991.

This paper presents two work we developed in the past two years. The first is sea ice freeboard retrieval by Cryosat-2 data; and the second is sea ice drift detection by Sentinel-1 SAR data.

For sea ice freeboard retrieval, a new method called Bézier curve fitting (BCF) that can simulate the CryoSat-2 (CS-2) SAR-mode waveform is developed for the retrieval of surface elevation of both sea ice and leads. We apply this method for optimizing the retracking procedure. Retracking points are fixed on positions at which the rise reaches 70% of the Bézier curve peak in case of leads, and 50% in case of sea ice. In order to evaluate the proposed retracker algorithm we compare it to other methods currently reported in the literature, namely the Threshold-First-Maximum-Retracker-Algorithm and the ESA CS-2 L2I. The results of the retracking procedure for the different algorithms are validated using data of the Operation IceBridge (OIB) airborne mission. For two OIB campaign periods in March 2015 and April 2016, the mean absolute differences between freeboard values retrieved from CS-2 and OIB data were 9.5 and 13.8 cm when using the BCF method, 11.4 cm and 15.6 cm for TFMRA, and 14.5 cm and 15.5 cm for L2I. This suggests that the sea ice freeboard data obtained from our proposed BCF method has a high accuracy.

For sea ice drift detection, in order to solve the problem of high error rate of sea ice drift retrieval that caused by SAR sea ice images have similarities in many areas. And for the purpose of improving the computational efficiency of SAR sea ice drift detection method, multi-scale fast sea ice drift detection method based on principal direction constraint was proposed. Firstly, a pair of full low-resolution SAR image pairs is divided into several sub-image pairs using SAR sea ice image segmentation method based on image matching, and then the main direction of sea ice drift is extracted. Finally, the main direction is used to limit the matching search area of the feature point of SURF algorithm to more accurately extract sea ice drift information of the original resolution SAR. To verify the performance of the fast SURF algorithm based on the main direction constraint. The method is compared with the classic sea ice drift retrieval method. The measured data results show that compared with the traditional SURF algorithm, the matching ratio of feature points is improved by about 10 times, and the calculation efficiency can be increased by about 1 times. Compared with the NCC algorithm, the computational efficiency of this method is dozens of times faster than NCC method, and the image matching accuracy is still higher than that of the NCC method.

Optical remote sensing is one of the most important methods for large-scale observation of ocean internal wave, which has the advantages of wide width and high temporal resolution. However, the optical remote sensing image is affected by cloud, sea condition and imaging angle, which brings difficulty to extract and retrieve ocean internal wave information from the optical remote sensing image. Currently, parameter inversion of internal solitary wave on optical remote sensing image is still based on the inversion model of SAR image. Therefore, a new approach is proposed to establish an experimental system of optical remote sensing to detect internal solitary wave in the laboratory, which aims to explore the response characteristics of optical remote sensing images caused by internal solitary waves. An experimental platform for detecting internal solitary wave by optical remote sensing is constructed by a 3D internal wave flume, a LED light source, CCD cameras and an air blower. The imaging principle of internal waves on optical remote sensing images is quasi-mirror reflection, and LED simulates the parallel incident of sunlight. The method of gravity collapse is used to generate internal waves in the flume of two-layer water. Internal solitary waves with different amplitudes are generated by different collapse heights. Two CCD cameras are used to synchronously observe the surface optical remote sensing images and vertical internal wave images caused by the propagation of internal solitary waves in the same field of view. The mechanism of the internal solitary waves detected on optical remote sensing is compared and analyzed by changing the parameters such as the collapse height, the zenith angle of the sun and the receiving angle of CCD in turn. The experimental results show that the higher the collapse height brings the larger the amplitude of the internal solitary wave. To be more precise, the amplitude is proportional to the collapse height in a certain range. During the process of internal solitary wave propagation, the surface mirror elements are inclined, and the response of the optical remote sensing image corresponds to the vertical displacement of the internal solitary wave one by one. At the same time, stripes are detected on the surface of water by optical remote sensing, which result in the change of gray scale. The relative gray value difference is positively correlated with the amplitude of the internal solitary wave. The larger the amplitude of the internal solitary wave leads to the larger slope of the surface, and finally the greater the change of the light intensity is received by the optical sensor. The research provides a useful reference for quantitative inversion of internal wave parameters on optical remote sensing image.

Keywords: optical remote sensing, internal solitary wave, surface response, relative gray value difference

Mesoscale eddies are rotating coherent structures of ocean currents, which generally refer to ocean signals with spatial scales from tens to hundreds of kilometers and time scales from days to months. Eddies can be found nearly everywhere in the world ocean, and dominate the ocean’s kinetic energy. Over the recent decades, with the advancements in remote sensing satellites and the abundance of in-situ observations data, people find that mesoscale eddies can transport water, heat, salt, and energy as they propagate in the ocean. By combining satellite altimetry and Argo profiling float data, the analysis of eddy three-dimensional structure becomes an important part of studying the oceanic eddy.

The Bay of Bengal, the largest bay in the world, forms the northeastern part of the Indian Ocean. It connects with the South China Sea through the Andaman Sea and the Strait of Malacca. The bathymetric contour of the Bay of Bengal is oriented east-west and the bay presents “n” pattern. As these bathymetric constraints, the local ocean dynamics is complex, with a broad spectrum of processes, from a seasonal reversing monsoon, cyclonic storms, small-scale river plumes, instabilities generated near the continental slope, eddies and large-scale circulation. The Bay of Bengal is a region abundant of mesoscale eddies. In this paper, we analyzed statistical characteristics of mesoscale eddies in the Bay of Bengal based on merged satellite altimetry data as well as Argo profile data.

Firstly, based on satellite altimeter data, the automatic identification method was used to extract the position and shape information of the mesoscale vortices. A series of statistical analysis methods were used to study the statistical characteristics of the mesoscale eddies in the region, e.g., eddy number and lifetime, geographical distribution of eddies, and evolution of eddy properties. Then, based on Argo profile data and climatology data, the eddy synthesis method was used to construct the three-dimensional temperature and salt structure of the eddy in this area.

The Bohai Sea is the southernmost frozen sea in the Northern Hemisphere. The sea ice is a major marine disaster to the Bohai Sea in the winter, which seriously impacts the marine transportation, oil and gas exploitation etc., leading to the great loss to the economical circle surrounding the Bohai Sea. It is very important to evaluate the damaging effects of the sea ice on the marine transportation and offshore constructions (e.g. the oil platform) quantitatively, which has not been studied and analyzed systematically using long-term data so far. In this paper, the quantitative evaluation of the sea-ice disaster in the Bohai Sea will be studied based on the GOCI and Sentinel-1 data. GOCI (Geostationary Ocean Color Imager), to be a payload of COMS satellite launched in Korea in 2010, is the first geostationary sensor in the world, which covers the whole Bohai Sea completely with a spatial resolution of about 500 m of 8 images for one daytime. The Sentinel-1 consists of two satellites (AB) loading C band SAR, which provides single- and dual-polarization data.

The different sea-ice-disaster indexes should be defined for different disaster-bearing bodies. For the marine transportation, its sea-ice-disaster index is equal to multiplying the sea-ice concentration (C_i) by the sea-ice thickness (H_i), which is represented by I₁, that is I₁= C_i × H_i (unit: %∙cm), indicating the sea-ice mass per unit area in physics, and a bigger value means harder breaking ice and less navigable; For the offshore constructions (e.g. the oil platform), its sea-ice-disaster index is equal to multiplying I₁ by the sea-ice velocity (V_i), which is represented by I₂ , that is I₂= I₁ × V_i = C_i × H_i × V_i (unit: %∙cm²∙s⁻¹), indicating the sea-ice momentum per unit area in physics, and a bigger value means a higher extruding pressure and impulse force imposed by the sea ice. In the paper, based on the GOCI and Sentinel-1 data, the sea ice and the sea water are recognized through combining the sea-ice optical and microwave features, which is used to calculate the sea-ice concentration; the sea-ice thickness is retrieved using the sea-ice optical information of GOCI; the sea-ice velocity is extracted through the GOCI geostationary characteristics and the maximum cross correlation method (MCC); based on the sea-ice parameters of the sea-ice concentration, thickness, and velocity, the two types of the sea-ice-disaster indexes I₁ and I₂ can be calculated, which are used to evaluate quantitatively the spatial distribution features and the interannual variations of the sea-ice disaster in the Bohai Sea in the period from 2011 to 2018. The research results will quantitatively shows that the period from 2011 to 2018 is conventional ice condition, which is relatively heavy in 2011 and 2013. The sea-ice-disaster indexes I₁ and I₂ will quantitatively illustrate the space-time distribution features of the sea-ice disaster for the marine transportation and the offshore construction, which can satisfy the request of the sea-ice disaster prevention and reduction and provide the reference of the monitoring and research on the sea-ice disaster.

Bohai sea is located in the northern latitude 37 ° 07 '- 41 ° 0', eastern longitude 117 ° 35 '-121 ° 10', the Bohai sea and its surrounding their rich oil and gas resources, there are a number of important large fields. However, due to the Accumulated ice that drift ice accumulates and accumulates will cause various degrees of impacts on shipping traffic, marine structures, and fishery production in Bohai. It may even cause serious disasters and bring incalculable losses to China's economy. There is an urgent need for studies related to sea ice drift monitoring. The daily drift of sea ice in Bohai sea is changing rapidly, The daily drift of sea ice in Bohai sea is changing rapidly, and the revisit period of microwave scatterometer, microwave radiometer and SAR is longer, and it cannot meet the demand for sea ice drift monitoring in Bohai Sea. The "GF-4" satellite is China's first high resolution geostationary optical remote sensing satellite. It has the unique advantages of short imaging time interval (20s) and high resolution (50m), and is more suitable for sea ice drift tracking. However, the effect of GF4 satellite image product's own error on sea ice drift is rarely researched at home and abroad. Therefore, it is necessary to carry out error analysis of sea ice drift tracking of GF4 satellite imagery.

This paper mainly uses GF4 satellite imagery to carry out the sea ice drift monitoring error analysis with time intervals of 1 minute, 3 hours, 4 hours, and 24 hours. Firstly, the orthorectification of the 28 image data available from August 2016 to March 2018 in the Bohai Sea area was carried out. Then we select the sea-land edge points as control points, and registration of two images which have the same time interval. Next, we recorded the marked same name points which searched from the bottom of Liaodong bay, east of Liaodong bay and west of Liaodong bay respectlly. Statistics the direction and frequency of land point offset sub-regionally and created the rose plots. And maked histogram of the offset and offset angle of land point.

The results show that, when the time interval is 4 hours and 24 hours, the dominant migration direction in the three regions in Liaodong bay is east; when the time interval is 1 minute, the dominant migration direction in Liaodong Bay bottom and Liaodong Bay west coast land is south, Followed by east and southeast respectively; the dominant migration in Liaodong Bay East Coast is north, followed by east; When the time interval is 3 hours, the dominant migration direction in west of Liaodong Bay, bottom of Liaodong Bay and east of Liaodong bay are east, west and south respectively, followed by southeast, east, southeast respectively. The land offset in three regions is major centralized distribution in a range which is from 60m to 80m. That is to say, the offset of land is basically equal to 1.2 times of pixels, and the maximum land offset is less than 2 times of pixels. Through statistical analysis, it can be seen that with the increase of time interval, the land offset will not change much. This study also paves the way for the study of the drift of sea ice.

Iceberg is a potential threat to maritime transport, drilling platforms and shore facilities in high latitude. In existing research iceberg is mainly detected by Constant False Alarm Ratio(CFAR) according to brightness variation between icebergs and background in Synthetic Aperture Radar image. The performance of iceberg detection strongly depends on the accurate statistical modeling of local background clutter measurements, which is also focused on in existing research. In order to accurately detecting iceberg especially iceberg edge, an iceberg detection method combining image segmentation and CFAR algorithm is proposed in this paper. The image is firstly segmented by watershed algorithm which can accurately determine edge of iceberg，the segmentation areas (aggregation of similar pixels) are used for subsequent processing instead of pixels to reduce speckle noise and improve operational efficiency. The statistical characterization of local background including sea ice and water is modeled accurately and the iceberg is finally detected by CFAR.

The Bohai Rim Region is an important economic circle in China. In winter the freezing of sea ice in the Bohai Sea has caused serious impacts on sea shipping and sea-related production, resulting in accidents such as channel blockage, ship damage, and oil platform collapse. The monitoring of sea ice in Bohai Sea is of great significance and has now become the routine operational work of the marine management department. The first geostationary orbit satellite launched by China on December 29, 2015—the High Resolution Four Satellite (GF-4), with an orbit altitude of 36,000 kilometers, equipped with a visible light sensor with 50 m resolution, 400 M-resolution mid-infrared sensors, and gaze cameras with a width greater than 400 km. It can perform a wide range of observations on about one-third of the Earth's surface and can obtain multiple observations within a day. The spatial resolution of the GF-4 is an order of magnitude better than that of the existing geostationary-satellite GOCI. At the same time, it has the characteristics of high temporal resolution of geostationary satellites. It is very advantageous to detect changes in the ice conditions of sea ice in the Bohai Sea. Within one hour, the drift and change of sea ice in the Bohai Sea are relatively fast. Therefore, the better spatial resolution of GF-4 is very suitable for Bohai Sea ice monitoring, play an important role in monitoring and forecasting sea ice conditions in the Bohai Sea.

This article based on the GF-4 Bohai Sea ice imagery studied the optimal wavebands for the identification of sea ice and seawater: use the 29 pictures remote sensing images of the Bohai Sea between 2017 and 2018 obtained from the GF-4 to extracted 377 samples of sea ice and seawater samples respectively, and normalize the spectral values of the five bands of sea ice and seawater samples respectively; There are a total of 57 species band combinations that single band, two bands combination(adding, subtracting, dividing) ,Band 2 (B2) and band 4 (B4) and band 5 (B5) three bands combination(only analysis of 208 sea ice and sea water samples in 2017: the recognition of sea ice and seawater in single band is relatively good, with B2, B4 and B5). Using graphic method and feature distance method to analyze the ability of these band combinations to identify sea ice and seawater. The graphic method is to display the spectral values of sea ice and seawater corresponding to each band combination in a scatter plot, by visual interpretation of scatter plots, qualitative analysis of sea ice and seawater aliasing (total number of mixed sea ice and seawater samples/samples total 377) is less than 10%, think this band can identify of sea ice and seawater; The feature distance method selects the Bahman distance and the Euclidean distance for quantitative analysis of the ability of each band combination to identify sea ice and seawater . Research results show that, In the graphic method, the B2/B4/B5 has the lowest rate of aliasing, which is 5.31%; In the feature distance method, the feature distance of B2/B4/B5 has the largest calculation result, the Euclidean distance calculation result is 8.89336, and the Bahrain distance calculation result is 91.84793; Shows that the analysis results of the two methods are consistent ,The conclusion is that the qualitative and quantitative analysis of the band results is consistent, B2/B4/B5 is the optimal band combination for GF-4 sea ice and seawater identification. The conclusions obtained in this paper have important significance and reference value for GF-4 sea ice monitoring.