It is presented in this paper the recent progresses of ESA-MOST China Dragon Cooperation Program (ID. 32249) in the field of microwave marine remote sensing including (1) GF-3 SAR ocean wind retrieval: the first view and preliminary assessment; (2) Preliminary analysis of Chinese GF-3 SAR quad-polarization measurements to extract winds in each polarization; (3) Assessments of ocean wind retrieval schemes and geophysical model functions used for Chinese GF-3 SAR data at each polarization; (4) Combined co- and cross-polarized SAR measurements under extreme wind conditions; (5) Joint retrieval of directional ocean wave spectra from SAR and RAR; (6) The first quantitative ocean remote sensing by using Chinese interferometric imaging radar altimeter onboard TG-2.

Sentinel-1, Gaofeng-3 and Radarsat-2 offer the unique possibility to observe the ocean surface at high resolution in both co- and cross- polarizations. This work shows how this new capabilities allow a new vision of the ocean surface over extreme events such as Hurricanes or Typhoon.

A database has been completed to gather all Sentinel-1 acquisitions over hurricane eyes. A collection of about 50 images now exist and a strategy to optimize the acquistitions over hurricane has been developed, proposed and tested with ESA Sentinel-1 Mission planning team.

Based on this data, an algorithm for cean surface wind speed measurements has been developped. Its performances are compared to analysis performed by hurricane experts in the hurricane centres, airborne measurements and parametric models.

SAR Radar-cross section over extreme are also directly compared to brigthness resolution from SMOS and SMAP L-band radiometer. In situation of rain rate less than 20 mm/hr, a striking linear relationship is found between both active and passive sensors. As interpreted, this can correspond to a regime change of the air-sea interactions during extreme events.

A new geophysical model function (GMF), called C_SARMOD2, has been developed to relate high resolution C-band Normalized Radar Cross Section (NRCS), acquired in VV polarization over the ocean, to the 10 m height wind speed. A total of 3078 RADARSAT-2 and Sentinel-1A VV-polarized SAR images acquired under different wind speed conditions were collocated with in situ buoy measurements. The paired dataset was used to derive transfer functions and coefficients of C_SARMOD2, and then to validate the wind speed retrievals. With almost no bias and a root mean square error of 1.84 m/s. Two representative quad- and dual-polarization SAR images acquired from coastal regions are used as case studies to examine C_SARMOD2 performances. The case study and statistical validation results suggest that the proposed C_SARMOD2 has the potential to measure coastal wind speeds at sub-kilometer resolutions. Although derived from low resolution NRCS measurements, this study also confirms the great robustness of CMOD5.N and recent CMOD7 when applied to SAR data. In addition, it shows that with the new generation of SAR satellite-borne sensors, it is no longer mandatory to rely on scatterometers in order to build a GMF that will be used for SAR applications. Such an approach is particularly important in view of the upcoming RADARSAT Constellation Mission (RCM) with new polarization configurations. Moreover, it also opens new perspectives on the derivation of GMFs in HH-polarization. However, these results also suggest that for coastal areas, the increase of the resolution to define the GMF is less important than adding other geophysical parameters to improve wind retrieval performance. This advocates for the necessity of revisiting the methodologies for ocean surface wind speed measurements in coastal areas.

Abstract:

Gaofen-3 (GF-3), the first Chinese civil C-band synthetic aperture radar (SAR), was successfully launched by the China Academy of Space Technology on 10 August 2016. GF-3 provides many SAR images for oceanography with its high resolution and large coverage. Among its 12 imaging modes, wave mode is designed to monitor the ocean surface waves over the open ocean.

The paper proposed an empirical algorithm for significant wave height from the GF-3 wave mode data, called QPCWAVE_GF3, which contains six image and spectra parameters of radar incidence angle, normalized radar cross section, imaging normalized variance, azimuth Cut-Off, peak wavelength and direction.

The validation of the QPCWAVE_GF3 model is performed through comparisons against independent WW3 modelling hindcasts, and observations from altimeters and buoys. The assessment shows a good agreement with root mean square error from 0.5m to 0.6m, and scatter index around 20%.

Keywords: Gaofen-3; significant wave height; empirical algorithm

This study proposed a joint method to retrieve directional ocean wave spectra from synthetic aperture radar (SAR) and real aperture radar (RAR). The method broke through the limitations existed in the single-sensor wave retrieval, by combining two sensors’ characteristics. First, the H_s was estimated from the SAR cutoff using an empirical model. On the other hand, the relative wave spectra at large scale were derived from RAR modulation spectra. After that, the first guess spectra were estimated by relative wave spectra and SAR-derived H_s. Finally, the full wave spectra at small scale were retrieved from the SAR image cross spectra with the help of first guess spectra using the Max-Planck-Institute scheme. The 180° ambiguity of retrieved wave spectra was removed using the imaginary part of SAR cross spectra. Both simulation and collocated data were used to validate the joint method. This method helps to complement traditional wave retrieval methods.

The GaoFen-3 (GF-3) is the first Chinese spaceborne SAR in C-band for civil applications. In the paper, we provide an overview on demonstrating capabilities of the GF-3 SAR on ocean, coast and polar observations, by presenting some representative cases, such as polarimetric characteristics of typical intertidal flat in the Subei shoal, the German Bight, observation of offshore wind turbine wakes in the North Sea and East China Sea, observation of internal waves generating in the Luzon Strait and their propagation to DongSha Atoll, as well as discrimination of sea ice and open water in the Arctic. Derivation of marine-meteo parameters in high spatial resolution is one of the most attractive applications of spaceborne SAR for ocean observation. This is also a primary goal of launching the GF-3 SAR, we also presented the current problem of using GF-3 for retrieval of oceanic dynamic parameters and some possible solutions.

Radar altimeter is an important part of ocean phenomena monitoring. Profile radar altimeters (such as Topex/Poseidon, Jason-2 and Sentinel-3) have provided abundant data for the ocean phenomena research in the past decades. But they only measure one-dimensional profile height along the satellite track, a 200~300 km gap usually exists between two successive tracks and the spatial resolution of their data products is sparse. Wide-swath altimeter (such as SWOT) calculate the target point height using the interferometric phase measured by two antennas of the altimeter. It can greatly improve the spatial resolution of the data product and makes up for the lack of profile altimeter. However, in the process of generating a digital elevation model with a wide-swath altimeter, the baseline roll error will cause height error which increases in the cross-track direction. Taking the design parameters of SWOT as an example, a baseline error of only 0.36arcsec (1/10000°) would result in an average height error of roughly 6 cm at the swath of 10km to 60km. In the present case, it’s difficult to control the measurement accuracy of baseline roll within 0.1arcsec by measuring instruments such as a gyroscope, and it is impossible to meet the high-accuracy requirement of 1-2cm. Therefore, it is necessary to adopt other methods to calibrate the measurement value of the baseline roll.

Due to the special geometrical relationship between the nadir point and two antennas, using the nadir interference phase can obtain a more accurate baseline roll angle value, estimate the flight attitude more effectively and improve the height measurement accuracy. The nadir interference phase is related to baseline length and roll angle. The contribution of measurement error of baseline length to the measurement error of roll angle is much smaller than that contributed by the measurement error of interferometric phase. The accuracy of interferometric phase is decided by both the hardware guaranteed accuracy and the echo guaranteed accuracy. An accuracy of 0.05° for open ocean surface is not difficult to achieve. Under this assumption, the measurement accuracy of roll angle can be as high as 0.0246arcsec.

A two-dimensional ocean surface which is simulated by the Pierson-Moscowitz spectrum. The slant range and interferometric phase of the resolution unit are obtained based on geometrical relationship. It is assumed that the interferometer can measure the nadir interferometric phase with an accuracy of 0.05°, while a gyroscope can measure the baseline roll angle with an accuracy of 0.36arcsec simultaneously. Reconstruct the sea surface using parameters of the SWOT mission and combining with the baseline roll that calculated by the nadir interference phase or measured by the simulated gyroscope, and then calculate the elevation error within the swath. The numerical simulation results show that the accuracy of the baseline roll can reach 0.03arcsec with a nadir interferometric phase accuracy of 0.05°, and the average height error within the swath of 10km-60km is 0.48cm.

Using the relationship between the nadir interference phase and the baseline roll angle to measure the roll angle indirectly, can achieve a more accurate baseline roll angle measurement than the general hardware. The height error caused by the baseline roll error could be reduced and the accuracy of data products of wide-swath altimeter could be improved which make it an effective way to calibration height error of wide-swath altimeter.

Tracing the evolution of subaqueous topography in coastal water enables us to understand the effects of intensive coastal development on bays and estuaries. Analysis of a series of historical bathymetric acoustic surveys has revealed large changes in morphology from 1960s to 2010s in Longkou Bay, China. Water depths were extracted from digitized admiralty charts to explore the accretion-erosion characteristics in a Geographical Information System (GIS) environment, providing quantitative estimates of morphological changes. Multibeam echosounders (MBES) were used to map and analyze the geomorphologic features caused by the construction of artificial islands. Results illustrated that the shoreline and bathymetry of Longkou Bay changed dramatically in recent decades. The subaqueous area decreased by about 15%, while land area increased by more than 13 km2 in the study area during the last 50 years. From 1960s to 1990s, the evolution of Longkou Bay was mainly governed by natural processes with a patchy distribution of deposition and erosion, and there were few signs of being related to large-scale human activities. During the period of 1990s to 2010s, intensive coastal developments including large port engineering projects, channel dredging and artificial islands construction became the main processes affecting morphological changes in the Longkou Bay. The high-resolution bathymetric results near the artificial island showed that the seafloor was dredged at many sites, leaving large areas of borrow pits. The sudden change of the underwater topography will lead to the destruction of local benthic habitat and effective measures need to be taken to protect and remediate heavily disturbed subaqueous environment.

The refraction and reconnection of internal solitary waves (ISWs) around the Dongsha Atoll (DSA) in the northern South China Sea (SCS) are investigated based on spaceborne synthetic aperture radar (SAR) observations and numerical simulations. In general, a long ISW front propagating from the deep basin of the northern SCS splits into northern and southern branches when it passes the DSA. In this study, the statistics of Envisat Advanced SAR (ASAR) images show that the northern and southern wave branches can reconnect behind the DSA, but the reconnection location varies. A previously developed nonlinear refraction model (NRM) is set up to simulate the refraction and reconnection of the ISWs behind the DSA, and the model is used to evaluate the effects of ocean stratification, background currents, and incoming ISW characteristics at the DSA on the variation in reconnection locations. The results of the first realistic simulation agree with consecutive TerraSAR-X (TSX) images captured within 12 h of each other,which proves the validity of the NRM model around the DSA. Further sensitivity simulations show that ocean stratification, background currents, and initial wave amplitudes all affect the phase speeds of wave branches and therefore shift their reconnection locations while shapes and locations of incoming wave branches upstream of the DSA profoundly influence the subsequent propagation paths. This study clarifies the variation in reconnection locations of ISWs downstream of the DSA and reveals the important mechanisms governing the reconnection process, which can improve our understanding of the propagation of ISWs near the DSA.

Most researchers pay more their attentions on the characteristics of oil spills when they construct the feature set for establishing an automatic sea surface oil spill monitoring system by spaceborne SAR. In this paper, taking oceanic internal waves as an example of oil look-likes, a Fourier spectrum feature subset is proposed based on the analysis of the characteristics of look-alikes. The aim is to reduce the false alarms resulting from oceanic internal waves and then to decrease the false discovery rate (FDR) of the automatic monitoring system. The proposed feature subset consists of 10 Fourier spectrum features. 53 SAR images rich in internal waves acquired over South China Sea are collected for this experimental study. An adaptive threshold image segmentation algorithm and its post-processing are applied on the SAR images to automatically generate dark target set with reasonable proportion between oil spills and look-alikes. Training and testing of classifier are conducted with 77 original features and 87 features including the additional 10 Fourier spectrum features, respectively. The results show that the system's FDR decreases from 19.6% to 14% due to the introduction of the Fourier spectrum feature subset.

Sentinel-2 MSI offers improved spatial resolution over sensors dedicated to water observations (e.g. OLCI). This makes it an attractive sensor to attempt water quality observations in coastal regions and inland water bodies. However, the band configuration of Sentinel-2 MSI is not optimized to resolve the optical features that are diagnostic of waterbody health. It is therefore worth investigating whether the SNR statistics of the MSI are good enough for water quality retrieval.

The predominant source of error in remote sensing of water quality is atmospheric correction, followed by selection of suitable water constituent retrieval algorithms. Here we present a comparative analysis of atmospheric correction solutions for MSI including Polymer, C2RCC, Acolite, iCOR, l2gen and Sen2Cor. In situ data from optically diverse sources (Baltic Sea, Western English Channel, and lakes in Estonia, Italy and the Netherlands) are used to generate > 1000 match-ups to compare the suitability and limitations of the different tools for different water environments. We further show how the dynamic algorithm selection of the Calimnos processing chain is implemented for Sentinel-2, leading to retrieval of a set of distinct Optical Water Types which describes how MSI 'sees' waterbodies.

The GaoFen-4 (GF-4) remote sensing satellite is China's first civilian high-resolution geostationary optical satellite, which has been launched at the end of December 2015. The GF-4 has the unique advantages of high temporal resolution (20s) and high spatial resolution (50m). In order to explore GF-4’s potential in ocean bloom monitoring, the GF-4 images were used in red tide detection in the Bohai Sea and drifting velocity of the green tide in the Yellow Sea. Results showed that the GF-4 images had great potential in small patches of red tide detection and could provide data support for accurate monitoring of green tide short-term movement.

Daily coverage of single ocean color sensor can only reach 10%~15% because of cloudy and rainy weather, solar flare, track gap, etc. Merging datasets from different missions into unified data products is a valid way to increase the spatial and temporal coverage of ocean color satellites.

ESA started the GlobColour project in 2005 with the aim of providing a continuous dataset of merged Level 3 ocean color products (1997–present). Based on long time series of merged ocean color products (2003–2016) from the ESA GlobColour dataset, spatial and temporal distributions on effective observation days of ocean color satellites of the East Yellow and East China Seas are analyzed. The results show that the average number of effective observation days for the East China Seasregion is 51±6.8 days per year. Large numbers of such days appeared for the West Korea Bay and western Liaodong Bay, at 100±8.3 days per year. Small numbers of days appeared for the southwestern southern Yellow Sea, northwestern East China Seas, and the branch of Kuroshio Current region, at 40±10.1 days per year. Effective observation days of the Yellow and East China Seas had strong seasonal characteristics. The Bohai Sea, northern Yellow Sea, and southern Yellow Sea had two peaks in March and October. The East China Seas had a single peak in July. A lack of effective observation reduces the quality of monthly ocean color products, with greater than 15% bias if the monthly data are averaged from 3 days and 30% bias if the monthly data are from 1 day only.

SeaWiFS and MERIS stopped successively in 2010~2012 and the number of ocean color sensors decreased. We tried to add Medium Resolution Spectral Imager (MERSI)/FY-3 of China in merged Chl-a products. The results show that the average daily coverage of merged products increases by ~9% when MERSI data are added in the merging process. Sampling frequency (temporal coverage) is greatly improved by combining MERSI data, with the median sampling frequency increasing from 15.6% (~57 days/year) to 29.9% (~109 days/year). The new merged products agree within ~10% of the merged Chl-a product from GlobColour. Time series of the Chl anomalies are similar to GlobColour products.

Environmental monitoring and early warning of water quality from space is now feasible at unprecedented spatial and temporal resolution following the latest generation of satellite sensors. The transformation of this data through classification into labelled, tracked event information is of critical importance to offer a searchable dataset.

Advances in image recognition techniques through Deep Learning research have been successfully applied to satellite remote sensing data. Deep Learning approaches that leverage optical satellite data are now being developed for remotely sensed multi- and hyperspectral reflectance. The combination of spectral with spatial feature extracting Deep Learning networks promises a significant improvement in the accuracy of classifiers using remotely sensed data.

This project aims to re-tool and optimise spectral-spatial Convolutional Neural Networks originally developed for land classification as a novel approach to identifying and labelling dynamic features in waterbodies, such as algal blooms and sediment plumes in high-resolution satellite sensors.

With accelerating climate change and receding summer ice cover, the problems of marine environments in the Arctic Ocean appear to be increasing. Ocean color remote sensing is one of the most effective methods with relatively low cost to monitor marine ecosystems. The quality assurance (QA) system of remote sensing reflectance (Rrs) developed by Wei et al. (2016) is used to assess the MERIS radiometric products in the Arctic Ocean over the 2002 ~2012 time period, which is scored according to the spectral shapes and amplitudes of Rrs spectra. Results show that monthly QA average scores are about 0.75 with little fluctuation (<0.1) and the life-cycle quality of the MERIS radiometric products keeps relatively steady. The majority of the Arctic Ocean has a QA score close to 0.7 while relatively lower QA scores (<0.4) are mainly found in the Kara Sea, Laptev Sea and Hudson Bay. There is less valid MERIS data in the spring and winter, which mainly distributes in the Norwegian Sea and the Denmark Straits with QA scores of about 0.7. More valid MERIS radiometric data are obtained in the summer and autumn, and the radiometric products in the Norwegian and Bering Sea are observed with relatively higher QA scores (>0.8).

Optical satellites of HY-1C and HY-1D will be launched by China in 2018 and 2019, onboard which the Coastal Zone Imager (CZI) is one of the shared payloads. CZI is designed to monitor the coastal zone by providing the optical images in the four bands (blue, green, red and near infrared) with wide swath (950km) and moderate spatial resolution (50m). Quantitative retrieval of the environmental parameters including water quality will be achieved for the coastal zone management.

In this paper, the atmospheric correction algorithm for the operational CZI data processing is proposed. Based on the atmosphere radiation transfer (6S) model and CZI band response functions, lookup tables have been established for the calculation of Rayleigh scattering, aerosol scattering and scattering transmittance for different aerosol models. With these lookup tables, two schemes of atmospheric correction algorithm have been developed. For the clear water with nearly null water-leaving radiance in the CZI red and near infrared bands, the aerosol scattering contributions are firstly estimated at these bands to determine the aerosol models close to actual situation. Then, the aerosol scattering at the blue and green bands is estimated with the lookup tables for the selected aerosol models. For the turbid coastal waters with significant water-leaving contributions in the red and near infrared bands, the aerosol optical depth observed by the Chinese Ocean Color and Temperature Scanner (COCTS), which is concurrent with CZI, is used as auxiliary data to determine aerosol models.

China is rich in neritic and tideland resources. Floating raft aquaculture is an important part of the coastal marine environment monitoring. With rapid development of the aquaculture industry and driven by interests, high-density culturing and occupation of key ecological function areas including core and buffer zones of natural reserves, and illegal use of public facilities protective zones for culturing including ports and waterways have been exacerbated year by year. Therefore, systematic and deep studies on distribution and area of Floating raft aquaculture can provide additional decision-making information for fisheries authorities to rationally plan the Floating raft aquaculture, and offer a reliable scientific basis for controlling culturing density, curbing the deterioration of culturing environment, and preventing and controlling mariculture diseases.

Taking the seawater and the floating raft aquaculture in the Jiangsu Lianyungang offshore area as the classified objects, and the domestic GF1 high-resolution remote sensing data as the data source, this paper explores the method of extracting the raft cultivation information with the domestic high- resolution satellite imagery. The GF1 satellite data are preprocessed, and spectral and texture features are combined and applied to the support vector machine(SVM) algorithm. Then, the classification results of extracted seawater and floating raft aquaculture are compared and analyzed. In this paper, blue and green bands sensitive to culturing information are firstly screened for calculation of texture features. Then, 8 characteristic variables of gray level co-occurrence matrix, namely mean value, variance, homogeneity, contrast, dissimilarity, entropy, angular second moment and correlation, are adopted. Texture feature variables are combined with the red, green, and blue spectral data to form 19-layer feature variables. In order to capture key samples and removes redundancy, those feature variables are processed by principal component conversion. The components of the first 8 principal components with large quantities of information and well-retained culturing information are screened and used for classification experiment of support vector machine. To verify the classification accuracy, this method is compared with the classic maximum likelihood estimation and minimum distance methods. The experimental results show that the method of applying texture features in extraction of culturing information method can improve the classification accuracy of floating raft aquaculture. Compared with the maximum likelihood estimation and minimum distance methods, this method has its classification accuracy improved by 3%-5% as a whole.

The project aims at exploiting microwave satellite measurements to generate innovative added-value products to observe coastal areas also under extreme weather conditions. The following added-values products are addressed: coastal water pollution, coast erosion, ship and metallic target detection, typhoon monitoring.

To better state the goals, the project is framed into three subtopics: 1) SARCO - SAR-based Coast Observation; 2) Ship and Coastal Water Pollution Observation with Polarimetric SAR Architectures (SCoPeSAR); 3) SHENLONG: Sea-surface High-wind ExperimeNts with Long-range (satellite) Observations using Numerical Geophysical methods.

To reach the above-mentioned goals, single-polarization and polarimetric models will be analyzed and/or developed to generate added-value products that consist of: a) time-evolution of oil seeps in Gulf of Mexico; b) ship detection methods using European and Chinese SAR data; c) data assimilation scheme to assimilate Sentinel-1 SAR winds in the Weather Research and Forecasting (WRF) model for typhoon observation purposes; d) a new SAR azimuth cut-off scheme to estimate wind from SAR imagery.

Typhoons are among the most powerful and destructive natural disasters. Accurate forecasting of Typhoon track and intensity is very important to disaster prevention and reduction. Satellite observations can effectively compensate for the shortcomings of traditional methods of sea surface measurement and provide all-weather observation over the sea surface, which is of great significance to improve the numerical prediction of strong convective weather over ocean. The spaceborne radar observes the backscattering caused by the sea surface roughness, and then, the sea surface wind can be retrieved. Within this context, the Synthetic Aperture Radar (SAR) is an important data source for sea surface monitoring, since a variety of meteorological hydrological elements can be retrieved by SAR observation, and it has been used in data assimilation in recent years. SAR imagery is also used to monitor strength and structure of typhoons. The accuracy of sea surface winds retrieved from SAR has been found to be comparable to that of scatterometer data, and these wind fields can be used with a data assimilation system to provide the initial conditions for the numerical weather prediction (NWP) model.

In this study, a data assimilation scheme is proposed to assimilate the Sentinel-1 SAR retrieved winds in the Weather Research and Forecasting (WRF) model. Numerical simulation experiments of the typhoon Lionrock (2016) are carried out to test and compare different data assimilation methods. A series of Sentinel-1A EW swath mode dual-polarization (VV/VH) images are used to retrieve sea surface wind speed. Their overpass time were around 20:35 UTC on 29 August 2016. We use two different methods to derive the sea surface wind maps. The first is based on the use of the VV+VH dual pol geophysical model functions, while the second is based on the azimuth cut-off method. The Weather Research and Forecasting model data assimilation system (WRFDA) developed by the National Center for Atmospheric Research (NCAR) is adopted in this study. The grid size of the assimilation region is 260×250; the horizontal resolution is 15 km; and the vertical discretization is 30 layers. The time of assimilation is 0900 UTC 29 August 2016. The NCEP FNL Operational Global Analysis data are used as the initial field and boundary conditions. We take the 21-h forecast adjustment from 1200 UTC 28 August 2016 to 0900 UTC 29 August 2016 as the background field of the assimilation system. After the assimilation, a 30-h forecast is made, which is a forecast to 1500 UTC 30 August 2016. In this study, a set of assimilation and comparison experiments is carried out. Preliminary results show that the forecast track from SAR observations agree better with the best track than the control experiment.

Satellite Synthetic Aperture Radar (SAR) has been proved to be a key tool for a broad range of environmental applications in the context of oceans and coastal areas monitoring, including ship detection, coastline extraction, land use/cover classification, oil spill observation and sea surface parameters retrieval. In particular, the capability of satellite SAR measurements to support operational activities in case of natural disasters and environmental hazards as the Deepwater Horizon oil spill accident occurred in the Gulf of Mexico in 2010 or the most recent Sanchi accidental oil spill occurred off the eastern coast of China.

In this study, we focused on one of the richest areas in offshore oil seepages, i. e, the northern part of the Gulf of Mexico near the Mississippi river delta, where the Taylor Energy oil drilling platform is located (28°56’17’’N,88°58’16’’W). The platform was destroyed by the Hurricane Ivan in 2004 and, since then, the underwater wells were continuously leaking oil. It was estimated that more than 100 oil gallons enters into the marine environment from the Taylor Energy platform site. This results in surface oil slicks whose average thickness and life–time are about 1 μm and 4 days, respectively.

The area was continuously observed from satellite SAR platforms since the accidental oil spill occurred. Space-borne SAR imagery witness that this coastal area was almost persistently affected by this anthropogenic oil seep as the slicks were detected in about 80% of the data collected over the site. Even if strictly speaking this leakage cannot be considered as a natural oil seep, the underwater origin of the oil seep together with the involved weathering and aging processes are fairly the same.

Hence, it represents a good opportunity to have a large and consistent time series of SAR imagery that covers a well-known oil seepage. A large time series of dual-polarimetric co-polarized TerraSAR-X high-resolution (1.2 x 6.6 slant range x azimuth nominal spatial resolution) SAR imagery, collected in StripMap mode between July 2011 and April 2016 in a wide range of incidence angles (25° - 45°) and sea state conditions (low-to-moderate wind conditions applied, i. e., 1.5 m/s – 8.5 m/s), is exploited.

In this study, despite of the rather high noise floor that characterizes TerraSAR-X StripMap SAR imagery (an estimated noise equivalent sigma zero, NESZ, in the range -20 dB – -23 dB), the time series is effectively exploited to monitor the Taylor Energy oil spill. A multi-polarization analysis, that includes co-polarized intensity and phase difference information, is undertaken on which the oil spill detection and characterization is grounded.

Wind speed retrieval is a topic of great interest since wind estimation is very useful for a number of meteorological and oceanographic applications: wind is the major responsible of problematic like coastal erosion, climate change, marine life and so on. Most of the remote-sensing satellite radar systems are able to provide sea-surface wind field information, and they can be considered the main sea-surface wind information source. Within this context, active microwave remote sensing, in particular scatterometer and Synthetic Aperture Radar (SAR), is worldwide recognized as one of the best suitable tools to perform a reliable sea-surface wind speed retrieval. Radar backscatter intensities and their statistical properties contain quantitative information about the state of the sea surface roughness and, therefore, can be used to derive sea-surface wind information. When using radar systems such as the scatterometer and the SAR, the backscatter signal from the sea surface is dominated by the so-called Bragg resonant mechanism (mainly for wind speeds lower than 15m/s). In this case, there is a strong relationship between Normalized Radar Cross Section (NRCS) and wind speed linked by a Geophysical Model Function (GMF), while an alternative spectral based approach to retrieve wind speed is represented by the azimuth cut-off procedure.

When dealing with SAR microwave sensors, Doppler misregistration in azimuth are induced by gravity wave orbital motion. This issue is the major responsible of a distortion of the imaged spectrum and of a strong cut-off in the azimuthal direction: this is the azimuth cut-off. In literature, the azimuth cut-off method is used to retrieve wind speed and several studies have been carried out to analyze the dependence of λc on sea surface parameters. In particular, there is a linear relationship between λc values and geophysical parameters, like wind speed and significant wave height. Recently, in [1] the ACF-based λc approach has been improved to deal with high wind speed regimes, e.g.; extreme weather conditions. The key issues that allow to extend the method to high wind regimes concern the tuning of the method with respect to pixel spacing, box size and the homogeneity of the SAR imagery. In particular, the box size is set at 1 km × 1 km and the median filter window is set at 90-120 m.

In this study, this novel SAR azimuth cut-off implementation is applied to an actual SAR dataset collected under high wind regimes, like tropical cyclones. Finally, the soundness of this improved azimuth-cut-off method under extreme weather conditions is discussed.

[1] M. Portabella, V. Corcione, X. Yang, Z. Jelenak, P. Chang, G. Grieco, A. Mouche, F. Nunziata, W. Li, “Analysis of the SAR-derived wind signatures over extra-tropical storm conditions”, Dragon 4 Symposium, Copenhagen, Denmark, 26-30 June

Tropical cyclone is a generic term that designs a rapidly rotating storm system characterized by a
low pressure center that produces strong winds and heavy rainfall. Cyclones are differently named according to the ocean basin where they develop: “Hurricanes” in the Northern Atlantic and Northeast Pacific Ocean, “Typhoons” in the Northwest Pacific Ocean, and “Cyclones” in the Indian Ocean and Southwest Pacific Ocean. Although tropical cyclones are among the most dangerous and destructive natural disasters, current models are still not able to give an accurate forecast of their intensity and track. Hence, within this context, spaceborne active microwave sensors, like the Synthetic Aperture Radar (SAR), are of paramount importance because of their all-weather and all-day capabilities together with a fine spatial resolution. In particular, SAR data can be used to directly monitor position and intensity of the storms, to analyze their structure or the rainfall-rate but also to estimate wind speed and direction. The purpose of this study is to apply the azimuth cut-off approach under extreme weather conditions.
In literature, the azimuth cut-off method is used to retrieve wind speed and several studies have
been carried out to analyze the dependence of λc on sea surface parameters. In particular, there is a linear relationship between λc values and geophysical parameters, like wind speed and significant wave height Recently, in [1] the ACF-based λc approach has been improved to deal with high wind speed regimes, e.g.; extreme weather conditions. The key issues that allow to extend the method to high wind regimes concern the tuning of the method with respect to some parameters: the pixel spacing, the box size and the homogeneity of the SAR imagery.
In this study, an actual SAR dataset collected in occasion of tropical cyclones is used to discuss
the validity of this improved azimuth-cut- off method under extreme weather conditions.

[1] M. Portabella, V. Corcione, X. Yang, Z. Jelenak, P. Chang, G. Grieco, A. Mouche, F. Nunziata, W. Li, “Analysis of the SAR-derived wind signatures over extra-tropical storm conditions”, Dragon 4 Symposium, Copenhagen, Denmark, 26-30 June.

Polarimetric Synthetic Aperture Radar (PolSAR) is a microwave imaging system with the capabilities to image day-and-night and penetrate cloud cover. It is becoming an effective means of monitoring the Earth’s surface. Examples of applications are disaster damage estimation, urban classification, and
object detection. In particular, ship detection with PolSAR data has attracted a great deal of attention in the last several decades. Ship location can help us deal with many troublesome issues, e.g., marine traffic, illegal fishing, illegal immigration. However, ship detection is a complex problem, which is not
only depended on the nature of ship but also depended on the sea state.

Compared with sea surface, a different backscattering behavior can be expected in ships. Due to the complicated structures, ship backscatter is often various, including single-bounce returns, double-bounce returns, multiple-bounce returns and so on [1]. By analyzing the different scattering mechanisms between sea surface and ships, many excellent works have been done on ship detection. The most straightforward approaches, such as the polarimetric whitening filter (PWF) and SPAN detectors [2], directly used the three channels of PolSAR data for ship detection. In [3], Nunziata et al. effectively utilized the reflection symmetry (RS) properties of the sea and man-made targets to detect ships. Marino et al. [4] further constructed a new scheme, called the geometrical perturbation-polarimetric notch filter method (GP-PNF), from the polarimetric target complex space to detect ships at sea.

In essence, the above ship detectors only exploit one single pixel information to extract the polarimetric features, which hardly consider the spatial information and still belong to ’pixel level’ category [5]. As a fact, the background pixels surrounding ship pixels can also provide rich information for ship detection. In this paper, we proposed a new strategy to add the phase information when computing the polarimetric covariance difference matrix (PCDM) [6]. Then a complete polarimetric covariance difference matrix (CPCDM) is developed, and a CPCDM-based algorithm is also proposed to detect ships. Experimental results demonstrate the effectiveness of the proposed algorithm.

“Wind Pump” is an important concept that has drawn significant attention in the recent years. Wind Pump is defined as a series of wind-driven processes that influence ocean currents and water movement, which subsequently affect marine ecological conditions. Wind Pump can change the transport of nutrients and promote the cycling of major elements in the ocean. It thus drives primary production and marine ecosystem and affects carbon fixation and global fishery resources (Tang, 2004). This presentation will introduce “Wind Pump” effects on marine systems and take some examples in the South China Sea.

Algal bloom is defined as a rapid increase or accumulation in biomass in an aquatic system. It not only can increase the primary production but also could result in negative ecological consequence, e.g., Harmful Algal Blooms (HABs). According to the two classical theories of algal blooms “critical depth” and “eutrophication”, oligotrophic waters are difficult to form a large area of algal blooms. Cruise observations were only able to capture sporadically the existence of algal blooms. Due to limitations of in-situ observational methods, most of previous studies investigated occasional or regional blooms along coastal eutrophic waters, without much success of understanding of main processes responsible in the offshore deep-ocean oligotrophic waters. Based on previous studies by taking a full advantage of remote sensing technology and multiple satellite data, we proposed the mechanism model of “Wind Pump effects”, which represent the oceanic dynamic mechanism of the bloom growth. Except for the classical coastal Ekman transport, the Wind Pumping effects explain that wind forcing affects the formation of algal bloom through a variety of mechanisms, including Ekman pumping, clip volume, stirring and mixing, and transport by wind and wind-induced surface currents.

The conventional way to study upwelling regions by remote sensing is to use infrared and optical sensors by which the sea surface temperature (SST) and the chlorophyll-a (Chl-a) concentration is measured. However, also synthetic aperture radars (SARs) are useful instruments to study upwelling regions. Upwelling regions are areas of high biological activity, where the marine beings (plankton and fish) secrete surface active substances which rise to the sea surface and damp there the short surface waves, which are responsible for the radar backscattering. Thus upwelling areas manifest themselves on SAR images often as areas of reduced normalized radar cross section (NRCS). However, not only biogenic slicks associated with upwelling regions cause a reduction of the NRCS, but also the change the stability of the air-sea interface (from neutrally-stable to stable) because in upwelling regions the SST is usually lower than over the adjacent areas. Biogenic slicks visible on SAR images as areas of reduced NRCS are often confounded with mineral oil films. Criteria for discriminating between both types of surface films are presented. Furthermore, the correlation between Chl-a distribution and biogenic slick coverage in upwelling areas, like in the South China Sea east of Hainan, the East China Sea north of Taiwan, the Atlantic Ocean west of South Africa, and the Agulhas Return Current in the Indian Ocean, is investigated. These upwelling events are studied by using Sentinel-1 SAR images, Modis SST and Chl-a maps and model data of geostrophic surface currents. It is shown that this synergism yields new insights into upwelling mechanisms.

Sea Surface Temperature (SST) is the most important parameter, which is widely applied for studying water masses, air-sea interaction, marine ecosystem and environment, and other subjects. With the development of half century, satellite remote sensing has become the dominant technique to detect the global SST. However, the satellite measured SST is more closely related to the skin temperature than the subsurface bulk temperature. It is not convictive to validate the satellite measured SST with the subsurface bulk temperature, which is generally measured at a depth of one meter or even deeper. In order to validate the satellite retrieved SST, it is necessary to measure skin temperature.

A new version of the Buoyant Equipment for Skin Temperature (BEST), has been recently manufactured. The new instrument consists of 1050 thermistors, which are integrated in one pole, and 840 thermistors are on the top part (505mm in length) of the pole at 0.6mm distance each and 210 thermistors are on the other part (1015mm in length) of the pole at distance about 5mm. The pole works with a liquid level meter, the liquid level meter uses the electrical capacitance sensors which were also arrayed at 0.6mm distance corresponding to the thermistors. The new instrument BEST was then calibrated in a thermal isolation calibration system, and totally 21 temperature points from temperature -4℃～45℃ were measured for the calibration. The calibration results show the accuracy of the BEST is 0.01K.

The new instrument was vertically floated in Haizhu lake, Guangzhou from January 30 to 31, 2018, continuously for 2 days when the weather is quite cold. It synchronically measures the temperatures of the bottom layer of the air, the skin layer and the subsurface layer of the water at every second and more than hundred thousand temperature profiles were measured. All the temperature profiles have similar distribution pattern. In the bottom of air, the closer to the water surface, the higher temperature. and under the water surface, there is a thin thermocline (or metalimnion) which is just several centimeters thick. In the thermocline the temperature increases with water depth quickly. The water generally increases in temperature by 0.65 degrees Celsius every centimeter. The thermocline has very strong intensity, which is thousand times stronger than normal thermocline occurs in the ocean columns.

Mapping the Yangtze River discharge and freshwater plume spreading is highly important for in the understanding of phytoplankton blooming and nutrient distribution and transportation from the estuary to the East China Sea. Satellite sensor synergy building on passive microwaves, imaging spectrometer and radars are explored together with in-situ observations and dynamic modeling. With new EO satellite data available, such as Chinese Gaofen-4 and the ESA Sentinel-1,2 and 3 there exist possibilities that the freshwater plume mix and transportation process on weekly to seasonal basis can be observed and modelled. Moreover, in this study the Yangtze River Plume transportation dynamics may also be studied by mapping the plumes over the past decades, which may link the variations with large damming in the catchment. We adapt some of the classical methods for retrieval of sea surface salinity distribution with optical remote sensing data by establishing relationships between colored dissolved organic matters (CDOM) and salinity. We will also opt for sea surface brightness temperature methods with which sea surface salinity is obtained by using K-S model, where the brightness temperature is derived from scattering coefficient of SAR data. A Debye Equation based synergic method for sea surface salinity inversion will be thoroughly explored, in which sea surface temperature is synergically derived from brightness temperature through high resolution optical images and sea surface emittance calculated from SAR data.

Large scale green tide (macroalgae blooms of Ulva prolifera) have ocurred in every summer in the Yellow Sea since 2007, causing serious damages on coastal ecological environment, aquaculture, tourism, transportation and so on. The green macroalgae of Ulva prolifera originate from the seaweed aquaculture zone in the Jiangsu shoal, and the blooms are mainly caused by the activity of recycling the seaweed aquaculture facilities. In this work, Gaofen (GF) optical images with high spatial resolution (16m) and high revisit frequency (4 days) and Sentinel-1 IW-GRD microwave data are used to monitor the seasonal changes in the seaweed aquaculture in Jiangsu Shoal (120.8–122°E, 31.9–33.5°N) in 2016 and 2017 with the aim of exploring the reasons on the changes in the magnitude of green tide in the Yellow Sea in the summer of 2016 and 2017.

Macroalgae have the similar spectral signature as that of green vegetation. The normalized differential vegetation index (NDVI) derived from the GF-1 reflectance spectra is used to extract the seaweed aquaculture zone. Considering the difficulty of detecting seaweed aquaculture zone under the ebb tide and bad weather conditions, Sentinel-1 IW-GRD images are used to determine whether it is seaweed aquaculture zone or not.

The result shows that the seaweed aquaculture facilities was recycled mainly in April and May. However, the area of the aquaculture zone was only 1.3 km2 on May 3rd, 2016 while it remained 137.4 km2 on May 7th, 2017. In 2017, the area of the aquaculture zone reduced to 0.7 km2 till June 9th, which shows that the completion time of recycling the seaweed aquaculture facilities in 2017 was about one month later than in 2016. We deduced that the lower magnitude of green tides in 2017 in the Yellow Sea than 2016 may be due to the delay of recycling the seaweed aquaculture facilities. In 2017, the late time of recycling the seaweed aquaculture facilities slowed down the speed of the green macroalgae into the sea, therefore, the scale of the Yellow Sea green tide decreased significantly due to the reduced release of green tide species.

It is well known that rain events leave fingerprints on synthetic aperture radar (SAR) images acquired over the ocean, but it is not always easy to identify them unambiguously, especially not on C-band SAR images. Rain becomes visible on SAR images acquired over the ocean via several mechanisms: 1) by variations of the sea surface roughness caused by downdraft winds associated with rain cells and by rain drops impinging onto the sea surface (surface scattering) generating ring waves, splash products (including stalks), and turbulence, and 2) by scattering and attenuation of the radar beam by rain drops in the atmosphere (volume scattering). Surface scattering is particularly intricate at C-band because the Bragg waves responsible for the radar backscattering at this radar frequency lie in the transition region, where the impinging raindrops can increase (usually) or decrease the backscattered radar power, and also because scattering at stalks generated by impinging rain drops can significantly enhance the radar backscattering. In addition, at very high rain rates, volume scattering and attenuation can also contribute.

In this paper we report about progress that has been made in our study of C-band radar signatures of rain over the ocean. Such studies are relevant also for retrieving sea surface wind fields from C-band scatterometer data. Rain is a main source of error in wind retrieval algorithms, especially when co- and cross-polarized scatterometer data are used, which will be the case in the future. In this study we have analyzed mainly Sentinel-1 SAR images acquired over the South China Sea and have compared them with rain data from the weather radar of the Hong Kong Observatory and from the Global Precipitation Measurement (GPM) mission. In contrast to previously analyzed ERS and Envisat SAR data, the Sentinel-1 SAR data are acquired at VV and VH polarization simultaneously, which allows investigating the role of scattering at stalks, consisting of small cylinders of water emanating from the sea surface, in more detail. Theoretical investigations show that coherent scattering at stalks is responsible for the large values of the normalized radar cross section (NRNCS) at VV and VH polarizations often observed in radar signatures of strong rain cells. This interpretation is supported also by data acquired by the Unmanned Aerial Vehicle Synthetic Aperture Radar (UAVSAR) of NASA/JPL over the Gulf of Mexico.

Yangtze Estuary is located in the margin of land, facing East China Sea. It is influenced by the interaction of land and ocean, developed special environmental characteristics. Riverine freshwater plumes appear in the estuarine area specially, which play an important role in the study of material transport and Yangtze River runoff. Salinity can directly reflect the distribution of freshwater plumes. Therefore, research on the spatial and time distribution and variation of Yangtze River salinity is significant to understanding the importance of freshwater plum and estuarine environment. Compared to the significance of salinity, the measurement of salinity cannot provide sufficient and timely dataset. Remote sensing as a new monitoring technique, is able to provide the real-time synchronous monitoring of large area fast and timely. Existing salinity satellite SOMS and Aquarius cannot apply to the estuarine area because of their low spatial and time resolution. Optical satellite like MODIS, has high spectral resolution, proved suitable to retrieve salinity in estuarine area. This study uses MODIS Terra/Aqua L1b data and field data from voyage and hydrometric station of year 2013 to 2017 to establish a half-experienced retrieval model of Yangtze Estuary. This study divides the study area into inside and outside the Yangtze river estuary. Statistical models are used to the salinity retrieval outside the estuary. A dynamic model is established to t retrieve the salinity inside the estuary, taking runoff volume and tide into consideration, because of the complex hydrological and dynamic environments. The salinity retrieval model is used to reconstruct the salinity distribution of Yangtze Estuary during recent 30 years and analyze the seasonal and spatial salinity variations.

Retrieval of ocean color information is one of the most important missiona of Sentinel-3 Ocean and Land Color Instrument (OLCI). As the successor to Medium Resolution Imaging Spectrometer (MERIS) aboard ENVISAT, OLCI shows significant superiority compared with MERIS as well as Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-Viewing Wide Field-of-View Sensor (SeaWiFS). The superiority shows in such aspects: the sensor has 21 bands, compared to 15 bands on MERIS, a design optimized to minimize sun-glint and a resolution of 300 m over all surfaces. In this study, we estimated the water quality in the Pearl River using Sentinel-3 OLCI. We appraise the precision of the water quality, including suspended sediment, Chlorophyll-a concentration, CDOM retrieved from OLCI, MERIS, MODIS and SeaWiFS. The results shows that the OLCI shows a good improvement in water quality detection in Pearl River Estuary. The additional bands enhance the ability to extract the information of coastal water quality.

Both the green tide caused by the outbreaks of Ulva prolifera and the golden tide caused by the outbreaks of Sargassum have appeared in the Yellow Sea and the East China Sea in recent years (Xing et al, 2017). The spectral characteristics of floating macroalgae are the basis for the remote detection by optical satellite remote sensing. A total of 10 samples of Ulva prolifera and Sargassum were collected from June 9, 2017 to June 19, 2017 in the Yellow Sea (33º37´～36º30´N, 120º00´～123º30´E). The spectral reflectance of them were measured by a hyperspectral spetroradiometer and a multi-spectral imager, respectively. The hyperspectral data was used to analyze spectral characteristics. The threshold method and neural network method based on the multi-spectral image were tested for the classifying of Ulva prolifera and Sargassum.
In this work, the Virtual-Baseline Floating macroAlage Height (VB-FAH) was calculated for extracting the floating macroalgae (Xing et al, 2016). The reasonable threshold was chosen for the classifying of the two macroalgae based on the trough depth (T-depth) and the Virtual-Baseline Floating macroAlage Height (VB-FAH) (Xing et al, 2013). And the pixel is regard as Ulva prolifera if the value of T-depth is larger than 0.30 or the value of VB-FAH is larger than 0.44. For the neural network method, we did 3 tests with different inputs: the 3-band reflectance image (Image_{_R}), the 3-band reflectance and the T-depth (Image_{_R+T-depth}), the 3-band reflectance and the VB-FAH (Image_{_R+VB-FAH}). The classification results of the above two methods were compared.

Xing Q G, Yu D F, Lou M J, et al, 2013. Using in-situ reflectance to monitor the Chlorophyll concentration in the surface layer of Tidal Flat. Spectroscopy and Spectral Analysis, 33(8): 2188—2191.

References

Xing Q G, Hu C, 2016. Mapping macrolagal blooms in the Yellow Sea and East China Sea using HJ – 1 and Landsat data: Application of a virtual baseline reflectance height technique. Remote Sensing of Environment, 178: 113—126.

Xing Q G, Guo R H, Wu L L, et al, 2017 . High-Resolution satellite observations of a new hazard of "Golden Tides" caused by floating Sargassum in Winter in the Yellow Sea. IEEE Geoscience and Remote Sensing Letters.

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.