Sea surface Fresnel reflections difference driven de-glint algorithm for airborne optical images.

This paper presents a glint correction algorithm for high spatial resolution optical remote sensing imagery captured by the ER-2 Airborne Visual Infrared Imaging Spectrometer (AVIRIS). The algorithm employs linear and differential techniques to mitigate sun glint and sky glint effects, encompassing statistical glint reflections resulting from variations in imaging angles within strips and inter-strip variations due to Fresnel reflectance disparities. It aims to diminish Fresnel reflectance diversity on water surfaces and mitigate the distortions induced by glint reflectance during spectral and ocean color inversion. A comparative analysis of spectral and ocean color information in AVIRIS images before and after correction reveals enhanced accuracy following the glint correction. By systematically addressing multiple glint reflections and their ramifications, this method offers a valuable framework for correcting water surface glint in diverse high spatial resolution optical imagery.

Radiometric cross-calibration of Sentinel-2B MSI with HY-1C SCS based on the near simultaneous imaging of common ground targets.

To simplify the cross-calibration process and improve calibration frequency and accuracy, this paper proposes a cross-calibration method for the multispectral remote sensor Multi-Spectral Instrument (MSI) carried by Sentinel-2B using the hyperspectral remote sensor, that is, the satellite calibration spectrometer (SCS) carried by Hai Yang (HY)-1C, as the reference sensor and establishes the calibration process. Precise spectral response matching between SCS and MSI spectral channels is performed by the interpolation and iteration of hyperspectral data to eliminate the difference in band settings and significantly improve the accuracy of cross-calibration coefficients. The SNO-x inherited from the simultaneous nadir overpass (SNO) method is used as a prediction method to carry out cross-calibration imaging in mid- and low-latitude regions, which improves the cross-calibration frequency and broadens the dynamic range of calibration. The cross-calibration coefficients and offsets of MSI B1∼B7 and B8a were obtained by processing the earth observation images of the MSI and SCS on January 24, 2019. Then, the cross-calibration coefficients and offsets are applied to the ocean, farmland and other ground objects with different reflectance, and the reliability and accuracy of the cross-calibration results are evaluated with the Moderate-resolution Imaging Spectroradiometer (MODIS) carried by Terra as a reference. To improve the accuracy of the evaluation, the spectral band adjustment factor between the corresponding channels of MSI and MODIS is used to correct the measured reflectance of MODIS based on the satellite calibration coefficient. The reflectance directly obtained by processing the MSI image is used as the MSI-measured reflectance, the reflectance obtained based on the cross-calibration coefficient is used as the MSI-calculated reflectance, and the reflectance corrected by the spectral band adjustment factor (SBAF) is used as the MODIS-calculated reflectance. The results show that the mean root-mean-square relative error (RMSRE) between the MODIS-calculated reflectance and the MSI-calculated reflectance is 2.16% and that the mean RMSRE between the MODIS-calculated reflectance and the MSI-measured reflectance is 3.05%, indicating that the reflectance corrected based on calibration coefficients is closer to the MODIS-calculated reflectance. Finally, each uncertainty source in the cross-calibration is analyzed, and the comprehensive uncertainty is found to be 4.03%, indicating that SCS can be used as a reference for MSI cross-calibration.

Quantifying ocean surface green tides using high-spatial resolution thermal images.

The use of thermal remote sensing for marine green tide monitoring has not been clearly demonstrated due to the lack of high-resolution spaceborne thermal observation data. This problem has been effectively solved using high-spatial resolution thermal and optical images collected from the sensors onboard the Ziyuan-1 02E (ZY01-02E) satellite of China. The characteristics and principles of spaceborne thermal remote sensing of green tides were investigated in this study. Spaceborne thermal cameras can capture marine green tides depending on the brightness temperature difference (BTD) between green tides and background seawater, which shows a positive or negative BTD contrast between them in the daytime or nighttime. There is a significant difference between thermal and optical remote sensing in the ability to detect green tides; compared with optical remote sensing, pixels containing less algae are not easily distinguishable in thermal images. However, there is a good linear statistical relationship between the BTD and the optical parameter (scaled algae index of virtual baseline height of floating macroalgae, SAI(VB)) of green tides, which indicates that the BTD can be used to quantify the green tide coverage area in a pixel or biomass per area. Then, the uncertainty in thermal quantitative remote sensing of green tides was clarified according to the pixel-to-pixel relationship between optical and thermal images. In a mixed pixel, green tide coverage and algal thickness have different thermal signal responses, which results in this uncertainty. In future research, more thermally remotely sensed images with high spatial resolution are needed to increase the observation frequency in the daytime and nighttime for the dynamic monitoring of green tides.

Onboard spectral calibration and validation of the satellite calibration spectrometer on HY-1C.

To monitor the spectral position drift, expansion and contraction of the full width at half maximum (FWHM) of the satellite calibration spectrometer (SCS) of the HY-1C satellite during on-orbit operation, an onboard spectral calibration method based on a wavelength diffuser is proposed in this paper. This method uses the wavelength diffuser reflectance measured prelaunch as the standard spectrum, convolves it with the spectral response function of the SCS to obtain a reference spectrum, uses the measured data of the onboard SCS as the measured spectrum, and obtains the spectral drift and variation of the FWHM through spectral line matching. Generally, the spectral response function of a hyperspectral remote sensor follows a Gaussian model, and so does that of the SCS. The spectral calibration results obtained based on the onboard wavelength diffuser are validated and evaluated in comparison to calibration based on an oxygen absorption line. Preliminary results show that (1) the SCS spectral drift is negative, indicating a shift in the shortwave direction, and its absolute value is gradually decreasing with increasing on-orbit operation time; (2) the mean values of the central wavelength and FWHM errors between the two calibration methods are 0.08 nm and 0.20 nm, respectively, indicating that the spectral calibration method based on the wavelength diffuser has high accuracy and reliability; and (3) the SCS spaceborne spectral calibration error has the greatest impact on radiometric calibration in Band 18, with an uncertainty of 0.99%, while the uncertainty in the other bands is less than 0.33%, indicating that the spectral calibration uncertainty meets radiometric calibration accuracy requirements.

Evaluation of regions suitable for vicarious calibration of ocean color satellite sensors in the South China Sea.

Accurate retrieval of biogeochemical components of the ocean at a global scale from space requires accurately calibrated top-of-atmosphere (TOA) radiance, which is usually achieved by deriving a vicarious gain coefficient (g-factor) through a process called system vicarious calibration (SVC). Currently, only two SVC sites, Marine Optical Buoy (MOBY) and BOUée pour l'acquiSition d'une Série Optique à Long termE (BOUSSOLE), are routinely operated to support the SVC process for all on-orbit ocean color satellite payloads. However, high-quality matchups between satellite observations and in situ measurements are rare because of the strict requirements of the SVC process. Meanwhile, a stable g-factor is usually computed by averaging sufficient gain measurements. Therefore, more SVC sites are required to derive a stable g-factor in a short duration, particularly for the initial calibration of newly launched satellite sensors. In this study, nearly twenty years of well-calibrated ocean color satellite data were used to calculate the mean and standard deviation of physical and optical properties of waters and the atmosphere in the South China Sea (SCS) to evaluate the feasibility of establishing a SVC site. A region was identified that meets all requirements that were used to evaluate the MOBY and BOUSSOLE sites. Two in situ measurements within this region were used to derive a g-factor for MODIS-Terra and MODIS-Aqua and were compared with the g-factor derived using MOBY data. The consistence of the two g-factors indicates that the identified region in the SCS could be a potential area for establishing a long-term moored SVC site.

Onboard absolute radiometric calibration and validation of the satellite calibration spectrometer on HY-1C.

As the reference radiometric calibration standard of sensors on the Haiyang-1C (HY-1C) satellite platform, the satellite calibration spectrometer (SCS) is equipped with an onboard calibration system composed of double solar diffusers and an erbium-doped diffuser to monitor the postlaunch radiometric response change. Herein, through onboard calibration data analysis, the calibration diffuser performance remains stable without degradation, and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra is adopted as a reference to repeatedly verify onboard radiometric calibration results by selecting different dates and reflectance scenes. The SCS equivalent reflectance is obtained by combining the mean digital number (DN) of the SCS crossing area image with the radiometric calibration coefficient. The spectral reflectance is obtained via interpolation and iteration, which is adopted as the actual MODIS incident pupil spectral reflectance because the small imaging time interval can be ignored and almost vertically observed, and it is convoluted with the MODIS spectral response function to obtain the predicted equivalent reflectance. Validation is completed by comparing the predicted MODIS equivalent reflectance to the measured value based on the onboard calibration coefficient. The results show that (1) the difference between the measured and predicted MODIS band equivalent reflectance is between -0.00466 and 0.0039, and (2) the percentage difference between the measured and predicted MODIS band equivalent reflectance ranges from 4.17% and 1.24%, indicating that the calibration system carried on HY-1C can perform high-precision SCS radiometric calibration, meeting the cross-calibration accuracy requirements of other loads on the same platform.

Vicarious calibration of COCTS-HY1C at visible and near-infrared bands for ocean color application.

Remote sensing reflectance obtained from space-borne ocean color sensors is of great importance to carbon cycle and ocean-atmospheric interactions by providing biogeochemical parameters on the global scale using specific algorithms. Vicarious calibration is necessary for obtaining accurate remote sensing reflectance that meets the application demands of atmospheric correction algorithms. For ocean color sensors, vicarious calibration must be done prior to atmospheric correction. The third Chinese Ocean Color and Temperature Scanner (COCTS) aboard the HY1C satellite was launched on September 7, 2018, and it will provide essential ocean color data that will complement those of existing missions. We used field measurements from the Marine Optical Buoy (MOBY) and aerosol information provided by the MODerate Imaging Spectroradiometer (MODIS) aboard the Terra satellite to calculate vicarious calibration coefficients, and we further evaluated the applicability of the established vicarious calibration approach by cross-calibration using MODIS data on the global scale. Finally, the established vicarious calibration coefficients were used to retrieve the aerosol optical depth and remote sensing reflectance, which were compared to Aerosol Robotic Network-Ocean Color (AERONET-OC) data and MODIS-Terra and Ocean and Land Color Instrument (OLCI)-Sentinel-3A operational products. The results show that the vicarious calibration coefficients are relatively stable and reliable for all bands ranging from visible to near-infrared and can be used to obtain accurate high-quality data.

Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations.

Monitoring of water quality changes in highly dynamic inland lakes is frequently impeded by insufficient spatial and temporal coverage, for both field surveys and remote sensing methods. To track short-term variations of chlorophyll fluorescence and chlorophyll-a concentrations in Poyang Lake, the largest freshwater lake in China, high-frequency, in-situ, measurements were collected from two fixed stations. The K-mean clustering method was also applied to identify clusters with similar spatio-temporal variations, using remote sensing Chl-a data products from the MERIS satellite, taken from 2003 to 2012. Four lake area classes were obtained with distinct spatio-temporal patterns, two of which were selected for in situ measurement. Distinct daily periodic variations were observed, with peaks at approximately 3:00 PM and troughs at night or early morning. Short-term variations of chlorophyll fluorescence and Chl-a levels were revealed, with a maximum intra-diurnal ratio of 5.1 and inter-diurnal ratio of 7.4, respectively. Using geostatistical analysis, the temporal range of chlorophyll fluorescence and corresponding Chl-a variations was determined to be 9.6 h, which indicates that there is a temporal discrepancy between Chl-a variations and the sampling frequency of current satellite missions. An analysis of the optimal sampling strategies demonstrated that the influence of the sampling time on the mean Chl-a concentrations observed was higher than 25%, and the uncertainty of any single Terra/MODIS or Aqua/MODIS observation was approximately 15%. Therefore, sampling twice a day is essential to resolve Chl-a variations with a bias level of 10% or less. The results highlight short-term variations of critical water quality parameters in freshwater, and they help identify specific design requirements for geostationary earth observation missions, so that they can better address the challenges of monitoring complex coastal and inland environments around the world.

Ocean color retrieval from MWI onboard the Tiangong-2 Space Lab: preliminary results.

The Moderate-resolution Wide-wavelengths Imager (MWI) is the ocean color sensor onboard the Chinese Tiangong-2 Space Lab, which was launched on Sept. 15, 2016. The MWI is also an experimental satellite sensor for the Chinese next generation ocean color satellites, HY-1E and HY-1F, which are scheduled for launch around 2021. With 100m spatial resolution and 18 bands in the visible light and infrared wavelengths, MWI provides high quality ocean color observations especially over coastal and inland waters. For the first time, this study presents some important results on water color products generated from the MWI for the oceanic and inland waters. Preliminary validation in turbid coastal and inland waters showed good agreement between the MWI-retrieved normalized water-leaving radiances (Lwn) and in situ data. Further, the MWI-retrieved Lwn values compared well with the GOCI-retrieved Lwn values, with the correlation coefficient greater than 0.90 and mean relative differences smaller than 26.63% (413 nm), 4.72% (443 nm), 3.69% (490 nm), 7.15% (565 nm), 9.45% (665 nm), 8.11% (682.5 nm), 14.68% (750 nm) and 18.55% (865 nm). As for the Level 2 product (e.g, total suspended matter TSM) in turbid Yangtze River Estuary and Hangzhou Bay waters, the relative difference between MWI and GOCI-derived TSM values was ~18.59% with the correlation coefficient of 0.956. In open-oceanic waters, the retrieved MWI-Chla distributions were well consistent with the MODIS/Aqua and VIIRS Chla values products and resolved finer spatial structures of phytoplankton blooms. This study provides encouraging results for the MWI's performance and operational applications in oceanic and inland regions.

[New Algorithms to Separate the Contribution of Petroleum Substances and Suspended Particulate Matter on the Scattering Coefficient Spectrum from Mixed Water].

In the water with petroleum pollution, the petroleum will be adsorbed on the surface of suspended particulate matter and form a double-layer structure, which impacts on the spectrum characteristics to the scattering coefficient. It is a key to improve the accuracy of the scattering theory model that the contribution of petroleum substances and suspended particulate matter on the scattering spectrum coefficient is be separated. A backward scattering coefficient spectrum measurement system was being built from linkage observation of three kinds of instruments, including DAWN HELEOS Ⅱ18 angle scattering measuring instrument (Wyatt company, American), LISST-100-xB size instrument(SEQUOIA SCIENTIFIC, INC, American), HydroScat-6 Sprctral Backscattering Sensor (HS6) ( Hobilabs company, American). Many parameters were measured such as voltage value of the scattering intensity, the particle size distribution, particle concentration and backward scattering coefficient in different water samples. Using the Mie scattering theory, a new algorithm to separate the scattering coefficient spectrum and new way of thinking to calculate volume scattering function ß(λ, θ) of the unknown refractive index material were proposed. The matching experiments were done by selecting quartz sand as particles whose refractive index (m) is known and petroleum sewage collected from different oilfield area. On the basis of matching experiments different water samples with different properties were obtained and related data were determinated. Firstly, according to Mie scattering theory the water volume scattering function ß(λ, θ) for each sample is calculated. Secondly, the equation was set up which can convert the scattering intensity corresponding to the voltage value V(θ) measured by DAWN HELEOS Ⅱ 18 Angle laser scattering instrument into volume scattering function ß(λ, θ). Thirdly, according to the method of optimum the equivalent refractive index (mos) of the oil sands mixed and the refractive index (mo) of petroleum sewage were estimated; Finally, using ß(λ, θ) and estimation of mos values and mo values to calculate the backscatter coefficient bb(λ) of all kinds samples, and new algorithms were set up which seperated quartz sand bb, s(λ) and petroleum sewage bb, o(λ) from mixed water with petroleum and sands respectively. The establishment of these separation algorithms improves the accuracy of the scattering theory model of the water petroleum pollution, on the other hand expands the Mie scattering theory in the application of ocean color remote sensing.

Origin of Improved Optical Quality of Monolayer Molybdenum Disulfide Grown on Hexagonal Boron Nitride Substrate.

Monolayer MoS2 is synthesized on hexagonal boron nitride (h-BN) flakes with a simple, high-yield method. Monolayer MoS2 on h-BN exhibits improved optical quality. Combining the theoretical and experimental analysis, it is concluded that the enhanced photoluminescence and Raman intensities of monolayer MoS2 probably originate from the relatively weak doping effect from the h-BN substrate rather than the optical interference effect.

Instantaneous influence of dust storms on the optical scattering property of the ocean: a case study in the Yellow Sea, China.

Asian dust storms originating from arid or semi-arid regions of China or her adjacent regions have important impact on the atmosphere and water composition, and ecological environment of the Eastern China Seas. This research used data collected in the middle of the South Yellow Sea, China, during a dust storm event from 23 April to 24 April 2006 to analyze the instantaneous influence of dust storms on optical scattering properties, which are closely related to particle characteristics. The analysis results showed that the dust storm had a remarkable influence on the optical scattering property in the upper mixed layer of water, and dust particles drily deposited from the dust storm with an aerosol optical depth of nearly 2.5 into the water could induce a 0.14 m-1 change in the water optical scattering coefficient at 532 nm at the depth of 4 m. The duration of the instantaneous influence of the dust storm on the water optical scattering properties was short, and this influence disappeared rapidly within approximately 3 hours after the end of the dust storm.

[Analysis of fluorescence spectrum of petroleum-polluted water].

In four ratio experiments, natural waters, sampled from the mountain reservoir and the sea water around Dalian city, were mixed with the sewage from petroleum refinery and petroleum exploitation plants. The fluorescence spectra of water samples containing only chromophoric dissolved organic matters(CDOM), samples containing only petroleum, and samples containing a mixture of petroleum and CDOM were analyzed, respectively. The purpose of this analysis is to provide a basis for determining the contribution of petroleum substances and CDOM to the total absorption coefficient of the petroleum-contaminated water by using fluorescence technique. The results showed that firstly, CDOM in seawater had three main fluorescence peaks at Ex: 225-230 nm/Em: 320-330 nm, Ex: 280 nm/Em: 340 nm and Ex: 225-240 nm/Em: 430-470 nm, respectively, and these may arise from the oceanic chlorophyll. CDOM in natural reservoir water had two main fluorescence peaks at EX: 240- 260 nm/Em: 420-450 nm and Ex: 310~350 nm/Em: 420--440 nm, respectively, and these may arise from the terrestrial sources; secondly, the water samples containing only petroleum extracted with n-hexane had one to three fluorescence spectral peaksat Ex: 220-240 nm/Em: 320-340 nm, Ex: 270-290 nm/Em: 310-340 nm and Ex: 220-235 nm/Em: 280-310 nm, respectively, caused by their hydrocarbon component; finally, the water samples containing both petroleum and CDOM showed a very strong fluorescence peak at Ex: 230-250 nm/Em: 320-370 nm, caused by the combined effect of CDOM and petroleum hydrocarbons.

Optimization of diabetes prediction methods based on combinatorial balancing algorithm.

BACKGROUND: Diabetes, as a significant disease affecting public health, requires early detection for effective management and intervention. However, imbalanced datasets pose a challenge to accurate diabetes prediction. This imbalance often results in models performing poorly in predicting minority classes, affecting overall diagnostic performance. OBJECTIVES: To address this issue, this study employs a combination of Synthetic Minority Over-sampling Technique (SMOTE) and Random Under-Sampling (RUS) for data balancing and uses Optuna for hyperparameter optimization of machine learning models. This approach aims to fill the gap in current research concerning data balancing and model optimization, thereby improving prediction accuracy and computational efficiency. METHODS: First, the study uses SMOTE and RUS methods to process the imbalanced diabetes dataset, balancing the data distribution. Then, Optuna is utilized to optimize the hyperparameters of the LightGBM model to enhance its performance. During the experiment, the effectiveness of the proposed methods is evaluated by comparing the training results of the dataset before and after balancing. RESULTS: The experimental results show that the enhanced LightGBM-Optuna model improves the accuracy from 97.07% to 97.11%, and the precision from 97.17% to 98.99%. The time required for a single search is only 2.5 seconds. These results demonstrate the superiority of the proposed method in handling imbalanced datasets and optimizing model performance. CONCLUSIONS: The study indicates that combining SMOTE and RUS data balancing algorithms with Optuna for hyperparameter optimization can effectively enhance machine learning models, especially in dealing with imbalanced datasets for diabetes prediction.

Coal-gangue sound recognition using hybrid multi-branch CNN based on attention mechanism fusion in noisy environments.

The coal-gangue recognition technology plays an important role in the intelligent realization of fully mechanized caving face and the improvement of coal quality. Although great progress has been made for the coal-gangue recognition in recent years, most of them have not taken into account the impact of the complex environment of top coal caving on recognition performance. Herein, a hybrid multi-branch convolutional neural network (HMBCNN) is proposed for coal-gangue recognition, which based on improved Mel Frequency Cepstral Coefficient (MFCC) as well as Mel spectrogram, and attention mechanism. Firstly, the MFCC and its smooth feature matrix are input into each branch of one-dimensional multi-branch convolutional neural network, and the spliced features are extracted adaptively through multi-head attention mechanism. Secondly, the Mel spectrogram and its first-order derivative are input into each branch of the two-dimensional multi-branch convolutional neural network respectively, and the effective time-frequency information is paid attention to through the soft attention mechanism. Finally, at the decision-making level, the two networks are fused to establish a model for feature fusion and classification, obtaining optimal fusion strategies for different features and networks. A database of sound pressure signals under different signal-to-noise ratios and equipment operations is constructed based on a large amount of data collected in the laboratory and on-site. Comparative experiments and discussions are conducted on this database with advanced algorithms and different neural network structures. The results show that the proposed method achieves higher recognition accuracy and better robustness in noisy environments.

Spectral variability of sea surface skylight reflectance and its effect on ocean color.

In this study, sea surface skylight spectral reflectance ρ(λ) was retrieved by means of the non-linear spectral optimization method and a bio-optical model. The spectral variability of ρ(λ) was found to be mainly influenced by the uniformity of the incident skylight, and a model is proposed to predict the ρ(λ) spectral dependency based on skylight reflectance at 750 nm. It is demonstrated that using the spectrally variable ρ(λ), rather than a constant, yields an improved agreement between the above-water remote sensing reflectance R(rs)(λ) estimates and concurrent profiling ones. The findings of this study highlight the necessity to re-process the relevant historical above-water data and update ocean color retrieval algorithms accordingly.

Coal-gangue recognition via multi-branch convolutional neural network based on MFCC in noisy environment.

Traditional coal-gangue recognition methods usually do not consider the impact of equipment noise, which severely limits its adaptability and recognition accuracy. This paper mainly studies the more accurate recognition of coal-gangue in the noise site environment with the operation of shearer, conveyor, transfer machine and other device in the process of top coal caving. Mel Frequency Cepstrum Coefficients (MFCC) smoothing method was introduced to express the intrinsic feature of sound pressure more clearly in the coal-gangue recognition site. Then, a multi-branch convolution neural network (MBCNN) model with three branches was developed, and the smoothed MFCC feature was incorporated into this model to realize the recognition of falling coal and gangue in noisy environment. The sound pressure signal datasets under the operation of different device were constructed through a great deal of laboratory and site data acquisition. Comparative experiments were carried out on noiseless dataset, single noise dataset and simulated site dataset, and the results show that our method can provide higher correct recognition accuracy and better robustness. The proposed coal-gangue recognition approach based on MBCNN and MFCC smoothing can not only recognize the state of falling coal or gangue, but also recognize the operational state of site device.

[Study on using apparent spectrum to retrieve the inherent optical properties of ocean water].

The inherent optical properties are needed when establishing the semi-analytic model in the ocean color retrieval algorithm. Using the in-situ measurements, a retrieval model for inherent optical properties from remote sensing reflectance was established. The in-situ data measured in the 2003 spring cruise over the Yellow and East China Seas is introduced. The measurement method for remote sensing reflectance, particle backscattering and absorption coefficients are detailed. Based on the bio-optical model, the inherent optical properties were retrieved by optimization of Nelder-Mead simplex. The retrieval results of the absorption and backscattering coefficients for the material other than pure water were compared with the counterpart of the in-situ measurements. The comparison shows that the root-mean-square relative error for the absorption coefficient of materials other than water is less than 33%. The value is 30% for the particle backscattering coefficient. The analysis of the error shows that the retrieval model established in this paper can provide an efficient approach to retrieving the absorption and backscattering coefficients. The retrieval model can provide a reference for the application of remotely sensed data to the research on the bio-optical properties of Yellow and East China Seas.

Analysis of longitudinal coupling dynamic characteristics of deep sea mining vessel and stepped lifting pipe.

In deep-sea mining, the coupling dynamic response between the mining vessel and the lifting pipe is a significant problem, which directly affects the structural design of the lifting system and the safety of field operation. The characteristics of coupled motion model have not been fully considered in the existing research. Therefore, this paper uses time-domain coupled numerical model as the research object, considering ocean current, surface wave, pipe dynamics and vessel-pipe contact mechanics, to study the dynamic behavior of the lifting pipe and mining vessel during the process of deep-sea mining using AQWA and OrcaFlex softwares. The response amplitude operator (RAO) is used to compare the measured and simulations dynamic response of the mining vessel. There is a very good agreement in RAO between the experiments and simulations. The coupling simulation results show that the coupling effect has a significant effect on the time domain dynamic response of the lifting pipe, but has little effect on the average effective tension and longitudinal amplitude along the pipe length. The research results of this paper are of great significance to the safety design of deep-sea mining lifting system and the planning of deep-sea operation activities.

[Influence of petroleum concentration in water on spectral backscattering coefficient].

The petroleum pollutants mixing proportion experiment and in-situ experiment were carried out in the estuary of Panjin, Liaoning province in May 2008 and August 2009. The optical properties and biochemical properties were measured to get the effect of petroleum concentration in water on backscattering coefficients spectrum. The results show that the power-law index of backscattering coefficient decreases as TSM concentration increases and the relationship of these variables follows logarithm mode. Specific backscattering coefficient's value of 440 to 856 nm is between 0.006 and 0.035 m2 x g(-1) and decreases as wavelength increases. The petroleum mass-specific backscattering coefficients (backscattering coefficients of unit petroleum concentration) decreases with the wavelength increasing and follows power law for petroleum concentration. Petroleum concentration has little effect on the power-law index of backscattering coefficient.