广东近海油类漂流扩散的试验和实践

根据海上溢油试验结果，结合20a来对海上溢油事故的观察结果分析了油类入海后漂流和扩散过程。经分析认为：1)海面油类漂流的速度和方向取决于风和表层海流的速度和方向，海面油类漂流的速度和方向基本符合Uo=Uc ζW和D=C流 r；2)海面油类扩散的形状与油类漂流的速度有关。油膜的扩散速度与时间可以用U扩=at^-b来表达，油类漂流速度越大，油膜的形状就越呈长而窄，反之则呈短而宽；3)经两起海上沉船溢事故的实例检验．结果比较接近；4)在1996年珠江口惠洲26—1油田海底输油管线溢油漂流预测分析过程中进行尝试，收到比较好的效果。     

海面溢油光学卫星遥感监测能力分析

 海面溢油对海洋生态的影响具有频率高、范围广和危害大的特点。卫星遥感已成为海面溢油监测的重要手段。本文从海面油膜光谱特性出发,与常用的光学卫星传感器建立对应关系,根据对不同光学遥感卫星的空间分辨率、时间分辨率、幅宽和波段数等主要物理参数的对比分析认为,MODIS传感器和HJ-1卫星有较强的海面溢油监测能力。故此,采用MODIS、BJ-1、HJ-1和FY-3光学卫星影像,对2006年3月和2011年6月渤海海面溢油污染事故进行了遥感监测。MODIS遥感图像可以清晰反映出2006年和2011年这2次溢油污染事故中海面油膜信息,HJ-1卫星遥感影像则能反映出2011年溢油污染事故中海面油膜信息,而BJ-1和FY-3卫星遥感影像不能反映出海面油膜信息。HJ-1、BJ-1和FY-3卫星在波段设置上相似,但是,BJ-1和FY-3卫星不能反映出油膜信息,所以,本文进一步对这2次溢油事件中的MODIS遥感影像的油水光谱反差和海水光谱方差进行计算,并对结果进行比较分析,实验结果表明,当MODIS某一波段的海水光谱方差小于油水光谱反差时,则该波段可以显示出油膜信息;而当油水光谱反差小于或接近海水方差时,则不能反映出海面油膜信息。从波谱响应、空间分辨率和时间分辨率,以及监测实例中说明MODIS传感器有较强的海面溢油监测能力。     

基于特征概率函数的双阈值分割海面溢油检测

 海面溢油对生态环境造成了严重危害,故及早发现和尽快处理对降低事故影响和经济损失起着至关重要的作用。合成孔径雷达(SAR)是观测海面溢油、快速检测和事故态势分析判断的有效技术途径。本文针对SAR图像的海面溢油检测,提出了一种特征概率函数的双阈值分割方法。首先,通过高低阈值分割提取不同层次的灰度信息,再利用密度估计提取灰度的空间分布信息,然后,通过构建概率函数对油膜和类油膜区域进行形态学分类,最后,结合辅助信息,获得最终的海面溢油检测结果。本文利用香港中文大学卫星地面站接收的ENVISAT ASAR图像开展实验,结果表明,本文提出的方法能够准确地排除由风场或者水流场导致的低散射区域,有效地检测和识别生成不久的中型油膜,从而有助于溢油事故的早期预警与处置。     

多元指标的海上溢油信息提取

 海上溢油给海洋生态环境带来了巨大的影响,甚至需要几十年才能恢复。运用卫星遥感进行海上溢油监测已成为目前溢油监测的主要手段。本文对海上溢油遥感监测方法进行了分析,鉴此,提出了一种SAR数据的多元指标溢油信息提取方法。首先,对图像进行分割,然后,建立溢油形状参数、纹理特征指数、物理特性指数等主要指标,并以层次分析法得出每一类指标的权重。针对每一类指标,以经现场验证的溢油图像为基础,选择形状参数,如周长与面积比值、复杂度等,建立溢油形状判读等级;选择纹理特征参数,以灰度共生矩阵的相关性、熵、变化等来表达溢油的纹理特性,建立溢油纹理特征判断等级;选择溢油物理特征,如溢油与海水的标准差、均方根差、对比度等,建立溢油物理参数判断等级。在此基础上,建立海上溢油遥感信息提取指数,计算分割图斑的溢油遥感信息提取指数,以此判断溢油遥感信息提取的置信度,为溢油识别提供依据。     

基于MODIS谱纹信息融合的海洋溢油检测方法

鉴于仅依赖光谱特征或纹理特征的传统溢油检测算法的信息检测精度较低的问题,本文提出了一种新的光学遥感数据的谱纹海面溢油检测方法。谱是光学遥感数据的油膜敏感波段图像,纹是利用灰度共生矩阵计算获得的图像纹理特征,将这些特征相结合,引入支持向量机方法（Support Vector Machine,SVM）,建立谱纹海面溢油检测模型。本文以2006年渤海溢油事故为例,利用中等分辨率成像光谱仪MODIS的光学遥感数据对溢油进行检测,MODIS的第2波段为油膜敏感波段,所以,第2波段图像即为选取的谱特征,经过对各个纹理特征的分析得到,均值、对比和相关3个特征量可作为溢油提取的纹理特征。检测结果的总体精度达91.23%。试验结果表明,将MODIS图像的光谱特征和纹理特征相结合,可有效地对渤海海洋油膜信息进行检测,并具有很强的抑制噪声能力。     

多源SAR遥感影像海上溢油业务化监测系统研究

随着海上石油运输业和海洋石油工业的迅速发展,海上溢油事故频繁发生,造成了巨大的生态和经济上的损失,因此,实时监测溢油信息对灾害防控具有重要意义。本文基于多源SAR影像数据,开展了溢油遥感监测研究,构建了基于GIS的海洋溢油业务化监测系统。系统基于GDAL对原始数据进行解析,实现影像输入和几何校正等处理;在此基础上,封装多尺度图像分割算法和灰度对比度特征提取算法,对SAR影像数据进行分块、分割、溢油识别、合并及参数赋值等自动化处理,实现溢油信息提取的一键化处理;面向溢油监测应用需求,制作各类标准化产品,自动添加制图整饰要素、影像参数、溢油面积和溢油源等各类信息,并实时生成专题快报。     

溢油污染对湛江生态和经济的影响与对策

结合湛江市的海洋产业结构及港口概况，对湛江港溢油污染状况进行了分析。并从可持续发展的角度，分析了溢油污染给湛江的生态和经济发展带来的影响，提出了相应的对策和建议，为湛江溢油的防治工作提供了一定的参考。     

基于高斯曲线拟合-FFT方法的南海风场反演

海面风场是海洋学的基本参量,获取海面风场对了解海洋的物理过程以及海洋与大气之间的相互作用至关重要。宽阔的海域面积及复杂的海面状况通常使南海海面上的风场信息很难被及时获取。ENVISAT ASAR是一种全天候全天时监测海面的微波雷达传感器,可实时获取海面风场数据。本文基于已有ASAR数据对南海海面风场进行反演实验,首先将结合高斯曲线拟合的FFT风向反演方法应用于南海风向反演,并参考Cross-Calibrated Multi-Platform （CCMP）风场数据去除180o方向模糊获得海面风向。然后,将高斯曲线拟合-FFT风向与传统的峰值-FFT风向进行对比,最后将准确率较高的高斯曲线拟合-FFT风向分别输入CMOD4模型和CMOD5模型获得海面风速大小。实验结果与CCMP参考数据的比较结果表明,在风条纹不明显的情况下,利用结合高斯曲线的FFT风向反演方法和CMOD4模型风速反演方法可有效地进行南海海面风场反演。该成果对利用SAR数据实时获取南海大面积海面风场信息,尤其是观测点缺乏海域的风场信息,具有重要的指导意义。     

利用GNSS反射信号监测海面高度变化——基于法国BRST站2019～2021年数据

GNSS反射测量(GNSS-R)技术凭借其数据来源广泛、低成本、高时空分辨率等优势,在地表与海洋环境监测等方面展现巨大潜力,已成为海面高度(SSH)反演的重要技术途径。现有研究大多聚焦于3～6个月内的短期GPS潮位反演,难以反映海面高度的季节性变化及年际特征,且在动态海面改正时仅考虑了垂向速度的影响,忽视了海面波动的垂向加速度,导致低潮位与高潮位的反演精度较差。基于此,以法国某一岸基跟踪站——BRST站为例,利用其连续3年的BDS/GPS/GLONASS/Galileo四系统反射信号,通过Lomb-Scargle谱分析和二阶动态潮位改正模型,采取稳健回归策略反演海面高度,并将最终结果与验潮站观测值进行对比,分析潮位变化趋势。结果表明：GNSS-R技术反演结果与验潮站观测值具有较好的一致性,反演精度有逐年提升的趋势,均方根误差(RMSE)为7.57 cm,相关系数为0.935;海面高度的季节性变化特征明显,秋、冬季平均海面高度偏高,夏季平均海面高度偏低,且海面高度的季节性变化与温度的季节性变化存在着相反的趋势;M2、S2、K1、O1、N2、K2、P1、Q1、M4等9个分潮的振幅差为0.0...     

利用ICESat/GLAS数据获取北极海冰出水高度的研究

利用ICESat激光测高卫星数据获取2003-10～2008-03北冰洋秋季与冬季海冰出水高度,结果与国外相关研究基本一致。出水高度数据的拟合结果表明,北极海冰出水高度以每年约2.3 cm的速度递减,该速度比此前的相关研究结果更快。在不同作者利用ICESat数据计算的北极海冰出水高度的对比中,不同方法得到的结果之间存在明显的系统误差。对引起系统误差的原因进行深入分析表明,高程滤波的窗口长度、确定海面高的范围以及海面观测值的选取方式都会使出水高度的计算产生cm级的误差。     

i4OilSpill,an operational marine oil spill forecasting model for Bohai Sea

Oil spill models can effectively simulate the trajectories and fate of oil slicks, which is an essential element in contingency planning and effective response strategies prepared for oil spill accidents. However, when applied to offshore areas such as the Bohai Sea, the trajectories and fate of oil slicks would be affected by time-varying factors in a regional scale, which are assumed to be constant in most of the present models. In fact, these factors in offshore regions show much more variation over time than in the deep sea, due to offshore bathymetric and climatic characteristics. In this paper, the challenge of parameterizing these offshore factors is tackled. The remote sensing data of the region are used to analyze the modification of wind-induced drift factors, and a well-suited solution is established in parameter correction mechanism for oil spill models. The novelty of the algorithm is the self-adaptive modification mechanism of the drift factors derived from the remote sensing data for the targeted sea region, in respect to empirical constants in the present models. Considering this situation, a new regional oil spill model (i4OilSpill) for the Bohai Sea is developed, which can simulate oil transformation and fate processes by Eulerian-Lagrangian methodology. The forecasting accuracy of the proposed model is proven by the validation results in the comparison between model simulation and subsequent satellite observations on the Penglai 19-3 oil spill accident. The performance of the model parameter correction mechanism is evaluated by comparing with the real spilled oil position extracted from ASAR images.     

The drift velocity of oil film on the sea

To make surface seawater flow, the shear stress of the wind blowing on the sea must overcome the work of cohesion of seawaterW _c. Oil film on the sea will drift along the wind direction so long as the shear stress of the wind overcomes the work of adhesion between the water and the oilW _a or the work of cohesion of oil W_t,o. Experiments bear out the theory that surface tension of seawater is more than twice that of oils generally, so that the wind influenced drift velocity of the oil film is over two times that of the wind-driven surface current. The wind factor for surface current in Jiaozhou Bay is 0.025, while those for the drift velocities of O-diesel oil film and the used light crude oil film are 0.070 and 0.052 respectively. Generally the primary factors influencing the movement velocity of oil film on the sea are current, wind, and the physicochemical properties of the oil. The drift velocity of oil film is determined from analysis of the work of adhesion between seawater and oil. Experiments and actual observations agree with the theoretical analysis. Contribution No. 1831 from the Institute of Oceanology, Academia Sinica     

Development of an oil spill forecast system for offshore China

An oil spill forecast system for of fshore China was developed based on Visual C++. The oil spill forecast system includes an ocean environmental forecast model and an oil spill model. The ocean environmental forecast model was designed to include timesaving methods, and comprised a parametrical wind wave forecast model and a sea surface current forecast model. The oil spill model was based on the "particle method" and fulfi lls the prediction of oil particle behavior by considering the drifting, evaporation and emulsifi cation processes. A specifi c database was embedded into the oil spill forecast system, which contained fundamental information, such as the properties of oil, reserve of emergency equipment and distribution of marine petroleum platform. The oil spill forecast system was successfully applied as part of an oil spill emergency exercise, and provides an operational service in the Research and Development Center for Off shore Oil Safety and Environmental Technology.     

Chaos particle swarm optimization combined with circular median filtering for geophysical parameters retrieval from Windsat

This paper established a geophysical retrieval algorithm for sea surface wind vector, sea surface temperature, columnar atmospheric water vapor, and columnar cloud liquid water from WindSat, using the measured brightness temperatures and a matchup database. To retrieve the wind vector, a chaotic particle swarm approach was used to determine a set of possible wind vector solutions which minimize the difference between the forward model and the WindSat observations. An adjusted circular median filtering function was adopted to remove wind direction ambiguity. The validation of the wind speed, wind direction, sea surface temperature, columnar atmospheric water vapor, and columnar liquid cloud water indicates that this algorithm is feasible and reasonable and can be used to retrieve these atmospheric and oceanic parameters. Compared with moored buoy data, the RMS errors for wind speed and sea surface temperature were 0.92 m s~(-1) and 0.88℃, respectively. The RMS errors for columnar atmospheric water vapor and columnar liquid cloud water were 0.62 mm and 0.01 mm, respectively, compared with F17 SSMIS results. In addition, monthly average results indicated that these parameters are in good agreement with AMSR-E results. Wind direction retrieval was studied under various wind speed conditions and validated by comparing to the Quik SCAT measurements, and the RMS error was 13.3?. This paper offers a new approach to the study of ocean wind vector retrieval using a polarimetric microwave radiometer.     

Retrieval algorithm of sea surface wind vectors for WindSat based on a simple forward model

WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this paper, a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat. The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model. Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation, by which a group of ambiguous wind directions was obtained. A median filter was then used to remove ambiguity of wind direction. Evaluated with sea surface wind speed and direction data from the U.S. National Data Buoy Center (NDBC), root mean square errors are 1.2 m/s and 30° for retrieved wind speed and wind direction, respectively. The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications, without reducing accuracy.     

On spatiotemporal characteristics of sea fog occurrence over the Northern Atlantic from 1909 to 2008

In this paper, the International Comprehensive Ocean and Atmosphere Data Set(ICOADS) is utilized to investigate the horizontal distribution of sea fog occurrence frequency over the Northern Atlantic as well as the meteorological and oceanic conditions for sea fog formation. Sea fog over the Northern Atlantic mainly occurs over middle and high latitudes. Sea fog occurrence frequency over the western region of the Northern Atlantic is higher than that over the eastern region. The season for sea fog occurrence over the Northern Atlantic is generally from April to August. When sea fogs occur, the prevailing wind direction in the study area is from southerly to southwesterly and the favorable wind speed is around 8 m s-1. It is most favorable for the formation of sea fogs when sea surface temperature(SST) is 5℃ to 15℃. When SST is higher than 25℃, it is difficult for the air to get saturated, and there is almost no report of sea fog. When sea fogs form, the difference between sea surface temperature and air temperature is mainly-1 to 3℃, and the difference of 0℃ to 2℃ is the most favorable conditions for fog formation. There are two types of sea fogs prevailing in this region: advection cooling fog and advection evaporating fog.     

Abundance quantification by independent component analysis of hyperspectral imagery for oil spill coverage calculation

The estimation of oil spill coverage is an important part of monitoring of oil spills at sea.The spatial resolution of images collected by airborne hyper-spectral remote sensing limits both the detection of oil spills and the accuracy of estimates of their size.We consider at-sea oil spills with zonal distribution in this paper and improve the traditional independent component analysis algorithm.For each independent component we added two constraint conditions:non-negativity and constant sum.We use priority weighting by higher-order statistics,and then the spectral angle match method to overcome the order nondeterminacy.By these steps,endmembers can be extracted and abundance quantified simultaneously.To examine the coverage of a real oil spill and correct our estimate,a simulation experiment and a real experiment were designed using the algorithm described above.The result indicated that,for the simulation data,the abundance estimation error is 2.52% and minimum root mean square error of the reconstructed image is 0.030 6.We estimated the oil spill rate and area based on eight hyper-spectral remote sensing images collected by an airborne survey of Shandong Changdao in 2011.The total oil spill area was 0.224 km~2,and the oil spill rate was 22.89%.The method we demonstrate in this paper can be used for the automatic monitoring of oil spill coverage rates.It also allows the accurate estimation of the oil spill area.