“HY—1A”卫星海洋水色扫描仪像旋转图像校正处理

"海洋1"号("HY—1A")卫星海洋水色扫描仪由于K镜的失效而出现了像旋现象,对获得的卫星图像质量产生直接影响。基于光学反射矢量理论,分析了多元探测器并行扫描方式下45°扫描镜加K镜的扫描轨迹特征,利用图像之间的相关性,首先自动寻找K镜停转的准确角度,然后根据K镜的停转角度与多元并扫理论对像旋图像进行了校正处理,获得了可用的校正图像。     

“HY-1”卫星COCTS水色遥感器精确瑞利散射算法研究

“HY-1”卫星是我国自主研制发射的第一颗海洋卫星,水色遥感器COCTS具有8个可见光(412,443,490,520,565,670 nm)、近红外通道(750,865 nm)以及2个热红外通道(10.30~11.40,11.40~12.50μm).COCTS遥感器上采用了多元并扫技术用以提高遥感器的信噪比和探测灵敏度,但是由于并扫会带来像元旋转的问题,于是我国“HY-1”卫星水色遥感器COCTS上采用了K镜消旋技术,而K镜消旋技术带来的一个消极影响是偏振响应很大,通过发射前实验室监测结果发现其值达到了8%.     

HY-1卫星水色扫描仪的辐射定标与真实性检验

主要阐述HY－1卫星10波段水色扫描仪辐射定标与真实性检验的基本原理和关键参数的测量方法，简要介绍已开展的工作，并对2类水体测量方法提出几点建议。     

HY-1C卫星运行轨道的计算研究

轨道数据是卫星资料处理过程涉及的重要参数,高质量HY-1 C卫星产品离不开准确的轨道计算.本文从两行报(Two-Line Orbital Element,TLE)中提取数据,使用STK(Satellite Tool Kit)软件准确模拟出卫星轨道并输出星历表,通过比较两种计算HY-1 C卫星轨道算法的精度,评估摄动因素...     

我国第一颗海洋卫星HY-1A的应用潜力研究

继美国1997年发射专用的海洋水色卫星"海星"号(SeaStar)后,2002年5月15日我国成功地发射了专门海洋水色卫星HY-1A.首先概要地介绍了HY-1A卫星的性能和特点;其次运用辐射模拟仿真得到的综合信噪比这一概念从理论上评价了HY-1A卫星资料的利用率,同时利用接收到的HY-1A卫星资料,通过与美国海洋水色卫星资料的比较,评价了测量精度;最后从海洋水色、水温等海洋要素的反演结果讨论了HY-1A卫星资料的应用潜力.研究结果表明,我国的第一颗海洋卫星将在海洋环境监测、海洋资源的管理、保护和开发以及国家权益等方面将有很大的应用潜力,并提出了改进建议.     

Study on application potentiality of the first China''s ocean satellite HY-1A

INTRODUCTIONSincethe 1 970s,withtherapiddevelopmentofearthobservationbymeansofspacehightechnology ,themarineopticalremotesensingshowsmoreandmorelatentcapabilitydaybyday .TheUSAlaunchedthefirstoceancolorsatelliteNimbus - 7,withthepayloadofcoastzonecolorscanner (CZCS)in 1 978andoperateduntil 1 986 .TheexcellentimagesofCZCSwerefirstappliedtothefindingofthetemporalandspatialdistributionofoceancolor (chloro phyll,suspendedmaterialandyellowsubstance)oftheearthbyhumanity .Sincethen ,themari…     

The HY-1 satellite and ground system in China

INTRODUCTIONWith the coming of the 21st century, we are faced the problems of the environment, re-sources and population. The ocean is regarded as supplier of resources such as food, minerals,energy and space, and plays an important role in sustainable economic development. At thesame time the ocean has a very important effect on the worldwide environmental changes.     

基于最优特征集的HY-1C卫星海岸带成像仪影像海冰分类方法研究

基于海洋一号C（HY-1C）卫星海岸带成像仪（CZI）遥感影像,提出了一种基于最优特征集的支持向量机海冰分类方法。分别提取CZI影像的光谱特征和纹理特征,采用基于距离可分性的判据进行特征选择,得到最优特征集,以最优特征集作为支持向量机分类器输入,分别对3期辽东湾海域CZI影像开展海冰分类实验和结果分析。结果表明：本文方法得到的海冰分类结果精度优于仅利用光谱特征或纹理特征的海冰分类精度;基于本文方法的3期影像的海冰分类精度均较高,2020年12月19日、2021年1月10日与2021年1月16日的海冰分类总体精度分别为93.67%、91.75%、84.89%,均在80%以上;利用海冰分类结果图估算海冰面积,发现3期辽东湾海冰面积依次增大,最大约为11 998.98 km²。     

HY-2A卫星海面高度数据质量评估

对HY-2A卫星雷达高度计数据进行筛选获取有效的观测点,利用HY-2A卫星第18~23周期数据和同时在轨的Jason-2数据进行交叉点选取,对两颗卫星在交叉点海面高度异常值的差值进行统计与分析,提出了基于交叉点差值统计特征的筛除HY-2A轨道数据方法,评估了HY-2A卫星雷达高度数据质量。结果显示,HY-2A卫星18~23周期阈值筛选去除的点个数占总海洋观测点约12%,HY-2A海面高度异常与Jason-2海面高度异常的标准偏差在7.0 cm,数据精度满足设计精度要求。     

HY-1/COCTS波段信息含量与波段相关性分析--以辽东湾为例

以2003年4月辽东湾的HY-1／COCTS数据为例,采用主成分分析法和相关分析法,从光谱的不同结构、主成分、相关性等方面来揭示COCTS图像的光谱信息。COCTS的10个波段中,9,10两个波段与其他几个波段相比,包含的信息较丰富。在其他的8个波段中,6,7波段的信息较为丰富,6波段对主成分的贡献大。这8个波段与9波段和10波段的相关性为负相关,表明它们间的重叠少。5波段与1波段、7波段与6波段、6波段与2波段的相关性较高,这说明这些数据间的彼此重叠较多,故在进行波段图像的假彩色合成时一般以8,4,3或8,4,1波段的组合为佳。以OIF指数来检查融合方法的可行性。     

Application of the HY-1 satellite to sea ice monitoring and forecasting

The HY-1A satellite is the first oceanic satellite of China. During the winter of 2002-2003, the data of the HY-1A were applied to the sea ice monitoring and forecasting for the Bohai Sea of China for the fhst time. The sea ice retrieval system of the HY-1A has been constructed. It receives 1B data from the satellite, outputs sea ice images and provides digital products of ice concentration, ice thickness and ice edge, which can be used as important information for sea ice monitoring and the initial fields of the numeric sea ice forecast and as one of the reference data for the sea ice forecasting verification. The sea ice retrieval system of the satellite is described, including its processes, methods and parameters. The retrieving results and their application to the sea ice monitoring and forecasting for the Bohai Sea are also discussed.     

Application of the HY-1 satellite to sea ice monitoring and forecasting

The HY-1A satellite is the first oceanic satellite of China. During the winter of 2002～2003, the data of the HY-1A were applied to the sea ice monitoring and forecasting for the Bohai Sea of China for the first time. The sea ice retrieval system of the HY-1A has been constructed. It receives 1B data from the satellite, outputs sea ice images and provides digital products of ice concentration, ice thickness and ice edge, which can be used as important information for sea ice monitoring and the initial fields of the numeric sea ice forecast and as one of the reference data for the sea ice forecasting verification. The sea ice retrieval system of the satellite is described, including its processes, methods and parameters. The retrieving results and their application to the sea ice monitoring and forecasting for the Bohai Sea are also discussed.     

Detection of oil spill based on CBF-CNN using HY-1C CZI multispectral images

Accurate detection of an oil spill is of great significance for rapid response to oil spill accidents. Multispectral images have the advantages of high spatial resolution, short revisit period, and wide imaging width, which is suitable for large-scale oil spill monitoring. However, in wide remote sensing images, the number of oil spill samples is generally far less than that of seawater samples. Moreover, the sea surface state tends to be heterogeneous over a large area, which makes the identification of oil spills more difficult because of various sea conditions and sunglint. To address this problem, we used the F-Score as a measure of the distance between forecast value and true value, proposed the Class-Balanced F loss function (CBF loss function) that comprehensively considers the precision and recall, and rebalances the loss according to the actual sample numbers of various classes. Using the CBF loss function, we constructed convolution neural networks (CBF-CNN) for oil spill detection. Based on the image acquired by the Coastal Zone Imager (CZI) of the Haiyang-1C (HY-1C) satellite in the Andaman Sea (study area 1), we carried out parameter adjustment experiments. In contrast to experiments of different loss functions, the F1-Score of the detection result of oil emulsions is 0.87, which is 0.03–0.07 higher than cross-entropy, hinge, and focal loss functions, and the F1-Score of the detection result of oil slicks is 0.94, which is 0.01–0.09 higher than those three loss functions. In comparison with the experiment of different methods, the F1-Score of CBF-CNN for the detection result of oil emulsions is 0.05–0.12 higher than that of the deep neural networks, supports vector machine and random forests models, and the F1-Score of the detection result of oil slicks is 0.15–0.22 higher than that of the three methods. To verify the applicability of the CBF-CNN model in different observation scenes, we used the image obtained by HY-1C CZI in the Karimata Strait to carry out experiments, which include two studies areas (study area 2 and study area 3). The experimental results show that the F1-Score of CBF-CNN for the detection result of oil emulsions is 0.88, which is 0.16–0.24 higher than that of other methods, and the F1-Score of the detection result of oil slicks is 0.96–0.97, which is 0.06–0.23 higher than that of other methods. Based on all the above experiments, we come to the conclusions that the CBF loss function can restrain the influence of oil spill and seawater sample imbalance on oil spill detection of CNN model thus improving the detection accuracy of oil spills, and our CBF-CNN model is suitable for the detection of oil spills in an area with weak sunglint and can be applied to different scenarios of CZI images.     

“海洋1号”卫星在海冰监测和预报中的应用

“海洋1号A”卫星是我国发射的第一颗海洋卫星.2002~2003年冬季,该卫星首次应用于我国渤海海冰监测和预报.建立了从卫星1B级数据开始的海冰反演系统,提供海冰遥感图像和海冰密集度、冰厚与冰外缘线数值产品,作为渤海海冰监测和海冰数值预报初始场的重要信息来源,以及海冰预报质量检验的参考依据之一.介绍所发展的“海洋1号A”卫星海冰反演系统的流程、算法和反演参数,海冰反演结果,及其在渤海海冰监测和预报中的应用.     

我国“海洋1”号卫星(HY-1)CCD图像数据定量化条带消除研究

条带(striping)对于大量的航天和航空传感器来说是一种普遍存在的现象,任何使用多个探测器进行数据获取的遥感器图像数据中均存在条带.目前消除条带的算法主要是针对光机扫描仪,对于CCD相机工作做得比较少.针对HY-1CCD线阵推扫式多光谱相机的特点,以及发射前辐射定标的结果,对遥感器图像数据中的条带问题进行了预研,提出了一种定量化的消条带算法.该方法根据卫星数据特性求出各探测器间的均衡化曲线以反映探测器之间的差异,并据此来消除条带.实验结果表明该方法能够有效解决CCD相机的条带问题,而且可以保持数据原有的物理意义,并可与在轨辐射校正衔接,保证发射前后定标算法的一致性.     

HY-2A卫星雷达高度计数据的全球统计评价及质量分析

自HY-2A卫星发射以来,针对HY-2A卫星雷达高度计产品的交叉定标、真实性检验及质量评估工作一直在持续开展。本文主要以HY-2A卫星高度计第44周期的IGDR产品数据为例,通过使用全球分布图、二维直方图和每日均值统计的方法完成了与Jason-2IGDR产品的比对验证,同时对主要环境校正参数及地球物理产品的数据质量稳定性进行了分析,结果显示高度计产品数据质量较稳定,此外利用HY-2A卫星升降轨交叉点海面高度差、与Jason-2卫星交叉点海面高度差以及沿轨海平面异常数据分析的方法进行了HY-2A卫星高度计观测系统的性能评估,结果显示,HY-2A卫星海面高度精度约为7.48cm,精度接近Jason-2,能满足海洋应用与科学研究的需要。     

HY-1C/D卫星中国海洋水色水温扫描仪几何定位方法

海洋一号C/D（HY-1C/D）卫星中国海洋水色水温扫描仪（Chinese Ocean Color and Temperature Scanner,COCTS）主要用于探测海洋水色、水温等要素,这些要素需要经过卫星资料处理才能获取,而几何定位是预处理的核心,直接影响这些要素的质量。COCTS具有114°视场角和四元逐点摆扫的特征,据此研究出一套完整的几何定位方法。从0级数据中提取卫星星历,利用插值法从中获取采样时间对应的卫星位置和速度,进而得到轨道（ORB）坐标系到地心旋转（ECR）坐标系的转换矩阵。基于四元逐点摆扫的特征,中心视矢量分别绕X轴、Y轴旋转相应角度,获得扫描行各采样点ORB视矢量,建立视矢量与地球交叉点关系模型,从而对根据波段数据绘制的遥感图像进行地理定位。本文使用插值法替代了传统需要6个轨道根数来计算卫星位置的复杂方法,同时直接计算ORB到ECR的转换矩阵,而不采用传统的两步转换方法。经过多组数据计算及定性定量验证,HY-1C/D COCTS几何定位结果一致;采样像元尺度效应导致从星下点到两侧边缘、从赤道到两极,误差逐渐增大,约在两个像元内。该方法满足一定的定位精度要求,可以用于COCTS的几何定位。     

基于散射计风场数据的台风强度诊断方法——以海洋二号卫星数据为例

本文提出了一种基于散射计风场数据的台风定强方法。该方法定义了台风所在海区的一个圆形区域上的风速平均值来对台风进行定强,并使用海洋二号卫星散射计历史数据对该方法进行了验证。验证结果表明,该台风定强方法可以克服散射计反演台风风速过低的问题。与台风强度监测的历史记录比较的结果显示,在台风强度低于"强台风"这一强度等级时,该方法能够有效估算台风强度。     

气体吸收对“HY-1A”CCD数据处理的影响分析模拟与瑞利散射的吸收修正

卫星传感器接收到的辐射能量不仅受到大气中分子和气溶胶散射的影响,还受到气体分子吸收的影响.对于可见光和近红外波段的水色遥感,吸收气体主要是臭氧、水汽和氧气,因此若传感器的光谱范围包含了这些气体的吸收波段,则应该在数据处理——计算瑞利、气溶胶反射率和透过率时予以考虑.波段光谱宽度为20 nm(两个近红外波段为40nm)的SeaWiFS在数据处理时主要考虑了臭氧和水汽的影响,并在计算气溶胶反射率时对受氧气吸收影响的波段进行了单独修正[1].由于“HY-1A”CCD的四个波段的光谱宽度均超过100 nm,覆盖了三种主要吸收气体的部分吸收线,因此它受到的气体影响会更大.     

HY-1C卫星CZI载荷的黄海绿潮提取研究

海洋一号C（HY-1C）卫星是中国首颗海洋水色业务卫星,其搭载的海岸带成像仪（CZI）在近海海洋环境监测中正发挥越来越重要的作用;随着搭载有相同传感器的HY-1D卫星发射,双星组网观测,可形成3天2次的高频次、大范围对海观测能力,在海洋漂浮藻类、海洋溢油等目标探测方面具备优异的效能。高空间分辨率光学数据中包含了丰富的海洋环境信息,给特定目标的识别提取带来一定干扰。本研究面向HY-1C卫星CZI载荷开展中国近海漂浮藻类识别提取的业务化应用需求,发展基于藻类缩放指数与虚拟基线高度融合的海洋漂浮藻类识别提取算法,算法优选适用于无短波红外波段国产数据的虚拟基线高度指数来增强藻类信号,通过藻类缩放指数滑动窗口运算,有效剔除高空间分辨率光学数据中的复杂干扰信息,实现了基于CZI数据的海洋漂浮藻类高精度提取,且具有较好的计算运行效率。此外,结合准同步高分卫星16 m多光谱数据,开展CZI数据含藻像元的不确定性分析,发现CZI数据反演结果对近海小斑块漂浮藻类存在不可忽视的高估现象。研究还指出,光学数据用于漂浮藻类监测,其不确定性不仅来源于传感器的空间分辨率差异,还与海洋漂浮藻类形态特征的空间分异性有关。明晰海洋漂浮藻类的形态学空间分异特征,将有助于提高光学数据反演结果的精度,并阐明不确定性。