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。     

Comparison of two wind algorithms of ENVISAT ASAR at high wind

Two wind algorithms of ENVISAT advanced synthetic aperture radar (ASAR), i. e. CMOD4 model from the European Space Agency (ESA) and CMOD IFR2 model from Quilfen et al., are compared in this paper. The wind direction is estimated from orientation of low and linear signatures in the ASAR imagery. The wind direction has inherently a 180° ambiguity since only a single ASAR image is used. The 180° ambiguity is eliminated by using the buoy data from the NOAA (National Oceanic and Atmospheric Administration) buoys moored in the Pacific. Wind speed is obtained with the two wind algorithms using both estimated wind direction and normalized radar cross section (NRCS). The retrieved wind results agree well with the data from Quikscat. The root mean square error (RMSE) of wind direction is 2.80? The RMSEs of wind speed from CMOD4 model and CMOD_IFR2 model are 1.09 m/s and 0.60 m/s, respectively. The results indicate that the CMOD_IFR2 model is slight better than CMOD4 model at high wind.     

Semi-Empirical Algorithm for Wind Speed Retrieval from Gaofen-3 Quad-Polarization Strip Mode SAR Data

Synthetic aperture radar(SAR)is a suitable tool to obtain reliable wind retrievals with high spatial resolution.The geophysical model function(GMF),which is widely employed for wind speed retrieval from SAR data,describes the relationship between the SAR normalized radar cross-section(NRCS)at the copolarization channel(vertical-vertical and horizontal-horizontal)and a wind vector.SAR-measured NRCS at cross-polarization channels(horizontal-vertical and vertical-horizontal)correlates with wind speed.In this study,a semi-empirical algorithm is presented to retrieve wind speed from the noisy Chinese Gaofen-3(GF-3)SAR data with noise-equivalent sigma zero correction using an empirical function.GF-3 SAR can acquire data in a quad-polarization strip mode,which includes cross-polarization channels.The semi-empirical algorithm is tuned using acquisitions collocated with winds from the European Center for Medium-Range Weather Forecasts.In particular,the proposed algorithm includes the dependences of wind speed and incidence angle on cross-polarized NRCS.The accuracy of SAR-derived wind speed is around 2.10ms−1 root mean square error,which is validated against measurements from the Advanced Scatterometer onboard the Metop-A/B and the buoys from the National Data Buoy Center of the National Oceanic and Atmospheric Administration.The results obtained by the proposed algorithm considering the incidence angle in a GMF are relatively more accurate than those achieved by other algorithms.This work provides an alternative method to generate operational wind products for GF-3 SAR without relying on ancillary data for wind direction.     

Evaluation of Wind Retrieval from Co-Polarization Gaofen-3 SAR Imagery Around China Seas

Gaofen-3(GF-3) is the first Chinese space-borne satellite to carry the C-band multi-polarization synthetic aperture radar(SAR). Marine applications, i.e., winds and waves retrieved from GF-3 SAR images, have been operational since January 2017. In this study, we have collected more than 1000 quad-polarization(vertical-vertical(VV); horizontal-horizontal(HH); vertical-horizontal(VH); horizontal-vertical(HV)) GF-3 SAR images, which were acquired around the China Seas from September 2016 to September 2017. Wind streaks were visible in these images in co-polarization(VV and HH) channel. Geophysical model functions(GMFs), including the CMOD5N together with polarization ratio(PR) model and C-SARMOD, were used to retrieve winds from the collected co-polarization GF-3 SAR images. Wind directions were directly obtained from GF-3 SAR images. Then, the SAR-derived wind speeds were compared with the measurements at a 0.25? grid from the Advanced Scatterometer on board the Metop-A/B and microwave radiometer WindSAT. Based on the analysis, empirical corrections are proposed to improve the performance of the two GMFs. Results of this study show that the standard deviation of wind speed is 1.63 m s^-1 with a 0.19 m s^-1 bias and 1.71 m s^-1 with a 0.26 m s^-1 bias for VV-and HH-polarization GF-3 SAR, respectively. Our work not only systematically evaluates wind retrieval by using the two advanced GMFs and PR models but also proposes empirical corrections to improve the accuracy of wind retrievals from GF-3 SAR images around the China Seas and thus enhance the accuracy of near real-time operational SAR-derived wind products.     

Deriving Changjiang coastal zone wind from C-band SAR and its application to salinity simulation

Wind plays an important role in hydrodynamic processes such as the expansion of Changjiang （Yangtze） River Diluted Water （CDW）, and shelf circulation in the Changjiang estuary. Thus, it is essential to include wind in the numerical simulation of these phenomena. Synthetic aperture radar （SAR） with high resolution and wide spatial coverage is valuable for measuring spatially inhomogeneous ocean surface wind fields. We have collected 87 ERS-2 SAR images with wind-induced streaks that cover the Cbangjiang coastal area, to verify and improve the validity of wind direction retrieval using the 2D fast Fourier transform method. We then used these wind directions as inputs to derive SAR wind speeds using the C-band model. To demonstrate the applicability of the algorithms, we validated the SAR-retrieved wind fields using QuikSCAT measurements and the atmospheric Weather Research Forecasting model. In general, we found good agreement between the datasets, indicating the reliability and applicability of SAR- retrieved algorithms under different atmospheric conditions. We investigated the main error sources of this process, and conducted sensitivity analyses to estimate the wind speed errors caused by the effect of speckle, uncertainties in wind direction, and inaccuracies in the normalized radar cross section. Finally, we used the SAR-retrieved wind fields to simulate the salinity distribution off the Changjiang estuary. The findings of this study will be valuable for wind resource assessment and the development of future numerical ocean models based on SAR images.     

Parameterized first-guess spectrum method for retrieving directional spectrum of swell-dominated waves and huge waves from SAR images

A method to retrieve ocean wave spectra from SAR images, named Parameterized First-guess Spectrum Method (PFSM), was proposed after interpretation of the theory to ocean wave imaging and analysis of the drawbacks of the retrieving model generally used. In this method, with additional information and satellite parameters, the separating wave-number is first calculated to determine the maximum wave-number beyond which the linear relation can be used. The separating wave-number can be calculated using the additional information on wind velocity and parameters of SAR satellite. And then the SAR spectrum can be divided into SAR spectrum of wind wave and of swell according to the result of separating wave-number. The portion of SAR spectrum generated by wind wave, is used to search for the most suitable parameters of ocean wind wave spectrum, including propagation direction of ocean wave, phase speed of dominating wave and the angle spreading coefficient. The swell spectrum is acquired by directly inversing the linear relation of ocean wave spectrum to SAR spectrum given the portion of SAR spectrum generated by swell. We used the proposed method to retrieve the ocean wave spectrum from ERS-SAR data from the South China Sea and compared the result with altimeter data. The agreement indicates that the PFSM is reliable.     

Retrieval of Significant Wave Height Under Typhoon Conditions from Gaofen-3 SAR Imagery

The objective of this paper is to propose an empirical method to inverse significant wave height(SWH)under typhoon conditions from collected dual-polarization Gaofen(GF)-3 synthetic aperture radar(SAR)imagery.The typhoon scenes were cap-tured from narrow scan(NSC)and wide scan(WSC)images,and collocated with European Center for Medium-Range Weather Fore-casts reanalysis data of(ECMWF).To improve the quality of GF-3 SAR images,the recalibration over rainforest and de-scalloping were carried out.To establish the empirical relationship between SAR-derived parameters and collocated SWH,the sensitivity analysis of typical parameters about the normalized radar cross section(Nrcs)and imagery variance(Cvar)were performed to both VV and VH polarized images.Four scenes from GF-3 SAR imagery under typhoon conditions were used for training the model by the multivari-ate least square regression,and one scene was used for preliminary validation.It was found that the joint retrieval model based on VV and VH polarized SAR imagery performed better than any single polarized model.These results,verified by using ECMWF data,revealed the soundness of this approach,with a correlation of 0.95,bias of 0 m,RMSE of 0.44 and SI of 0.01 when VV polarization and VH polarization data were both used.     

A new algorithm for sea-surface wind-speed retrieval based on the L-band radiometer onboard Aquarius

Aquarius is the second satellite mission to focus on the remote sensing of sea-surface salinity from space and it has mapped global sea-surface salinity for nearly 3 years since its launch in 2011. However,benefiting from the high atmospheric transparency and moderate sensitivity to wind speed of the L-band brightness temperature(TB),the Aquarius L-band radiometer can actually provide a new technique for the remote sensing of wind speed. In this article,the sea-surface wind speeds derived from TBs measured by Aquarius' L-band radiometer are presented,the algorithm for which is developed and validated using multisource wind speed data,including Wind Sat microwave radiometer and National Data Buoy Center buoy data,and the Hurricane Research Division of the Atlantic Oceanographic and Meteorological Laboratory wind field product. The error analysis indicates that the performance of retrieval algorithm is good. The RMSE of the Aquarius wind-speed algorithm is about 1 and 1.5 m/s for global oceans and areas of tropical hurricanes,respectively. Consequently,the applicability of using the Aquarius L-band radiometer as a near all-weather wind-speed measuring method is verified.     

HY-2散射计风速降雨影响的神经网络校正

海洋二号搭载的笔形圆锥扫描微波散射计(HY2-scat)是国内第一个业务化运行的,可提供大量实时海面风场数据的微波传感器。由于Ku波段散射计测风原理和微波传输特性,受到降雨影响的散射计反演风场数据准确度降低。降雨导致的微波传播路径衰减,雨滴对微波直接后向散射导致的回波能量增加和雨滴对海表面毛细波的干扰等综合效应,使得降雨条件下散射计测风风速计算值偏高,风向计算值偏差较大。针对散射计反演风速受降雨影响的特点引入神经网络模型,使用准确度较高的NWP数值预报模式风场数据作为参考,对受降雨影响的HY-2散射计反演L2B级标准风场数据产品进行校正,改进HY-2散射计反演风矢量在降雨条件下的准确度。与受降雨影响的散射计反演风场风速偏差相比较,经过神经网络校正后的风速偏差减小,说明该方法适用于改善受降雨影响的HY-2散射计测风风速精度。     

Rapid detection to long ship wake in synthetic aperture radar satellite imagery

The maritime administrative department employs synthetic aperture radar(SAR)satellite remote sensing technology to obtain evidence of illegal discharge of ships.If the ship is discharged during navigation,it forms a long dark wake on the SAR image due to the suppression of the Bragg wave by the oil film.This study investigates key techniques for rapid detection of long ship wakes,thereby providing law enforcement agencies with candidate ships for possible discharge.This paper presents a rapid long ship wake detection method that uses satellite imaging parameters and the axial direction of the ship in images to determine the potential detection area of the wake.Then,the threshold of long ship wake detection is determined using statistical analysis,the area is binarized,and isolated points are removed using a morphological filter operator.The method was tested with ENVISAT Synthetic Aperture Radar and GF-3 SAR data,and results showed that the method was effective,and the overall accuracy of the decision reaches 71%.We present two innovations;one is a method that draws a Doppler shift curve,and uses the SAR imaging parameters to determine the detection area of the long wake to achieve rapid detection and reduce the image detection area.The other is where a classical linear fitting method is used to quickly and accurately determine whether the detected dark area is a long ship wake and realizes the twisted long ship wake detection caused by the sea surface flow field,which is otherwise difficult to detect by the traditional Radon and Hough transform methods.This method has good suppression performance for the dark spot false alarm formed by low speed wind region or upward flow.The method is developed for maritime ship monitoring system and will promote the operational application of maritime ship monitoring system.     

A joint method to retrieve directional ocean wave spectra from SAR and wave spectrometer data

This paper proposes a joint method to simultaneously retrieve wave spectra at dif ferent scales from spaceborne Synthetic Aperture Radar(SAR) and wave spectrometer data. The method combines the output from the two dif ferent sensors to overcome retrieval limitations that occur in some sea states. The wave spectrometer sensitivity coeffi cient is estimated using an ef fective signifi cant wave height(SWH), which is an average of SAR-derived and wave spectrometer-derived SWH. This averaging extends the area of the sea surface sampled by the nadir beam of the wave spectrometer to improve the accuracy of the estimated sensitivity coeffi cient in inhomogeneous sea states. Wave spectra are then retrieved from SAR data using wave spectrometer-derived spectra as fi rst guess spectra to complement the short waves lost in SAR data retrieval. In addition, the problem of 180° ambiguity in retrieved spectra is overcome using SAR imaginary cross spectra. Simulated data were used to validate the joint method. The simulations demonstrated that retrieved wave parameters, including SWH, peak wave length(PWL), and peak wave direction(PWD), agree well with reference parameters. Collocated data from ENVISAT advanced SAR(ASAR), the airborne wave spectrometer STORM, the PHAROS buoy, and the European Centre for Medium-Range Weather Forecasting(ECMWF) were then used to verify the proposed method. Wave parameters retrieved from STORM and two ASAR images were compared to buoy and ECMWF wave data. Most of the retrieved parameters were comparable to reference parameters. The results of this study show that the proposed joint retrieval method could be a valuable complement to traditional methods used to retrieve directional ocean wave spectra, particularly in inhomogeneous sea states.     

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。     

基于可视范围的图像检索方法

图像是视觉所及环境的自然再现,具有表达直观、内容丰富的特性,其已成为GIS空间数据采集与应用中一种重要的可视数据源。随着硬件终端的高速发展,集成的传感器愈加丰富,多源传感器信息融合已成为移动GIS数据釆集的发展趋势。针对移动终端获取方位角偏差问题,本文重点阐述了基于移动终端的重力传感器与磁力传感器获取镜头拍摄朝向的算法,并基于EXIF图像格式实现了图像元数据、定位信息、方位信息一体化采集生成可定位图像。针对现有可定位图像以点代面建模方式的不足,本文以镜头视野范围AOV（Angle of View）模型为基础,提出了以图像元数据、位置信息以及方位信息构建图像可视域的方法,并采用多级网格方式对图像可视域面状特征建立空间索引,实现基于可视域的图像检索。在此基础上,针对福建省野外遥感核查采集的8022幅可定位图像,采用点建模及可视域建模2种方式建立检索图像集。从检索速度、检索结果2个方面进行对比分析,表明基于可视域图像检索方法不仅能检索出拍摄位置在检索区域内的图像,还可检索出拍摄位置在检索区域外但实际拍摄场景在检索范围内的图像。同时,通过多级空间网格索引可提升6.22-8.64倍检索速度。     

两种海浪模式对一次台风浪过程的模拟分析

以CCMP（Cross—Calibrated,Multi—Platfoml）风场为驱动场,分别驱动目前国际先进的第3代海浪模式ww3（WAVEWATCH—III）、SWAN（Simulating WAves Nearshore）,对2010年9月发生在东中国海的台风“圆规”所致的台风浪进行数值模拟,就台风浪的特征进行分析,并对比分析两个海浪模式的模拟效果。结果表明：1）以CCMP风场分别驱动WW3、SWAN海浪模式,可以较好地模拟发生在东中国海的台风浪,风向与波向保持了大体一致,波高与风速的分布特征保持了很好的一致性;2）综合相关系数、偏差、均方根误差、平均绝对误差来看,两个模式模拟的有效波高（SWH—Significant Wdve Height）都具有较高精度,SWAN模拟的SWH略低于观测值,WW3模拟的SWH与观测值更为接近;3）台风浪可给琉球群岛海域带来5m左右的大浪,台风浪进入东海后,波高、风速都有一定程度的增加,当台风沿西北路径穿越朝鲜半岛时,受到半岛地形的巨大影响,风速和波高都明显降低。     

The Influence of wave state and sea spray on drag coefficient from low to high wind speeds

Ocean waves alter the roughness of sea surface, and sea spray droplets redistribute the momentum flux at the air-sea interface. Hence, both wave state and sea spray influence sea surface drag coefficient. Based on the new sea spray generation function which depends on sea surface wave, a wave-dependent sea spray stress is obtained. According to the relationship between sea spray stress and the total wind stress on the sea surface, a new formula of drag coefficient at high wind speed is acquired. With the analysis of the new drag coefficient, it is shown that the drag coefficient reduces at high wind speed, indicating that the sea spray droplets can limit the increase of drag coefficient. However, the value of high wind speed corresponding to the initial reduced drag coefficient is not fixed, and it depends on the wave state, which means the influence of wave cannot be ignored. Comparisons between the theoretical and measured sea surface drag coefficients in field and laboratory show that under different wave ages, the theoretical result of drag coefficient could include the measured data, and it means that the new drag coefficient can be used properly from low to high wind speeds under any wave state condition.     

A physics-based dual-frequency approach for altimeter wind speed retrieval

The altimeter normalized radar cross section(NRCS) has been used to retrieve the sea surface wind speed for decades, and more than a dozen of wind speed retrieval algorithms have been proposed. Despite the continuing efforts to improve the wind speed measurements, a bias dependence on wave state persists in all wind algorithms. On the basis of recent evidence that short waves are essentially modulated by local winds and much less affected by wave state, we proposed a physics-based approach to retrieve the wind speed from the dual-frequency difference in terms of the mean square slope of short waves. A collocated dataset of coincident altimeter/buoy measurements were used to develop and validate the approach. Validation against buoy measurements indicates that the approach is almost unbiased and has an overall root mean square error of 1.24 m s-1, which is 5.3% lower than the single-parameter algorithm in operational use(Witter and Chelton, 1991) and 2.4% lower than another dual-frequency approach(Chen et al., 2002). Furthermore, the results indicate that the new approach significantly improves the wave-dependent bias compared to the single-parameter algorithm. The capacity of altimeter to retrieve sea surface wind speed appears to be limited for the case of winds below 3 m s-1. The validity of the approach at high winds needs to be further examined in the future study.     

一种由粗到精的光学与SAR遥感图像配准算法

由于光学遥感图像和SAR图像具有明显的非线性强度差异,且SAR图像存在斑点噪声,使得其配准存在较大难度。为此,本文结合基于特征和基于区域图像配准方法的优点,并组合为混合模型,提出一种由粗到精的自动配准算法。以光学遥感图像和SAR图像分别为参考图像和待配准图像,先以基于特征点的SAR-SIFT完成粗配准,再以基于区域的ROEWA-HOG完成精配准。① 采用SAR-SIFT算法进行特征点检测和特征匹配来计算图像的仿射变换模型,以消除参考图像和待配准图像之间明显的旋转、尺度和平移差异,至此完成图像粗配准;② 在此基础上利用分块Harris角点检测在参考图像上获得特征点,并根据特征点确定待配准图像上的同名点搜索区域;③ 计算图像的ROEWA梯度,构造以特征点为中心的模板区域内的HOG特征向量,以SSD作为相似性测度搜索待配准图像上的同名点,完成高精度的图像配准;④ 进行图像配准实验,对配准结果进行目视检查和精度评估。经过多组光学与SAR图像配准实验,验证本文算法能够结合基于特征和基于区域的图像配准方法的优点,较好地抵抗光学与SAR图像之间的非线性强度、旋转、尺度、平移差异和SAR图像的噪声影响,并逐步提高配准精度,最终配准精度达到1个像素左右,实现了光学与SAR图像的高精度自动配准,能够满足光学与SAR图像后续综合应用。     

Wave Height Estimation from SAR Imagery

This paper presents a method developed for estimating wave height from synthetic aperture radar (SAR) imagery without prior assumption of noise distribution. It is based on two-dimenslonal ocean wave spectra retrieved from fully calibrated SAR images. Wen‘s spectrum was used as first-guess wave spectrum in the retrieval process. Comparison of the estimated wave height obtained by this method from two ERS-1 SAR subimages dated 23 July 1994 with in-situ measurements showed that the method works well.     

SAR image coregistration using fringe definition detection

In order to overcome the limitation of cross correlation coregistration method for Synthetic Aperture Radar(SAR) interferometric pairs with low coherence,a new image coregistration algorithm based on Fringe Definition Detection(FDD) is presented in this paper.The Fourier transformation was utilized to obtain spectrum characteristics of interferometric fringes.The ratio between spectrum mean and peak was proposed as the evaluation index for identifying homologous pixels from interferometric images.The satellites ERS-1/2 C-band SAR acquisitions covering the Yangtze River plain delta,eastern China and ALOS/PALSAR L-band images over the Longmen Shan mountainous area,southwestern China were respectively employed in the experiment to validate the proposed coregistration method.The testing results suggested that the derived Digital Elevation Model(DEM) from FDD method had good agreement with that from the cross correlation method as well as the reference DEM at high coherence area.However,The FDD method achieved a totally improved topographic mapping accuracy by 24 percent in comparison to the cross correlation method.The FDD method also showed better robustness and achieved relatively higher performance for SAR image coregistration in mountainous areas with low coherence.     

Detection of ocean internal waves based on Faster R-CNN in SAR images

Ocean internal waves appear as irregular bright and dark stripes on synthetic aperture radar(SAR) remote sensing images. Ocean internal waves detection in SAR images consequently constituted a difficult and popular research topic. In this paper, ocean internal waves are detected in SAR images by employing the faster regions with convolutional neural network features(Faster R-CNN) framework; for this purpose, 888 internal wave samples are utilized to train the convolutional network and identify internal waves. The experimental results demonstrate a 94.78% recognition rate for internal waves, and the average detection speed is 0.22 s/image. In addition, the detection results of internal wave samples under dif ferent conditions are analyzed. This paper lays a foundation for detecting ocean internal waves using convolutional neural networks.