Automatic detection and validity of the sea-ice edge: an application of enhanced-resolution QuikScat/SeaWinds data

Sea-ice edge detection is an essential task at the different national ice services to secure navigation in ice-covered seas. Comparison between the Remund and Long ice mask image from enhanced-resolution QuikScat/SeaWinds (QS) products and the analyzed ice edge from high-resolution RADARSAT synthetic aperture radar has shown that the automatically determined QS ice mask underestimates the Arctic ice extent. QS data was statistically analyzed by colocating the data with ice charts around Greenland and with the National Aeronautics and Space Administration Team's Special Sensor Microwave/Imager (SSM/I) ice concentration algorithm over the whole Arctic region. All variables, i.e., the backscatter in vertical and horizontal polarization, the active polarization ratio (APR) and the daily standard deviation, are sensitive to ice types and are strongly correlated with ice concentration when the relationship is expressed in exponential form. Our study showed that the APR is especially suitable for ice-ocean separation, and a threshold of -0.02 was determined. An ice edge algorithm based on this APR threshold was developed using the other variables with conservative season-dependent thresholds to eliminate additional ocean noise. Also, the history of the ice cover is considered in order to detect single ice fields that are separated from the main Arctic pack ice. Validation with RADARSAT 1 and with the Advanced Very High Resolution Radiometer showed that the new algorithm successfully detects very low ice concentrations of about 10% during the entire year. The validity of the detected ice edge for near-real-time issues is also discussed in relation to the ice motion in the Marginal Ice Zone and the integration time necessary to produce the enhanced-resolution images. The new algorithm improves the automatic global ice edge resolution by a factor of two when compared to SSM/I products and could be used in both model initialization and data assimilation.     

On the utility of SeaWinds/QuikSCAT data for the estimation of the thermodynamic state of first-year sea ice

The thermodynamic state of sea ice is important to accurately and remotely monitor in order to provide improved geophysical variable parameterizations in sea ice thermodynamic models. Operationally, monitoring the thermodynamic state of sea ice can facilitate eased ship navigation routing. SeaWinds/QuikSCAT (QuikSCAT) dual-polarization [i.e., horizontal (HH) and vertical (VV)] active microwave data are available at a sufficiently large spatial scale and high temporal resolution to provide estimates of sea ice thermodynamics. This analysis evaluated the temporal evolution of the backscatter coefficient (/spl sigma//spl deg/) and VV/HH copolarization ratio from QuikSCAT for estimating sea ice thermodynamics. QuikSCAT estimates were compared against RADARSAT-1 synthetic aperture radar (SAR) imagery and the Canadian Ice Service (CIS) prototype operational ice strength algorithm. In situ data from the Collaborative Interdisciplinary Cryospheric Experiment (C-ICE) for 2000, 2001, and 2002 were used as validation. Results indicate that the temporal evolution of /spl sigma//spl deg/ from QuikSCAT is analogous to RADARSAT-1. The QuikSCAT /spl sigma//spl deg/ temporal evolution has the ability to identify winter, snow melt, and ponding thermodynamic states. Moreover, the copolarization VV/HH ratio of QuikSCAT could provide a second estimate of the ponding state in addition to identifying the drainage state that is difficult to detect by single-polarization SAR. QuikSCAT detected thermodynamic states that were found to be in reasonable agreement to that of in situ observations at the C-ICE camp for all years. Operational implications of this analysis suggest QuikSCAT is a more effective and efficient medium for monitoring ice decay compared to RADARSAT-1 and can be utilized to provide more robust modeled ice strength thresholds.     

Validation of sea ice motion from QuikSCAT with those from SSM/I and buoy

Arctic sea ice motion for the period from October 1999 to March 2000 derived from QuikSCAT and ocean buoy observations.Special Sensor Microwave/Imager (SSM/I) data using the wavelet analysis method agrees well with ocean buoy observations. Results from QuikSCAT and SSM/I are compatible when compared with buoy observations and complement each other. Sea ice drift merged from daily results from QuikSCAT, SSM/I, and buoy data gives more complete coverage of sea ice motion. Based on observations of six months of sea ice motion maps, the sea ice motion maps in the Arctic derived from QuikSCAT data appear to have smoother (less noisy) patterns than those from NSCAT, especially in boundary areas, possibly due to constant radar scanning incidence angle. For late summer, QuikSCAT data can provide good sea ice motion information in the Arctic as early as the beginning of September. For early summer, QuikSCAT can provide at least partial sea ice motion information until mid-June. In the Antarctic, a case study shows that sea ice motion derived from QuikSCAT data is consistent with pressure field contours.     

Comparison of NASA Team2 and AES-york ice concentration algorithms against operational ice charts from the Canadian ice service

Ice concentration retrieved from spaceborne passive-microwave observations is a prime input to operational sea-ice-monitoring programs, numerical weather prediction models, and global climate models. Atmospheric Environment Service (AES)-York and the Enhanced National Aeronautics and Space Administration Team (NT2) are two algorithms that calculate ice concentration from SpecialSensor Microwave/Imager observations. This paper furnishes a comparison between ice concentrations (total, thin, and thick types) output from NT2 and AES-York algorithms against the corresponding estimates from the operational analysis of Radarsat images in the Canadian Ice Service (CIS). A new data fusion technique, which incorporates the actual sensor's footprint, was developed to facilitate this study. Results have shown that the NT2 and AES-York algorithms underestimate total ice concentration by 18.35% and 9.66% concentration counts on average, with 16.8% and 15.35% standard deviation, respectively. However, the retrieved concentrations of thin and thick ice are in much more discrepancy with the operational CIS estimates when either one of these two types dominates the viewing area. This is more likely to occur when the total ice concentration approaches 100%. If thin and thick ice types coexist in comparable concentrations, the algorithms' estimates agree with CIS's estimates. In terms of ice concentration retrieval, thin ice is more problematic than thick ice. The concept of using a single tie point to represent a thin ice surface is not realistic and provides the largest error source for retrieval accuracy. While AES-York provides total ice concentration in slightly more agreement with CIS's estimates, NT2 provides better agreement in retrieving thin and thick ice concentrations.     

A numerical model for electromagnetic scattering from sea ice

A numerical model for scattering from sea ice based on the finite difference time domain (FDTD) technique is presented. The sea ice medium is modeled as consisting of randomly located spherical brine scatterers with a specified fractional volume, and the medium is modeled both with and without a randomly rough boundary to study the relative effects of volume and surface scattering. A Monte Carlo simulation is used to obtain numerical results for incoherent υυ backscattered normalized radar cross sections (RCSs) in the frequency range from 3 to 9 GHz and for incidence angles from 10° to 50° from normal incidence. The computational intensity of the study necessitates an effective permittivity approach to modeling brine pocket effects and a nonuniform grid for small scale surface roughness. However, comparisons with analytical models show that these approximations should introduce errors no larger than approximately 3 dB. Incoherent υυ cross sections backscattered from sea ice models with a smooth surface show only a small dependence on incidence angle, while results for sea ice models with slightly rough surfaces are found to be dominated by surface scattering at incidence angles less than 30° and by scattering from brine pockets at angles greater than 30°. As the surface roughness increases, surface scattering tends to dominate at all incidence angles. Initial comparisons with measurements taken with artificially grown sea ice are made, and even the simplified sea ice model used in the FDTD simulation is found to provide reasonable agreement with measured data trends. The numerical model developed ran be useful in interpreting measurements when parameters such as surface roughness and scatterer distributions lie outside ranges where analytical models are valid     

风云三号卫星MERSI影像提取北极海冰参数的方法

风云三号卫星MERSI影像的空间分辨率达到250 m,不仅可以长期宏观监测海冰整体分布变化,而且能够观测分析破碎冰块的面积、圆度等细节形态特征.从海冰光谱特征和冰块灰度分布特征出发,给出MERSI影像提取海冰整体分布参数和冰块形态参数方法,包括海冰识别、冰块分离提取以及海冰参数提取,利用这些方法成功提取了2014年夏季弗拉姆海峡海冰边缘区的海冰细节信息.给出的方法可为研究分析北极海冰变化及海气相互作用提供方法支持和信息保障.     

AIRS radiance validation over ocean from sea surface temperature measurements

Demonstrates the accuracy of methods and in situ data for early validation of calibrated Earth scene radiances measured by the Atmospheric InfraRed Sounder (AIRS) on the Aqua spacecraft. We describe an approach for validation that relies on comparisons of AIRS radiances with drifting buoy measurements, ship radiometric observations and mapped sea surface temperature products during the first six months after launch. The focus of the validation is on AIRS channel radiances in narrow spectral window regions located between 800-1250 cm/sup -1/ and between 2500 and 2700 cm/sup -1/. Simulated AIRS brightness temperatures are compared to in situ and satellite-based observations of sea surface temperature colocated in time and space, to demonstrate accuracies that can be achieved in clear atmospheres. An error budget, derived from single channel, single footprint matchups, indicates AIRS can be validated to better than 1% in absolute radiance (equivalent to 0.5 K in brightness temperature, at 300 K and 938 cm/sup -1/) during early mission operations. The eventual goal is to validate instrument radiances close to the demonstrated prelaunch calibration accuracy of about 0.4% (equivalent to 0.2 K in brightness temperature, at 300 K and 938 cm/sup -1/).     

Surface roughness characterizations of sea ice and ice sheets: case studies with MISR data

This work is an examination of potential uses of multiangular remote sensing imagery for mapping and characterizing sea ice and ice sheet surfaces based on surface roughness properties. We use data from the Multi-angle Imaging SpectroRadiometer (MISR) to demonstrate that ice sheet and sea ice surfaces have characteristic angular signatures and that these angular signatures may be used in much the same way as spectral signatures are used in multispectral classification. Three case studies are examined: sea ice in the Beaufort Sea off the north coast of Alaska, the Jakobshavn Glacier on the western edge of the Greenland ice sheet, and a region in Antarctica south of McMurdo station containing glaciers and blue-ice areas. The MISR sea ice image appears to delineate different first-year ice types and, to some extent, the transition from first-year to multiyear ice. The MISR image shows good agreement with sea ice types that are evident in concurrent synthetic aperture radar (SAR) imagery and ice analysis charts from the National Ice Center. Over the Jakobshavn Glacier, surface roughness data from airborne laser altimeter transects correlate well with MISR-derived estimates of surface roughness. In Antarctica, ablation-related blue-ice areas, which are difficult to distinguish from bare ice exposed by crevasses, are easily detected using multiangular data.     

Snow cover detected by diurnal warming of sea ice/snow surface offLabrador in NOAA imagery

Four consecutive NOAA-9 infrared images show diurnal warming of the sea-ice surface off the coast of Labrador. For three subdomains with scales of ~100 km, the warming of the surface is obtained on the assumption that the warming of the surface is obtained on the assumption that the warming in one pixel is proportional to ice compactness, which is given in turn by brightness of a visible (daytime) image. A one-dimensional heat transfer equation for snow and ice is solved. An algorithm to estimate the snow thickness, which is required to calculate the heat flux through ice, from this extra warming is proposed     

Azimuthal modulation of C-band scatterometer σ0over Southern Ocean sea ice

In a continuing evaluation of the ERS-1 C-band scatterometer as a tool for studying polar sea ice, the authors evaluate the azimuthal modulation characteristics of Antarctic sea ice. ERS-1 AMI scatterometer mode data sets from several study regions dispersed in the Antarctic seasonal sea ice pack are evaluated for azimuthal modulation. When appropriate, the incidence angle dependence is estimated and removed in a study region before determining whether azimuthal modulation is present in the data. Other comparisons are made using the fore and aft beam measurement difference. The results show that over the ice pack, azimuthal modulation is less than 1 dB at the scale of observation of the ERS-1 C-band scatterometer     

Reliability estimation from zero-failure LiNbO/sub 3/ modulator bias drift data

Since x-cut LiNbO/sub 3/ (LN) optical modulators exhibit bias drift that rolls over around a voltage limit of most systems, their laboratory aging tests sometimes yield zero-failures and do not generate sufficient estimates of device reliability. In this regard, a modified calculation method is proposed and applied to data of OC192 x-cut LN modulators. The calculation presumes a time-independent probability that modulators are expected to have a voltage peak higher than the failure criterion. The obtained small failure rate is considered to be consistent with a rolling-over type drift behavior of these modulators.     

Arctic sea ice, cloud, water, and lead classification using neural networks and 1.6-/spl mu/m data

Polar sea ice plays a critical role in regulating the global climate. Seasonal variation in sea ice extent, however, coupled with the difficulties associated with in situ observations of polar sea ice, makes remote sensing the only practical way to estimate this important climatic variable on the space and time scales required. Unfortunately, accurate retrieval of sea ice extent from satellite data is a difficult task. Sea ice and high cold clouds have similar visible reflectance, but some other types of clouds can appear darker than sea ice. Moreover, strong atmospheric inversions and isothermal structures, both common in winter at some polar locations, further complicate the classification. This paper uses a combination of feed-forward neural networks and 1.6-/spl mu/m data from the new Chinese Fengyun-1C satellite to mitigate these difficulties. The 1.6-/spl mu/m data are especially useful for detecting illuminated water clouds in polar regions because 1) at 1.6 /spl mu/m, the reflectance of water droplets is significantly higher than that of snow or ice and 2) 1.6-/spl mu/m data are unaffected by atmospheric inversions. Validation data confirm the accuracy of the new classification technique. Application to other sensors with 1.6-/spl mu/m capabilities also is discussed.     

空间位姿测量中面阵点云CPD方法的优化及验证

面阵激光成像雷达可以实现瞬态三维探测,适用于运动平台及非合作目标的位姿测量。针对相邻像元间具有串扰特性的面阵非均匀格网型稀疏点云,提出了一种适用于空间非合作目标位姿测量的多视角点云自动配准方法。该方法基于改进的相干点漂移(Coherent Point Drift, CPD),将目标点云视为观测数据集,源点云视作为高斯混合模型(Gaussian mixture model, GMM)的质心点集。利用贝叶斯后验概率公式及期望最大化(Expectation-Maximum, EM)方法,对构造的GMM模型似然函数进行求解,在寻优过程中通过点云重叠特性对运算点集的权值参数进行自适应调整。对单次EM迭代后源点云间距离残差进行排序,选取最优变换点云对使用最近邻方法建立局部扰动量,得到每次漂移迭代的空间变换矩阵。为了避免陷入局部解,通过监督点云均方误差更新率,对参与漂移运算的点集属性进行交替。针对空间配准目标,建立了两种近似运行下的阵列成像仿真工况。试验结果表明：在强背景及像元模糊干扰下,该配准框架具有鲁棒性优势,其结果平均最大公共点集测度相对于粗+精组合配准框架提升约61%,可应用于空间面阵平台下...     

A wavelet transform coder supporting browsing and transmission of sea ice SAR imagery

A wavelet-transform-based algorithm for sea ice synthetic aperture radar (SAR) image data compression is presented. Compression of the relatively low resolution (100 m) SAR data is necessary to enable the transmission of such images from the Finnish Ice Service to users in the Baltic Sea. On board the ships, the SAR images are used for navigation purposes. Hence, in the visual appearance of the compressed image, special attention must be paid to the sharpness of small details. Several target-dependent features are incorporated in the compression scheme developed. The addition of these features was motivated by an examination of the wavelet coefficient statistics for the SAR data. In the quantization phase, the sensitivity characteristics of the human visual system were taken into account. As a result, the proposed algorithm deviates in several respects from the standard procedures used in wavelet-based compression. The algorithm requires the setting up of multiple user-defined parameters to satisfy the requirements of the users and data. This requires supervision of an expert, but also makes it flexible for many kinds of data and user requirements. The algorithm presented gives satisfactory results with a compression ratio of 20:1. Since only the location of ice-covered areas is of significance for ship traffic, the algorithm introduced contains an option to mask off open sea areas with the aid of an automatic open-water detection procedure. We also report the results of a user evaluation, in which the proposed algorithm is compared to the algorithm currently used by the Finnish Ice Service, as well as to the JPEG standard. The results of the evaluation favor the use of the proposed algorithm.     

C-band backscatter signatures of old sea ice in thecentral Arctic during freeze-up

Radar backscatter signatures of old sea ice in the central Arctic have been measured and analyzed. A ship-mounted scatterometer was used to acquire backscattering coefficients at 5.4 GHz in the four linear polarization states and at incidence angles between 20° and 60°. Detailed in situ characterizations of the snow and ice were also made to enable comparison with theoretical backscatter models. Freeze-up conditions were prevalent during the experiment. The average backscattering coefficient was found to increase when the temperature of the ice surface layer decreased. The semi-empirical backscatter model is used to evaluate the measurements and shows that the backscatter increase is due to an increasing penetration depth, causing the volume scattering to increase. Model predictions also show that both surface and volume scattering contribute significantly at incidence angles of 20° to 26°. At these incidence angles, the dominating scattering mechanism changes from surface to volume scattering as the ice surface temperature decreases     

Effective index drift from molecular hydrogen diffusion inhydrogen-loaded optical fibres and its effect on Bragg gratingfabrication

When hydrogen loading is used to enhance the photosensitivity of silica-based optical waveguides and fibres, the presence of molecular hydrogen dissolved in the glass matrix changes the effective index of propagation of guided optical modes by as much as 0.05%. Real-time monitoring of the reflectivity spectrum of Bragg gratings written in such conditions shows that the centre wavelength follows the changes in hydrogen concentration due to diffusion and reaction with glass defects     

The discrete wavelet transform and the scale analysis of thesurface properties of sea ice

The formalism of the one-dimensional discrete wavelet transform (DWT) based on Daubechies wavelet filters is outlined in terms of finite vectors and matrices. Both the scale-dependent wavelet variance and wavelet covariance are considered and confidence intervals for each are determined. The variance estimates are more accurately determined with a maximal-overlap version of the wavelet transform. The properties of several Daubechies wavelet filters and the associated basis vectors are discussed. Both the Mallat orthogonal-pyramid algorithm for determining the DWT and a pyramid algorithm for determining the maximal-overlap version of the transform are presented in terms of finite vectors. As an example, the authors investigate the scales of variability of the surface temperature and albedo of spring pack ice in the Beaufort Sea. The data analyzed are from individual lines of a Landsat TM image (25-m sample interval) and include both reflective (channel 3, 30-m resolution) and thermal (channel 6, 120-m resolution) data. The wavelet variance and covariance estimates are presented and more than half of the variance is accounted for by scales of less than 800 m. A wavelet-based technique for enhancing the lower-resolution thermal data using the reflected data is introduced. The simulated effects of poor instrument resolution on the estimated lead number density and the mean lead width are investigated using a wavelet-based smooth of the observations     

First-order theory and analysis of MF/HF/VHF scatter from the sea

Scatter from the sea near grazing from MF through VHF is analyzed in this paper. Results based on the compensation theorem show that the dependence upon the grazing angles, as well as upon frequency, range, and the effective surface impedance, can be removed for vertical polarization as the familiar "Norton attenuation factors." Time variation of the surface is included, and results are derived for both the average received power and its spectral density. The first-order dispersion relationship for gravity waves is used to show that the received spectrum from a patch of sea consists of two discrete Doppler shifts above and below the carrier, predictable from simple Bragg diffraction considerations. Using the Phillips wind-wave model as an upper limit for wave heights, estimates forsigma^{0}(radar cross section per unit area) of - 17 dB are obtained near grazing. Both the magnitude ofsigma_{upsilonnu}^{0}predicted from theory and the nature of the received spectrum are compared with measurements, and the agreement supports the theory on both counts. Finally, the use of MF/HF radars for measuring sea state is suggested and discussed.     

A high performance CNFET-based operational transconductance amplifier and its applications

High performance electronic systems face several challenges in driving innovative integrated circuits when the internal transistors are scaled down below 45 nm. Carbon nanotube field effect transistors (CNFETs) are considered as excellent candidates for building energy-efficient electronic systems in the near future, due to their unique characteristics such as ballistic transport, scalability, and better channel electrostatics. In this paper, a new high performance operational transconductance amplifier (OTA) based on 32 nm CNFET devices is presented. The proposed OTA maintains a highly linear wide continuous tuning range and a wide frequency response range, enabled by splitting the linear voltage-to-current conversion and tuning two different blocks. As an application, a universal second-order transconductance-capacitor (G _m  ? C) filter realized using the OTA is introduced. Simulation results show that the CNFET-based OTA offers very a low current consumption of 2.35 μA from a ± 0.9 V power supply, achieves a bandwidth of 9.5 MHz, and has an input dynamic range of ± 0.2 V.     

Comparing cooccurrence probabilities and Markov random fields for texture analysis of SAR sea ice imagery

This paper compares the discrimination ability of two texture analysis methods: Markov random fields (MRFs) and gray-level cooccurrence probabilities (GLCPs). There exists limited published research comparing different texture methods, especially with regard to segmenting remotely sensed imagery. The role of window size in texture feature consistency and separability as well as the role in handling of multiple textures within a window are investigated. Necessary testing is performed on samples of synthetic (MRF generated), Brodatz, and synthetic aperture radar (SAR) sea ice imagery. GLCPs are demonstrated to have improved discrimination ability relative to MRFs with decreasing window size, which is important when performing image segmentation. On the other hand, GLCPs are more sensitive to texture boundary confusion than MRFs given their respective segmentation procedures.