Classification of sea ice types in the Ross Sea,Antarctica from SAR and AVHRR imagery

ERS-2 synthetic aperture radar (SAR) and Advanced Very High Resolution Radiometer (AVHRR) imagery are used to examine spectral characteristics of late winter/early spring ice in the Ross Sea, Antarctica. The combined spectral signatures are used to distinguish six ice types: fast ice, new ice, smooth first year ice, rough first year ice, thin new ice/wind roughened open water and glacial ice. The procedure firstly involves 'picking' class boundaries from SAR imagery based on the morphology of a speckle reduced backscatter spectrum. These class boundaries are then used as input to an iterative segmentation procedure that involves the repeated application of a speckle reduction filter to the image. For an image from late September 1996 the segmentation procedure enabled separation of five general ice categories each with a characteristic backscatter range. However because of the combined contributions of ice thickness, surface roughness, salinity and water content to the SAR backscatter, further decision criteria are required to separate some physical ice types unable to be resolved individually using this method. Coincident and co-registered infrared data from the AVHRR sensor are used to extract spectral characteristics for the final ice classes. Using this procedure we were able to distinguish floating glacier ice from thin new ice/wind roughened open water and new ice from nearshore fast ice. These ice types were unable to be separated using SAR backscatter intensity alone. In addition image subtraction was also able to clearly delineate areas of shore fast ice.     

Iceberg observations and estimation of submarine ridges in the western Weddell Sea

A number of small patches of relatively high temperatures and low rcflectances were observed in the western and south-western Weddell Sea between October 1991 and February 1994 by aid of Advanced Very High Resolution Radiometer (AVHRR) images. From ERS-I Synthetic Aperture Radar (SAR) data acquired during the same period these patches could be identified as high backscatter areas in the lee of small icebergs. Most of the icebergs were grounded for the entire period of observation. North of the icebergs a number of extended bands (> 100km) of high backscatter and low reflectance were detected in most of the images. These bands demonstrate the etTect of the icebergs as fixed barriers on the drifting ice cover creating a perturbation in the lee of the barriers. The combination of SAR data, AVHRR data and the Argos tracked buoys shows a very homogenous behaviour of the ice cover on the continental shelf with strong tidal component and low large scale shear activities. From the analysis of the shadows created by the tabular icebergs a rough estimation of the heights of the icebergs and the corresponding draughts could be made, which were then used for an estimation of the submarine topography responsible for the grounding of the icebergs. These indirect measurements are the first ones made on the continental shelf off the Antarctic Peninsula. They indicate a submarine ridge of about 150 to 300m water depth nearly perpendicular to the coastline at about 70° 45° S between 56° 30° Wand 58° 30' W.     

Retrieval of phenological stages of onion fields during the first year of growth by means of C-band polarimetric SAR measurements

The phenological stages of onion fields in the first year of growth are estimated using polarimetric observables and single-polarization intensity channels. Experiments are undertaken on a time series of RADARSAT-2 C-band full-polarimetric synthetic aperture radar (SAR) images collected in 2009 over the Barrax region, Spain, where ground truth information about onion growth stages is provided by the European Space Agency (ESA)-funded agricultural bio/geophysical retrieval from frequent repeat pass SAR and optical imaging (AgriSAR) field campaign conducted in that area. The experimental results demonstrate that polarimetric entropy or copolar coherence when used jointly with the cross-polarized intensity allows unambiguously distinguishing three phenological intervals.     

全极化合成孔径雷达影像地形纠正及其在雪冰制图中的应用

针对合成孔径雷达（SAR）影像由于地形起伏引起的图像畸变问题,文章提出了基于相干矩阵的全极化SAR影像地形纠正算法,并运用于雪冰制图。该方法首先采用距离多普勒模型建立SAR成像几何模型;然后利用全极化Cloude特征分解方法对全极化SAR图像进行融合,将融合后的SAR图像与模拟图像进行配准提高SAR影像几何定位精度;最后利用投影面积归一化和极化方位角移动补偿技术对地形引起的辐射畸变进行纠正。采用中国长江源区南部唐古拉山中段冬克玛底冰川区域的C波段Radarsat-2全极化SAR数据进行验证,配准模拟SAR和原始SAR影像的控制点方位向和距离向的均方根误差（RMSE）分别为7.765和14.586个像素;经过地形纠正后的地物分类精度达80%以上。结果表明：（1）该方法能够有效消除SAR影像中几何和辐射畸变的影响;（2）地形纠正后的SAR数据在雪冰制图中具有可行性。     

Observations of ice surface temperature and thickness in the Baltic Sea

This paper presents the results of an airborne thermal infrared (TIR) experiment. The data were obtained during 6–9 February 1992 period in the Bay of Bothnia, the northern section of the Baltic Sea, in connection with an ERS‐1 field campaign. Two Aegema model 880 TIR cameras were used with nominal wavelengths at 5 and 10 µm, attached to the front of the helicopter with a Tyler mount. The camera's thermal resolution is 0.2 K; after corrections for atmosphere effects, the surface temperature accuracy is 0.5 K. The spatial resolution of individual images is 70 cm at the 300‐m flight altitude. The measurement programme was successful, producing high‐quality TIR data over ice for two different days, even under difficult weather conditions. Ice temperatures ranged from open water temperatures to 261 K for fast ice conditions on the day on the first flight. The standard deviation of the surface temperature, generally, increased with ice thickness with a value of ～0.4 K for maximum thickness, and autocorrelation length scales not exceeding a value of 5 m. Generally, all the higher values of standard deviation (>0.7) of surface temperatures were for scenes with mixed ice/open water. The results show that TIR has a substantial ability to classify ice type and thickness when the air temperature is less than 269 K, from open water at the freezing point to thin nilas and thicknesses up to 20–45 cm in the fast ice zone. In addition, a quasi‐steady sea‐ice model is used to provide a physical interpretation of the sea‐ice surface temperatures. The use of the model requires information on the atmospheric surface layer and snow thickness data, together with calibration points. The model worked well when the air temperature was around 260 K or less.     

Real-time use of ERS-l SAR imagery for ice service and ice breaking operations in the Baltic Sea

Sea ice forms every winter in the Baltic Sea and several icebreakers in Sweden and Finland keep the major ports in the area open for sea-trade all the year around. Information and forecasts of the sea ice formation, drift and deformation are vital for safe and efficient winter navigation. In this respect, Synthetic Aperture Radar (SAR) imagery is of great interest, since this technique is almost cloud independent and has potential for real-time ice mapping. The usefulness of SAR imagery for sea ice operations has been evaluated in the Baltic Sea. The imagery was used both for ice mapping, for icebreaker operations and ship routeing. Images presented onboard the icebreakers were highly appreciated and easily interpreted by the crew. The data were frequently used for ship routeing (33 per cent) of merchant vessels and for direct icebreaker assistance (53 per cent). It was concluded by several icebreaker masters that an image resolution of about 100m was indeed enough to distinguish ridged areas and in the same time obtain a large enough geographical coverage per image.     

Analysis of sea ice motion and deformation in the marginal ice zone of the Bering Sea using SAR data

This paper presents a study of sea ice motion and deformation in the marginal ice zone (MIZ) of the Bering Sea in the winter season. Segmentation techniques and statistical methods are applied to high‐resolution synthetic aperture radar (SAR) images to derive ice motion and deformation maps. These techniques involve dynamic local thresholding (DLT), which allows separation of sea ice into different classes of thickness and type. Two ice motion characteristics are observed, one consisting of a translation and a rotation at a scale larger than about 10 km day^?1 and the other consisting of field deformations at a spatial scale of less than about 5 km over a 3‐day period. Sea ice deformation rates are calculated, and the divergence and shear feature of the sea ice in different regions identified. Possible causes, associated with wind, wave, current and internal ice forces, for the sea ice motion and deformation are discussed.     

Detection of urban housing development by fusing multisensor satellite data and performing spatial feature post-classification

A large number of change detection techniques have been developed, but little has been done to detect detailed changes, such as urban housing development, using satellite data. In this study a new approach is presented. By fusing multispectral satellite data, e.g. Landsat Thematic Mapper (TM) or SPOT XS, with panchromatic satellite data, e.g. SPOT pan, big buildings (10-20 m in width) in urban areas can be extracted. By performing the spatial feature post-classification, e.g. (1) co-occurrence matrix-based filtering for separating buildings from noise, (2) axis-oriented linking and segmentation for a complete extraction of urban water areas, and (3) mathematical morphology operations for improving the classified green areas, the accuracy of the extracted classes is significantly increased and a detailed urban housing map can be generated. By overlaying this map with the built-up areas extracted from data of an earlier date, newly developed built-up areas can be detected and big buildings can individually be highlighted. This new approach was tested in the urban area of Shanghai, China, using Landsat TM and SPOT pan data. More detailed change detection than with conventional methods resulted in an average accuracy of the building extraction of 86%.     

Airborne freeboard measurements of sea ice and lake ice at the Sea of Okhotsk coast in 1993-95 by a laser altimeter

An airborne laser altimeter using a Nd:YAG laser was constructed to measure surface profiles of sea ice and frozen lakes. The measurements were conducted to develop a technique for estimating the ice amount of the sea ice in the Sea of Okhotsk off the northern shore of Hokkaido Island, Japan. Distributions of freeboards, mean elevations and ice concentrations were investigated from the data observed in 1993-95. Distribution functions of the ice freeboard changed considerably depending on ice concentrations in contrast with the decreasing function for the sea ice in the Arctic Ocean. The mean ice freeboard, however, correlated very well with the ice concentration, which is very important for estimating total ice amounts in regions of drifting ice. The surface roughness of a frozen lake was also observed and analysed.     

Estimation of thin ice thickness from AMSR-E data in the Chukchi Sea

In this study, we have developed an algorithm for estimating thin ice thickness in the Chukchi Sea of the Arctic Ocean using Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) data. The algorithm is based on comparisons between the polarization ratio (PR) of AMSR-E brightness temperatures from the 89 and 36 GHz channels (PR₈₉ and PR₃₆) and the thermal ice thickness. The thermal ice thickness is estimated from a heat budget calculation using the ice surface temperature from clear-sky Moderate-Resolution Imaging Spectroradiometer (MODIS) infrared data. Whereas coastal polynyas have been the main target of previous algorithms, this algorithm is also applicable for marginal ice zones. AMSR-E has twice the spatial resolution of Special Sensor Microwave/Imager (SSM/I) data and can therefore resolve polynyas at a smaller scale. Although the spatial resolution of the 89 GHz data (6.25 km) is twice that of the 36 GHz data (12.5 km), the 89 GHz data can be contaminated by atmospheric water vapour. We propose an exclusion method of data affected by water vapour to resolve this issue. A combined algorithm of thin ice and ice concentration is also discussed, in which the ice thickness can be estimated independently from the open water fraction in grid cells with less than 100% ice concentration. The PR–thickness relationship in this study is somewhat different from previous studies, which is likely due to the difference in prevailing ice types caused by background environmental conditions.     

Multi-criteria selection of a deep-water port in the Eastern Baltic Sea

Sea ports play a significant role in the development of a modern economy. The Baltic Sea is an arterial transport corridor between Eastern and Western Europe. There is need to develop a deep-water sea port in the Klaipeda region to satisfy economic needs. This problem involves a multitude of requirements and uncertain conditions that have to be taken into consideration simultaneously. Numerous studies have been designated for the resolution of similar problems by employing multi-criteria as an aid. This paper proposes an integrated multi-criteria decision-making model to solve the problem. The backbone of the proposed model consists of a combination of Analytic Hierarchy (AHP) and Fuzzy Ratio Assessment (ARAS-F) methods. This model is presented as a form of decision aiding that could to be implemented when regarding any specific port or a like site selection.     

Improving the performance of lung nodule classification by fusing structured and unstructured data

We investigated the issue of improving the classification performance for pulmonary nodules by learning the fusion features of structured and unstructured data. Current strategies for lung nodule classification, such as radiomics methods and deep learning approaches, all share the flaw of only using the unstructured data of patients, which is always a collection of medical images (e.g., computed tomography (CT) scans, X-rays, and pathological sections), while ignoring the structured data (e.g., baseline demographics, clinical characteristics, and laboratory examinations). However, from a clinical perspective, all of this information is required for accurate patient diagnosis. Therefore, to exploit all patient information, we addressed a more difficult problem: jointly modeling the multimodal patient data. Two models are proposed to combine structured and unstructured data. One employs deep learning with a softmax classifier (the structured and unstructured data fusion neural network (SUDFNN)), and the other implements an extreme gradient boosting (XGBoost) classifier (the structured and unstructured data fusion XGBoost (SUDFX)). The annotated structured data in the extensible markup language (XML) file from the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) database and the CT scans from the LUng Nodule Analysis 2016 (LUNA16) dataset were used to validate our model. The results show that the performance of the model is significantly improved when introducing the structured data, regardless of the nodule cube size and which classifier is used. The rationale for the improvement with the addition of structured features is provided. The optimal accuracy, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) values reached 0.936, 0.919, 0.956, and 0.971, respectively. Consequently, fusing structured and unstructured data can uncover more patient information and provide better decision support for the clinical diagnosis and treatment process, providing good application value and promotion prospects.     

一种海空背景下小信号的检测算法

本文对于天文导航系统中一般舰船存在的摇角问题,提出了水天线测量法,利用小波变换技术对水天线信号进行边沿检测。     

Comparison between in situ and MODIS-derived spectral reflectances of snow and sea ice in the Amundsen Sea,Antarctica

The spectral albedo and directional reflectance of snow and sea ice were measured on sea ice of various types, including nilas, grey ice, pancake ice, multi-year pack ice, and land-fast ice in the Ross, Amundsen and Bellingshausen seas during a summer cruise in February through March 2000. Measurements were made using a spectroradiometer that has 512 channels in the visible and near-infrared (VNIR) region in which 16 of the 36 bands of the Moderate Resolution Imaging Spectroradiometer (MODIS) are covered. Directional reflectance is also retrieved from the MODIS radiometrically calibrated data (Level 1B) concurrently acquired from the first National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) satellite, Terra. The locations of the ground ice stations are identified accurately on the MODIS images, and the spectral albedo and directional reflectance values at the 16 VNIR MODIS bands are extracted for those pixel locations. MODIS-derived reflectance is then corrected for the intervening atmosphere whose parameters are retrieved from the MODIS atmospheric profiles product (MOD07_L2) for the same granule. The corresponding spectral albedo and directional reflectance with the same viewing geometry as MODIS are derived from our ground-based spectroradiometer measurements. Because the footprint of the ground spectroradiometer is much smaller than the pixel sizes of MODIS images, the averaged spectral reflectance and albedo in the vicinity of each ice station are simulated for the corresponding MODIS pixel from the ground spectral measurements by weighting over different surface types (various ice types and open water). An accurate determination of ice concentration is important in deriving ground reflectance of a simulated pixel from in situ measurements. The best agreement between the in situ and MODIS measurements was found when the ground had 10/10 ice concentration (discrepancy range 0.2–11.69%, average 4.8%) or was oneice-type dominant (discrepancy range 0.8–16.9%, average 6.2%). The more homogeneous the ground surface and the less variable the ground topography, the more comparable between the in situ and satellite-derived reflectance is expected.     

On the classification of melt season first-year and multi-year sea ice in the Beaufort Sea using Radarsat-2 data

Interpreting satellite microwave sea ice data during the melt season is difficult. Warm temperatures allow for a greater presence of water in the liquid phase at the surface and within the ice, resulting in similar backscattering responses for first-year ice (FYI) and multi-year ice (MYI). Differentiating these ice types is important, especially during summer, in view of the higher presence of seasonal marine traffic, functioning of the ecosystem, and the Inuit use of the marine icescape in summer. In this article, we investigate the similarities between geophysical, thermodynamic, and dielectric characteristics of the late-season MYI and FYI, and discuss how this can lead to a false detection of MYI. The study uses Radarsat-2 data for ice detection during summer. This involves an analysis of co-polarization versus cross-polarization (HH vs. HV), various incident angles (20°, 35°, and 45°), and ice types (FYI vs. MYI). Statistical analyses of the measurements obtained in 2009 identify the difficulty in differentiating ice types during summer. The results show that the physical and electromagnetic properties of the ice surfaces are virtually identical with few differences in the scattering of microwave energy. We conclude with suggestions on how a more effective differentiation of MYI and FYI types in the summer season can be accomplished.     

Characterization of the coherent scattering induced by ridging patterns in agriculture by the use of polarimetric SAR imagery

This article investigates the scattering characteristics of ridging patterns in agriculture by the use of C-band polarimetric synthetic aperture radar (PolSAR) images. The polarimetric signatures of periodic potato fields and row wheat in different directions are highlighted using a set of polarimetric parameters. Enhanced coherent scattering is observed when the alignment direction of the ridging patterns is perpendicular to the radar’s line of sight (LOS). The dominant backscattering mechanism of the ridging patterns is deduced by evaluating different polarimetric parameters. The increased copolarized backscattering coefficients and copolarized correlation coefficient, and the reduced entropy and polarimetric alpha angle, indicate a strong contribution of odd scattering to ridging patterns aligned perpendicular to the LOS. We also compare the dominant contributions to the backscattering of ridging patterns in different phenological stages. Although the canopy changes of potato and wheat with time are significant, the underlying periodic surface changes the dominant scattering mechanism of potato fields over all the phenological stages, and the wheat aligned parallel with the flight direction of radar still has relatively high coherent scattering in the different vegetation development stages. The variability analyses undertake in this study allow a more detailed documentation of the physical scattering process of the ridging patterns in agriculture, and will improve the applicability of synthetic aperture radar images in agriculture.     

Experimental study on the effect of porosity on the uniaxial compressive strength of sea ice in Bohai Sea

For the abnormal ice condition in 2009–2010 winter,sea ice samples were collected in a tide ditch outside a port in the east coast of Liaodong Bay,and ice specimens were prepared.Experimental study was carried out with a temperature-control precision of 0.1°C,and 117 columnar-grained ice specimens were loaded along the direction parallel to ice surface under different test temperatures(-4,-7,-10,-13,-16°C)and strain rates ranging from 10-6 to 10-2 s-1 within which the ductile region,ductile-brittle transiti...     

Detection of total suspended sediments in the North Sea using AVHRR and ship data

This study reports on a combined investigation between in situ measurements of total suspended sediments, collected by ship, and remotely sensed data provided by the Advanced Very High Resolution Radiometer (AVHRR) during the winter-summer period of 1989. It is meant to be a case study stating the problems inherent to coastal waters and proposing a methodology to understand them. Ship and satellite data are compared in order to detect suspended sediments in case 2 waters in the North Sea through a linear regression analysis. The results show a wide range of coefficient of determination (R²) values. The highest values correspond to summer dates, while the lowest belonged to the winter and spring period. It was found that for the summer dates the relatively still atmospheric and water conditions were suitable for comparison with satellite data providing good values of R². In winter and spring, unsettled sea water conditions complicated the comparison of the data. It can be concluded that the seasonal stratification of the water column during summer time allows a better correlation between in situ and remotely sensed data than the typically well-mixed waters during winter.     

Evaluation of the traffic parameters in a metropolitan area by fusing visual perceptions and CNN processing of webcam images

This paper proposes a traffic monitoring architecture based on a high-speed communication network whose nodes are equipped with fuzzy processors and cellular neural network (CNN) embedded systems. It implements a real-time mobility information system where visual human perceptions sent by people working on the territory and video-sequences of traffic taken from webcams are jointly processed to evaluate the fundamental traffic parameters for every street of a metropolitan area. This paper presents the whole methodology for data collection and analysis and compares the accuracy and the processing time of the proposed soft computing techniques with other existing algorithms. Moreover, this paper discusses when and why it is recommended to fuse the visual perceptions of the traffic with the automated measurements taken from the webcams to compute the maximum traveling time that is likely needed to reach any destination in the traffic network.     

Detection of small-scale roughness and refractive index of sea ice in passive satellite microwave remote sensing

Polar ice masses and sheets are sensitive indicators of climate change. Small-scale surface roughness significantly impacts the microwave emission of the sea ice/snow surface; however, published results of surface roughness measurements of sea ice are rare. Knowing the refractive index is important to discriminate between objects. In this study, the small-scale roughness and refractive index over sea ice are estimated with AMSR-E observations and a unique method. Consequently, the small-scale surface roughness of 0.25 cm to 0.5 cm at AMSR-E 6.9 GHz shows reasonable agreement with the results of known observations, ranging from 0.2 cm to 0.6 cm for the sea ice in the Antarctic and Arctic regions. The refractive indexes are retrieved from 1.6 to 1.8 for winter, from 1.2 to 1.4 for summer in the Arctic and the Antarctic, which are similar to those of the sea ice and results from previous studies. This research shows the physical characteristics of the sea ice edges and melting process. Accordingly, this investigation provides an effective procedure for retrieving the small-scale roughness and refractive index of sea ice and snow. Another advantage of this study is the ability to distinguish sea ice from the sea surface by their relative small-scale roughness.