Natural and man-made sea slicks in the North Sea investigated by a helicopter-borne 5-frequency radar scatterometer

In April 1994 natural sea slicks and five man-made slicks, which were spread as a pure substance and from two different spreading solvents, n-hexane and ethanol, respectively, were overflown by a helicopter carrying a five-frequency multi-polarization radar scatterometer, the so-called Heliscat. For the first time, natural sea slicks were successfully simulated by spreading hexadecanoic acid methyl ester (palmitic acid methyl ester (PME)), representing the fatty acid fraction of biogenic slicks, from the spreading solvent ethanol. It is shown that the different slick generation procedures (pure substance, spreading solvents n-hexane or ethanol) give rise to different influences on backscattered radar signals: a PME slick spread from ethanol induces slightly stronger suppressions of the radar backscattering than a PME slick spread from n-hexane; the wave damping maximum of oleyl alcohol (OLA) spread as a pure substance is shifted to higher wave numbers as compared to OLA slicks spread from solvents and the backscattered radar power measured over both PME and OLA slicks spread from solvents show a dependence on the incidence angle, while no angular dependence was observed over OLA slicks spread without a spreading solvent. These phenomena are explained by the different morphology of the slicks induced by the respective spreading solvent. Furthermore, previous assumptions that the physicochemical characteristics of OLA slicks may sufficiently well represent those of natural sea slicks were verified. With regard to the effects summarized above no differences were discernable between the HH and VV radar signals. Simulation of the very first stage of the development of sea slicks revealed that wave damping is continuously increasing during the first time after slick generation. This is in accordance with the assumption that relaxation effects give rise to increasing order within the surface film and thus to increasing hydrophobic interaction both between the film-forming substances and the adjacent water layer.     

Demonstration of an improved calibration scheme for ERS-l SAR imagery using a scatterometer wind model

The importance of an improved calibration scheme for the derivation of the normalized radar cross-section coefficient σ° for distributed targets using ERS-l SAR imagery is assessed. The improved calibration scheme includes corrections relating to the saturation of the on-board Analogue to Digital Convertor (ADC) and to variations in the replica pulse power. The significance and effectiveness of the additional corrections is demonstrated by comparing the range variation of σ° from 10 ERS-l.SAR.PRI images of the English Channel with that predicted by the CMOD4 scatterometer wind model. Close agreement is found at all range positions, provided the additional corrections are applied.     

Snowmelt detection on the Greenland ice sheet using microwave scatterometer measurements

Microwave scatterometer measurements have been used in monitoring the snowmelt characteristics of the Greenland ice sheet. The melt signals and the appropriate threshold scheme are critical to the detection of ice-sheet snowmelt. We propose a scatterometer ice-sheet snowmelt detecting method based on diurnal variation and polarization ratio (DVPR) time series. We implement the algorithm to detect the snowmelt of the Greenland ice sheet using Quick Scatterometer (QuikSCAT) data. Moreover, the detection results of the DVPR method are compared with two other scatterometer snowmelts and validated by the automatic weather station (AWS) data in Greenland. The results show that the method based on the DVPR time series has better detection accuracy and this method is more precise for detecting the melt onset and melt end of ice sheets.     

The observation of the surface roughness characteristics of the Rhine plume frontal boundaries by simultaneous airborne thematic mapper and multifrequency helicopter-borne radar scatterometer

In this paper, we describe how high spatial resolution (10 m) multisensor remote sensing techniques can be used to study the surface roughness characteristics of large scale frontal boundaries (in this case associated with the Rhine Plume). The instrumentation employed in the research consisted of a Daedalus AADS 1268 Airborne Thematic Mapper (ATM) operated by the UK National Environment Council, the HELISCAT helicopter-borne multifrequency microwave scatterometer of the University of Hamburg, and research vessels (R.V.s) from the University of Wales and the Dutch Rijkswaterstaat. The data we present were gathered on 24 April 1991 when calm wind conditions developed within the test area. A sequence of thermal infrared images gathered by the ATM provides a record of the motion of a frontal boundary through this experimental region which is then used to identify the frontal signature in the HELISCAT data. ATM sunglint images show that the front is characterized by a zone of reduced surface roughness, some 75m in width, which is detected on the 'upstream' side of the front (as defined relative to the tidal flow direction), where surface current convergence can be expected. Radar backscatter levels at X and C bands are reduced by 10 dB in this region but with increase in radar wavelength, the signature weakens and is rarely detected at L band. On crossing the front in the downstream direction, radar backscatter levels are rapidly restored. The available evidence indicates that the reduced backscatter signature is caused by a surface slick which is formed at the frontal interface rather than by short gravity wave damping from shear in local surface currents.     

Assessment of the offshore wind resource in Japan with the ASCAT microwave scatterometer

We analysed wind speed and direction off the coast of Japan using data from the satellite-borne Advanced Scatterometer (ASCAT) and the Weather Research and Forecasting model (WRF), validated these data using in situ wind measurements from 20 buoys, and evaluated the effect of the long time intervals from ASCAT observations on wind resource assessment. More than 25 km from the coast, and at heights of 10 m, the ASCAT wind speed has negative biases of up to 3.4% and root mean square errors of up to 18.5%; its wind direction has 11° to 27° of mean absolute error compared to buoy measurements at a height of 10 m. These accuracies are better than either the expected accuracies reported in the technical manual or those simulated with WRF with its spatial resolution of 10 km. We also evaluated long-term average ASCAT wind speeds in comparison to 4- and 5-year averages of in situ buoy wind speeds measured at three buoys, with resulting differences of –0.3%, –6.3%, and – 1.6%. Furthermore, wind roses show that appearance frequencies of the ASCAT wind direction for the long term are in a good agreement with those of the measurements at the three buoys. Our results show that the ASCAT-derived wind speed and direction are appropriate more than 25 km from the coast, and that the long time interval between ASCAT observations has an insignificant effect on wind resource assessment, if at least 4 or 5 years of averaged ASCAT data are used.     

A blended global snow product using visible,passive microwave and scatterometer satellite data

A joint US Air Force/National Aeronautics and Space Administration (NASA) blended global snow product that uses Earth Observation System Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and Quick Scatterometer (QuikSCAT or QSCAT) data has been developed. Existing snow products derived from these sensors have been blended into a single, global, daily, user-friendly product by using a newly developed Air Force Weather Agency (AFWA)/NASA Snow Algorithm (ANSA). This initial blended snow product uses minimal modelling to expeditiously yield improved snow products, which include, or will include, snow-cover extent, fractional snow cover, snow water equivalent (SWE), onset of snowmelt and identification of actively melting snow cover. The blended snow products are currently 25-km resolution. These products are validated with data from the lower Great Lakes region of the USA, from Colorado obtained during the Cold Land Processes Experiment (CLPX), and from Finland. The AMSR-E product is especially useful in detecting snow through clouds; however, passive microwave data miss snow in those regions where the snow cover is thin, along the margins of the continental snowline, and on the lee side of the Rocky Mountains, for instance. In these regions, the MODIS product can map shallow snow cover under cloud-free conditions. The confidence for mapping snow-cover extent is greater with the MODIS product than with the microwave product when cloud-free MODIS observations are available. Therefore, the MODIS product is used as the default for detecting snow cover. The passive microwave product is used as the default only in those areas where MODIS data are not applicable due to the presence of clouds and darkness. The AMSR-E snow product is used in association with the difference between ascending and descending satellite passes or diurnal-amplitude variations (DAV) to detect the onset of melt, and a QSCAT product will be used to map areas of snow that are actively melting.     

Geothermal observations by use of a helicopter-borne remote sensing system

Detailed infrared images are useful for investigating thermal features of geothermal fields. A remote sensing system which is installed on low-altitude-flying helicopters is developed to get the infrared images with high resolution. But those images can cover only a limited domain. As the system can fit visible images on infrared ones simultaneously obtained, within a common field of view, this makes it possible to determine the positions of target areas by finding out geographical and topographical features over the visible images in spite of its limited areas. Observations by means of the helicopter-borne system are described for the two geothermal fields in Japan. Finally, heat discharge from those fields are estimated by analyzing the observed thermal images.     

中心折反射相机标定方法综述

近十几年来,计算机视觉越来越受研究者们的欢迎,特别是全景相机由于其具有较大的视场而被广泛应用到许多领域,包括视频监控、机器人导航、电视电话会议、场景重建以及虚拟现实等。摄像机标定是从二维图像获得三维信息必不可少的一步,摄像机标定结果的好坏直接决定着三维重建结果以及其它计算机视觉应用效果的好坏,所以,研究摄像机的标定方法具有重要的理论研究意义和重要的实际应用价值。这里将2000年到2012年折反射相机标定方法按照标定像的不同分为五大类：基于线的标定、基于二维标定块标定、基于三维点的标定、基于球的标定和自标定,且简要分析其优缺点。     

多站位CCD相机参数的标定方法研究

单站位的标定方法对于大视场的相机只能保证标定区域有很好的测量精度.为此,提出了多站位数字相机内部参数的标定方法.该方法将相机像面划分为若干个区域,规划相机的站位分布和位置姿态,确保所有站位下控制点能够分布相机整个像面,从而使标定的结果能够反映整个像面的畸变影响.多站位标定方法能够很好地解决单站位标定中被测点超出标定的区域时成像精度无规则变化的问题.实验结果表明:对基准尺在6个位置进行测量,多站位标定方法计算出的结果都可以保持在一定的水平上,不会出现单站位计算出的个别位置误差过大的情况.     

Survey on zoom-lens calibration methods and techniques

This paper surveys zoom-lens calibration approaches, such as pattern-based calibration, self-calibration, and hybrid (or semiautomatic) calibration. We describe the characteristics and applications of various calibration methods employed in zoom-lens calibration and offer a novel classification model for zoom-lens calibration approaches in both single and stereo cameras. We elaborate on these calibration techniques to discuss their common characteristics and attributes. Finally, we present a comparative analysis of zoom-lens calibration approaches, highlighting the advantages and disadvantages of each approach. Furthermore, we compare the linear and nonlinear camera models proposed for zoom-lens calibration and enlist the different techniques used to model the camera’s parameters for zoom (or focus) settings.     

一种磁阻式电子罗盘测试和标定方法研究

在分析了影响磁罗盘工作过程中可能存在的误差及其来源,针对罗差误差,提出一种椭圆假设补偿法与最小二乘法求补偿系数相结合的方法对电子罗盘进行标定。实验验证了最大误差达34.2°的电子罗盘系统经过标定补偿后误差降至3°以内,能基本满足一般导航系统的要求。该方法也适用于其他磁罗盘的标定。     

Wind-fetch dependence of Seasat scatterometer measurements

Abstract

This work is focused on the effects of large-scale wind-generated gravity waves on scatterometer wind-measurement accuracy. We present theoretical and experimental evidence of the important role played by the degree of wind-wave coupling in surface geometry and therefore in microwave signatures. Seasat scatterometer wind-measurement errors are analysed, and an error bias is found to be related to the degree of wind-wave development. Attention is focused on a dynamic measure of wind-wave development that characterizes the rate of energy transfer from the mean wind to the energy-carrying portion of the wave spectrum. An explanation of the bias is suggested based on the consideration of an additional component of surface scattering caused by electromagnetic-wave diffraction at the crests of individual, sufficiently steep wavelets.     

Evaluation of measurement errors in ground surface reflectance for satellite calibration

Abstract

One of the more efficient methods used for in-flight calibration of Earth resource satellites is based on measurements performed at ground level on a test site. An experimental study has been conducted in La Crau Sèche (south east France), where a calibration site for SPOT satellites is intended. The accuracy of the calibration depends, critically, on the accuracy of ground bidirectional reflectance factor (BDRF) measurements.

All of the different sources of error are analysed. These are due to two series of factors depending on the characteristics of the radiometer (electronic charac teristics, absolute calibration, angular setting of the radiometer) and of the ground surface (the spectral, spatial, angular and temporal variability of the BDRF). The relative weight of these different causes of error is determined from experimental data. This analysis shows that, besides the well-known disturbing factors such as the calibration of the radiometer and the spatial variability of the BDRF, two other factors can introduce large measurement errors: the spectral and angular variability of reflectance of the site.

This detailed analysis of the different causes of error is not only valid for the calibration of a satellite, but it can also be used to draw up guidelines for performing accurate BDRF measurements in natural conditions for any application.     

Evaluation of the Lakshadweep Sea as a site for vicarious calibration of the Ocean Colour Monitor

The uncertainty in the top-of-the-atmosphere (TOA) radiance is a result of uncertainties in aerosol components, water-leaving radiance (due to seawater constitutions) and whitecap radiance. This paper investigates the variability of these individual terms over the Arabian Sea and particularly in Lakshadweep region, to establish a site for vicarious calibration of the Ocean Colour Monitor (OCM). We found that fractional coverage of whitecap radiance is less than 0.5% for winds lower than 8 m s^?1 and its radiance contribution can be assigned to a constant value. For higher winds, the contribution from whitecap radiance to TOA radiance has to be considered along with the atmospheric stability factor. The Lakshadweep Sea, for most of the time, is characterized by a low concentration of chlorophyll-a, an oligotrophic water body and maritime aerosol.     

Evaluation methods for improving CAL materials

The main objective of the study was to develop systematic methods for improving CAL materials by comparing the five coursewares which were produced by independent authors and related to high school mathematics, science and engineering. Various kinds of evaluation were undertaken before, immediately before, during and immediately after CAL implementation; e.g. evaluators check on the drafts for courseware; evaluators check on the problems encountered in each frame while studying at the terminals; the readiness, pre- and post-tests; an anxiety scale; questionnaires for assessing any difficulties with learning in each chapter and each course; the course test; an image scale, an attitude scale and a line-connecting type of content analysis. Each courseware was evaluated and compared with others on the basis of the data analysis of tests and questionnaires as well as the learning history records, e.g., total learning duration, total number of passed frames, frequency of use of function keys, actual transitive path graph, actual average branch ratio, relative entropy in each frame and the index of educational effectiveness. A number of important evaluation items were selected by factor analysis. Finally an evaluation package instrument for improving CAL courseware were developed.     

Evaluation of non-geometric methods for visual odometry

Visual Odometry (VO) is one of the fundamental building blocks of modern autonomous robot navigation and mapping. While most state-of-the-art techniques use geometrical methods for camera ego-motion estimation from optical flow vectors, in the last few years learning approaches have been proposed to solve this problem. These approaches are emerging and there is still much to explore. This work follows this track applying Kernel Machines to monocular visual ego-motion estimation. Unlike geometrical methods, learning-based approaches to monocular visual odometry allow issues like scale estimation and camera calibration to be overcome, assuming the availability of training data. While some previous works have proposed learning paradigms to VO, to our knowledge no extensive evaluation of applying kernel-based methods to Visual Odometry has been conducted. To fill this gap, in this work we consider publicly available datasets and perform several experiments in order to set a comparison baseline with traditional techniques. Experimental results show good performances of learning algorithms and set them as a solid alternative to the computationally intensive and complex to implement geometrical techniques.     

The preliminary cross-calibration of the HY-2A calibration microwave radiometer with the Jason-1/2 microwave radiometers

This article focuses on the cross-calibration of the Haiyang-2A (HY-2A) calibration microwave radiometer (CMR) with the Jason-1 microwave radiometer (JMR) and the Jason-2 advanced microwave radiometer (AMR). The temporal trends in the CMR brightness temperatures (BTs) are compared with those of the JMR and the AMR in terms of period-averaged BT (averaged over each satellite cycle). The differences between them are observed and then corrected. The data pairs at the crossover points of HY-2A and Jason-1/2 are collected. The differences between the BTs of the CMR and those of the JMR and the AMR are further reduced by a latitude correction. The validation results show that after the time and latitude corrections, the root mean square values of the BT differences are clearly reduced by about 0.8, 0.8, and 0.6 K in the three channels, respectively. Based on the time and latitude corrected data, seven kinds of retrieval model (of vapour-induced wet tropospheric path delay, water vapour, cloud liquid, and sea surface wind speed) are built for the CMR. The results of the retrieval models based on the artificial neural networks show smaller differences from the JMR and AMR data than those of the other models.     

Evaluation of binarization methods for document images

This paper presents an evaluation of eleven locally adaptive binarization methods for gray scale images with low contrast, variable background intensity and noise. Niblack's method (1986) with the addition of the postprocessing step of Yanowitz and Bruckstein's method (1989) added performed the best and was also one of the fastest binarization methods     

Robust refinement methods for camera calibration and 3D reconstruction from multiple images

This paper proposes robust refinement methods to improve the popular patch multi-view 3D reconstruction algorithm by Furukawa and Ponce (2008). Specifically, a new method is proposed to improve the robustness by removing outliers based on a filtering approach. In addition, this work also proposes a method to divide the 3D points in to several buckets for applying the sparse bundle adjustment algorithm (SBA) individually, removing the outliers and finally merging them. The residuals are used to filter potential outliers to reduce the re-projection error used as the performance evaluation of refinement. In our experiments, the original mean re-projection error is about 47.6. After applying the proposed methods, the mean error is reduced to 2.13.     

Evaluation of emission from snow-covered ground for passive microwave remote sensing

This article investigates emission behaviour at frequencies of 18.7, 36.5 and 89 GHz and an incidence angle of 55° over a snow-covered surface at the local scale observation site in Fraser, CO, USA, using both one-layer and two-layer emission models. The models employ the matrix doubling approach to implement the radiative-transfer equation based on dense media theory and the advanced integral equation model. When compared to Ground-Based Passive Microwave Radiometer (GBMR-7) observation on 21 February 2003, both the models could simulate the observed brightness temperature well, but the polarization difference between the observation and the models was smaller for the two-layer emission model than the one-layer model. In addition, we successfully interpreted the emission magnitude and polarization separation of a snow-removed surface by incorporating a Mie scattering transition layer above the soil medium. In this work, we also demonstrated the effect of snow fraction on the brightness temperature difference at 18.7 and 36.5 GHz over a snow-covered surface with the field observation. In conclusion, we demonstrate the snow impact on soil surface with snow depth (SD) and snow fraction variation through modelling and in situ data.