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Geoscience and Remote Sensing, IEEE Transactions on

Issue 6 • Date June 2009

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Displaying Results 1 - 25 of 33
  • [Front cover]

    Page(s): C1
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    Freely Available from IEEE
  • IEEE Transactions on Geoscience and Remote Sensing publication information

    Page(s): C2
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    Freely Available from IEEE
  • Table of contents

    Page(s): 1573 - 1574
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    Freely Available from IEEE
  • Variability of Passive Microwave Radiometric Signatures at Different Spatial Resolutions and Its Implication for Rainfall Estimation

    Page(s): 1575 - 1584
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (531 KB) |  | HTML iconHTML  

    Analysis of precipitation radar (PR) and Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI) data collected from the TRMM satellite shows that rainfall inhomogeneity, as represented by the coefficient of variation (CV), depends on a spatial scale, i.e., the CV appears to be nearly constant at all rain rates within the field of view (FOV) of the TMI 37-GHz channel, while it decreases with rain rate at lower spatial resolutions, such as the FOV sizes of the low-frequency TMI channels (10.7 and 19.4 GHz). It is known that the brightness temperature (Tb) for a low-frequency channel decreases with increasing rainfall inhomogeneity for a given rain rate. As such, more inhomogeneous rainfall at low rain rates leads to a lower Tb compared with that of a FOV with homogeneous rainfall; however, less inhomogeneous rainfall at high rain rates tends to produce a Tb similar to that of homogeneous rainfalls. These results indicate that the observed radiometric signatures of low-frequency channels at low spatial resolutions are characterized by a larger response range and smaller variability than those at a higher spatial resolution. Based on the observational characteristics of the TMI and PR data sets, we performed synthetic retrievals of rainfalls, employing a Bayesian retrieval methodology at different retrieval resolutions corresponding to the FOV sizes of the TMI channels at 10.7, 19.4, and 37 GHz. Comparisons of the rainfalls retrieved at the different resolutions and their temporal and regional averages show that the systematic bias resulting from the rainfall inhomogeneity is smaller in the lower resolution data than in their higher resolution counterparts. We note that such low-resolution rainfall retrievals are not expected to describe the instantaneous features of rain fields; however, they could be useful for climatological estimates at large temporal and spatial scales. View full abstract»

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  • Refined Physical Retrieval of Integrated Water Vapor and Cloud Liquid for Microwave Radiometer Data

    Page(s): 1585 - 1594
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1040 KB) |  | HTML iconHTML  

    Monitoring atmospheric water is essential for the understanding of the dynamic processes of the atmosphere and for the assessment of wave-propagation properties. Microwave radiometers, in combination with a thermal infrared channel, have the potential to fulfill these tasks. This paper is focused on the surface-based system TROWARA with microwave channels at 21.3 and 31.5 GHz. TROWARA has been used for tropospheric water measurements at Bern since 1994 together with a standard meteo station. So far, emphasis has been put on integrated water vapor (IWV) measurements, particularly for climate studies, but integrated liquid water (ILW) has been retrieved as well. We report on methodological advances with the data analysis. First, the original algorithm was replaced by a new statistical retrieval based on the simulations of TROWARA data using radiosonde profiles. Second, in a physical refinement, the cause of the variable ILW bias has been identified, and a method for its reduction to the level of 0.001 to 0.005 mm has been developed and tested. The bias is mainly a result of the variable water-vapor influence on absorption at 31 GHz. The bias correction also influences the IWV retrieval. The refined physical retrieval includes the temperature dependence of cloud absorption based on a recent dielectric model of water. The three algorithms (original, new, and refined) have been compared for two years of data. The applications of the refined algorithm are focused on physical processes, such as the development of supercooled clouds. Future advances will include precipitation measurements. View full abstract»

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  • A Wind and Rain Backscatter Model Derived From AMSR and SeaWinds Data

    Page(s): 1595 - 1606
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1120 KB) |  | HTML iconHTML  

    The SeaWinds scatterometer was originally designed to measure wind vectors over the ocean by exploiting the relationship between wind-induced surface roughening and the normalized radar backscatter cross section. Rain can degrade scatterometer wind estimation; however, the simultaneous wind/rain (SWR) algorithm was developed to enable SeaWinds to simultaneously retrieve wind and rain rate data. This algorithm is based on colocating data from the Precipitation Radar on the Tropical Rainfall Measuring Mission and SeaWinds on QuikSCAT. This paper develops a new wind and rain radar backscatter model for SWR using colocated data from the Advanced Microwave Scanning Radiometer (AMSR) and SeaWinds aboard the Advanced Earth Observing Satellite II. This paper accounts for rain height in the model in order to calculate surface rain rate from the integrated rain rate. The performance of SWR using the new wind/rain model is measured by comparison of wind vectors and rain rates to the previous SWR algorithm, AMSR rain rates, and National Center for Environmental Prediction numerical weather prediction winds. The new SWR algorithm produces more accurate rain estimates and improved winds, and detects rain with a low false alarm rate. View full abstract»

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  • Building an Automated Integrated Observing System to Detect Sea Surface Temperature Anomaly Events in the Florida Keys

    Page(s): 1607 - 1620
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2365 KB) |  | HTML iconHTML  

    Satellite-derived sea surface temperature (SST) images have had limited applications in near-shore and coastal environments due to inadequate spatial resolution, incorrect geocorrection, or cloud contamination. We have developed a practical approach to remove these errors using Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS) 1-km resolution data. The objective was to improve the accuracy of SST anomaly estimates in the Florida Keys and to provide the best quality (in particular, high temporal and spatial resolutions) SST data products for this region. After manual navigation of over 47 000 AVHRR images (1993-2005), we implemented a cloud-filtering technique that differs from previously published image processing methods. The filter used a 12-year climatology and plusmn3-day running SST statistics to flag cloud-contaminated pixels. Comparison with concurrent ( plusmn0.5 h) data from the SEAKEYS in situ stations in the Florida Keys showed near-zero bias errors (<0.05degC) in the weekly anomaly for SST anomalies between -3degC and 3degC, with standard deviations <0.5degC. The cloud filter was implemented using Interactive Data Language for near-real-time processing of AVHRR and MODIS data. The improved SST products were used to detect SST anomalies and to estimate degree-heating weeks (DHWs) to assess the potential for coral reef stress. The mean and anomaly products are updated weekly, with periodic updates of the DHW products, on a Web site. The SST data at specific geographical locations were also automatically ingested in near real time into National Oceanic and Atmospheric Administration's (NOAA) Integrated Coral Observing Network Web-based application to assist in management and decision making through a novel expert system tool (G2) implemented at NOAA. View full abstract»

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  • Seabed Segmentation Using Optimized Statistics of Sonar Textures

    Page(s): 1621 - 1631
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1840 KB) |  | HTML iconHTML  

    In this paper, we propose and compare two supervised algorithms for the segmentation of textured sonar images, with respect to seafloor types. We characterize seafloors by a set of empirical distributions estimated on texture responses to a set of different filters. Moreover, we introduce a novel similarity measure between sonar textures in this feature space. Our similarity measure is defined as a weighted sum of Kullback-Leibler divergences between texture features. The weight setting is twofold. First, each filter is weighted according to its discrimination power: The computation of these weights are issued from a margin maximization criterion. Second, an additional weight, evaluated as an angular distance between the incidence angles of the compared texture samples, is considered to take into account sonar-image acquisition process that leads to a variability of the backscattered value and of the texture aspect with the incidence-angle range. A Bayesian framework is used in the first algorithm where the conditional likelihoods are expressed using the proposed similarity measure between local pixel statistics and the seafloor prototype statistics. The second method is based on a variational framework as the minimization of a region-based functional that involves the similarity between global-region texture-based statistics and the predefined prototypes. View full abstract»

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  • A Comparison of the Impact of QuikScat and WindSat Wind Vector Products on Met Office Analyses and Forecasts

    Page(s): 1632 - 1640
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (749 KB) |  | HTML iconHTML  

    Several studies have demonstrated that retrievals of wind vectors from the WindSat polarimetric radiometer are of sufficient quality to be considered for assimilation in operational numerical weather prediction models. In this paper, WindSat data are used in a state-of-the-art global meteorological analysis and forecasting system. Each wind vector contains a directional ambiguity and so is assimilated in a similar way to that of scatterometer data. The forecast impact of using analyses containing information from WindSat data was investigated for a period during August and September of 2005, when a large number of tropical cyclones were present. Forecast errors were reduced in the surface pressure fields, and the average improvement across the forecast range was found to be 1.0%. This is comparable to the improvement of 1.1% found in the same fields when winds were assimilated from the QuikScat scatterometer. The impact on tropical cyclone tracks in the forecasts was also studied. The scatterometer improved (reduced) the track errors markedly by 25% in the analyses. When impacts across the forecast range out to five days were also included, the improvement was found to be 8%. In contrast, the assimilation of WindSat data improved the analysis track errors by 7%, although this figure was found to be 10% across the complete forecast range. View full abstract»

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  • A Numerical Study of the Retrieval of Sea Surface Height Profiles From Low Grazing Angle Radar Data

    Page(s): 1641 - 1650
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (960 KB) |  | HTML iconHTML  

    A numerical study of the retrieval of sea surface height profiles from low grazing angle radar observations is described. The study is based on a numerical method for electromagnetic scattering from 1-D rough sea profiles, combined with the ldquoimproved linear representationrdquo of Creamer for simulating weakly nonlinear sea surface hydrodynamics. Numerical computations are performed for frequencies from 2975 to 3025 MHz so that simulated radar pulse returns are achieved. The geometry utilized models a radar with an antenna height of 14 m, observing the sea surface at ranges from 520 to 1720 m. The low grazing angles of this configuration produce significant shadowing of the sea surface, and standard analytical theories of sea scattering are not directly applicable. Three approaches for retrieving sea height profile information are compared. The first method uses a statistical relationship between the surface height and the computed radar cross sections versus range (an incoherent measurement). A second method uses the phase difference between scattering measurements in two vertically separated antennas (ldquovertical interferometry) in the retrieval. The final technique retrieves height profiles from variations in the apparent Doppler frequency (coherent measurements) versus range and requires that time-stepped simulations be performed. The relative advantages and disadvantages of each of the three approaches are examined and discussed. View full abstract»

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  • C-Band Scatterometer Measurements of Multiyear Sea Ice Before Fall Freeze-Up in the Canadian Arctic

    Page(s): 1651 - 1661
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (775 KB) |  | HTML iconHTML  

    Backscatter signatures of multiyear sea ice (MYI) during the late summer and early fall season before the fall freeze-up in the Canadian Arctic archipelago (CAA) have been obtained through the use of a ship-based polarimetric scatterometer. The device operates in C-band, and measurements were conducted in swaths from incidence angles of 20 deg-60deg. Three characteristic sites on MYI floes were investigated in the high Arctic and the central Arctic regions. In situ snow and sea-ice thermophysical data were collected at each site in conjunction with local scatterometer measurements. The thermophysical data were subsequently analyzed using dielectric modeling techniques and coupled with the backscattering measurements (sigmadeg). Observed backscatter values and ratios were found to be in agreement with literature data, with volumetric scattering as the dominant scattering mechanism. View full abstract»

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  • Empirically Adopted IEM for Retrieval of Soil Moisture From Radar Backscattering Coefficients

    Page(s): 1662 - 1672
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (926 KB) |  | HTML iconHTML  

    The integral equation model (IEM) is considered as a promising algorithm for soil moisture retrieval from active microwave data over bare soil and sparsely vegetated conditions. However, the soil dielectric constant is implicitly embedded in the complicated IEM; inversion of soil moisture is often accomplished through iteration and is thus computationally expensive, particularly when it is applied to retrieve soil moisture from active microwave data on a large scale. To simplify the inversion process of soil moisture directly from the active microwave data, basic math functions were adopted to fit the simulation results of the original IEM so that the radar backscattering coefficient becomes an explicit function of soil dielectric constant or the soil dielectric constant is an explicit function of radar backscattering coefficient. Soil moisture is then calculated directly from radar backscattering coefficient without iteration. We called this model empirically adopted IEM (EA-IEM). The accuracy of the EA-IEM to the original IEM and its applicability are analyzed through three processes: model intercomparison, sensitivity analysis, and model comparison with in situ measurements. The average differences of backscattering coefficients between the EA-IEM and the original IEM are 0.14 dB for HH-polarization and 0.12 dB (Gaussian correlation function) and 0.2 dB (exponential correlation function) for VV-polarization. The sensitivity of soil moisture variation is examined under the consideration of absolute and relative calibration errors. A comparison between the soil moisture estimated and the measurements is performed, and the root-mean-square (rms) error is found to be 3.4%, suggesting that the EA-IEM performs well in these real cases. All these analyses indicate that the EA-IEM is a good representative of the original IEM and can be used to retrieve soil moisture under the tested range of model parameters: incidence angles between 10deg and 60- - deg, soil dielectric constants between 4 and 42, surface rms height from 4 to 31 mm, and correlation length from 50 to 250 mm. View full abstract»

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  • Interactive Hyperspectral Image Visualization Using Convex Optimization

    Page(s): 1673 - 1684
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1416 KB) |  | HTML iconHTML  

    In this paper, we propose a new framework to visualize hyperspectral images. We present three goals for such a visualization: 1) preservation of spectral distances; 2) discriminability of pixels with different spectral signatures; 3) and interactive visualization for analysis. The introduced method considers all three goals at the same time and produces higher quality output than existing methods. The technical contribution of our mapping is to derive a simplified convex optimization from a complex nonlinear optimization problem. During interactive visualization, we can map the spectral signature of pixels to red, green, and blue colors using a combination of principal component analysis and linear programming. In the results, we present a quantitative analysis to demonstrate the favorable attributes of our algorithm. View full abstract»

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  • An Adaptive and Fast CFAR Algorithm Based on Automatic Censoring for Target Detection in High-Resolution SAR Images

    Page(s): 1685 - 1697
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (796 KB) |  | HTML iconHTML  

    An adaptive and fast constant false alarm rate (CFAR) algorithm based on automatic censoring (AC) is proposed for target detection in high-resolution synthetic aperture radar (SAR) images. First, an adaptive global threshold is selected to obtain an index matrix which labels whether each pixel of the image is a potential target pixel or not. Second, by using the index matrix, the clutter environment can be determined adaptively to prescreen the clutter pixels in the sliding window used for detecting. The G 0 distribution, which can model multilook SAR images within an extensive range of degree of homogeneity, is adopted as the statistical model of clutter in this paper. With the introduction of AC, the proposed algorithm gains good CFAR detection performance for homogeneous regions, clutter edge, and multitarget situations. Meanwhile, the corresponding fast algorithm greatly reduces the computational load. Finally, target clustering is implemented to obtain more accurate target regions. According to the theoretical performance analysis and the experiment results of typical real SAR images, the proposed algorithm is shown to be of good performance and strong practicability. View full abstract»

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  • A Method for Assessing Spectral Image Utility

    Page(s): 1698 - 1706
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (634 KB) |  | HTML iconHTML  

    The utility of an image is an attribute that describes the ability of that image to satisfy performance requirements for a particular application. This paper establishes the context for spectral image utility by first reviewing traditional approaches to assessing panchromatic image utility and then discussing differences for spectral imagery. We define spectral image utility for the subpixel target detection application as the area under the receiver operating curve summarized across a range of target detection scenario parameters. We propose a new approach to assessing the utility of any spectral image for any target type and size and detection algorithm. Using six airborne hyperspectral images, we demonstrate the sensitivity of the assessed image utility to various target detection scenario parameters and show the flexibility of this approach as a tool to answer specific user information requirements. The results of this investigation lead to a better understanding of spectral image information vis-a-vis target detection performance and provide a step toward quantifying the ability of a spectral image to satisfy information exploitation requirements. View full abstract»

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  • A Multiobjective Genetic SVM Approach for Classification Problems With Limited Training Samples

    Page(s): 1707 - 1718
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (898 KB) |  | HTML iconHTML  

    In this paper, a novel method for semisupervised classification with limited training samples is presented. Its aim is to exploit unlabeled data available at zero cost in the image under analysis for improving the accuracy of a classification process based on support vector machines (SVMs). It is based on the idea to augment the original set of training samples with a set of unlabeled samples after estimating their label. The label estimation process is performed within a multiobjective genetic optimization framework where each chromosome of the evolving population encodes the label estimates as well as the SVM classifier parameters for tackling the model selection issue. Such a process is guided by the joint minimization of two different criteria which express the generalization capability of the SVM classifier. The two explored criteria are an empirical risk measure and an indicator of the classification model sparseness, respectively. The experimental results obtained on two multisource remote sensing data sets confirm the promising capabilities of the proposed approach, which allows the following: (1) taking a clear advantage in terms of classification accuracy from unlabeled samples used for inflating the original training set and (2) solving automatically the tricky model selection issue. View full abstract»

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  • Two-Dimensional Contrast Source Inversion Method With Phaseless Data: TM Case

    Page(s): 1719 - 1736
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3274 KB) |  | HTML iconHTML  

    In this paper, two new approaches are presented for the solution of electromagnetic inverse scattering problems when amplitude-only data are available. The proposed techniques are based on a customized version, which are the so-called contrast source inversion (CSI) and multiplicative regularized CSI (MRCSI) methods. In the proposed approaches, denoted as the phaseless-data (PD)-CSI and the PD-MRCSI, only the term of the cost functional concerning the mismatch between the measured and estimated field data (i.e., the data equation) has been properly redefined. Moreover, the back-projection algorithm has been modified to provide an initial solution ensuring the rapid convergence of the optimization procedures and avoid the reconstruction of false solutions. A set of representative results concerning numerical as well as experimental tests is reported to show the accuracy of the proposed amplitude-only reconstruction approaches. View full abstract»

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  • Automatic Generation of Seamline Network Using Area Voronoi Diagrams With Overlap

    Page(s): 1737 - 1744
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (966 KB) |  | HTML iconHTML  

    The mosaicking of orthoimages has been used to cover a large geographic region for various applications ranging from environmental monitoring to disaster management. However, existing mosaicking methods mainly focus on the generation of seamlines between two adjacent orthoimages. In this paper, we present a novel approach based on the use of a seamline network formed by a novel area Voronoi diagrams with overlap and the use of effective mosaic polygons (EMPs) to define the pixels of each orthoimage for the final mosaic. The generated seamline network is global based and is also optimized after refinement. It gives an effective partitioning for the regions of all orthoimages to form EMPs. The partitioning is unique, seamless, and has no redundancy. The algorithm is parallel, and the EMP of each orthoimage only has relation to orthoimages which have overlaps with it. It can ensure the flexibility and efficiency of mosaicking, without an intermediate process and independent of the sequence of the image composite. The experimental results obtained from the mosaicking of 40 color orthoimages demonstrate considerable potential for generating a seamline network automatically and effectively. This is extremely useful when a seamless mosaic is required to cover a large geographic region. View full abstract»

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  • A Study of the Shapiro–Wilk Test for the Detection of Pulsed Sinusoidal Radio Frequency Interference

    Page(s): 1745 - 1751
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1191 KB) |  | HTML iconHTML  

    The performance of the Shapiro-Wilk (S-W) test of normality for the detection of pulsed sinusoidal radio frequency interference (RFI) in microwave radiometry is analyzed. The study is motivated by the fact that the S-W test has been shown in the statistical literature to be effective in detecting a wide variety of non-Gaussian signal types. The basic properties of the S-W test statistic are reviewed, and the implementation of the test in digital hardware is discussed. Because the properties of the test statistic are difficult to obtain analytically, Monte Carlo simulations are utilized to compute performance. Results show that the test can provide reasonable performance in detecting pulsed sinusoidal RFI and that quantization of data has only a minimal impact on the sensitivity achieved. Detection performance is also compared with that of the kurtosis test for normality. It is shown that the S-W test produces comparable but degraded sensitivity compared to that of the kurtosis test in most cases while avoiding the ldquoblind spotrdquo associated with the kurtosis test for pulsed interferers having 50% duty cycle. Test performance is also shown to be improved if a priori knowledge of expected RFI pulse lengths is incorporated. View full abstract»

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  • An Assessment of a Ka-Band Radar Interferometer Mission Accuracy Over Eurasian Rivers

    Page(s): 1752 - 1765
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1870 KB) |  | HTML iconHTML  

    The Water Elevation Recovery satellite mission is dedicated to the determination of land surface water extent, elevation, and slope using a Ka-band radar interferometer (KaRIn) as its primary instrument. Determining these parameters to the accuracy desired for hydrologic applications is challenging. The scientific objectives of the mission have been set up to 10 cm for the height budget and 10 murad (1 cm/1 km) for the slope budget. In this paper, we implement a Virtual Mission simulation and use it to examine the measurement performances for three case studies in Europe: a relatively small river such as the Meuse in Northern Western Europe, the Lena river in Russia, one of the major Siberian rivers, and Lake Leman in Western Europe. We simulate KaRIn data with the associated instrument and geophysical error sources and implement ground processing techniques to go from the original raw data to science data. We examine the impact of external errors in detail and implement calibration techniques that rely on the use of ancillary topographic data, such as the Shuttle Radar Topography Mission digital elevation model (DEM). We find that the impact of external errors can be reduced to a few centimeters. The random error budget can also be reduced below 10 cm by means of appropriate processing. The scientific requirements of the mission are shown to be met for all cases. View full abstract»

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  • Surface-Based Polarimetric C-Band Microwave Scatterometer Measurements of Snow During a Chinook Event

    Page(s): 1766 - 1776
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (887 KB) |  | HTML iconHTML  

    This paper presents a case study of C-band backscatter observations of snow during a Chinook event. A surface-based C-band polarimetric data set collected in February 2006 is used to contrast the polarimetric response to sampled conditions of bare frozen ground, cold snow-covered ground, and snow during a Chinook event. Chinook activity is inherently spatially and temporally variable across the region in winter and produces considerable spatial variability of snow-cover physical properties associated with snow-water-equivalent (SWE) estimates. A temporal analysis of polarimetric backscatter sensed during a Chinook-induced ablation event on February 27, 2006 is used to describe the associated changes in snow conditions and scattering mechanisms. Analysis reveals that the polarimetric surface-based C-band scatterometer data respond to changes in snow parameters associated with the specific ground and snow conditions and to the temporal Chinook ablation event. Use of the copolarizations, cross-polarization, depolarization ratio, copolarization ratio, complex copolarization correlation coefficient, and the copolarized phase difference information show promise in describing changes in snow physical parameters, differing ground and snow conditions, and transitional ablation events, based on differing scattering mechanisms. This paper infers that an increase in volume scattering and fluctuations in surface scattering during the Chinook ablation event may be associated with specific physical changes such as density, crystal structure, and permittivity caused by wind speed. This paper has implications for remotely sensed estimations of snow-covered area (SCA) and SWE. Association of SCA and SWE with backscatter coefficients is not explicit in this paper; however, changes in SWE and snow properties are inferentially linked to changes in backscatter. View full abstract»

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  • Cassini RADAR Sequence Planning and Instrument Performance

    Page(s): 1777 - 1795
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (841 KB) |  | HTML iconHTML  

    The Cassini RADAR is a multimode instrument used to map the surface of Titan, the atmosphere of Saturn, the Saturn ring system, and to explore the properties of the icy satellites. Four different active mode bandwidths and a passive radiometer mode provide a wide range of flexibility in taking measurements. The scatterometer mode is used for real aperture imaging of Titan, high-altitude (around 20 000 km) synthetic aperture imaging of Titan and Iapetus, and long range (up to 700 000 km) detection of disk integrated albedos for satellites in the Saturn system. Two SAR modes are used for high- and medium-resolution (300-1000 m) imaging of Titan's surface during close flybys. A high-bandwidth altimeter mode is used for topographic profiling in selected areas with a range resolution of about 35 m. The passive radiometer mode is used to map emission from Titan, from Saturn's atmosphere, from the rings, and from the icy satellites. Repeated scans with differing polarizations using both active and passive data provide data that can usefully constrain models of surface composition and structure. The radar and radiometer receivers show very good stability, and calibration observations have provided an absolute calibration good to about 1.3 dB. Relative uncertainties within a pass and between passes can be even smaller. Data are currently being processed and delivered to the planetary data system at quarterly intervals one year after being acquired. View full abstract»

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  • Through-the-Wall Surveillance With Millimeter-Wave LFMCW Radars

    Page(s): 1796 - 1805
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1323 KB) |  | HTML iconHTML  

    The use of millimeter-wave radars allows a weight and size reduction of circuits and antennas, which is an important characteristic for Through-the-Wall Surveillance (TWS) applications. Furthermore, when using the millimeter-wave band, a large amount of bandwidth can be easily transmitted, given that the relative bandwidth is smaller. This leads to a high range resolution that allows for the discrimination of several targets that are very close in range, e.g., inside a room. The azimuth resolution is also improved due to the availability in this band of directive antennas with small dimensions. This paper studies the feasibility of using a millimeter-wave linear frequency-modulated continuous-wave radar in a TWS application. A TWS experiment in a real scenario has been done to demonstrate the validity of the theoretical analysis. View full abstract»

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  • Cloud and Rain Effects on AltiKa/SARAL Ka-Band Radar Altimeter—Part I: Modeling and Mean Annual Data Availability

    Page(s): 1806 - 1817
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1438 KB) |  | HTML iconHTML  

    The AltiKa project, developed by the French Centre National d'Etudes Spatiales, is based on a wideband Ka-band altimeter (35.75 GHz). The technical characteristic of the instrument will offer higher performance both in terms of spatial and vertical resolutions that will lead to the improved observation of ice, coastal areas, inland waters, and wave height. An Indian Space Research Organization satellite, called Satellite with ARgos and AltiKa, will embark the AltiKa altimeter. The launch is scheduled at the end of 2010. The major drawback of Ka-band use is the attenuation of the radar signal by atmospheric liquid water. Clouds and rain effects will thus be a strong constraining factor, because the altimeter link budget imposes an attenuation of less than 3 dB. The impact of rain and clouds on Ka-band altimeter data is analyzed and quantified using an analytical model that computes AltiKa waveforms in the presence of rain or clouds. The results are then used to quantify the waveform attenuation and distortion, as well as the error induced on the altimeter geophysical parameter estimates. Because of the nonlinearity of attenuation relations, the impact of clouds/rain depends more on the cloud/rain variability within the altimeter footprint than on the mean characteristics, which makes correction using coincident rain or cloud data difficult. Small rain cell and small dense clouds can thus strongly distort the waveforms and lead to erroneous geophysical parameter estimates. The probability of 20 Hz and 1-s averaged data loss are computed from the model results and from cloud and rain climatologies. On a global scale, about 3.5% of the 20-Hz data will be lost because of rain and clouds and 2.5% of the 1-s averaged data. However, the probability strongly varies over the global ocean and can exceed 10% in the Tropics. View full abstract»

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  • Cloud and Rain Effects on AltiKa/SARAL Ka-Band Radar Altimeter—Part II: Definition of a Rain/Cloud Flag

    Page(s): 1818 - 1826
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (493 KB) |  | HTML iconHTML  

    The main instrument of the French-Indian AltiKa/SARAL mission scheduled for launch in 2010 is the Ka-band AltiKa altimeter. The high attenuation due to atmospheric water (liquid or vapor) at this frequency band is the major drawback of the use of Ka-band. In part I of this paper, the impact of rain/clouds on Ka-band data and on the accuracy of the estimates of the geophysical parameters has been analyzed and quantified using an analytical model of waveform. Waveform distortion and errors on the geophysical parameters can be significant particularly for small dense clouds and rain cells. It is thus necessary to flag the data potentially affected by rain and clouds. The use of a single channel for AltiKa prevents the use of the classical dual-frequency rain flag used for Topex or Jason altimeters, and requires the definition of a new flag based on the altimeter signal alone. Past studies showed that clouds and rain are characterized by sharp coherent along-track fluctuations of the off-nadir angle estimates. The new flagging algorithm is based on the analysis of the variations of this parameter by the Matching Pursuit (MP) algorithm. MP allows the decomposition of a signal into a few salient features or atoms chosen from a dictionary of elementary functions. The dictionary is here defined by the wavelet decomposition of the signal. The method has been tested on an ensemble of AltiKa passes simulated for cloudy, rainy, and cloud/rain-free situations. The false alarm rate is almost nil while the detection performances are better than 90% at a range error of 5 cm and significant wave height error of 20 cm. The flag can easily be adapted to other altimeters' data and has been used to flag several Jason-1 passes. The comparison to the operational dual-frequency flag shows that the MP flag performs better in detecting range errors and waveforms distortion, while its performances are inferior in detecting samples attenuated by rain. View full abstract»

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.

 

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Antonio J. Plaza
University of Extremadura