By Topic

Geoscience and Remote Sensing, IEEE Transactions on

Issue 3 • Date March 2011

Filter Results

Displaying Results 1 - 25 of 28
  • [Front cover]

    Publication Year: 2011 , Page(s): C1
    Save to Project icon | Request Permissions | PDF file iconPDF (209 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Geoscience and Remote Sensing publication information

    Publication Year: 2011 , Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (41 KB)  
    Freely Available from IEEE
  • Table of contents

    Publication Year: 2011 , Page(s): 881 - 882
    Save to Project icon | Request Permissions | PDF file iconPDF (50 KB)  
    Freely Available from IEEE
  • Improved Temperature Sounding and Quality Control Methodology Using AIRS/AMSU Data: The AIRS Science Team Version 5 Retrieval Algorithm

    Publication Year: 2011 , Page(s): 883 - 907
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5158 KB) |  | HTML iconHTML  

    This paper describes the Atmospheric Infrared Sounder (AIRS) Science Team Version 5 retrieval algorithm in terms of its three most significant improvements over the methodology used in the AIRS Science Team Version 4 retrieval algorithm: the use of AIRS clear-column radiances in the entire 4.3-μm CO2 absorption band in the retrieval of temperature profiles T(p) during both day and night, with tropospheric sound ing of 15-μm CO2 observations now being used primarily in the generation of clear-column radiances R̂i for all channels; development of a new methodology to provide accurate case-by-case error estimates for retrieved geophysical parameters and for channel-by-channel clear column radiances and their use in a new approach for quality control; and an approach to provide AIRS soundings in partially cloudy conditions that does not require use of any microwave data. This new AIRS-only sounding methodology, referred to as AIRS Version 5 AO, was developed as a backup to AIRS Version 5 should the Advanced Microwave Sounding Unit (AMSU)-A instrument fail. Results are shown that compare the relative performance of the AIRS Version 4, Version 5, and Version 5 AO. Results using Version 5 retrievals in conjunction with different quality control thresholds are also shown for a recent period to demonstrate that empirical coefficients continue to be applicable in later time periods. The Goddard Data and Information Services Center (DISC) is now generating and distributing products derived using the AIRS Science Team Version 5 retrieval algorithm. This paper describes the quality control flags contained in the DISC AIRS/AMSU retrieval products and their intended use for scientific purposes. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Full-System Testing in Laboratory Conditions of an L-Band Snow Sensor System for In Situ Monitoring of Snow-Water Content

    Publication Year: 2011 , Page(s): 908 - 919
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1789 KB) |  | HTML iconHTML  

    An L-band transmitter-receiver system wireless sensor to monitor snow accumulation and snow wetness was designed, fabricated, and tested under laboratory conditions. The sensor was designed to operate at 39 discrete frequencies (39 channels) in the 1.00-1.76-GHz frequency range (0.02-GHz increments). Full-system testing of the first-generation system was conducted using commercial attenuators up to 20.0 dB to test the prototypes against design specifications. It was determined that performance was nearly optimal in the 1-1.2-GHz range. Next, snow layers of varying snow wetness were physically modeled under controlled laboratory conditions. This was achieved by adding varying amounts of water to a layer of fixed porosity foam inside a rectangular tank placed above the transmitter. The attenuation and relative phase shift of the RF signal propagating through the experimental “snowpack” and through the laboratory “atmosphere” were subsequently analyzed as a function of volumetric water content equivalent to snow wetness. Under the space and geometry limitations of the laboratory setup, the data show that the single-frequency measurements exhibit high sensitivity for wetness values up to 24%, whereas multifrequency retrieval is necessary for higher liquid water contents. Measurements from a field deployment during snowfall in January 2009 are also presented. The results suggest that there is potential for using the RF sensor to measure cumulative snowfall for short-duration events. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Two-Frequency Radar Experiments for Sounding Glacier Ice and Mapping the Topography of the Glacier Bed

    Publication Year: 2011 , Page(s): 920 - 929
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1319 KB) |  | HTML iconHTML  

    We performed airborne experiments using 150- and 450-MHz radars to measure ice thickness on the Greenland ice sheet. Our objectives were to investigate to what degree surface clutter obscures the basal echo when airborne measurements are made at different elevations and at different frequencies. We also explored interferometric techniques for processing the data to form swath measurements of ice thickness. We found that surface clutter was minimal for either frequency when operated at low aircraft elevations (500 m above the ice sheet surface) or over benign regions of the ice sheet. Because signal-to-clutter ratios were favorable, we found that we could retrieve the swath measurements of ice thickness at both frequencies using an interferometric technique. At high elevation, surface clutter degraded the 150-MHz signal, but the nadir ice thickness was still retrievable. The basal return in high-elevation 450-MHz data was detectable only after additional beam-steering techniques were applied to the data to reduce the surface clutter signal. Results suggest that interferometric cross-track ice-thickness measurements can be successfully made given a sufficient number of antenna elements driven at either 150 or 450 MHz and flown at both high and low elevations over the interior ice sheet. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Improved Biomass Estimation Using the Texture Parameters of Two High-Resolution Optical Sensors

    Publication Year: 2011 , Page(s): 930 - 948
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2072 KB) |  | HTML iconHTML  

    Accurate forest biomass estimation is essential for greenhouse gas inventories, terrestrial carbon accounting, and climate change modeling studies. Unfortunately, no universal and transferable technique has been developed so far to quantify biomass carbon sources and sinks over large areas because of the environmental, topographic, and biophysical complexity of forest ecosystems. Among the remote sensing techniques tested, the use of multisensors and the spatial as well as the spectral characteristics of the data have demonstrated a strong potential for forest biomass estimation. However, the use of multisensor data accompanied by spatial data processing has not been fully investigated because of the unavailability of appropriate data sets and the complexity of image processing techniques in combining multisensor data with the analysis of the spatial characteristics. This paper investigates the texture parameters of two high resolution (10 m) optical sensors (Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) and SPOT-5) in different processing combinations for biomass estimation. Multiple regression models are developed between image parameters extracted from the different stages of image processing and the biomass of 50 field plots, which was estimated using a newly developed "allometric model" for the study region. The results demonstrate a clear improvement in biomass estimation using the texture parameters of a single sensor (r2 = 0.854 and rmse = 38.54) compared to the best result obtained from simple spectral reflectance (r2 = 0.494) and simple spectral band ratios (r2 = 0.59). This was further improved to obtain a very promising result using the texture parameter of both sensors together (r2 = 0.897 and rmse = 32.38), the texture parameters from the principal component analysis of both sensors (r2 = 0.851 and rmse = 38.80), and the texture parameters from the av eraging of both sensors (r2 = - - 0.911 and rmse = 30.10). Improvement was also observed using the simple ratio of the texture parameters of AVNIR-2 (r2 = 0.899 and rmse = 32.04) and SPOT-5 (r2 = 0.916), and finally, the most promising result (r2 = 0.939 and rmse = 24.77) was achieved using the ratios of the texture parameters of both sensors together. This high level of agreement between the field and image data derived from the two novel techniques (i.e., combination/fusion of the multisensor data and the ratio of the texture parameters) is a very significant improvement over previous work where agreement not exceeding r2 = 0.65 has been achieved using optical sensors. Furthermore, biomass estimates of up to 500 t/ha in our study area far exceed the saturation levels observed in other studies using optical sensors. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Developing a Global Data Record of Daily Landscape Freeze/Thaw Status Using Satellite Passive Microwave Remote Sensing

    Publication Year: 2011 , Page(s): 949 - 960
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1189 KB) |  | HTML iconHTML  

    The landscape freeze-thaw (F/T) state parameter derived from satellite microwave remote sensing is closely linked to the surface energy budget, hydrological activity, vegetation growing season dynamics, terrestrial carbon budgets, and land-atmosphere trace gas exchange. Satellite microwave remote sensing is well suited for global F/T monitoring due to its insensitivity to atmospheric contamination and solar illumination effects, and its strong sensitivity to the relationship between landscape dielectric properties and predominantly frozen and thawed conditions. We investigated the utility of multifrequency and dual polarization brightness temperature (Tb) measurements from the Special Sensor Microwave Imager (SSM/I) to map global patterns and daily variations in terrestrial F/T cycles. We defined a global F/T classification domain by examining biophysical cold temperature constraints to vegetation growing seasons. We applied a temporal change classification algorithm based on a seasonal thresholding scheme to classify daily F/T states from time series Tb measurements. The SSM/I F/T classification accuracy was assessed using in situ air temperature measurements from the global WMO weather station network. A single-channel classification of 37 GHz, V-polarization Tb time series provided generally improved performance over other SSM/I frequencies, polarizations and channel combinations. Mean annual F/T classification accuracies were 92.2 ±0.8 [SD] % and 85.0 ±0.7 [SD] % for respective SSM/I time series of P.M. and A.M. orbital nodes over the global domain and a 20-year (1988-2007) satellite record. The resulting database provides a continuous and relatively long-term record of daily F/T dynamics for the global biosphere with well-defined accuracy. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Pairwise Orthogonal Transform for Spectral Image Coding

    Publication Year: 2011 , Page(s): 961 - 972
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1463 KB) |  | HTML iconHTML  

    Spectral transforms are widely used for the codification of remote-sensing imagery, with the Karhunen-Loêve transform (KLT) and wavelets being the two most common transforms. The KLT presents a higher coding performance than the wavelets. However, it also carries several disadvantages: high computational cost and memory requirements, difficult implementation, and lack of scalability. In this paper, we introduce a novel transform based on the KLT, which, while obtaining a better coding performance than the wavelets, does not have the mentioned disadvantages of the KLT. Due to its very small amount of side information, the transform can be applied in a line-based scheme, which particularly reduces the transform memory requirements. Extensive experimental results are conducted for the Airborne Visible/Infrared Imaging Spectrometer and Hyperion images, both for lossy and lossless and in combination with various hyperspectral coders. The results of the effects on Reed Xiaoli anomaly detection and k-means clustering are also included. The theoretical and experimental evidences suggest that the proposed transform might be a good replacement for the wavelets as a spectral decorrelator in many of the situations where the KLT is not a suitable option. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Denoising of Hyperspectral Imagery Using Principal Component Analysis and Wavelet Shrinkage

    Publication Year: 2011 , Page(s): 973 - 980
    Cited by:  Papers (29)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (940 KB) |  | HTML iconHTML  

    In this paper, a new denoising method is proposed for hyperspectral data cubes that already have a reasonably good signal-to-noise ratio (SNR) (such as 600 : 1). Given this level of the SNR, the noise level of the data cubes is relatively low. The conventional image denoising methods are likely to remove the fine features of the data cubes during the denoising process. We propose to decorrelate the image information of hyperspectral data cubes from the noise by using principal component analysis (PCA) and removing the noise in the low-energy PCA output channels. The first PCA output channels contain a majority of the total energy of a data cube, and the rest PCA output channels contain a small amount of energy. It is believed that the low-energy channels also contain a large amount of noise. Removing noise in the low-energy PCA output channels will not harm the fine features of the data cubes. A 2-D bivariate wavelet thresholding method is used to remove the noise for low-energy PCA channels, and a 1-D dual-tree complex wavelet transform denoising method is used to remove the noise of the spectrum of each pixel of the data cube. Experimental results demonstrated that the proposed denoising method produces better denoising results than other denoising methods published in the literature. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Subspace-Based Optimization Method for Inverse Scattering Problems Utilizing Phaseless Data

    Publication Year: 2011 , Page(s): 981 - 987
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (595 KB) |  | HTML iconHTML  

    This paper presents a novel variation of the subspace-based optimization method (SOM) to reconstruct the scatterer's permittivity profile by utilizing only phaseless measurements (i.e., intensity data of the total field with no phase information). Based on spectrum analysis, the contrast source is partitioned into two orthogonally complementary portions (viz., deterministic and ambiguous portions). The original SOM's procedure to obtain the deterministic portion has to be modified in order to accommodate the lack of phase information while the ambiguous portion is determined by another nonlinear optimization. The numerical results presented for the two examples of scatterers under transverse-electric incidence have demonstrated that the proposed method is capable of reconstructing complicated patterns with rapid rate of convergence and robust immunity to noise. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Inversion of a Radiative Transfer Model for Estimating Forest LAI From Multisource and Multiangular Optical Remote Sensing Data

    Publication Year: 2011 , Page(s): 988 - 1000
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1252 KB) |  | HTML iconHTML  

    This paper presents a new forest leaf area index (LAI) inversion method from multisource and multiangle data combined with a radiative transfer model and the strategy of -means clustering and artificial neural network (ANN). Four scenes of Landsat-5 Thematic Mapper (L5TM) and Beijing-1 small satellite multispectral sensors (BJ1) images, acquired at different times, were selected to construct multisource and multiangle image data in this study. Considering a vertical distribution of forest LAI from both overstory and understory, a hybrid model of the invertible forest reflectance model (INFORM) was used to support the retrieval of forest LAI to eliminate the dependence of understory vegetation. The simulated data from INFORM outputs, added with a random noise, were first clustered by -means method, and were then trained by ANN to obtain the inversion model for each group (cluster). Next, the inversion model was applied to the different combinations of multiangle data to retrieve the forest LAI. Finally, a validation of inverted results with Moderate Resolution Imaging Spectroradiometer LAI product and field measurements was conducted. The experimental results indicate that the accuracy of the inverted forest LAI can be improved through the addition of observation angle data, if the quality of the image data is ensured. The inversion accuracy of LAI with the multiangle image data is improved by 30% compared to the average accuracy of the inverted LAI with the single angle data after considering the addition of random noise to the ANN training data. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Improving Subpixel Classification by Incorporating Prior Information in Linear Mixture Models

    Publication Year: 2011 , Page(s): 1001 - 1013
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1454 KB) |  | HTML iconHTML  

    This paper introduces a new subpixel classification algorithm that incorporates prior information from known class proportions in the linear mixture model. The prior information is expressed in terms of the occurrence probabilities of each land-cover class in a pixel. The use of different error cost functions that measure the similarity between the model-derived mixed spectra and the observed spectra is also investigated. Under these assumptions, the maximum a posteriori (MAP) methodology is employed for optimization. Finally, optimization problems under the MAP criteria for different error cost functions are formulated and solved. Our numerical results illustrate that the performance of the subpixel classification algorithm can be significantly improved by incorporating prior information from the known class proportions. Furthermore, there are marginal differences in accuracy when different error cost functions are used. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Batch-Mode Active-Learning Methods for the Interactive Classification of Remote Sensing Images

    Publication Year: 2011 , Page(s): 1014 - 1031
    Cited by:  Papers (47)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (728 KB) |  | HTML iconHTML  

    This paper investigates different batch-mode active-learning (AL) techniques for the classification of remote sensing (RS) images with support vector machines. This is done by generalizing to multiclass problem techniques defined for binary classifiers. The investigated techniques exploit different query functions, which are based on the evaluation of two criteria: uncertainty and diversity. The uncertainty criterion is associated to the confidence of the supervised algorithm in correctly classifying the considered sample, while the diversity criterion aims at selecting a set of unlabeled samples that are as more diverse (distant one another) as possible, thus reducing the redundancy among the selected samples. The combination of the two criteria results in the selection of the potentially most informative set of samples at each iteration of the AL process. Moreover, we propose a novel query function that is based on a kernel-clustering technique for assessing the diversity of samples and a new strategy for selecting the most informative representative sample from each cluster. The investigated and proposed techniques are theoretically and experimentally compared with state-of-the-art methods adopted for RS applications. This is accomplished by considering very high resolution multispectral and hyperspectral images. By this comparison, we observed that the proposed method resulted in better accuracy with respect to other investigated and state-of-the art methods on both the considered data sets. Furthermore, we derived some guidelines on the design of AL systems for the classification of different types of RS images. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The SMOS L3 Mapping Algorithm for Sea Surface Salinity

    Publication Year: 2011 , Page(s): 1032 - 1051
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3003 KB) |  | HTML iconHTML  

    The Soil Moisture and Ocean Salinity (SMOS) mission launched in November 2009 will provide, for the first time, satellite observations of sea surface salinity (SSS). At level 3 (L3) of the SMOS processing chain, the large amount of SSS data obtained by the satellite will be summarized in gridded products with the aim of synthesizing the information and reducing the error of individual SSS observations. In this paper, we present the algorithm adopted by the CP34 SMOS processing center to generate the SMOS L3 products and discuss the choices adopted. The algorithm is based on optimal statistical interpolation. This method needs the following: 1) the prescription of a background field; 2) a prefiltering procedure to reduce the data set size; 3) the definition of a suitable correlation model; and 4) the characterization of the observational error statistics. For the present initial stage, a monthly climatology is chosen as the best background field. The spatiotemporal correlations between the departures from the climatology are described using a bivariate Gaussian function. The correlation model parameters are obtained by fitting the function to the realistic ocean model data. The sensitivity experiments show that an accurate correlation model that permits local variations in the correlation parameters is the best option. The observational error statistics (bias, variance, and correlation) are addressed from the results of the SMOS level-2 processor simulator. Finally, several sensitivity experiments show that a bad prescription of observational errors in the L3 algorithm does result in a dramatic impact on the generation of L3 products. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The Seoul Water Vapor Radiometer for the Middle Atmosphere: Calibration, Retrieval, and Validation

    Publication Year: 2011 , Page(s): 1052 - 1062
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1231 KB) |  | HTML iconHTML  

    A new ground-based 22-GHz radiometer, designed to deliver middle atmospheric water vapor profiles over the mid-latitudinal Asian continent, was designed at the University of Bern, Switzerland. In this paper, we outline the calibration and retrieval concepts of the instrument, which has been in operation in Seoul (37.32° N, 126.57° E), Korea, since November 2006. In addition, a quality assessment of the delivered profiles is presented, through the validation with the data from the Microwave Limb Sounder (MLS) onboard the Aura satellite. The differences between the Seoul Water Vapor Radiometer and Aura MLS are better than 2 % between 1 and 0.2 hPa, and they decline nearly linearly to -14.5 % between 0.2 and 0.01 hPa. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Analysis of RFI Issue Using the CAROLS L-Band Experiment

    Publication Year: 2011 , Page(s): 1063 - 1070
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (481 KB) |  | HTML iconHTML  

    In this paper, different methods are proposed for the detection and mitigation of the undesirable effects of radio-frequency interference (RFI) in microwave radiometry. The first of these makes use of kurtosis to detect the presence of non-Gaussian signals, whereas the second imposes a threshold on the standard deviation of brightness temperatures in order to distinguish natural-emission variations from RFI. Finally, the third approach is based on the use of a threshold applied to the third and fourth Stokes parameters. All these methods have been applied and tested, with the cooperative airborne radiometer for ocean and land studies radiometer operating in the L-band, on the data acquired during airborne campaigns made in the spring of 2009 over the southwest of France. The performance of each approach, or of two combined approaches, is analyzed with our database. We thus show that the kurtosis method is well suited to detect pulsed RFI, whereas the method based on the second moment of brightness temperatures seems to be better suited to detect continuous-wave RFI in airborne brightness-temperature measurements. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Investigation on Doppler Shift and Bandwidth of Backscattered Echoes From a Composite Sea Surface

    Publication Year: 2011 , Page(s): 1071 - 1081
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (353 KB) |  | HTML iconHTML  

    In the general framework of the second-order small-slope approximation (SSA) (SSA-II), Doppler shifts of backscattered fields from time-varying sea surfaces are predicted at small and moderate incidence angles. The composite sea surface is modeled as a superposition of large-scale gravity waves and small-scale ripples. Here, the elevation of the large-scale surface component, on which each small facet travels along a closed orbit under the condition of the first-order approximation, is described by the coordinates of the small facets. The predicted Doppler shifts are compared with the results obtained by the small perturbation method (SPM), the geometrical optics method, the first-order SSA (SSA-I), and the two-scale scattering method (TSM). We can find that the predicted Doppler shifts for SPM and SSA-I in copolarized configuration are insensitive to the polarization state. However, the results obtained by SSA-II are consistent with those obtained by TSM and yield significant differences between HH and VV polarizations. Spectrum bandwidth is mainly induced by sea-surface orbit motions. In this paper, the formula of the spectrum bandwidth for the scattered echoes from the composite sea surface is also derived on the basis of TSM. The predicted bandwidths are compared with the Monte Carlo simulated results and the measured data. Furthermore, the dependences of the Doppler shift and the bandwidth on the parameters, such as the polarization, wind speed, radar frequency, etc., are also discussed. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Modeling the Configuration of HF Electrical Antennas for Deep Bistatic Subsurface Sounding

    Publication Year: 2011 , Page(s): 1082 - 1091
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1255 KB) |  | HTML iconHTML  

    In the frame of the European Space Agency's 2016 ExoMars mission, the Electromagnetic Investigation of the SubSurface (EISS) ground-penetrating radar has been designed and developed to perform deep soundings of the Martian subsurface from the surface. The EISS is designed to take advantage of the potential for bistatic radar investigations of the Martian subsurface between the fixed station (Lander) and the mobile platform (rover) and to characterize the 3-D structure and stratigraphy of the subsurface at depths ranging from 100 m to a few kilometers out to a 1-km radius around the lander. The EISS makes use of an electric dipole antenna made of two identical 35-m resistively loaded monopoles to transmit (and also receive in a monostatic mode) the high-frequency signal. However, the EISS's most innovative capability is its potential for bistatic operation, made possible by the accommodation of a small magnetic sensor on the rover (as initially planned for the ExoMars mission) which can measure the magnetic field (all three components) of the received waves whatever the direction and orientation of the rover. The aim of this paper is to show that the two monopoles of the antenna must be deployed on the surface in nearly opposite directions but not aligned to ensure good volume coverage around the transmitter. This paper is based on Finite Difference in Time Domain (FDTD) electromagnetic simulations. The simulated data have been used to study the impact of the angle between these two monopoles on the instrument performance. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Ship Surveillance With TerraSAR-X

    Publication Year: 2011 , Page(s): 1092 - 1103
    Cited by:  Papers (39)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1777 KB) |  | HTML iconHTML  

    Ship detection is an important application of global monitoring of environment and security. In order to overcome the limitations by other systems, surveillance with satellite synthetic aperture radar (SAR) is used because of its possibility to provide ship detection at high resolution over wide swaths and in all weather conditions. A new X-band radar onboard the TerraSAR-X (TS-X) satellite gives access to spatial resolution as fine as 1 m. In this paper, first results on the combined use of TS-X ship detection, automatic identification system (AIS), and satellite AIS (SatAIS) is presented. The AIS system is an effective terrestrial method for tracking vessels in real time typically up to 40 km off the coast. SatAIS, as a space-based system, allows almost global coverage for monitoring of ships since not all ships operate their AIS and smaller ships are not equipped with AIS. The system is considered to be of cooperative nature. In this paper, the quality of TS-X images with respect to ship detection is evaluated, and a first assessment of its performance for ship detection is given. The velocity of a moving ship is estimated using complex TS-X data. As test cases, images were acquired over the North Sea, Baltic Sea, Atlantic Ocean, and Pacific Ocean in Stripmap mode with a resolution of 3 m at a coverage of 30 km 100 km. Simultaneous information on ship positions was available from TS-X and terrestrial as well as SatAIS. First results on the simultaneous superposition of SatAIS and high-resolution radar images are presented. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Adaptive Model-Based Decomposition of Polarimetric SAR Covariance Matrices

    Publication Year: 2011 , Page(s): 1104 - 1113
    Cited by:  Papers (46)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3010 KB) |  | HTML iconHTML  

    Previous model-based decomposition techniques are applicable to a limited range of vegetation types because of their specific assumptions about the volume scattering component. Furthermore, most of these techniques use the same model, or just a few models, to characterize the volume scattering component in the decomposition for all pixels in an image. In this paper, we extend the model-based decomposition idea by creating an adaptive model-based decomposition technique, allowing us to estimate both the mean orientation angle and a degree of randomness for the canopy scattering for each pixel in an image. No scattering reflection symmetry assumption is required to determine the volume contribution. We examined the usefulness of the proposed decomposition technique by decomposing the covariance matrix using the National Aeronautics and Space Administration/Jet Propulsion Laboratory Airborne Synthetic Aperture Radar data at the C-, L-, and P-bands. The randomness and mean orientation angle maps generated using our adaptive decomposition significantly improve the physical interpretation of the scattering observed at the three different frequencies. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • On the Discrimination of Radar Signatures of Atmospheric Gravity Waves and Oceanic Internal Waves on Synthetic Aperture Radar Images of the Sea Surface

    Publication Year: 2011 , Page(s): 1114 - 1126
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1603 KB) |  | HTML iconHTML  

    Synthetic aperture radar (SAR) images acquired over the ocean frequently show sea wave-like patterns that have wavelengths well above those of ocean surface waves and that are sea surface signatures of oceanic internal waves (OIWs) or of atmospheric gravity waves (AGWs). However, it is often difficult to decide whether they result from the first or the second kind of waves, which has led many investigators to misinterpret SAR images of the sea surface. Based on solitary wave and radar imaging theories of AGWs and OIWs, we present criteria that help distinguish between them. However, there are cases where these criteria, which are based solely on the shape and structure of the features visible on the SAR images, yield ambiguous results. In these cases, one must resort to additional information on the generation of AGWs and OIWs, which are listed in this paper. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Impact of DEM-Assisted Coregistration on High-Resolution SAR Interferometry

    Publication Year: 2011 , Page(s): 1127 - 1143
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2035 KB) |  | HTML iconHTML  

    Image alignment is a crucial step in synthetic aperture radar (SAR) interferometry. Interferogram formation requires images to be coregistered with an accuracy of better than a few tenths of a resolution cell to avoid significant loss of phase coherence. In conventional interferometric precise coregistration methods for full-resolution SAR data, a 2-D polynomial of low degree is usually chosen as warp function, and the polynomial parameters are estimated through least squares fit from the shifts measured on image windows. In case of rough topography or long baselines, the polynomial approximation may become inaccurate, leading to local misregistrations. These effects increase with spatial resolution of the sensor. An improved elevation-assisted image-coregistration procedure can be adopted to provide better prediction of the offset vectors. This approach computes pixel by pixel the correspondence between master and slave acquisitions by using the orbital data and a reference digital elevation model (DEM). This paper aims to assess the performance of this procedure w.r.t. the “standard” one based on polynomial approximation. Analytical relationships and simulations are used to evaluate the improvement of the DEM-assisted procedure w.r.t. the polynomial approximation as well as the impact of the finite vertical accuracy of the DEM on the final coregistration precision for different resolutions and baselines. The two approaches are then evaluated experimentally by processing high-resolution SAR data provided by the COnstellation of small Satellites for the Mediterranean basin Observation (COSMO/SkyMed) and TerraSAR-X missions, acquired over mountainous areas in Italy and Tanzania, respectively. Residual-range pixel offsets and interferometric coherence are used as quality figure. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Strategy of Data Processing for GPS Rover and Reference Receivers Using Different Sampling Rates

    Publication Year: 2011 , Page(s): 1144 - 1149
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (788 KB) |  | HTML iconHTML  

    In Global Positioning System (GPS) applications, the double-difference (DD) model is often employed, which requires that the reference station and the rover receivers adopt the same sampling rate. On the premise of the need fulfillment, could the existing static receivers of Global Navigation Satellite System networks with a low sampling rate be used as the references for the rover with a high sampling rate? If feasible, how to process such data? In this paper, an integrated processing scheme is presented to deal with such data in the posterior mode, i.e., after initialization, both the single-difference (SD) and the DD models will be employed when synchronous data are available, while only the SD model will be used when only the rover receiver data are obtained. The deviations of the results obtained with the SD model from those with the DD model at the synchronous epoch might be considered as the accumulated systematical errors, which could be linearly interpolated into individual nonsynchronous epochs of that interval. This strategy takes full advantage of all available observations, rather than discarding the nonsynchronous GPS data, and it provides a promising application for the precise kinematic point positioning. The total expense of the surveying mission will be greatly reduced by adopting the low-sampling-rate receivers of the Continuously Operating Reference Station or the other similar GPS network as the reference stations. A data set of an airplane flight experiment was processed to verify the new algorithm, and the results revealed that the positioning accuracy could reach a centimeter level. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The Seafloor: A Key Factor in Lidar Bottom Detection

    Publication Year: 2011 , Page(s): 1150 - 1157
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (811 KB) |  | HTML iconHTML  

    The environmental factors that determine the ability of airborne lidar bathymetry (ALB) to detect the seafloor are not well understood; however, water clarity is often considered the single factor for detection. A comparison of data from two different ALB systems (LADS-MKII and SHOALS-3000) of a small area offshore Gerrish Island, Maine, USA shows a striking correlation (95% overlap) in areas of no bottom detection that is independent of the tide status, the date of collection and the orientation of the survey flight. The laser measurements from the two ALB systems are compared to acoustic measurements of depth, seafloor slope, and backscatter from a Kongsberg EM3002 echosounder. The comparison shows that in water depths deeper than 7 m, there is a close correlation between the ALB detection patterns and bottom features. The study results indicate that lack of bottom detection by ALB does not necessarily indicate that water depths deeper than the surrounding areas have lidar strong bottom detection. No bottom detection in the study area actually reflects a change in bottom characteristics. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

Aims & Scope

 

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.

 

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Antonio J. Plaza
University of Extremadura