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  • Articles  (2,784)
  • 2010-2014  (2,784)
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  • IEEE Geoscience and Remote Sensing Letters  (1,190)
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  • 1
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    Training Sample Selection for Space-Time Adaptive Processing in Heterogeneous Environments (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: As training samples are not always identically distributed with the clutter in the cell under test (CUT) in heterogeneous environments, the estimated clutter covariance matrix for space-time adaptive processing (STAP) is not accurate, which degrades the performance of STAP. To improve the performance of STAP in heterogeneous environments, this letter proposes a novel training sample selection algorithm to estimate the covariance matrix. Based on the subaperture smoothing techniques, subapertures' covariance matrices are estimated, which are used to measure the similarities between the clutter covariance matrix of the CUT and the clutter covariance matrices of the training samples. Training samples whose clutter covariance matrices are similar to that of the CUT are selected, leading to a better estimation of the clutter covariance matrix, and the performance of STAP improves. Experimental results confirm the performance of the proposed algorithm.
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  • 2
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    Weakly Supervised Learning for Target Detection in Remote Sensing Images (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: In this letter, we develop a novel framework of leveraging weakly supervised learning techniques to efficiently detect targets from remote sensing images, which enables us to reduce the tedious manual annotation for collecting training data while maintaining the detection accuracy to large extent. The proposed framework consists of a weakly supervised training procedure to yield the detectors and an effective scheme to detect targets from testing images. Comprehensive evaluations on three benchmarks which have different spatial resolutions and contain different types of targets as well as the comparisons with traditional supervised learning schemes demonstrate the efficiency and effectiveness of the proposed framework.
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  • 3
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    Scaling Transform Method for Remotely Sensed FAPAR Based on FAPAR-P Model (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: Climate and land–atmosphere models rely on accurate land-surface parameters, such as the fraction of absorbed photosynthetically active radiation (FAPAR). It is known that FAPAR values retrieved from remote-sensing images suffer from scaling effects. Scaling transformation aims to derive accurate FAPAR values at a specific scale from values at other scales. In this letter, the scaling-effect mechanism and the scale-transformation algorithm are derived using a Taylor series expansion method based on the FAPAR model based on $P$ after simplification. The scaling algorithm was validated in the Heihe River Basin. The multiscale FAPAR values are inverted from 5-, 50-, and 100-m hyperspectral reflectance data. The scale-transformation formula was used, and the results agreed well with actual values.
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  • 4
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    Joint Sparsity Model for Multilook Hyperspectral Image Unmixing (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: Recent work on hyperspectral image (HSI) unmixing has addressed the use of overcomplete dictionaries by employing sparse models. In essence, this approach exploits the fact that HSI pixels can be associated with a small number of constituent pure materials. However, unlike traditional least-squares-based methods, sparsity-based techniques do not require a preselection of endmembers and are thus able to simultaneously estimate the underlying active materials along with their respective abundances. In addition, this perspective has been extended so as to exploit the spatial homogeneity of abundance vectors. As a result, these techniques have been reported to provide improved estimation accuracy. In this letter, we present an alternative approach that is able to relax, yet exploit, the assumption of spatial homogeneity by introducing a model that captures both similarities and differences between neighboring abundances. In order to validate this approach, we analyze our model using simulated as well as real hyperspectral data acquired by the HyMap sensor.
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  • 5
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    A Robust Delaunay Triangulation Matching for Multispectral/Multidate Remote Sensing Image Registration (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: A novel dual-graph-based matching method is proposed in this letter particularly for the multispectral/multidate images with low overlapping areas, similar patterns, or large transformations. First, scale invariant feature transform based matching is improved by normalizing gradient orientations and maximizing the scale ratio similarity of all corresponding points. Next, Delaunay graphs are generated for outlier removal, and the candidate outliers are selected by comparing the distinction of Delaunay graph structures. In order to bring back the inliers removed in Delaunay triangulation matching iterations and to exclude the remaining outliers, the recovery strategy equipped with the dual graph of Delaunay is explored. Inliers located in the corresponding Voronoi cells are recovered to the residual sets. The experimental results demonstrate the accuracy and robustness of the proposed algorithm for various representative remote sensing images.
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  • 6
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    Theoretical Analysis and Verification of Time Variation of Background Ionosphere on Geosynchronous SAR Imaging (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: Geosynchronous synthetic aperture radar (SAR) (GEO SAR) has the characteristic of long integration time; thus, the time-freezing model assumption of background ionosphere for traditional low Earth orbit (LEO) SAR no longer holds in GEO SAR. Furthermore, the background ionosphere variation within the integration time cannot be omitted either. In this letter, the variation of total electron content within integration time is analyzed and described in detail by using polynomial approximation, and a new GEO SAR signal model influenced by background ionosphere is also proposed. In view of this novel model, the analytical expression of image shift and defocusing phase error are derived in the first place. Then, a quantitative analysis for the image shift and image defocusing in the range and azimuth directions is conducted, and the performance bounds of time-varying parameters of background ionosphere effects on focusing are obtained. Finally, the U.S. Total Electron Content measured data are used to verify the theoretical results of background ionosphere effects on GEO SAR focusing.
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  • 7
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    Automatic Data Quality Control of Observations in Wireless Sensor Network (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: Emerging multisource earth observation technologies represented by wireless sensor network (WSN) technology are widely used in land surface observation and simulation studies. Consequently, data quality control of massive observation data has brought challenges to researchers. This letter describes a comprehensive approach applied to automatic data quality control of WSN data. First, summarize the quality element of WSN observation data which can be achieved through automated methods by analyzing the characteristics of WSN observation data, and develop a decision algorithm for each quality element. Then, associate the data type and algorithm through data quality control rules. Finally, establish an automatic data quality control system based on data quality control rules. As a matter of fact, this system has run for one and a half years and processed more than 500 million observation data records without human intervention. Application results show that this method system can effectively control the data quality of WSN data automatically.
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  • 8
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    An Adaptive Density-Based Model for Extracting Surface Returns From Photon-Counting Laser Altimeter Data (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: The Ice, Cloud and land Elevation Satellite-2 (ICESat-2) mission of the National Aeronautics and Space Administration is scheduled to launch in 2017. This upcoming mission aims to provide data to determine the temporal and spatial changes of ice sheet elevation, sea ice freeboard, and vegetation canopy height. A photon-counting lidar onboard ICESat-2 yields point clouds resulting from surface returns and noise. In support of the ICESat-2 mission, this letter derives an adaptive density-based model that is capable of detecting the ground surface and vegetation canopy in photon-counting laser altimeter data. Based on results from point clouds generated by a first principle simulation and those observed by the Multiple Altimeter Beam Experimental Lidar, the ground and canopy returns can be reliably extracted using the proposed approach. Further study on performance assessment shows that smoother surfaces will result in improved accuracy of ground height estimation. In addition, the proposed detection approach has better performance in environments with lower noise, although the performance evaluation metric $F$ -measure does not vary significantly over a range of noise rates (0.5–5 MHz). This proposed approach is generally applicable for surface and canopy finding from photon-counting laser altimeter data.
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  • 9
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    A New Self-Training-Based Unsupervised Satellite Image Classification Technique Using Cluster Ensemble Strategy (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: This letter addresses the problem of unsupervised land-cover classification of remotely sensed multispectral satellite images from the perspective of cluster ensembles and self-learning. The cluster ensembles combine multiple data partitions generated by different clustering algorithms into a single robust solution. A cluster-ensemble-based method is proposed here for the initialization of the unsupervised iterative expectation–maximization (EM) algorithm which eventually produces a better approximation of the cluster parameters considering a certain statistical model is followed to fit the data. The method assumes that the number of land-cover classes is known. A novel method for generating a consistent labeling scheme for each clustering of the consensus is introduced for cluster ensembles. A maximum likelihood classifier is henceforth trained on the updated parameter set obtained from the EM step and is further used to classify the rest of the image pixels. The self-learning classifier, although trained without any external supervision, reduces the effect of data overlapping from different clusters which otherwise a single clustering algorithm fails to identify. The clustering performance of the proposed method on a medium resolution and a very high spatial resolution image have effectively outperformed the results of the individual clustering of the ensemble.
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  • 10
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    Rotation-Invariant Object Detection in Remote Sensing Images Based on Radial-Gradient Angle (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: To improve the detection precision in complicated backgrounds, a novel rotation-invariant object detection method to detect objects in remote sensing images is proposed in this letter. First, a rotation-invariant feature called radial-gradient angle (RGA) is defined and used to find potential object pixels from the detected image blocks by combining with radial distance. Then, a principal direction voting process is proposed to gather the evidence of objects from potential object pixels. Since the RGA combined with the radial distance is discriminative and the voting process gathers the evidence of objects independently, the interference of the backgrounds is effectively reduced. Experimental results demonstrate that the proposed method outperforms other existing well-known methods (such as the shape context-based method and rotation-invariant part-based model) and achieves higher detection precision for objects with different directions and shapes in complicated background. Moreover, the antinoise performance and parameter influence are also discussed.
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  • 11
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    Impulse Borehole Radar Imaging Based on Compressive Sensing (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: A novel data acquisition and imaging method based on compressive sensing is utilized for impulse borehole radar (IBR). With the sparse transform that we present for IBR systems, only 50% or even less samples are needed to be collected and transmitted to reconstruct the target space, which reduces the sampling rate and data transmission rate of IBR systems. The simulation and experiment results show that the proposed method is more robust in noise environment and the reconstructed target spaces have less artifacts compared with the solutions of the traditional Stolt migration method.
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  • 12
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    Gaussian Conditional Random Fields for Aggregation of Operational Aerosol Retrievals (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: We present a Gaussian conditional random field model for the aggregation of aerosol optical depth (AOD) retrievals from multiple satellite instruments into a joint retrieval. The model provides aggregated retrievals with higher accuracy and coverage than any of the individual instruments while also providing an estimation of retrieval uncertainty. The proposed model finds an optimal temporally smoothed combination of individual retrievals that minimizes the root-mean-squared error of AOD retrieval. We evaluated the model on five years (2006–2010) of satellite data over North America from five instruments (Aqua and Terra MODIS, MISR, SeaWiFS, and the Ozone Monitoring Instrument), collocated with ground-based Aerosol Robotic Network ground-truth AOD readings, clearly showing that the aggregation of different sources leads to improvements in the accuracy and coverage of AOD retrievals.
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  • 13
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    Compressed Sensing of a Remote Sensing Image Based on the Priors of the Reference Image (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: Basic compressed-sensing algorithms for image reconstructions mainly deal with the computation of sparse regularization. Remote sensing applications often have multisource or multitemporal images whose different components are acquired separately. Therefore, this letter considers the reconstruction of a remote sensing image using an auxiliary image from another sensor or another time as the reference. For this application, a new compressed-sensing object function is developed that uses a reference image as a prior. In the new model, the sparsity constraints in the transform domain come from the target image, and the gradient priors in the spatial domain come from the auxiliary reference image. The hybrid regularization is optimized by basing the algorithm on the Bregman split method. The proposed method shows better performances when compared with other three popular compressed-sensing algorithms.
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  • 14
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    Electromagnetic Scattering From Vegetation Cylindrical Components (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: An approach for calculating electromagnetic scattering, valid in the near- and far-field regions, from a homogeneous finite cylindrical vegetation sample at oblique incidence is presented and discussed. The proposed solution will help in taking into account multiple scattering effects due to plant structure. It does not require assumptions on the dimensions or electromagnetic properties of the vegetation cylinder.
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  • 15
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    A Three-Component Fisher-Based Feature Weighting Method for Supervised PolSAR Image Classification (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: This letter presents a feature weighting method for polarimetric synthetic aperture radar (PolSAR) image classification. Appropriate feature weighting is essential for obtaining accurate classifications but so far has remained an open research problem. We propose in this letter a supervised three-component feature weighting method based on the Fisher linear discriminant. Fisher linear discriminant method is used to calculate a coefficient for each feature. Then, these coefficients are modified according to a three-component scattering power decomposition model, combining both physical and statistical scattering characteristics to adapt them for the particular scattering mechanisms inherent in PolSAR data and assigned to the coherency matrix to enhance the discriminating ability of the features. Freeman decomposition and Wishart classifier are used to classify the PolSAR image. The effectiveness of the proposed method is demonstrated by experiments NASA/JPL AIRSAR L-band and CSA Radarsat-2 C-band PolSAR images of the San Francisco area.
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  • 16
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    Surface Roughness and Microwave Surface Scattering of High-Resolution Imaging Radar (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: This study aims to understand the effects of spatial resolution on the surface backscattering characteristics of polarimetric radar. Surface scattering models based on approximate methods are formulated by the roughness second-order statistics to obtain a closed-form expression for the radar scattering response. Most studies have been carried out based on the roughness parameters of the infinite surface. In this letter, we propose the roughness autocorrelation function of truncated surfaces for a more realistic description of the roughness parameters of high-resolution radar. The use of roughness parameters for a truncated surface in the scattering model is pertinent to explain the dependence of the backscattering coefficient on the spatial resolution. Simulation results indicate that the traditional computation of the surface backscattering based on the autocovariance function of an infinite surface leads to an underestimation of the backscattering signature of the high-resolution radar.
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  • 17
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    On the Estimation of Boreal Forest Biomass From TanDEM-X Data Without Training Samples (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: Boreal forests play an important part in the climate system, and estimates of the biomass are important also from an economic point of view. In this letter, forest aboveground biomass is estimated from bistatic TanDEM-X data, a Lidar digital elevation model (DEM), and the interferometric water cloud model, without using training samples to calibrate the model. The forest was characterized by allometric relations for area fill (vegetation fraction) and height versus stem volume, and stem volume versus biomass. Biomass was estimated for 202 forest stands at least 1 ha large at the forest test site of Remningstorp, Sweden, from 18 bistatic TanDEM-X acquisitions with a relative root-mean-square error (RMSE) of 16%–32%. TanDEM-X acquisitions with a height of ambiguity around 80 m resulted in the best results. A multitemporal combination resulted in a relative RMSE of 17%. This result is comparable with the retrieval error obtained in a previous study when training the model using a set of known forest stands.
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  • 18
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    Finding Leaves in the Forest: The Dual-Wavelength Echidna Lidar (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: The dual-wavelength Echidna lidar is a portable ground-based full-waveform terrestrial scanning lidar for characterization of fine-scale forest structure and biomass content. While scanning, the instrument records the full time series of returns at a half-nanosecond rate from two coaligned 5-ns pulsed lasers at 1064 and 1548 nm wavelengths. Leaves absorb more strongly at 1548 nm compared to stems, allowing discrimination of forest composition at milliradian scales from the ground to the forest canopy. This work describes the instrument design and data products and demonstrates the power of two wavelength lidar to clearly distinguish leaves from woody material with preliminary field data from the Sierra Nevada National Forest.
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  • 19
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    Classification of Hyperspectral Image Based on Sparse Representation in Tangent Space (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: In many real-world problems, data always lie in a low-dimensional manifold. Exploiting the manifold can greatly enhance the discrimination between different categories. In this letter, we propose a classification framework based on sparse representation to directly exploit the underlying manifold. Specifically, using the tangent plane to approximate the local manifold of each test sample, the proposed method classifies the sample by sparse representation in tangent space. Unlike several existing sparse-representation-based classification methods, which sparsely represent the test sample itself, the proposed method sparsely represents the local manifold of the test sample by tangent plane approximation. Therefore, it goes beyond the sample itself and is more robust to kinds of variations confronted in hyperspectral image (HSI) such as illustration differences and spectrum mixing. Experimental results show that the proposed algorithm outperforms several state-of-the-art methods for the classification of HSI with limited training samples.
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  • 20
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    Backscattering Feature Analysis and Recognition of Civilian Aircraft in TerraSAR-X Images (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: This letter first analyzes the scattering features of civilian aircraft (CA) using high-resolution TerraSAR-X images of the Hong Kong International Airport based on the electromagnetic scattering theory. The main stable scattering features are found to be salient points. Then, a salient point vector (SPV) is proposed to describe the salient points. By adding two relaxation variables to the matching process, the SPV becomes both translationally and rotationally invariant over a certain orientation range. In addition, a recognition scheme is designed to validate the scattering analysis and the SPV descriptor. Finally, 43 test chips are collected from another TerraSAR-X image acquired in November 2013 in the same location with similar imaging parameters. The test chips are applied to validate the analysis, the SPV descriptor, and the recognition scheme. The results of the experiment indicate that the recognition rate of the Boeing 747 CA reaches 80% and that the scattering features of the aircraft are rotationally invariant to within at least 5 $^{circ}$ . This research verifies the potential application of CA monitoring using high-resolution synthetic aperture radar images.
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  • 21
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    Nonlocal SAR Interferometric Phase Filtering Through Higher Order Singular Value Decomposition (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: Interferometric phase filtering is an indispensable step to obtain accurate measurement of digital elevation model and surface displacement. In the case of low-correlation or complicated topography, traditional phase filtering methods fail in balancing noise elimination and phase preservation, which leads to inaccurate interferometric phase. A new nonlocal interferometric phase filtering method taking advantage of higher order singular value decomposition (HOSVD) is proposed in this letter. For each pixel of the interferometric phase, a 3-D data array is established, and shrinkage is applied after HOSVD. A Wiener filter is used to improve the denoising performance in the end. Simulated and real data are employed to validate that the proposed method outperforms other traditional methods and some of the state-of-the-art nonlocal methods.
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  • 22
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    Multilayer CFAR Detection of Ship Targets in Very High Resolution SAR Images (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: This letter proposes a new ship target detection method for very high resolution (VHR) synthetic aperture radar (SAR) images based on multilayer constant false alarm rate (CFAR). First, combined with log-normal distribution, a multilayer CFAR method is designed to overcome the holes and the fracture in the traditional detected results. This method can retain more details of ships and takes much less time than the traditional CFAR method for VHR SAR images. Second, based on a priori knowledge of ships, we use the sliding window to remove the false alarm targets. Finally, In order to measure the size and shape of a ship, we extract the outline of a ship and fill it by a level set method. Experimental results, carried out on real SAR images, demonstrate that the proposed approach outperforms the previous one in terms of the detection ratio of pixels instead of the number of ships.
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  • 23
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    Potential of Operational High Spatial Resolution Near-Infrared Remote Sensing Instruments for Snow Surface Type Mapping (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: Snow changes its morphology permanently from the moment a snow flake touches the ground. Under the influence of meteorological factors such as temperature, humidity, and wind, snow grains form complex structures of ice bonds enclosing variable portions of air. The characteristics of such structures are important for the formation of snow avalanches. Certain snow types such as surface hoar, ice crusts, or windblown snow play a major role in the formation of weak layers and slabs, which are precondition for dangerous slab avalanches. The reflection properties of snow depend on the optical equivalent grain size of the ice particles that constitute the snow cover. High spatial resolution remote sensing instruments with near-infrared (0.7–1.4 $muhbox{m}$ ) bands are able to detect such differences in the optical reflection of snow. We use normalized difference index band ratios from a spaceborne and an airborne remote sensing instrument to distinguish and map different snow-surface types in the neighborhood of Davos, Switzerland, enabling a valuable visualization of the spatial variability of the snow surface.
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  • 24
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    An Adaptive Pixon Extraction Technique for Multispectral/Hyperspectral Image Classification (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: Hyperspectral imaging has gained significant interest in the past few decades, particularly in remote sensing applications. The considerably high spatial and spectral resolution of modern remotely sensed data often provides more accurate information about the scene. However, the complexity and dimensionality of such data, as well as potentially unwanted details embedded in the images, may act as a degrading factor in some applications such as classification. One solution to this issue is to utilize the spatial–spectral features to extract segments before the classification step. This preprocessing often leads to better classification results and a considerable decrease in computational time. In this letter, we propose a Pixon-based image segmentation method, which benefits from a preprocessing step based on partial differential equation to extract more homogenous segments. Moreover, a fast algorithm has been presented to adaptively tune the required parameters used in our Pixon-based schema. The acquired segments are then fed into the support vector machine classifier, and the final thematic class maps are produced. Experimental results on multi/hyperspectral data are encouraging to apply the proposed Pixons for classification.
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    Background Suppression and Strong Phase Codes in Incoherent Scatter Lag Profile Inversion (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: High range resolution incoherent scatter spectra are routinely measured by means of alternating codes and random codes. These radar transmission modulations are cycles of phase-coded pulses whose lagged products form complementary code sets, enabling decoding of incoherent scatter lag profiles by means of matched filtering. Numerically optimized near-perfect modulations are potential successors of the alternating codes and random codes because they enable new measurement techniques, such as so-called multipurpose experiments. The near-perfect modulations cannot be decoded by means of matched filtering, but they are designed for analysis by means of lag profile inversion. Two improvements to this combination are introduced in this letter: Suppression of background noise correlations is implemented as part of lag profile inversion, removing the need for dedicated background measurements, and the concept of strong phase codes is adopted to near-perfect modulations, allowing one to neglect the receiver impulse response in lag profile inversion.
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    Effect of Land-Cover Type on the SMAP Active/Passive Soil Moisture Downscaling Algorithm Performance (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: A brightness temperature ( $hbox{Tb}$ ) downscaling algorithm based on the synergy between active and passive microwave observations is tested using airborne data that simulate the Soil Moisture Active Passive (SMAP) mission of the National Aeronautics and Space Administration scheduled for launch in January 2015. While this algorithm has been adopted as the baseline for SMAP, it has only been tested on a limited variety of land uses and vegetation types. Consequently, this study evaluates the SMAP active/passive downscaling algorithm using data with varied conditions. The SMAP experiment conducted in Australia has been used for this purpose. The algorithm was applied over several 9 km $times$ 9 km pixels with different land covers, so as to evaluate the accuracy of this algorithm under different heterogeneity levels. Brightness temperatures were downscaled from 9 to 3 km (approximating the resolution ratio of SMAP downscaling approach) across nine days of data. Results show that the root-mean-square error of $hbox{Tb}$ in grassland could meet the 2.4-K target accuracy of SMAP, while in cropping, it was 2 K higher than the target. The influence from water bodies was also assessed and confirmed to have a significant impact if not removed prior to downscaling.
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    Sliding Spotlight and TOPS SAR Data Processing Without Subaperture (2011)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2011-11-01
    Description: During the data acquisition of a sliding spotlight or terrain observation by progressive scan (TOPS) synthetic aperture radar (SAR), the steering of the antenna main beam increases the azimuth bandwidth but could result in the azimuth signal aliasing in the Doppler domain. To remove the aliasing, one has used a subaperture method. In this letter, we show a focusing scheme without the use of the subaperture for both sliding spotlight and TOPS SARs. In doing so, we eliminated the obvious increase in data volume or the subaperture division by choosing the pulse repetition frequency that is only 20% greater than the instantaneous bandwidth. The method was incorporated with an available imaging algorithm and then used to process simulated and collected data of the sliding spotlight and TOPS SARs. Well-focused results without aliasing were obtained.
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    Inexpensive FM-CW Radar for Boundary-Layer Precipitation Studies (2011)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2011-11-01
    Description: A vertically pointing C-band (5.8-GHz) frequency-modulated (FM) continuous-wave Doppler radar was developed for less than U.S. $6000, which can estimate the Doppler velocity power spectra from 20 to 300 m above the ground with a 5-m resolution. Three key design elements kept the costs low. First, the data acquisition system (DAS) commanded a direct digital synthesizer to start the FM sweep and then collected all voltage samples. This architecture insured phase coherence between the transmit FM sweep and the sampled voltages, which is critical for the Doppler processing that detects target phase changes over several successive FM sweeps. Second, a 5-m range resolution was achieved by increasing the FM bandwidth to over 36 MHz and decreasing the DAS sample rate to 500 kHz, enabling the use of an inexpensive DAS. Third, the Doppler processing at each range was achieved using two fast Fourier transforms (FFTs), i.e., a range FFT converted FM sweep voltages into in-phase and quadrature voltages I and Q at each range, and a Doppler FFT converted I and Q voltages from consecutive sweeps into the Doppler velocity power spectra. Observations show precipitation variability at 1-s and 5-m resolutions in the lowest 300 m of the atmosphere.
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    Support-Vector-Based Hyperspectral Anomaly Detection Using Optimized Kernel Parameters (2011)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2011-11-01
    Description: In this letter, a method to optimally determine the kernel bandwidth of the Gaussian radial basis function (RBF) kernel for support vector (SV)-based hyperspectral anomaly detection is presented. In this method, the support of a local background distribution is first nonparametrically learned by a technique called SV data description (SVDD). The SVDD optimally models an enclosing hypersphere around the local background data in a high-dimensional feature space associated with the Gaussian RBF kernel. Any test pixel that lies outside this hypersphere surrounding the local background is considered an anomaly and, hence, a possible target pixel. Considerable improvement in detection performance due to kernel parameter optimization can be seen in the simulation results when the algorithm is applied to hyperspectral images.
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    An Automated Approach to Detect Oceanic Eddies From Satellite Remotely Sensed Sea Surface Temperature Data (2011)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2011-11-01
    Description: Cyclonic (anticyclonic) oceanic eddies drive local upwelling (downwelling), leaving footprints in the sea surface temperature (SST) field as local extremes. Satellite-measured SST images can therefore be used to obtain information of the characteristics of oceanic eddies. Remotely sensed measurements represent very large data sets, both spatially and temporally. Manual eddy detection and analysis are thus practically impossible. In this letter, an automated scheme for eddy detection from remote sensing SST data is presented. The method is based on the analysis of velocity fields derived from SST measurements (thermal-wind velocity field). Using the geometric features of the velocity field, we can identify positions of eddy centers and derive eddy size, intensity, path, and lifetime. The scheme is applied to a realistic remotely sensed SST data set in a strong eddy activity region: Kuroshio Extension region.
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    Impact of Gypsum on Electromagnetic Properties of Desert Soils (2011)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2011-11-01
    Description: Radar remote sensing of soil requires an understanding about the electromagnetic properties of soils. Propagation velocities and attenuation rates at ground-penetrating radar frequencies (0.25-4 GHz) were measured as a function of soil moisture content for soils from Iraq and Afghanistan. Soil samples in the study include two with and two without gypsum (CaSO 4 ·2H 2 O) as a major mineral component. When measured at 100°C, volumetric moisture content of gypsum-rich soils ranged from 12% to 24%. In addition to the high moisture content, the propagation velocities were higher than expected, and attenuation rates were lower than expected for soils with moisture contents in this high range. The apparently anomalous relationship between high moisture content and low attenuation rate is explained by the presence and characteristics of gypsum in the soil. Radar signals are not affected by the chemically bound water molecules in gypsum which dehydrates at 100°C. These results show that soil mineralogy is critically important to the interpretation of dielectric properties.
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    Coherent Shift Estimation for Stacks of SAR Images (2011)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2011-11-01
    Description: Speckle tracking is used with synthetic aperture radar (SAR) images to estimate displacements, in ways that support or integrate interferometric measurements. This letter derives Fisher information expressions for the displacement estimation using coherent speckle tracking, for the multi-image scenario with an arbitrary coherence structure. Previous results were limited to image pairs. An estimator that approaches the theoretical bound is also proposed, establishing a link with phase estimation for multi-image SAR interferometry. The derivation of the Fisher information is given in the general case when the coherence is a function of the frequency.
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    A Novel Strategy of Nonnegative-Matrix-Factorization-Based Polarimetric Ship Detection (2011)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2011-11-01
    Description: In this letter, a new strategy based on nonnegative matrix factorization (NMF) is proposed for polarimetric ship detection. This method utilizes the sparse feature of nonnegative eigenvalues, and the sparse degree is proposed to be estimated from the histogram which can reveal the sparse distribution of eigenvalues. Combining the nonnegative and sparse features, the NMF-based ship detection method can be implemented flexibly and efficiently. It has been carried out on the C-band quad polarimetric synthetic aperture radar (PolSAR) and dual PolSAR ocean data sets to validate its effectiveness. Unlike a constant-false-alarm-rate detector, the NMF method does not depend on target size and therefore offers improved detection performance under low-signal-to-clutter-ratio conditions.
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    High-Resolution SAR Radargrammetry: A First Application With COSMO-SkyMed SpotLight Imagery (2011)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2011-11-01
    Description: The availability of new high-resolution radar spaceborne sensors offers new interesting potentialities for the acquisition of data useful for the generation of Digital Surface Models (DSMs). Two different approaches may be used to generate DSMs from Synthetic Aperture Radar (SAR) data: the interferometric and the radargrammetric one. At present, the importance of the radargrammetric approach is rapidly growing due to the new high-resolution imagery [up to 1 m Ground Sample Distance (GSD)] which can be acquired by COSMO-SkyMed, TerraSAR-X and RADARSAT-2 in SpotLight mode. The defined and implemented model is related to COSMO- SkyMed SpotLight imagery in zero-Doppler geometry; it performs a 3-D orientation based on two range and two zero-Doppler equations, allowing for the least squares estimation of some calibration parameters, related to satellite position and velocity and to the range measure. The model has been implemented in SISAR (Software per Immagini Satellitari ad Alta Risoluzione), a scientific software developed at the Geodesy and Geomatic Institute of the University of Rome “La Sapienza”. Starting from this model, based on a geometric reconstruction, also a tool for the Rational Polynomial Coefficients (RPCs) generations has been implemented. To test the effectiveness of the new model, a stereo pair over the test sites of Merano (Northern Italy) has been orientated using the rigorous model and the RPCs one, and first results of radargrammetric DSM generation are presented; they display the possibility to reach an overall average accuracy of 3.5 m.
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    Four-Component Decomposition of Polarimetric SAR Images With Deorientation (2011)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2011-11-01
    Description: A modified Yamaguchi decomposition with deorientation is proposed for analyzing multilook polarimetric synthetic aperture radar (PolSAR) data. Deorientation is first applied to a coherence matrix; then, the coherence matrix is decomposed into four components by the Yamaguchi decomposition. A special kind of target is found for which the original Yamaguchi decomposition output is not appropriate. This problem is solved by applying deorientation prior to the Yamaguchi decomposition. Moreover, the deorientation procedure enhances double-bounce scattering from urban areas in the decomposition output. Comparisons of the Yamaguchi decompositions with and without deorientation are shown for PolSAR data from both airborne and spaceborne systems.
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    Advertisement - IEEE Foundation (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-03-14
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    First Demonstration of Agriculture Height Retrieval With PolInSAR Airborne Data (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-02-03
    Description: A set of three quad-pol images acquired at the L-band in interferometric repeat-pass mode by the German Aerospace Center (DLR) with the Experimental SAR (E-SAR) system, in parallel with the AgriSAR2006 campaign, has been used to provide, for the first time with airborne data, a demonstration of the retrieval of vegetation height from agricultural crops by means of polarimetric SAR interferometry (PolInSAR)-based techniques. Despite the low frequency of the data, hence providing a weak response from the vegetation volume in contrast to the ground, accurate estimates of vegetation height at field level have been obtained over winter rape and maize fields. The same procedure does not yield valid estimates for wheat, barley, and sugar beet fields due to a mismatch with the physical model employed in the inversion and to the specific crop condition at the date of acquisition. These results show the value of the information provided by both interferometry and polarimetry for some agriculture monitoring practices.
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    Soil Salinity Impacts on L-Band Remote Sensing of Soil Moisture (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-02-03
    Description: The recently launched Soil Moisture and Ocean Salinity (SMOS) satellite is providing soil moisture observations at continental scales by measuring L-band microwave radiation emitted from the land surface. While its retrieval algorithms will correct for factors such as vegetation and surface roughness, it will not correct for soil salinity. This letter tests the assumption that soil salinity will have a negligible impact on L-band brightness temperature $(T_{b})$ at SMOS scales using field data; airborne $T_{b}$ observations were collected in a saline groundwater discharge area near Nilpinna Station, South Australia. At the 500-m scale, the airborne observations of $T_{b}$ could not be reproduced using the baseline algorithm of the SMOS Level 2 retrieval scheme, without accounting for soil salinity in the model. The analysis in this letter shows that soil moisture retrieval errors of at least 0.04 $hbox{m}^{3} hbox{m}^{-3}$ (i.e., the entire SMOS error budget) will occur due to salinity alone in SMOS footprints with saline coverage as low as 25% (possibly even much less). Consequently, fractional salinity coverage cannot be considered a negligible factor by microwave soil moisture satellite missions.
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    A Novel Method for Adaptive SAR Barrage Jamming Suppression (2012)
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    Publication Date: 2012-02-03
    Description: Based on the difference in statistical distribution between the target and jamming signal in the synthetic aperture radar (SAR) image, this letter proposes a novel adaptive method for barrage jamming suppression. In this method, the covariance matrix of jamming is estimated from the SAR image. Then, the 2-D sinc function of the ideal point target is utilized as the steering vector to obtain the optimal adaptive filter. This filter can suppress the random barrage jamming effectively, thus improving the image contrast and interpretability. Additionally, this letter analyzes in detail the theoretical basis and performance of the proposed method. Finally, simulations are provided to demonstrate its effectiveness.
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    SAR Target Analysis Based on Multiple-Sublook Decomposition: A Visual Exploration Approach (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-02-03
    Description: The advent of submeter-resolution synthetic aperture radar (SAR) images from satellites such as TerraSAR-X has given a new dimension to SAR image understanding. Even though emphasis is always on discovering automatic means of target characterization, visual exploration of targets and objects is the first step in many applications. While considering the complex-valued SAR images, visual inspection of the targets in an image may provide incomplete and misleading information, as sometimes two entirely different behaving objects look quite similar in SAR images. Thus, a need was felt to develop a methodology to support visual target recognition and analysis. In this letter, we present a method which looks into the complex-valued spectrum of SAR images, thus allowing a detailed physical interpretation of the scattering behavior of objects. The presented method is a joint time–frequency analysis method based on sublook decomposition. With the presented results, we emphasize the use of complex-valued SAR images for target characterization, the use of which is primarily restricted to polarimetric and interferometric applications as of now.
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    A Neighborhood-Based Ratio Approach for Change Detection in SAR Images (2012)
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    Publication Date: 2012-02-03
    Description: This letter presents a novel neighborhood-based ratio (NR) operator to produce a difference image for change detection in synthetic aperture radar (SAR) images. In order to reduce the negative influence of speckle noise on SAR images, the proposed NR operator produces a difference image by combining gray level information and spatial information of neighbor pixels. The performance comparisons of the proposed operator with a traditional ratio operator and a log-ratio operator indicate that the NR operator is superior to these traditional methods and produces better detection results.
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    Topography Mapping With a Portable Real-Aperture Radar Interferometer (2012)
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    Publication Date: 2012-02-03
    Description: In this letter, the requirements to derive topography from a portable terrestrial radar interferometer are introduced, the instrument design and the relationship between interferometric phase shift and surface topography are explained, and two examples of topographic maps from measurements at the Rhone glacier and Grabengufer rock glacier in Switzerland are presented. In the first case, an external digital elevation model was used to assess the error of topography mapping with the portable radar interferometer and to analyze ice surface changes of the glacier in the last 14 years. We found that the height error standard deviation is about 3 m within a distance of 2 km from the sensor and observed massive thinning of the Rhone glacier. In the second case, we used the terrestrial radar interferometer in order to measure the height difference between August 2009 and March 2010 over the rock glacier as a consequence of its destabilization.
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    Calibration of an InSAR-Derived Coseimic Deformation Map Associated With the 2011 Mw-9.0 Tohoku-Oki Earthquake (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-02-03
    Description: We map the coseismic deformation of the 2011 Tohoku-Oki earthquake with data from three descending Envisat/ASAR tracks and six ascending ALOS/PALSAR tracks that cover most of northeastern Japan. Due to the inaccurate estimation of the satellite status, orbital ramps commonly exist in the coseismic interferograms, which resulted in inconsistency among the deformation maps released by several research groups. In this letter, calibration has been performed to accurately remove these ramps by a 2-D quadratic-phase model derived based on GPS measurements from the ARIA team at the Jet Propulsion Laboratory and Caltech. The average RMS of the interferometric synthetic aperture radar (InSAR) measurements, as compared with GPS measurements at the validation stations, has decreased from 17.8 to 7.7 cm after the orbital ramp correction is made, indicating that much more accurate InSAR measurements are achieved. The corrected coseismic deformation from the InSAR measurements is consistent with not only the GPS observations at the individual GPS stations but also with the coseismic deformation interferogram from interpolated GPS observation in the SAR viewing directions. The corrected coseismic deformation measurement results show a maximum line-of-sight displacement of up to 3.7 m from the ascending PALSAR tracks and 2.4 m from the descending ASAR tracks, respectively.
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    Vegetation Water Content Estimation Using GNSS Measurements (2012)
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    Publication Date: 2012-02-03
    Description: Global Navigation Satellite Systems (GNSS) opportunity signals reflected at or near the Earth's surface have already shown their potential to perform retrievals of a number of geophysical parameters. Radio occultations using GNSS signals are also used for atmospheric sensing. This letter presents a GNSS technique to retrieve vegetation water content (VWC). This technique measures the received powers of the GPS signals in open sky and under the vegetation layer. From these two powers, the attenuation due to the vegetation is computed, which is related to the VWC. This letter presents the results obtained after deploying the instrument in a walnut-tree stand for 11 months.
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    High-Dimensional Waveform Inversion With Cooperative Coevolutionary Differential Evolution Algorithm (2012)
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    Publication Date: 2012-02-03
    Description: In this letter, an improved differential evolution (DE) for high-dimensional waveform inversion is proposed. In conventional evolutionary algorithms, an individual is treated as a whole, and all its variables (genes) are evaluated with a uniform fitness function. This evaluation criterion is not effective for a high-dimensional individual. Therefore, for high-dimensional waveform inversion, we incorporate the decomposition strategy of cooperative coevolution into DE to decompose the individual into some subcomponents. Another novel feature that we introduce is a local fitness function for each subcomponent, and a new mutation operator is designed to guide the mutation direction of each subcomponent with the corresponding local fitness value. Coevolution among different subcomponents is realized in the selection operation with the global fitness function. Many experiments have been carried out to evaluate the performance of this new algorithm. The results clearly show that, for high-dimensional waveform inversion, this algorithm is effective and performs better than some other methods. Finally, the new method has been applied to real seismic data.
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    Kernel Entropy Component Analysis for Remote Sensing Image Clustering (2012)
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    Publication Date: 2012-02-03
    Description: This letter proposes the kernel entropy component analysis for clustering remote sensing data. The method generates nonlinear features that reveal structure related to the Rényi entropy of the input space data set. Unlike other kernel feature-extraction methods, the top eigenvalues and eigenvectors of the kernel matrix are not necessarily chosen. Data are interestingly mapped with a distinct angular structure, which is exploited to derive a new angle-based spectral clustering algorithm based on the mapped data. An out-of-sample extension of the method is also presented to deal with test data. We focus on cloud screening from Medium Resolution Imaging Spectrometer images. Several images are considered to account for the high variability of the problem. Good results obtained show the suitability of the proposal.
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    MERIS Atmospheric Water Vapor Correction Model for Wide Swath Interferometric Synthetic Aperture Radar (2012)
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    Publication Date: 2012-02-03
    Description: A major source of error for repeat-pass interferometric synthetic aperture radar is the phase delay in radio signal propagation through the atmosphere, particularly the part due to tropospheric water vapor. These effects become more significant for ScanSAR observations due to their wider coverage (e.g., 400 km $times$ 400 km for ENVISAT Advanced Synthetic Aperture Radar (ASAR) wide swath (WS) mode versus 100 km $times$ 100 km for ASAR image mode). In this letter, we demonstrate for the first time that a Medium Resolution Imaging Spectrometer water vapor correction model can significantly reduce atmospheric water vapor effects on ASAR WS interferograms, with the phase variation in non-deforming areas decreasing from 3.8 cm before correction to 0.4 cm after correction.
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    Multimodal Remote Sensing Data Fusion via Coherent Point Set Analysis (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-12-20
    Description: We present a novel fusion algorithm for electronic-reconnaissance (ER) satellite and optical imaging satellite data using coherent point set (CPS) analysis. This work is motivated by a large-scale maritime surveillance problem, where ship groups in the observations are of particular interest for tactical and strategic operations. Fusion of observations from ER satellite and optical imaging satellite is a challenging task. On the one hand, dense and continuous measurement is not available for optical imagery. On the other hand, it is difficult to extract robust features from ER measurements. Considering that the size of a ship is often less than the distance among different ships, we treat each ship as a mass point. The contributions of our work are threefold. First, multisensor data fusion is accomplished by CPS association. To the best of our knowledge, this letter is the first to investigate CPS for multimodal remote sensing data fusion. Second, a novel geometry descriptor, which encodes the topological characteristics of a point set, is presented. Third, we combine both topological features and attributive features within the framework of Dempster–Shafer theory for CPS analysis. The proposed method has been tested using different sets of simulated data and recorded data. Experimental results demonstrate the effectiveness of the proposed method.
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    Using MODIS NDVI Time Series to Identify Geographic Patterns of Landslides in Vegetated Regions (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-12-20
    Description: The 2008 Wenchuan Earthquake that occurred in a mountainous region of China induced massive landslides and caused numerous casualties and property losses. Analyzing the disturbances on vegetation detected from the abnormal sudden drops of the normalized difference vegetation index (NDVI) within a short period can be used for the purpose of rapid landslide identification. Although much research has confirmed the necessity of high-resolution satellite images in landslides identification, Moderate Resolution Imaging Spectroradiometry (MODIS) products still have their usefulness for high temporal resolution, as investigated by the authors. Using MODIS MOD09Q1 NDVI products at a temporal interval of 8 days during 2008, this letter presents a method that has been developed to identify landslide distribution and evolution patterns. First, to find the optimal threshold, the MODIS NDVI time series are analyzed in a training area by an iteration searching procedure. Second, the chosen threshold is used in a larger validation area. To examine the effectiveness of the proposed method, the results are compared to interpreted landslides using SPOT5 images with a spatial resolution of 2.5 m acquired before and after the main shock. An overall 75% accuracy is achieved, and better consistency is observed for landslides extending over one MODIS pixel. The proposed method has also been applied to the Wenchuan earthquake affected areas with seismic intensity IX and greater, and the similar spatial pattern of landslides distribution is obtained when compared with results by using high-resolution images and field investigation. This technique can be applied practically for rapid landslide assessment at a relatively large region after a major earthquake or other severe disturbance events.
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    Bridge Thermal Dilation Monitoring With Millimeter Sensitivity via Multidimensional SAR Imaging (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-12-20
    Description: The new generation of synthetic aperture radar (SAR) sensors is providing images with very high spatial resolution, improved up to the meter scale. Such a resolution increase allows more accurate monitoring capabilities by means of interferometric approaches. The use of higher frequency enhances the sensitivity of the system even to minute changes, such as thermal dilations. This phenomenon has an impact on the interferometric products, particularly on the deformation velocity maps, if not properly handled. Man-made structures, such as steel core bridges and specific buildings, may be very sensible to thermal dilation effects. By extending the multitemporal differential interferometry SAR processing chains, in our case based on the multidimensional imaging (MDI) approach, an additional parameter related to temperature differences at acquisition instants, the thermal coefficient, can be accurately estimated. This parameter provides interesting perspectives in application to infrastructure monitoring: It brings information about the thermal behavior of the imaged objects. In this letter, we investigate the thermal response of the Musmeci bridge (Potenza, Italy), by experimenting the extended MDI approach on a real TerraSAR-X data set. Results highlight the possibility of such a technique to obtain measurements of the motion that is highly correlated with temperature, thus providing useful information about the static structure of bridges.
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    Unsupervised Change Detection on SAR Images Using Triplet Markov Field Model (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-12-20
    Description: The triplet Markov field (TMF) model is powerful in the nonstationary synthetic aperture radar (SAR) image analysis. Taking the speckle noise and the correlation of nonstationarities in two multitemporal SAR images into account, we propose a change-detection method based on the TMF model in this letter. The third field $U$ in the TMF model is redefined to describe the nonstationary textural similarity between the two images for change detection. The corresponding prior energy of $(X, U)$ is reconstructed. The adaptive weight parameter in prior energy is introduced to cope with the detection tradeoff issue. An automatic estimation of the parameter is obtained with low level of complexity. The Bayesian maximum posterior marginal criterion is utilized with the TMF model to obtain change detection. Experimental results on real SAR images validate the superiority of the proposed TMF method over the Markov random field method.
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    Seasonal Snow Cover Mapping in Alpine Areas Through Time Series of COSMO-SkyMed Images (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-12-20
    Description: A time series of COSMO-SkyMed (CSK) images is exploited for detection of seasonal snow cover in alpine areas. For the first time, a complete time series of CSK images acquired during snow fall and melt periods in winter 2010–2011 is addressed to verify the snow cover mapping capabilities of X-band radar images under different conditions (from dry to wet snow). The algorithm for snow detection is based on a multitemporal approach with the concept that free water in the snowpack attenuates the X-band synthetic aperture radar signal and wet snow can be classified by comparing images acquired under wet snow and snow-free conditions. Thresholds to make this distinction are compared across all the images to check sensitivity to different winter conditions and land-use classes. The impact of variable and fixed thresholds on the retrieved snow-covered areas is assessed. Snow maps from CSK images compared with Landsat Enhanced Thematic Mapper Plus snow maps indicate a constant underestimation in the detection of snow extent, particularly during winter season, thus showing a scarce sensitivity of X-band signals to snow in dry conditions. Probability of error maps are also calculated for each CSK snow map, thus providing information on the classification error associated to each pixel labeled as snow. The analysis of the snow line variation during spring determines good time consistency in the determination of snow maps from CSK images.
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    Wavelet Packet Analysis and Gray Model for Feature Extraction of Hyperspectral Data (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-12-20
    Description: Wavelet packet analysis (WPA) and gray model (GM) are investigated for nonlinear unsupervised feature extraction of hyperspectral remote sensing data in this letter. Treated as derivative series, a hyperspectral response curve of each pixel is decomposed into an approximation and various detailed compositions by WPA, and then, GM is continuously applied to find the relationship among those detailed compositions. Cluster–space representation is used for determining the optimal wavelet. New extracted features can reveal the intrinsic identities of hyperspectral data. Experimental results show the feasibility and reliability of our proposed method in terms of classification accuracy.
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    Linear Feature Extraction for Hyperspectral Images Based on Information Theoretic Learning (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-12-20
    Description: This letter proposes a new supervised linear feature extractor for hyperspectral image classification. The criterion for feature extraction is a modified maximal relevance and minimal redundancy (MRMD), which has been used for feature selection until now. The MRMD is a function of mutual information terms, which possess higher order statistics of data; thus, it is effective for hyperspectral data with informative higher order statistics. The batch and stochastic versions of the gradient ascent are performed on the MRMD to find the optimal parameters of a linear feature extractor. Preliminary results achieve better classification performance than the traditional methods based on the first- and second-order moments of data.
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    Azimuth Overlapped Subaperture Algorithm in Frequency Domain for Highly Squinted Synthetic Aperture Radar (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-12-20
    Description: The high-resolution imaging of a highly squinted synthetic aperture radar remains difficult because of the severe coupling between the range and the azimuth. “Squint minimization” compensates for the range walking in the azimuth time domain, which efficiently increases the orthogonality between the range and the azimuth. However, this “squint minimization” introduces the azimuth space-variant phases, which can be compensated by the azimuth nonlinear chirp-scaling (ANCS) algorithm using large computational loads. In this letter, an azimuth overlapped subaperture algorithm (AOSA) is proposed to compensate for these phases in the Doppler frequency domain. The validity constraint of this algorithm is then analyzed. The AOSA has an advantage over ANCS in terms of the computational load and is considerably more suitable for real-time processing.
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    Sensitivity of Main Polarimetric Parameters of Multifrequency Polarimetric SAR Data to Soil Moisture and Surface Roughness Over Bare Agricultural Soils (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-12-20
    Description: The potential of polarimetric synthetic aperture radar data for the soil surface characterization of bare agricultural soils was investigated by using air- and spaceborne data acquired by Radar Aéroporté Multi-Spectral d'Etude des Signatures (RAMSES), Système Expérimental de Télédétection Hyperfréquence Imageur (SETHI), and RADARSAT-2 sensors over several study sites in France. Fully polarimetric data at ultrahigh frequency, X-, C-, L-, and P-bands were compared. The results show that the main polarimetric parameters studied (entropy, $alpha$ angle, and anisotropy) are not very sensitive to the variation of the soil surface parameters. Low correlations are observed between the polarimetric and soil parameters (moisture content and surface roughness). Thus, the polarimetric parameters are not very relevant to the characterization of the soil surface over bare agricultural areas.
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    Airborne Dual-Polarization Observations of the Sea Surface NRCS at C-Band in High Winds (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-12-20
    Description: Airborne dual-polarization observations of sea surface normalized radar cross section (NRCS) were conducted over the North Atlantic during January–February 2011. Observations were made using the University of Massachusetts' Imaging Wind and Rain Airborne Profiler radar system installed on the National Oceanic and Atmospheric Administration's WP-3D research aircraft during several winter storm events to determine the high-wind response of the sea surface NRCS for both horizontal and vertical polarizations. During the flights, the aircraft performed several constant-roll circle maneuvers to allow collection of NRCS over a range of incidence angles. We find consistency with prior reports in the polarization ratio observed at moderate incidence angles at the winds encountered. For larger incidence angles, we observe a measurable decrease in polarization ratio with increasing wind speed.
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    Mask Cut Optimization in Two-Dimensional Phase Unwrapping (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: This letter proposes an improved mask cut method for 2-D phase unwrapping. The method is designed to generate thin mask cuts to balance the residues. Network flow ideas are taken to build the strategy of mask cut generation. The predecessor index is recorded for every pixel during searching, and the path from the current residue to its last residue ancestor is traced by the predecessor index information. This path is taken as an optimal path from residue to residue. All the pixels on these paths compose the final mask cuts. The proposed method successfully prevents most of the unnecessary pixels from going into the mask cuts. Comparing with the original mask cut method, experimental results show that the proposed method generates thinner and more accurate mask cuts than that generated by the original method. A significant improvement on the unwrapping result is achieved by the proposed method.
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    IEEE Geoscience and Remote Sensing Letters publication information (2012)
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    Publication Date: 2012-04-04
    Description: Provides a listing of current society officers.
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    Lake Water Footprint Identification From Time-Series ICESat/GLAS Data (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: To provide high-quality data for time-series change detection of lake water level, an automatic and robust algorithm for lake water footprint (LWF) identification is developed. Based on the Ice, Cloud, and Land Elevation Satellite GLA14 data file, six parameters were taken as features of an algorithm for LWF identification, and they are elevation difference between adjacent footprints, waveform width, number of peaks, reflectivity, kurtosis, and skewness of laser echoes. The sensitivity of each parameter was discussed, and elevation difference between adjacent footprints was proved to be most effective. The algorithm was described as a combination of these six parameters, and the thresholds of each parameter were set through statistics of LWF covering Peiku Co in Tibet, China, from 2003 to 2009. The performance of this classification algorithm was evaluated by the user's accuracy and producer's accuracy. Greater than 94% is achieved for all four tested lakes with 97% being the best result of producer's accuracy, and the user's accuracy ranges from 97.9% to 90% for these four lakes.
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    Tracking of Vector Roads for the Determination of Seams in Aerial Image Mosaics (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: This letter proposes a novel approach using vector roads to aid in generating seams for aerial image mosaicking. A representative seam of two adjacent images is extracted as follows. First, the vector roads in the overlapping area of adjacent images are overlaid with the straight skeleton of the overlapping area to build a weighted graph G(V, E). Dijkstra's algorithm is then applied to And the lowest cost path in G(V, E) that connects two intersections of the boundary polygons of adjacent images. The lowest cost path is considered as a seam candidate. Second, the seam candidate is refined by considering its surrounding pixels. The refined seam is employed as the final seam. Experiments demonstrate that this vector-based approach is typically more efficient than the existing raster-based approaches, particularly when vector road networks are available.
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    Omega-K Algorithm for Spaceborne Spotlight SAR Imaging (2012)
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    Publication Date: 2012-04-04
    Description: Since the spaceborne spotlight synthetic aperture radar (SAR) has the long slant range and the high altitude, it generates the curved flight path due to the orbit curvature effect and the time delay due to the long round-trip time of the chirp pulse. Thus, to obtain the SAR image with high quality, we extend the omega-K algorithm. First, we convert the curved path into the straight-line path based on the resampling and the rotation of the transmitted-pulse path and the received pulse path. Then, using the modified matched filter and the modified Stolt interpolation based on the principle of the stationary phase, we compensate the phase error induced by the start-stop assumption of the omega-K algorithm.
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    Soil Texture Estimation Over a Semiarid Area Using TerraSAR-X Radar Data (2012)
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    Publication Date: 2012-04-04
    Description: In this letter, it is proposed to use TerraSAR-X data for analysis and estimation of soil surface texture. Our study is based on experimental campaigns carried out over a semiarid area in North Africa. Simultaneously with TerraSAR-X radar acquisitions, ground measurements (texture, soil moisture, and roughness) were made on different test fields. A strong correlation is observed between soil texture and a processed signal from two radar images, with the first acquired just after a rain event and the second corresponding to dry soil conditions, acquired three weeks later. An empirical relationship is proposed for the retrieval from radar signals of clay content percent. Soil texture mapping is proposed over the study site, which includes bare soils and olive groves.
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    Positive and Negative Information for Assessing and Revising Scores of Burn Evidence (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: A straightforward way to map burned areas from remotely sensed imagery is to integrate partial evidence of burn provided by multiple spectral indices (SIs). Our approach relies on fuzzy set theory to generate integrated layers of overall positive evidence (PE) and negative evidence (NE) scores. In order to reduce commission errors, we propose the use of NE for revising the overall PE. Revised layers are input for a region growing algorithm to produce a map of burned areas. Thematic Mapper (TM) images, acquired over the Mediterranean area, were used to derive the SIs and to define the soft constraints (membership functions). The performance of the revision process is tested for a TM image acquired over Portugal: The revision decreases the commission error from 59.5% to 1.3% and increases the overall accuracy from 42.6% up to 91.3%.
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    Comparison of Statistical and Multifractal Properties of Soil Moisture and Brightness Temperature From ESTAR and PSR During SGP99 (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: Global soil moisture products are based on passive microwave sensors of brightness temperature at different frequencies, including Land C-bands. Two airborne sensors used to develop and test retrieval algorithms for soil moisture estimation are the L-band Electronically Scanned Thinned Array Radiometer (ESTAR) and the C-band Polarimetric Scanning Radiometer (PSR). In this letter, we compare the statistical and multifractal properties of soil moisture and brightness temperature from ESTAR and PSR during the Southern Great Plains Experiment in 1999. We show that differences between products are minimized at a support scale close to the satellite resolution. Then, we compare the subfootprint variabilities of each product in eight coarse domains of 25.6 × 25.6 km 2 . Scale-invariance and multifractal properties were found in all the three available soil moisture products, but multifractality was negligible in brightness temperature fields, implying that the nonlinear transformations in retrieval algorithms introduce the multifractal behavior in soil moisture. Subfootprint variability and the multifractal behavior for diverse wetness conditions are also different for the three products. Since discrepancies between the subfootprint variabilities of PSR and ESTAR brightness temperatures are small, the factors leading to the differences among the soil moisture products are mainly due to the level of detail of the retrieval algorithm and to the spatial variability of forcing data and parameters related to surface roughness and vegetation.
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    GLRT Detection of Moving Targets via Multibaseline Along-Track Interferometric SAR Systems (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: Along-track interferometric synthetic aperture radar systems can be used for ground moving target indication. We analyze a scheme for detecting moving targets with unknown parameters (velocity and signal-to-clutter ratio) and with constant false-alarm rates, based on the generalized likelihood ratio test (GLRT), and adopting a Gaussian model for target and clutter signals. We compare its performance with the one obtained in the ideal case of known target parameters applying the likelihood ratio test (LRT). A closed form for the LRT receiver operating characteristic is derived and used as reference for GLRT performance assessment. The analysis is carried out on simulated TerraSAR-X data.
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    A Tomographic Approach for Helicopter-Borne Ground Penetrating Radar Imaging (2012)
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    Publication Date: 2012-04-04
    Description: Airborne ground penetrating radar is a suitable tool to perform cost-effective surveys of the underground of large possibly nonaccessible areas. To tackle the imaging problem underlying this technology, we propose a regularized inverse scattering procedure. The capabilities of the approach to achieve a stable solution and its imaging performance are first assessed against synthetic data. Then, results obtained by processing data collected by means of a gated stepped frequency system mounted on a helicopter are provided as examples of on-field test cases.
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    CryoSat SAR-Mode Looks Revisited (2012)
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    Publication Date: 2012-04-04
    Description: The precision of sea-surface (or ice-surface) height measurements by radar altimetry improves in direct proportion to the square root of the number of statistically independent waveforms contributing to the measurement average. The closed-burst strategy used on CryoSat constrains the amount of averaging to be less than the theoretical limit by a factor of approximately three. Open-burst operation would allow the capture of nearly all available looks. Optimal performance requires that the radar pulse-repetition frequency be less than the usual Nyquist lower bound, which is acceptable for an altimeter viewing surfaces that have relatively small topographic relief.
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    Degree of Polarization at Simultaneous Transmit: Theoretical Aspects (2012)
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    Publication Date: 2012-04-04
    Description: We consider weather radar measurements at simultaneous transmission and simultaneous reception of horizontal and vertical polarizations and show that the degree of polarization at simultaneous transmit ( p s ) is related to differential reflectivity and copolar correlation coefficient at simultaneous transmit (namely, Z DR s and ρ hy s ). We evaluate the potential of degree of polarization at simultaneous transmit for weather radar applications. Ultimately, we explore the consequences of adjusting the transmit polarization state of dual-polarization weather radars to circular polarization.
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    Nonwhite Noise Reduction in Hyperspectral Images (2012)
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    Publication Date: 2012-04-04
    Description: Noise reduction is an important preprocessing step to analyze the information in the hyperspectral image (HSI). Because the common filtering methods for HSIs are based on the data vectorization or matricization while ignoring the related information between image planes, there are new approaches considering multidimensional data as whole entities, for example, multidimensional Wiener filtering (MWF) based on Tucker3 tensor decomposition. However, if HSIs are not disturbed by white noise, MWF cannot effectively remove the nonwhite noise and obtain the expected signal. To reduce nonwhite noise from HSIs, a new method is proposed in this letter. The first step of this method is to whiten the noise in HSIs through a prewhitening procedure. Then, MWF can help to denoise the prewhitened data. At last, an inverse prewhitening process can rebuild the estimated signal. Comparative studies with existing denoising methods show that the proposed approach has promising prospects in this field.
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    Subpixel Land Cover Mapping by Integrating Spectral and Spatial Information of Remotely Sensed Imagery (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: Subpixel mapping (SPM) is a technique to predict spatial locations of land cover classes within mixed pixels in remotely sensed imagery. The two-step approach first estimates fraction images by spectral unmixing and then inputs fraction images into an SPM algorithm to generate the final subpixel land cover map. A shortcoming of this approach is that the information about the credibility of fraction images is not considered. In this letter, we proposed a general framework of SPM which is directly applied to original coarse resolution remotely sensed imagery by integrating spectral and spatial information. Based on the proposed framework, the linear unmixing model and the maximal spatial dependence model were combined to construct a novel SPM model aiming to minimize the least squares error of spectral signature and make the subpixel land cover map spatially smooth, simultaneously. By applying to an Airborne Visible/Infrared Imaging Spectrometer hyperspectral image, the proposed model was evaluated both visually and quantitatively by comparing it with hard classification and the two-step SPM approach. The results showed that the regularization parameter, which balances the influence of spectral and spatial terms, plays an important role on the solution. The L-curve approach was a reasonable method to select the regularization parameter, with which an increased accuracy of the proposed model was obtained.
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    Remote-Sensing Image Denoising Using Partial Differential Equations and Auxiliary Images as Priors (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: In this letter, a new method for denoising remote-sensing images based on partial differential equations (PDEs) is proposed. The method employs the similarity between the different band images in a multicomponent image. Initially, one of the noise-free images in multicomponent remote-sensing images as a prior is introduced into the PDE denoising method. To make use of the priors of the noise-free image in denoising, we construct a new smoothing term for the PDE so as to compute the total variation. The new smoothing term refers to a specific smoothing direction and a specific smoothing intensity of the reference image when denoising the noisy image. The proposed smoothing term is added as a new constraint into the PDE denoising method. Based on the proposed method, the similarity of the directions of the edges between the noisy image and the reference image enables the new algorithm to smooth out more noise and conserve more detail in the denoising process. We also present the discrete form of the proposed denoising model. Multispectral remote-sensing images and hyperspectral remote-sensing images are experimented in this letter. A better performance is achieved by the proposed method when compared with other methods.
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    A Geometry-Based Doppler Centroid Estimator for Bistatic Forward-Looking SAR (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: For high-quality synthetic aperture radar (SAR) processing, Doppler centroid estimation is an essential procedure. An incorrect Doppler centroid would cause a loss of signal-to-noise ratio, an increase in the azimuth ambiguity level, and a shift in the location of the target. Based on the analysis of the range migration characteristic of the transmitter-fixed bistatic forward-looking SAR, a geometry-based Doppler centroid estimator is proposed in this letter. By searching for the range walk slope based on the minimum entropy, this method estimates the unambiguous Doppler centroid directly. Simulations validate the effectiveness of this method.
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    Thin Cloud Detection of All-Sky Images Using Markov Random Fields (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: Thin cloud detection for all-sky images is a challenge in ground-based sky-imaging systems because of low contrast and vague boundaries between cloud and sky regions. We treat cloud detection as a labeling problem based on the Markov random field model. In this model, each pixel is represented by a combined-feature vector that aims at improving the disparity between thin cloud and sky. The distribution of each label in the feature space is defined as a Gaussian model. Spatial information is coded by a generalized Potts model. During the estimation, thin cloud is detected by minimizing the posterior energy with an iterative procedure. Both subjective and objective evaluation results demonstrate higher accuracy of the algorithm compared with some other algorithms.
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    Generation of Zonal Map From Point Data via Weighted Skeletonization by Influence Zone (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: Data about many variables are available as numerical values at specific geographical locations. We develop a methodology based on mathematical morphology to convert point-specific data into zonal map. This methodology relies on weighted skeletonization by zone of influence that determines the points of contact of multiple frontlines propagating, from various points spread over the space, at the traveling rates depending upon the variable's strength. We demonstrate this approach for converting rainfall data available at specific rain gauge locations (points) into a spatially distributed zonal map that suggests zones of equal rainfall.
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    Uncertainties in Remote Sensing Reflectance From MODIS-Terra (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: A validation analysis of remote sensing reflectance ( R RS ) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard Terra (MODIS-T) is conducted with field R RS data obtained at three fixed sites equipped with autonomous radiometers in the coastal northern Adriatic Sea and at two locations in the Baltic Sea, and during oceanographic campaigns in the Baltic, Black, and Mediterranean Seas and the English Channel. Validation results show mean relative differences |ψ| between satellite and field R RS values of 10%-13% at 531 and 547 nm and 23%-36% at 667 nm. There are much larger deviations in statistics for shorter wavelengths with large |ψ| and bias values in the Baltic Sea. The root-mean-square differences tend to decrease with wavelength from 0.0011-0.0014 sr -1 at 412 nm to 0.0002-0.0005 sr -1 at 667 nm. Overall, the uncertainties shown for MODIS-T are very consistent with those associated with MODIS onboard Aqua.
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    On MODIS Retrieval of Oil Spill Spectral Properties in the Marine Environment (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: With its two daily acquisitions and the possibility to obtain near-real-time data free of charge, the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) shows interesting potential as a cost-effective supplementary tool for oil spill monitoring in the marine environment. The mechanism behind MODIS oil feature detection, as well as the type of information that might be retrieved, strictly depends on the illumination conditions. In the presence of sunglint contamination, MODIS can just locate the oil spill as a sea surface roughness anomaly, in similarity with radar observations, and no additional spectral information can be retrieved. MODIS detection in the absence of sunglint contamination however might allow extraction of oil feature spectral properties, which, in turn, may help in oil discrimination and classification. Careful atmospheric correction must be applied. An example of oil spill spectral property extraction from MODIS images is here shown for the Deepwater Horizon accidental oil spill.
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    Resonance Effects Within S-Band in Echoes From Birds (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: It is shown that the scattering resonance effects in echoes from migrating birds are so strong that a 10% frequency deviation within S-band can result in more than 10-dB changes in reflectivity values. Differential reflectivity values from adjacent polarimetric WSR-88D weather radars operating at offset frequencies can differ by several decibels in “clear air” echoes.
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    Precise Recovery of the Earth's Gravitational Field With GRACE: Intersatellite Range-Rate Interpolation Approach (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: First, a new observation equation of a satellite from the intersatellite range-rate interpolation approach (IRRIA) is created by inserting the precise intersatellite range-rate measurements into the line-of-sight component of the orbital velocity difference vector. Second, by a comparison of the two-point, four-point, six-point, and eight-point interpolation formulas, the accuracy of the Earth's gravitational field is substantially improved using the six-point IRRIA formula due to an optimum signal-to-noise ratio. Third, a new Gravity Recovery and Climate Experiment (GRACE) satellite-only Earth gravity field model WHIGG-GEGM02S is produced by GRACE-Level-1B real data during the year 2009 using the IRRIA, and the cumulative geoid height error and cumulative gravity anomaly error are 1.140 ×10 -1 m and 1.807 ×10 -6 m/s 2 at degree 120, respectively. Finally, the new WHIGG-GEGM02S model is much closer to the existing GGM02S model by a comparison of the root mean square of the geoid height differences between the global positioning system/leveling observations and the existing seven GRACE global gravity field models.
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    Phenomenology of P-Band Scattering From a Tropical Forest Through Three-Dimensional SAR Tomography (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: The aim of this letter is to discuss recent results from the tomographic analysis of the P-band synthetic aperture radar multibaseline data set acquired by ONERA over French Guyana, in the frame of the European Space Agency campaign TropiSAR. Such a data set is characterized by a vertical resolution of about 20 m, whereas forest height ranges from 20 to 40 m. These features make it possible to map the 3-D distribution of the scene complex reflectivity in up to three independent layers by coherent focusing, i.e., without assuming any physical model or employing superresolution techniques. The most relevant features within the observed results are the presence of dihedral-like scattering in the ground layer, which is hardly noticeable in the original single-look complex data, and the substantial invariance of the innermost forest layer to topographic slopes.
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    Active and Passive Microwave Remote Sensing of Springtime Near-Surface Thaw at Midlatitudes (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: Active and passive microwave remote sensing data were used to identify springtime near-surface thaw events in northern China and Mongolia. Typical signatures of the time series (the first 180 days of a year) in the region characterized by three different winter surface conditions, i.e., high-moisture frozen ground, nonfrozen ground, and low-moisture cold (desert/dryland) regions, were analyzed with meteorological records. In all regions, brightness temperature showed an increasing trend during the first 180 days of the year, but backscatter trends decreased in frozen ground regions, increased in nonfrozen ground regions, and were steady in desert regions. Diurnal brightness temperature differences were lesser in regions with than without seasonal freeze-thaw events due to the surface diurnal temperature differences in winter. A method based on these signature analysis results was proposed. First, frozen ground, nonfrozen ground, and desert regions could be distinguished by using two proposed indices, the temporal difference between morning and evening brightness temperatures ( TI ) and the slope ratio between backscatter and brightness temperature time series ( SI ). Second, a logistic function of the daily signal difference between active and passive time series ( DI i ) could detect the beginning and end of the freeze-thaw transition.
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    Improved Ground Subsidence Monitoring Using Small Baseline SAR Interferograms and a Weighted Least Squares Inversion Algorithm (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: We present the application of a weighted least squares (WLS) method based on image mode interferometric data to monitor the spatiotemporal evolution of land surface subsidence in Mashhad valley, northeast Iran. The technique is based on an appropriate combination of differential interferograms produced by image pairs with small orbital separation to limit the spatial decorrelation phenomena. Our data consist of 17 ASAR single-look-complex images acquired from a descending orbit by the European ENVISAT satellite in image mode (I2), spanning a time interval from June 2004 to November 2007. Fifty-three reliable differential interferograms with relatively little noise and a continuous unwrapped phase are constructed from this data set and are analyzed using a WLS adjustment technique to produce time series of the displacement field. The time-series analysis suggests that the subsidence occurs within a northwest-southeast elongated elliptically shaped bowl along the axis of Mashhad valley. The maximum accumulated subsidence during the 1260-day period reaches approximately 86 cm, located northeast of Mashhad city. The comparison between SAR-interferometry time-series results with continuous Global Positioning System measurements yields an estimated root-mean-square error of ~ 1.0 cm.
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    Experimental Measurements of the Response of a Single-Transmitter–Receiver Electromagnetic Induction Sensor to a Linear Conductor (2012)
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    Publication Date: 2012-04-04
    Description: The experimental results of the response of a single-transmitter-single-receiver electromagnetic induction sensor to a linear conductor are reported. First, the sensor geometry is given, and a simple model is derived to predict the survey profile of the instrument as it moves over a linear conductor. Next, the experimental apparatus is described, and the acquired results are compared with those predicted by the model. As part of this analysis, various orientations of the transmitter and receiver dipoles are considered, as well as different tilt angles of the sensor head. The variation of peak signal strength with height above the linear conductor is also investigated. In all cases, excellent agreement between experiment and theory is achieved. These results demonstrate the potential for implementing simple sensors for detecting linear conductors or buried utilities and are important for verification of theoretical analyses.
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    Postearthquake Building Damage Assessment Using Multi-Mutual Information From Pre-Event Optical Image and Postevent SAR Image (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: An approach of multi-mutual information (M-MI) is presented for change detection and evaluation of building damages after an earthquake. Fusion of very high resolution pre-event optical and postevent synthetic aperture radar (SAR) images becomes feasible for timely evaluation of earthquake losses. Based on the geometric parameters extracted from an optical pre-event image, SAR images of rectangular building objects, i.e., nondamaged or damaged, are first numerically simulated by our mapping and projection approach and are then, using M-MI, applied to similarity analysis with the real postevent SAR image. Three models of building damages, i.e., collapsed, subsided, and deformed, are proposed for classifying mutual information (MI). The M-MI, including normalized MI (NMI), gradient MI (GMI), and regional MI (RMI), are all applied and compared for MI change detection of building damages. Based on the maximum, mean value, and height deviation of NMI, GMI, and RMI, the building damages can be detected and evaluated. As an example, the Ikonos pre-event and GeoEye postevent optical images and COSMO-SkyMed and Radarsat-2 postevent SAR images during the 2010 Haiti earthquake are applied in this M-MI experiment.
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    Analysis of Urban Areas Affected by the 2011 Off the Pacific Coast of Tohoku Earthquake and Tsunami With L-Band SAR Full-Polarimetric Mode (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: The 2011 off the Pacific coast of Tohoku earthquake was observed using phased array type L-band synthetic aperture radar (PALSAR) and polarimetric and interferometric airborne synthetic aperture radar (PiSAR) full-polarimetric data. Representative polarimetric parameters were calculated from full-polarimetric data for urban areas, where most of the buildings were destroyed by the subsequent tsunami, in order to identify the radar scattering mechanism in these areas. These parameters were compared with the ones observed before the disaster. The full-polarimetric data analysis shows that the affected areas were represented by surface scattering with high entropy, indicating that a complex scattering mechanism with nonreflection symmetry is involved. The coherence between HH and VV and that between RR and LL are the most important factors in distinguishing the disaster areas from the data. Alpha angle and anisotropy are also important factors in this respect; however, anisotropy derived from PiSAR data does not show the difference between areas with collapsed and still-standing buildings. This may be because the azimuth slope angle for the target urban area is different before and after the disaster for both PALSAR and PiSAR data. Owing to the double-bounce scattering from azimuthally rotated targets in the urban areas, the power estimated from the four-component decomposition model is distributed within a wide range not only for double-bounce scattering but also for volume and surface scatterings. Additionally, the model does not show a systematic change between before and after the disaster, and σ 0 for four polarizations with 30-m resolution does not show a systematic difference.
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    Toward an Optimal Algorithm for LiDAR Waveform Decomposition (2012)
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    Publication Date: 2012-04-04
    Description: This letter introduces a new approach for light detection and ranging (LiDAR) waveform decomposition. First, inflection points are identified by the Ramer-Douglas-Peucker curve-fitting algorithm, and each inflection point has a corresponding baseline during curve fitting. Second, according to the spatial relation between the baseline and the inflection point, peaks are selected from the inflection points. The distance between each peak and its baseline and the maximum number of peaks are employed as a criterion to select a “significant” peak. Initial parameters such as width and boundaries of peaks provide restraints for the decomposition; right and left boundaries are estimated via a conditional search. Each peak is fitted by a Gaussian function separately, and other parts of the waveform are fitted as line segments. Experiments are implemented on waveforms acquired by both small-footprint LiDAR system LMS-Q560 and large-footprint LiDAR system Laser Vegetation Imaging Sensor. The results indicate that the algorithm could provide an optimal solution for LiDAR waveform decomposition.
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    Analysis and Interpretation of the COSMO-SkyMed Observations of the 2011 Japan Tsunami (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: The major outcomes of the analysis of the COSMO-SkyMed (CSK) synthetic aperture radar (SAR) observations of the area hit by the 2011 Japan tsunami are presented. The height of the tsunami waves was such as to cause a widespread inundation of the coastal area. The SAR acquisitions have been performed on March 12 (i.e., one day after the tsunami occurred) and March 13, 2011 in interferometric mode, so that not only the information on the intensity of the radar signals, but also the complex coherence has been used. The interpretation of the available data has allowed us to detect the flooded areas, as well as the receding of the floodwater from March 12 to March 13, 2011 and the presence of the debris floating above the water surface. Moreover, thanks to the high spatial resolution of the CSK images, the presence of floodwater in some urban areas in the Sendai harbor has been revealed by exploiting the information on the coherence. Our interpretations have been confirmed by a couple of optical images used as benchmarks.
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    A Low-Computational-Complexity Algorithm for Hyperspectral Endmember Extraction: Modified Vertex Component Analysis (2012)
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    Publication Date: 2012-04-04
    Description: Endmember extraction represents one of the most challenging aspects of hyperspectral image processing. In this letter, a new algorithm for endmember extraction, named modified vertex component analysis (MVCA), is presented. This new technique outperforms the popular vertex component analysis (VCA) by applying a low-complexity orthogonalization method and by utilizing integer instead of floating-point arithmetic when dealing with hyperspectral data. The feasibility of this technique is demonstrated by comparing its performance with VCA on synthetic mixtures as well as on the well-known Cuprite hyperspectral image. MVCA shows promising results in terms of much lower computational complexity, still reproducing similar endmember accuracy than its original counterpart. Moreover, the features of this algorithm combined with state-of-the-art hardware implementations qualify MVCA as a good potential candidate for all those applications in which real time is a must.
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    Assess Calibration Consistency of MODIS and AVHRR Thermal Infrared Bands Using SNO Observations Corrected for Atmospheric Effects (2012)
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    Publication Date: 2012-04-04
    Description: Monitoring environmental changes from space requires extremely well-calibrated observations to achieve the necessary high accuracy and stability. The calibration differences between the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Very High Resolution Radiometer (AVHRR) thermal bands provide a valuable quality assessment of the instrument performance. This letter compares the calibration differences between the Aqua MODIS and NOAA-18 AVHRR bands at 11.0 and 12.0 μm using simultaneous nadir overpass observations obtained in nearly parallel orbits. Impacts due to the relative spectral-response differences between the two sensors are estimated by MODTRAN simulations with real-time atmospheric profiles of temperature, water vapor, atmospheric pressure and ozone, and surface skin temperatures. Results show that the temperature difference after the removal of atmospheric impacts is within 0.30 K (or 0.40% in radiance) across the effective calibration range for the 11.0-μm band/channel. For the 12.0-μm band, the differences are 0.40 K (or 0.50%) at the typical radiance and up to 0.70 K (or 0.90%) close to the maximum radiance, indicating an excellent calibration consistency between MODIS and AVHRR for both bands.
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    Evaluation of Envisat MERIS Terrestrial Chlorophyll Index-Based Models for the Estimation of Terrestrial Gross Primary Productivity (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: This letter evaluates three Envisat Medium Resolution Imaging Spectrometer Terrestrial Chlorophyll Index (MTCI)-based models for the estimation of terrestrial gross primary productivity (GPP) across a range of vegetation types. Correlations between flux tower measures of GPP and models for years between 2003 and 2007 were established for 30 sites across USA, Canada, and Brazil. Correlations were seen to range from very strong to weak, depending on seasonal variation in photosynthetic capacity (which is influenced by chlorophyll content) exhibited by the vegetation at each site. At least one of the three models obtained a statistically significant relationship with GPP at every site. Results indicate that chlorophyll content (as measured by the MTCI) is a most relevant community property for estimating primary productivity and chlorophyll-related vegetation indexes provide favorable approximations of the GPP of terrestrial vegetation. The inclusion of radiation information (photosynthetically active radiation (PAR) and fraction of photosynthetically active radiation (fPAR)) into the models extended the applicability of the models and the accuracy of the GPP estimate. Although further investigation is required to fully understand the applicability of these models and their parameters, these results point to the possibility of a total remote sensing approach to GPP estimation.
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    Use of TerraSAR-X Data to Retrieve Soil Moisture Over Bare Soil Agricultural Fields (2012)
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    Publication Date: 2012-04-04
    Description: The retrieval of the bare soil moisture content from TerraSAR-X data is discussed using empirical approaches. Two cases were evaluated: (1) one image at low or high incidence angle and (2) two images, one at low incidence and one at high incidence. This study shows by using three databases collected between 2008 and 2010 over two study sites in France (Orgeval and Villamblain) that TerraSAR-X is a good remote sensing tool for the retrieving of surface soil moisture with accuracy of about 3% (rmse). Moreover, the accuracy of the soil moisture estimate does not improve when two incidence angles (26 ° -28 ° or 50 ° -52 ° ) are used instead of only one. When compared with the result obtained with a high incidence angle (50 ° -52 ° ), the use of low incidence angle (26 ° -28 ° ) does not enable a significant improvement in estimating soil moisture (about 1%).
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    Extraction of Vibrating Features With Dual-Channel Fixed-Receiver Bistatic SAR (2012)
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    Publication Date: 2012-04-04
    Description: Strong ground clutter may submerge the signals of vibrating targets and bring great difficulties to extract their micro-Doppler (m-D) signatures. Furthermore, if the vibrating direction is perpendicular to the radar line of sight, its m-D would be very weak in the monostatic synthetic aperture radar (SAR). In this letter, a configuration of bistatic SAR with a dual-channel fixed receiver is presented to handle the two problems. The displaced phase center antenna technique is adopted to suppress the clutter and to reserve the signals of vibrating targets in the range-compressed data domain. Then, the fractional Fourier transform is utilized to compensate for the radar Doppler shift. Finally, the m-D feature of vibration can be extracted effectively by using time-frequency transform. The validity of the proposed method is evaluated with simulated data.
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    A Batch-Mode Active Learning Technique Based on Multiple Uncertainty for SVM Classifier (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: In this letter, we present a novel batch-mode active learning technique for solving multiclass classification problems by using the support vector machine classifier with the one-against-all architecture. The uncertainty of each unlabeled sample is measured by defining a criterion which not only considers the smallest distance to the decision hyperplanes but also takes into account the distances to other hyperplanes if the sample is within the margin of their decision boundaries. To select batch of most uncertain samples from all over the decision region, the uncertain regions of the classifiers are partitioned into multiple parts depending on the number of geometrical margins of binary classifiers passing on them. Then, a balanced number of most uncertain samples are selected from each part. To minimize the redundancy and keep the diversity among these samples, the kernel k -means clustering algorithm is applied to the set of uncertain samples, and the representative sample (medoid) from each cluster is selected for labeling. The effectiveness of the proposed method is evaluated by comparing it with other batch-mode active learning techniques existing in the literature. Experimental results on two different remote sensing data sets confirmed the effectiveness of the proposed technique.
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    Polar Format Algorithm Wavefront Curvature Compensation Under Arbitrary Radar Flight Path (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-04-04
    Description: An improved space-variant postfiltering approach to compensate for the wavefront curvature effect in polar format imagery is presented in this letter. The main contribution of this new method is the construction of a space-variant filter, which is based on exploiting the endomorphism property of the polar format transformation. The new approach provides an accurate and general solution to wavefront curvature compensation under arbitrary radar flight path. Finally, point target simulation has validated the effectiveness of the new approach.
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    Discriminative Gabor Feature Selection for Hyperspectral Image Classification (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-09-08
    Description: Three-dimensional Gabor wavelets have recently been successfully applied for hyperspectral image classification due to their ability to extract joint spatial and spectrum information. However, the dimension of the extracted Gabor feature is incredibly huge. In this letter, we propose a symmetrical-uncertainty-based and Markov-blanket-based approach to select informative and nonredundant Gabor features for hyperspectral image classification. The extracted Gabor features with large dimension are first ranked by their information contained for classification and then added one by one after investigating the redundancy with already selected features. The proposed approach was fully tested on the widely used Indian Pine site data. The results show that the selected features are much more efficient and can achieve similar performance with previous approach using only hundreds of features.
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  • 96
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    Electromagnetic Scattering by a Metallic Cylinder Buried in a Lossy Medium With the Cylindrical-Wave Approach (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-09-08
    Description: The 2-D electromagnetic scattering of a plane wave by a perfectly conducting cylinder buried in a lossy medium is presented. The problem of reflection and transmission of both the plane wave and the cylindrical wave at the interface with a dissipative medium has been faced, taking into account the general case of inhomogeneous waves. The scattering problem has been solved with the cylindrical-wave approach. The theoretical solution has been numerically implemented in a Fortran code, and the numerical results have been compared with both the literature and simulations with a commercial software.
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    Laboratory Studies of Polarized Light Reflection From Sea Ice and Lake Ice in Visible and Near Infrared (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-09-08
    Description: As the knowledge of polarized reflection from ice may be important for understanding radiative transfer in ice and be of potential value in imaging applications, spectral reflectances and linear polarization of sea ice and lake ice have been measured in visible and near infrared (NIR) (350–2500 nm) at nadir and the specular direction, respectively. Results are presented for three ice types: 1) black lake ice (bubble-free ice); 2) lake ice with air bubbles; and 3) sea ice with brine pockets but no air bubbles. The effects of air bubbles and brine pockets on spectral reflectance and degree of linear polarization (DLP) are investigated in ice of 0.15 m thick at $-20 ^{circ}hbox{C}$ . Spectral reflectances are sensitive to ice condition, consistent with earlier studies of lake ice and sea ice. The DLP of ice in the specular reflection direction is found to be inversely but nonlinearly proportional to reflectance. The case of 1) polarized clearly more light than 2) or 3) in visible wavelength, but they were similar in NIR wavelength, implying the significant contribution of polarization derived from specular reflection. Apparent changes are predicted as volume scattering from air bubbles and brine pockets play an important role in decreasing the DLP of ice in the specular direction.
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    Novel Change Detection in SAR Imagery Using Local Connectivity (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-09-08
    Description: Most change-detection techniques in synthetic aperture radar (SAR) imagery are based on the analysis of the difference image with a pixel-level decision approach. However, the pixel-level decision approach would cause a noisy change-detection map, with holes in connected regions and jagged boundaries. In this letter, we propose a novel change-detection method to deal with the problem of the pixel-level decision approach by considering local connectivity. We first get an initial change-detection result with an improved Gustafson–Kessel clustering algorithm using local spatial information and then refine the initial result through region-of-interest extraction and consideration of local connectivity of changed areas. Experimental results on real SAR image data sets demonstrate that the proposed method outperforms the related ones for change detection.
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    Locating Incipient Volcanic Vents Using Multidisciplinary Remote Sensing Data and Source Modeling Information (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-09-08
    Description: Knowing the location of an impending volcanic eruption would aid civil authorities in preparing the proper response to a developing crisis. Deterministic predictions of an eruption's location are not possible due to the highly complex nature of volcanic processes. Therefore, probabilistic forecasting techniques are required for estimating the location of an impending eruption. In this letter, we present a process for locating incipient volcanic vents using a spatial probability density function (PDF) constructed from a combination of multidisciplinary remote sensing data and source modeling information. Our process is flexible and designed to adapt to changing data availability and geologic conditions that typically occur during a developing volcanic crisis. The utility of our process is evaluated through the analysis of PDFs that forecast probable vent locations prior to Okmok's 2008 eruption. Results show our multidisciplinary approach produces a robust PDF that is spatially constrained to areas exhibiting various types of volcanic unrest and adapts to evolving conditions at the site.
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    A New Model-Independent Method for Change Detection in Multitemporal SAR Images Based on Radon Transform and Jeffrey Divergence (2012)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2012-09-08
    Description: This letter presents a new approach for change detection in multitemporal synthetic aperture radar images. Considering about the existence of speckle noise, the local statistics in a sliding window are compared instead of pixel-by-pixel comparison. Edgeworth series expansion is applied to estimate the probability density function (pdf), which is on the assumption that the pdf is not too far from normal distribution. To transcend such a limitation, in each analysis window, the image is projected onto two vectors in two independent dimensions; thus, the pdf of each projection is closer to a Gaussian density. In order to measure the distance between the two pairs of projections, the proposed algorithm uses a modified Kullback–Leibler (KL) divergence, called Jeffrey divergence, which turns out to be more numerically stable than KL divergence. Experiments on the real data show that the proposed detector outperforms all the others when a high detection rate is demanded.
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