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  Subjects -> ELECTRONICS (Total: 155 journals)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 2)
Advances in Electronics     Open Access   (Followers: 4)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 5)
Advances in Microelectronic Engineering     Open Access   (Followers: 2)
Advances in Power Electronics     Open Access   (Followers: 7)
Aerospace and Electronic Systems, IEEE Transactions on     Hybrid Journal   (Followers: 132)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 13)
Annals of Telecommunications     Hybrid Journal   (Followers: 5)
APL : Organic Electronics and Photonics     Hybrid Journal   (Followers: 2)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 6)
Archives of Electrical Engineering     Open Access   (Followers: 9)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 5)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 10)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 17)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 15)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 6)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 5)
BULLETIN of National Technical University of Ukraine. Series RADIOTECHNIQUE. RADIOAPPARATUS BUILDING     Open Access   (Followers: 2)
Bulletin of the Polish Academy of Sciences : Technical Sciences     Open Access  
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 13)
China Communications     Full-text available via subscription   (Followers: 4)
Circuits and Systems     Open Access   (Followers: 10)
Consumer Electronics Times     Open Access   (Followers: 4)
Control Systems     Hybrid Journal   (Followers: 30)
Electronic Design     Partially Free  
Electronic Markets     Hybrid Journal   (Followers: 5)
Electronic Materials Letters     Hybrid Journal   (Followers: 3)
Electronics     Open Access   (Followers: 10)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 5)
Electronics Letters     Hybrid Journal   (Followers: 20)
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 23)
Energy Harvesting and Systems : Materials, Mechanisms, Circuits and Storage     Hybrid Journal   (Followers: 3)
EPJ Quantum Technology     Open Access  
EURASIP Journal on Embedded Systems     Open Access   (Followers: 9)
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Frequenz     Hybrid Journal   (Followers: 3)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 2)
Geoscience and Remote Sensing, IEEE Transactions on     Hybrid Journal   (Followers: 20)
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 3)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 15)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 13)
IEEE Consumer Electronics Magazine     Full-text available via subscription   (Followers: 18)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 13)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 3)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 7)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 13)
IEEE Transactions on Audio, Speech, and Language Processing     Hybrid Journal   (Followers: 14)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 27)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 17)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 8)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 14)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 21)
IEEE Transactions on Signal and Information Processing over Networks     Full-text available via subscription  
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 8)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 8)
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 6)
IET Power Electronics     Hybrid Journal   (Followers: 14)
IET Wireless Sensor Systems     Hybrid Journal   (Followers: 10)
IETE Journal of Education     Open Access   (Followers: 2)
IETE Journal of Research     Open Access   (Followers: 9)
IETE Technical Review     Open Access   (Followers: 4)
Industrial Electronics, IEEE Transactions on     Hybrid Journal   (Followers: 12)
Industry Applications, IEEE Transactions on     Hybrid Journal   (Followers: 3)
Informatik-Spektrum     Hybrid Journal  
Instabilities in Silicon Devices     Full-text available via subscription  
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 2)
International Journal of Advanced Electronics and Communication Systems     Open Access   (Followers: 5)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 20)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 3)
International Journal of Aerospace Innovations     Full-text available via subscription   (Followers: 13)
International Journal of Antennas and Propagation     Open Access   (Followers: 7)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 1)
International Journal of Biomedical Nanoscience and Nanotechnology     Hybrid Journal   (Followers: 6)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 4)
International Journal of Computer & Electronics Research     Full-text available via subscription   (Followers: 1)
International Journal of Control     Hybrid Journal   (Followers: 14)
International Journal of Electronics     Hybrid Journal   (Followers: 2)
International Journal of Electronics & Data Communication     Open Access   (Followers: 4)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 3)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 1)
International Journal of High Speed Electronics and Systems     Hybrid Journal  
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 1)
International Journal of Nano Devices, Sensors and Systems     Open Access   (Followers: 4)
International Journal of Nanoscience     Hybrid Journal  
International Journal of Numerical Modelling:Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 2)
International Journal of Power Electronics     Hybrid Journal   (Followers: 8)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 2)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 4)
International Journal of Superconductivity     Open Access  
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 2)
International Journal on Communication     Full-text available via subscription   (Followers: 12)
International Journal on Electrical and Power Engineering     Full-text available via subscription   (Followers: 10)
International Transaction of Electrical and Computer Engineers System     Open Access  
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 2)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 5)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 1)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription  
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 4)
Journal of Electrical Bioimpedance     Full-text available via subscription   (Followers: 2)

        1 2 | Last

Journal Cover   Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
  [SJR: 1.632]   [H-I: 19]   [17 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1939-1404
   Published by Institute of Electrical and Electronics Engineers (IEEE) Homepage  [177 journals]
  • IEEE Transactions on Geoscience and Remote Sensing institutional listings
    • Abstract: The GRSS Society invites application for Institutional Listings from firms interested.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote
           Sensing Information for Authors
    • Abstract: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Front cover
    • Abstract: Presents the front cover for this issue of the publication.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote
           Sensing publication information
    • Abstract: Provides a listing of the editors, board members, and current staff for this issue of the publication.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Table of Contents
    • Pages: 3745 - 3747
      Abstract: Presents the table of contents for this issue of the publication.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Foreword to the Special Issue on Advances in SAR and Radar Technology
    • Authors: Hirose; A.;Rosen, P.A.;Yamada, H.;Zink, M.;
      Pages: 3748 - 3750
      Abstract: The twenty-five articles in this special issue focus on the latest advances in synthetic aperture radar (SAR) and radar technology. These papers were presented at the Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) 2013, an International Conference devoted to SAR and radar technology, held in Tsukuba, Japan, on September 23???27, 2013.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Analysis of the Polarimetric SAR Scattering Properties of Oil-Covered
    • Authors: Haiyan Li;Perrie; W.;Yijun He;Jin Wu;Xuye Luo;
      Pages: 3751 - 3759
      Abstract: An analysis of the polarimetric scattering properties of oil-covered waters is conducted using the classic Poincaré ellipticity parameter chi (χ) and the degree of polarization (m) from the Stokes parameters of hybrid polarized mode synthetic aperture radar (SAR). Oil spills reduce m for all four cases considered in this study. However, for the natural oil seep case considered, χ has a change in signs, comparing oil-covered waters with the “clean” ocean surface. The χ sign reversal is basic for “sign difference oil spill detection methods.” However, a problem is that the oil spill related to the deep water horizon (DWH) disaster did not exhibit a reversal in χ signs, comparing the “clean” ocean surface to the area contaminated by crude oil. The scattering mechanism related to the oil seep is different from that of the DWH oil spill; the former is dominated with even bounce scattering and the latter is dominated by Bragg scattering, similar to that of the clean oil-free ocean surface, in the imaging area.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • The Extended Bragg Scattering Model-Based Method for Ship and Oil-Spill
           Observation Using Compact Polarimetric SAR
    • Authors: Junjun Yin;Jian Yang;Zheng-Shu Zhou;Jianshe Song;
      Pages: 3760 - 3772
      Abstract: Ocean surveillance is one of the important applications in synthetic aperture radar (SAR) imagery. Polarimetric SAR provides multichannel information and shows great potential for ocean target observation. Oil-spills and ships possess different polarimetric features from the ocean surface, whose physical backscattering property is generally admitted as being dominated by the Bragg resonant scattering. In this study, we focus on the oil-spill and ship observation based on the polarimetric features. Oil-spills present a non-Bragg scattering property. While backscatter from ships is predominated by the double-bounce scattering and the multiple reflections between the ship and sea surface. Ships exhibit very different scattering characteristics from the ocean Bragg scattering. Based on the extended Bragg (X-Bragg) model, a new method is proposed for observing oil-spills and ships. This method allows distinguishing oil-spills from two kinds of important look-alikes, i.e., biogenic slicks and the low-wind region (LWR), and also shows good performance for ship enhancement. Experiments are performed on the C-band fully polarimetric SAR data acquired by both SIR-C/X-SAR and RADARSAT-2. The other issue concerned is the application potential of the hybrid dual-polarimetric (i.e., compact polarimetry (CP)) SAR mode, which has the advantage of providing larger imaging coverage compared to the full polarimetry. Based on the X-Bragg model, where the backscatter reflection symmetry is assumed, an equivalent method is proposed with the circularly polarized transmission CP mode. Experimental results show that similar results can be obtained between the CP and full polarimetry for ocean target observation.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Snow Water Equivalent of Dry Snow Measured by Differential Interferometry
    • Authors: Leinss; S.;Wiesmann, A.;Lemmetyinen, J.;Hajnsek, I.;
      Pages: 3773 - 3790
      Abstract: Large scale mapping of snow water equivalent (SWE) is a long-lasting request in many scientific and economical fields. Active and passive microwave remote sensing methods are explored, as local methods cannot be generalized due to the spatial inhomogeneity of the snow pack. Microwaves interact with snow by absorption, scattering, and refraction. For dry snow of a few meters depth and frequencies below 20 GHz, absorption and scattering in the snow volume are negligible compared with the backscattered energy from the underlying ground. The signal delay caused by refraction can be measured with differential radar interferometry, but phase wrapping errors and temporal decorrelation must be considered. We demonstrate that large ΔSWE can be accurately determined from dense time series of differential interferograms at Xand Ku-band by temporal integration. Lost phase cycles are reconstructed with a two-frequency approach. Temporal decorrelation is minimized by a temporal resolution of 4 h. A linear function between ΔSWE and phase difference is derived, which deviates only a few percent from the exact solution and which depends negligibly on snow density and stratigraphy. ΔSWE retrieved from observations of the SnowScat instrument (SSI) were validated against observed SWE from different reference instruments, installed at a test site near the town of Sodankylä, Finland. An accuracy below ±6 mm SWE was achieved at frequencies of 10 and 16 GHz for up to 200 mm of ΔSWE. An exceptionally high temporal coherence was observed for up to 30 days for dry snow, whereas for wet snow it decayed within hours.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • A Machine Learning Framework for Detecting Landslides on Earthen Levees
           Using Spaceborne SAR Imagery
    • Authors: Mahrooghy; M.;Aanstoos, J.V.;Nobrega, R.A.A.;Hasan, K.;Prasad, S.;Younan, N.H.;
      Pages: 3791 - 3801
      Abstract: Earthen levees have a significant role in protecting large areas of inhabited and cultivated land in the United States from flooding. Failure of the levees can result in loss of life and property. Slough slides are among the problems which can lead to complete levee failure during a high water event. In this paper, we develop a method to detect such slides using X-band synthetic aperture radar (SAR) data. Our proposed methodology includes: radiometric normalization of the TerraSAR image using high-resolution digital elevation map (DEM) data; extraction of features including backscatter and texture features from the levee; a feature selection method based on minimum redundancy maximum relevance (mRMR); and training a support vector machine (SVM) classifier and testing on the area of interest. To validate the proposed methodology, ground-truth data are collected from slides and healthy areas of the levee. The study area is part of the levee system along the lower Mississippi River in the United States. The output classes are healthy and slide areas of the levee. The results show the average classification accuracies of approximately 0.92 and Cohen's kappa measures of 0.85 for both healthy and slide pixels using ten optimal features selected by mRMR with a sigmoid SVM. A comparison of the SVM performance to the maximum likelihood (ML) and back propagation neural network (BPNN) shows that the average accuracy of the SVM is superior to that of the BPNN and ML classifiers.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Evaluation of ALOS/PALSAR L-Band Data for the Estimation of
           Eucalyptus Plantations Aboveground Biomass in Brazil
    • Authors: Baghdadi; N.;Le Maire, G.;Bailly, J.-S.;Ose, K.;Nouvellon, Y.;Zribi, M.;Lemos, C.;Hakamada, R.;
      Pages: 3802 - 3811
      Abstract: The Phased Array L-band Synthetic Aperture Radar (PALSAR-1) has provided very useful images dataset for several applications such as forestry. L-Band radar measurements have been widely used but with somewhat contradictory conclusions on the potential of this radar wavelength to estimate the aboveground biomass (AGB). The first objective of this study was to analyze the L-band SAR backscatter sensitivity to forest biomass for Eucalyptus plantations. The results showed that the radar signal is highly dependent on biomass only for values lower than 50 t/ha, which corresponds to plantations of approximately 3 years of age. Next, random forest (RF) regressions were performed to evaluate the potential of PALSAR data to predict the Eucalyptus biomass. Regressions were constructed to link the biomass to both radar signal and age of plantations. Results showed that the age was the variable that best explained the biomass followed by the PALSAR HV polarized signal. For biomasses lower than 50 t/ha, HV signal and plantation age were found to have the same level of importance in predicting biomass. For biomasses higher than 50 t/ha, plantation age was the main variable in the RF models. The use of PALSAR signal alone did not correctly predict the biomass of Eucalyptus plantations [ℝ2 lower than 0.5 and root-mean-squared error (RMSE) higher than 46.7 t/ha]. The use of plantation age in addition to the PALSAR signal improved slightly the prediction results (ℝ2 increased from 0.88 to 0.92 and RMSE decreased from 22.7 to 18.9 t/ha). PALSAR imagery does not allow a direct estimation of planting date of Eucalyptus stands but can follow efficiently the occurrence of clear-cuts if images are acquired sequentially, therefore allowing a rough estimate of the following plantation date because a stand of Eucalyptus is generally replanted 2-4 months after cutting. With a time series of radar images, it could be, therefore, possible to estimate the pla- tation age, and therefore improving the estimates of plantation biomass.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Capability of Rice Mapping Using Hybrid Polarimetric SAR Data
    • Authors: Lei Xie;Hong Zhang;Fan Wu;Chao Wang;Bo Zhang;
      Pages: 3812 - 3822
      Abstract: The objectives of this paper are to investigate the capability of hybrid polarimetric synthetic aperture radar (SAR) data for rice mapping and to explore the relationships between the hybrid polarimetric information and rice biophysical parameters. The linear polarization ratio (μL) is analyzed on the basis of reflection symmetry and simulated data, and has been demonstrated to behave similarly to the HH/VV polarization ratio, which has been widely used in rice and wheat mapping. The degree of linear polarization (PL) shows great potential in rice monitoring as well. In addition, a modified entropy-alpha decomposition method for hybrid polarimetric SAR is proposed to analyze the temporal scattering behaviors of rice in different growth stages. The degree of polarization (m), μL and PL are shown to be able to reflect the growth status of rice to a certain extent, and their empirical models are explored. Time-series images acquired by Radarsat-2 at C-band and in situ data, such as the fresh biomass, dry biomass, height, and days after transplantation (DAT), are used to demonstrate the analytical method and the foresaid conclusions.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Soil Salinity Characterization Using Polarimetric InSAR Coherence: Case
           Studies in Tunisia and Morocco
    • Authors: Barbouchi; M.;Abdelfattah, R.;Chokmani, K.;Ben Aissa, N.;Lhissou, R.;El Harti, A.;
      Pages: 3823 - 3832
      Abstract: The phenomenon of soil salinization in semi-arid regions is getting amplified and accentuated by both anthropogenic practices and climate change. Land salinization mapping and monitoring using conventional strategies are insufficient and difficult. Our work aims to study the potential of synthetic aperture radar (SAR) for mapping and monitoring of the spatio-temporal dynamics of soil salinity using interferometry. Our contribution in this paper consists of a statistical relationship that we establish between field salinity measurement and InSAR coherence based on an empirical analysis. For experimental validation, two sites were selected: 1) the region of Mahdia (central Tunisia) and 2) the plain of Tadla (central Morocco). Both sites underwent three ground campaigns simultaneously with three Radarsat-2 SAR image acquisitions. The results show that it is possible to estimate the temporal change in soil electrical conductivity (EC) from SAR images through the InSAR technique. It has been shown that the radar signal is more sensitive to soil salinity in HH polarization using a small incidence angle. However, for the HV polarization, a large angle of incidence is more suitable. This is, under considering the minimal influence of roughness and moisture surfaces, for a given InSAR coherence.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Snow Density and Ground Permittivity Retrieved from L-Band Radiometry: A
           Synthetic Analysis
    • Authors: Schwank; M.;Matzler, C.;Wiesmann, A.;Wegmuller, U.;Pulliainen, J.;Lemmetyinen, J.;Rautiainen, K.;Derksen, C.;Toose, P.;Drusch, M.;
      Pages: 3833 - 3845
      Abstract: A synthetic study was performed to determine the potential to retrieve dry-snow density and ground permittivity from multiangular L-band brightness temperatures. The thereto employed emission model was developed from parts of the “microwave emission model of layered snowpacks” (MEMLS) coupled with components adopted from the “L-band microwave emission of the biosphere” (L-MEB) model. The restriction to L-band made it possible to avoid scattering and absorption in the snow volume, leading to a rather simple formulation of our emission model. Parametric model studies revealed L-band signatures related to the mass density of the bottom layer of a dry snowpack. This gave rise to the presented analysis of corresponding retrieval performances based on measurements synthesized with the developed emission model. The question regarding the extent to which random noise translates into retrieval uncertainties was investigated. It was found that several classes of snow densities could be distinguished by retrievals based on L-band brightness temperatures with soil moisture and ocean salinity (SMOS)-typical data quality. Further synthetic retrievals demonstrated that propagation effects must be taken into account in dry snow even at L-band when retrieving permittivity of the underlying ground surface. Accordingly, current SMOS-based retrievals seam to underestimate actual ground permittivity by typically 30% as dry snow is wrongly considered as “invisible.” Although experimental validation has not yet been performed, the proposed retrieval approach is seen as a promising step toward the full exploitation of L-band brightness temperatures available from current and future satellite Earth observation missions, especially over the cold regions of the Northern Hemisphere.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Distortion Reduction in Singularity-Spreading Phase Unwrapping With
           Pseudo-Continuous Spreading and Self-Clustering Active Localization
    • Authors: Oshiyama; G.;Hirose, A.;
      Pages: 3846 - 3858
      Abstract: Singularity-spreading phase unwrapping (SSPU) realizes low calculation-cost phase unwrapping by utilizing its nature completely free from the combinatorial problem of pairing singular points (SPs), which is unavoidable in conventional branch-cut methods. However, the SSPU sometimes suffers from low-frequency global distortion. It occurs when the singularity is spread to excessively large area. To solve this problem, in this paper, we propose two methods, namely, fully isotropic SSPU and nonhollow SSPU, both of which realize pseudo-continuous spreading. By extending these methods, we also propose self-clustering active localization. Experiments demonstrate successful reduction of the low-frequency distortion, showing about 2-3 dB improvement of signal-to-noise ratio (SNR) in generated digital elevation model (DEM) with only 1/4-1/3 calculation time of that in conventional SSPU. The performance is totally discussed among a branch-cut method, conventional SSPU method, and proposed SSPU methods.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • InSAR Water Vapor Data Assimilation into Mesoscale Model MM5: Technique
           and Pilot Study
    • Authors: Pichelli; E.;Ferretti, R.;Cimini, D.;Panegrossi, G.;Perissin, D.;Pierdicca, N.;Rocca, F.;Rommen, B.;
      Pages: 3859 - 3875
      Abstract: In this study, a technique developed to retrieve integrated water vapor from interferometric synthetic aperture radar (InSAR) data is described, and a three-dimensional variational assimilation experiment of the retrieved precipitable water vapor into the mesoscale weather prediction model MM5 is carried out. The InSAR measurements were available in the framework of the European Space Agency (ESA) project for the “Mitigation of electromagnetic transmission errors induced by atmospheric water vapor effects” (METAWAVE), whose goal was to analyze and possibly predict the phase delay induced by atmospheric water vapor on the spaceborne radar signal. The impact of the assimilation on the model forecast is investigated in terms of temperature, water vapor, wind, and precipitation forecast. Changes in the modeled dynamics and an impact on the precipitation forecast are found. A positive effect on the forecast of the precipitation is found for structures at the model grid scale or larger (1 km), whereas a negative effect is found on convective cells at the subgrid scale that develops within 1 h time intervals. The computation of statistical indices shows that the InSAR assimilation improves the forecast of weak to moderate precipitation (
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • SAR Images Retrieval Based on Semantic Classification and Region-Based
           Similarity Measure for Earth Observation
    • Authors: Licheng Jiao;Xu Tang;Biao Hou;Shuang Wang;
      Pages: 3876 - 3891
      Abstract: Based on the semantic categorization and region-based similarity measure, a novel synthetic aperture radar (SAR) image retrieval method is proposed in this paper, which is inspired by the existing content-based image retrieval (CBIR) techniques and is oriented toward the Earth observation (EO). First, due to the large sizes of SAR images, new method semantically classifies the land covers in the patch level rather than the pixel level by the classic semisupervised learning (SSL), which could reduce the workload of selecting the representative image patch and decrease the searching space in the similarity calculation component. Furthermore, to overcome the inevitable classification error, our method provides an error recovery scheme, preventing the errors produced in categorization to contaminate the retrieval results. Third, the similarity between two patches is calculated by the improved integrated region matching (IIRM) measure based on the region-based similarity measure, which fails to meet the expectation in SAR images. The proposed method can be embedded into any EO mining systems to help them complete the EO missions. After comparing the method presented in this paper to others, it is evident that our method performs more effectively than others from the CBIR aspect.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • AIS-Based Evaluation of Target Detectors and SAR Sensors Characteristics
           for Maritime Surveillance
    • Authors: Pelich; R.;Longepe, N.;Mercier, G.;Hajduch, G.;Garello, R.;
      Pages: 3892 - 3901
      Abstract: This paper studies the performances of different ship detectors based on adaptive threshold algorithms. The detection algorithms are based on various clutter distributions and assessed automatically with a systematic methodology. Evaluation using large datasets of medium resolution SAR images and AIS (automatic identification system) data as ground truths allows to evaluate the efficiency of each detector. Depending on the datasets used for testing, the detection algorithms offer different advantages and disadvantages. The systematic method used in discriminating real detected targets and false alarms in order to determine the detection rate, allows us to perform an appropriate and consistent comparison of the detectors. The impact of SAR sensors characteristics (incidence angle, polarization, frequency and spatial resolution) is fully assessed, the vessels' length being also considered. Experiments are conducted on Radarsat-2 and CosmoSkymed ScanSAR datasets and AIS data acquired by coastal stations.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • SAR Imaging With Structural Sparse Representation
    • Authors: Fangfang Shen;Guanghui Zhao;Zicheng Liu;Guangming Shi;Jie Lin;
      Pages: 3902 - 3910
      Abstract: Sparse representation (SR)-based SAR imaging approaches have shown their superior performance compared with conventional approaches. However, for an image with rich spatial structures, a fixed global dictionary is usually ineffective to characterize the local structures. Piecewise autoregressive (PAR) model indicates that each pixel can be linearly represented by its local neighboring pixels. Inspired by this, an adaptive sparse space, effectively characterizing the varying image local structures, is designed, in which the entries are derived from the PAR model. By incorporating the adaptive SR into the SAR imaging, a novel structural SR-based SAR (SSR-SAR) imaging approach is proposed. Due to the fact that the adaptive sparse space is greatly dependent on the prior information of the SAR image, updating of the adaptive sparse space and SAR imaging is a joint optimization problem. In our approach, we propose to introduce the alternative minimization scheme to solve the problem. Besides, the Augmented Lagrangian Multiplier technique is adopted to accelerate the computation speed. Finally, experimental results are shown to demonstrate the validity of the proposed approach.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • An Iterative Generalized Hybrid Decomposition for Soil Moisture Retrieval
           Under Vegetation Cover Using Fully Polarimetric SAR
    • Authors: Jagdhuber; T.;Hajnsek, I.;Papathanassiou, K.P.;
      Pages: 3911 - 3922
      Abstract: An iterative, generalized hybrid polarimetric decomposition, combining model-based and eigen-based techniques together with a generalized vegetation model, is developed for soil moisture retrieval under agricultural vegetation cover. The algorithm is physically based without the need of empirical calibration or fitting with auxiliary data and runs in two iterations. The algorithm is applied on L-band fully polarimetric data sets acquired by DLR's E-SAR sensor. The flights were conducted within the AgriSAR, OPAQUE, and SARTEO campaigns carried out between 2006 and 2008 on three different test sites. The algorithm achieves inversion rates always higher than 95% for a variety of crop types at different phenological stages. The validation is performed against in situ time-domain reflectometry (TDR), frequency-domain reflectometry (FDR), and gravimetric measurements. The moisture levels range from 5 vol.% to 40 vol.%. The achieved root-mean-square error (RMSE) levels stay between 4.0 vol.% and 4.4 vol.% for all three sites across different vegetation and soil types, comprising the entire phenological cycle (e.g., April-July 2006).
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Fully Polarimetric SAR Image Classification via Sparse Representation and
           Polarimetric Features
    • Authors: Lamei Zhang;Liangjie Sun;Bin Zou;Moon; W.M.;
      Pages: 3923 - 3932
      Abstract: Feature extraction and image classification using polarimetric synthetic aperture radar (PolSAR) images are currently of great interest in SAR applications. Generally, PolSAR image classification is a high-dimensional nonlinear mapping problem. Sparse representation-based techniques have shown great potential for pattern recognition problems. Therefore, on the basis of the sparse characteristics of the features for PolSAR image classification, a supervised PolSAR image classification method based on sparse representation is proposed in this paper. First, the effective features are extracted to describe the distinction of each class. Then, the feature vectors of the training samples construct an over-complete dictionary and obtain the corresponding sparse coefficients; meanwhile, the residual error of the pending pixel with respect to each atom is evaluated and considered as the criteria for classification, and the ultimate class results can be obtained according to the atoms with the least residual error. In addition, a Simplified Matching Pursuit (SMP) algorithm is proposed to solve the optimization problem of sparse representation of PolSAR images. The verification tests are implemented using Danish EMISAR L-band fully polarimetric SAR data of Foulum area, Denmark. The preliminary experimental results confirm that the proposed method outputs an excellent result and moreover the classification process is simpler and less time consuming.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • A New Decomposition of a POLSAR Coherency Matrix Using a Generalized
           Scattering Model
    • Authors: Kusano; S.;Takahashi, K.;Sato, M.;
      Pages: 3933 - 3940
      Abstract: A new POLSAR model-based decomposition with a generalized scattering model is proposed. The generalized scattering model is built based on the particle cloud model adding the ellipticity angle. The model is highly flexible so that it represents the surface, double-bounce, volume, and helix scattering. Moreover, a uniform decomposition procedure to employ the model is proposed. For the first step, polarimetric coherency matrix is decomposed into two parts: the generalized scattering model and residue. Unknowns in the model are determined so that the resultant model matrix is subtracted, as much as possible, keeping the nonnegative eigenvalue condition in the residue. Then, the same operation is applied to the residue. By iteratively applying the process, the residue becomes null at last and the decomposed matrices perfectly fit the observed one. The procedure avoids branch conditions through the decomposition which often produce unreasonable decomposed power images. The proposed procedure is regarded as an extension of the eigenvalue-based decomposition considering the depolarization. The demonstration of the proposed decomposition shows that the results are considerably different from those of the eigenvalue-based one especially in forest area: more straightforwardly interpreted, since the model fits observed coherency matrix better. Furthermore, it is shown that the orientation angle randomness is physically important not only to measure the reliability of estimated orientation angles but also to estimate volume scattering power more accurately conventional model-based decomposition.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Sparse Representation-Based ISAR Imaging Using Markov Random Fields
    • Authors: Lu Wang;Lifan Zhao;Guoan Bi;Chunru Wan;
      Pages: 3941 - 3953
      Abstract: To encourage the continuity of the target scene, a novel sparse representation (SR)-based inverse synthetic aperture radar (ISAR) imaging algorithm is proposed by leveraging the Markov random fields (MRF). The ISAR imaging problem is reformulated in a Bayesian framework where correlated priors are used for the hidden variables to enforce the continuity of target scene. To further enforce the nonzero or zero scatterers to cluster in a spatial consistent manner, the MRF is used as the prior for the support of the target scene. To surmount the difficulty of calculating the posterior due to the imposed correlated priors and the MRF, variational Bayes expectation-maximization (VBEM) method is used to simultaneously approximate the posterior of the hidden variables and estimate the model parameters of the MRF. The convergence of the method is easily diagnosed by commonly used stopping criterion. Both the synthetic and the experimental results demonstrate that the proposed algorithm can achieve substantial improvements in terms of preserving the weak scatterers and removing noise components over other reported SR-based ISAR imaging algorithms.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • ISAR Imaging for Fluctuating Ships Based on a Fast Bilinear Parameter
           Estimation Algorithm
    • Authors: Jibin Zheng;Tao Su;Guisheng Liao;Hongwei Liu;Zheng Liu;Qing Huo Liu;
      Pages: 3954 - 3966
      Abstract: For inverse synthetic aperture radar (ISAR) imaging of ships fluctuating with oceanic waves, azimuth echoes of a range cell have to be modeled as cubic phase signals (CPSs) after the range alignment and the phase adjustment. In ISAR imaging based on the CPS model, the chirp rate and the quadratic chirp rate are identified as causes of the target image defocus and need to be estimated with an effective algorithm. In this paper, a fast bilinear parameter estimation algorithm is proposed and applied in ISAR imaging for fluctuating ships by employing the cubic phase bilinear function, the nonuniform fast Fourier transform (NUFFT), and the parameter space switching method. Compared to two existing representative parameter estimation algorithms for the CPS, the advantages of this proposed estimation algorithm are: the computational cost is lower due to the NUFFT and the parameter space switching method and the bilinearity and the energy accumulation operation guarantee a higher anti-noise performance and a better suppression on cross-terms. Through simulations on synthetic models and the real radar data, we verify the effectiveness of this fast bilinear parameter estimation algorithm and the corresponding ISAR imaging algorithm.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • An Airborne SAR Moving Target Imaging and Motion Parameters Estimation
           Algorithm With Azimuth-Dechirping and the Second-Order Keystone Transform
    • Authors: Jiefang Yang;Yunhua Zhang;
      Pages: 3967 - 3976
      Abstract: In this paper, we propose an algorithm for airborne SAR moving target imaging and motion parameters estimation in Doppler ambiguity situation with azimuth-dechirping and the second-order keystone transform (SOKT) applied. In this algorithm, we use a third-order phase model for the echo signal, and after the compensation of third-order phase, the moving target can be symmetrically focused in azimuth. This algorithm has five major steps. The azimuth-dechirping is conducted to eliminate the Doppler ambiguity. The SOKT is conducted to correct the range curvature. The Radon transform is applied to estimate the trajectory slope for range walk correction and the across-track velocity estimation. The fractional Fourier transform (FrFT) is utilized to estimate the Doppler rate for estimating the along-track velocity. The moving target is focused after azimuth compression and third-order phase compensation. Both simulation and real SAR data are processed to validate the proposed algorithm.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • A New Chirp Scaling Algorithm for Highly Squinted Missile-Borne SAR Based
           on FrFT
    • Authors: Si Chen;Shuning Zhang;Huichang Zhao;Yong Chen;
      Pages: 3977 - 3987
      Abstract: Since synthetic aperture technology was employed in radar signal processing, a lot of imaging algorithms have been developed for highly squinted synthetic aperture radar (SAR). However, the high-resolution imaging for highly squinted SAR data is still a difficult issue due to the large range migration and strong space-variant characteristic. To accommodate for this problem, a new fractional chirp scaling algorithm (FrCSA) for highly squinted missile-borne SAR is proposed from high resolution point of view in this paper. The performance of the FrCSA is compared to the classical CSA based on fast Fourier transform (FFT). Simulation and real data results indicate that the FrCSA offers better focusing capabilities, greater peak sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR) by appropriately choosing the rotation angles for the range and azimuth fractional Fourier transform (FrFT).
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Deception Jamming for Squint SAR Based on Multiple Receivers
    • Authors: Bo Zhao;Feng Zhou;Zheng Bao;
      Pages: 3988 - 3998
      Abstract: A deception jamming method for synthetic aperture radar (SAR) based on multiple receivers is proposed. This method deals with the parameters of hostile SAR as a whole for deception jamming. By measuring the range differences between different receivers, higher accuracy can be achieved than detecting each of the parameters directly. The squint angle, which is hard to be obtained for the electronic reconnaissance, is also included in the parameters the multireceiver system gets, so this method works on the squint SAR. The accuracy of the algorithm and the system noise are analyzed. Simulation results verify the effectiveness of the algorithm.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Modeling and Processing of Two-Dimensional Spatial-Variant Geosynchronous
           SAR Data
    • Authors: Dexin Li;Manqing Wu;Zaoyu Sun;Feng He;Zhen Dong;
      Pages: 3999 - 4009
      Abstract: Imaging of spatial-variant geosynchronous synthetic aperture radar (GEO SAR) in the L band with long integration time is discussed. To compensate for spatial variances in both range and azimuth directions, a new algorithm based on improved omega-K (ωK) and three-time azimuth chirp scaling (3ACS) is proposed. First, the integration time and the slant range model were analyzed. Second, the two-dimensional (2-D) spectrum was used for range cell migration correction (RCMC), secondary range compression (SRC), and azimuth compression, and the influences of spatial variances on each term were considered. Third, the improved ωK was used to compensate for the range variance, and 3ACS was used to compensate for the azimuth variance. The scope of 2-D focusing in high-resolution GEO SAR imaging was clearly enlarged. Finally, the performance of the algorithm was demonstrated using simulations based on a spaceborne radar advance simulator (SBRAS).
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • High-Resolution Inverse Synthetic Aperture Radar Imaging and Scaling With
           Sparse Aperture
    • Authors: Gang Xu;Meng-Dao Xing;Xiang-Gen Xia;Qian-Qian Chen;Lei Zhang;Zheng Bao;
      Pages: 4010 - 4027
      Abstract: In high-resolution radar imaging, the rotational motion of targets generally produces migration through resolution cells (MTRC) in inverse synthetic aperture radar (ISAR) images. Usually, it is a challenge to realize accurate MTRC correction on sparse aperture (SA) data, which tends to degrade the performance of translational motion compensation and SA-imaging. In this paper, we present a novel algorithm for high-resolution ISAR imaging and scaling from SA data, which effectively incorporates the translational motion phase error and MTRC corrections. In this algorithm, the ISAR image formation is converted into a sparsity-driven optimization via maximum a posterior (MAP) estimation, where the statistics of an ISAR image is modeled as complex Laplace distribution to provide a sparse prior. The translational motion phase error compensation and cross-range MTRC correction are modeled as joint range-invariant and range-variant phase error corrections in the range-compressed phase history domain. Our proposed imaging approach is performed by a two-step process: 1) the range-invariant and range-variant phase error estimations using a metric of minimum entropy are employed and solved by using a coordinate descent method to realize a coarse phase error correction. Meanwhile, the rotational motion can be obtained from the estimation of range-variant phase errors, which is used for ISAR scaling in the cross-range dimension; 2) under a two-dimensional (2-D) Fourier-based dictionary by involving the slant-range MTRC, joint MTRC-corrected ISAR imaging and accurate phase adjustment are realized by solving the sparsity-driven optimization with SA data, where the residual phase errors are treated as model error and removed to achieve a fine correction. Finally, some experiments based on simulated and measured data are performed to confirm the effectiveness of the proposed algorithm.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Noise Reduction Method Based on Principal Component Analysis With Beta
           Process for Micro-Doppler Radar Signatures
    • Authors: Lan Du;Baoshuai Wang;Penghui Wang;Yanyan Ma;Hongwei Liu;
      Pages: 4028 - 4040
      Abstract: In radar remote-sensing area, the radar returns from a target are usually under relatively low signal-noise ratio (SNR) due to the large distance between radar and target, which will bring difficulties in target detection, tracking, and classification. In this paper, an efficient algorithm is proposed to denoise the returned micro-Doppler radar signals under low SNR conditions. The new algorithm develops a nonparametric extension to the principal component analysis (PCA) model with the Beta process (BP) prior. The BP is a fully Bayesian conjugate prior which allows analytic posterior calculation and straightforward interference. This proposed Beta process-based principal component analysis (BP-PCA) is utilized to model the returned micro-Doppler signals from airplane targets and ground moving targets with low-resolution radar, where the number of principal components in PCA can be selected adaptively with the BP prior-based Bayesian structure. Noise reduction is accomplished via reconstructing the echo within the subspace that composed of the selected principal components and discarding the residual noise subspace. We demonstrate the noise reduction performance of the proposed model with measured micro-Doppler data from some different kinds of targets. The experimental results are also compared with some other state-of-the-art approaches.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Change Detection in Full and Dual Polarization, Single- and Multifrequency
           SAR Data
    • Authors: Nielsen; A.A.;Conradsen, K.;Skriver, H.;
      Pages: 4041 - 4048
      Abstract: When the covariance matrix formulation is used for multilook polarimetric synthetic aperture radar (SAR) data, the complex Wishart distribution applies. Based on this distribution, a test statistic for equality of two complex variance-covariance matrices and an associated asymptotic probability of obtaining a smaller value of the test statistic are given. In a case study, airborne EMISAR C- and L-band SAR images from the spring of 1998 covering agricultural fields and wooded areas near Foulum, Denmark, are used in single- and bifrequency, bitemporal change detection with full and dual polarimetry data.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Evaluation of Chlorophyll-Related Vegetation Indices Using Simulated
           Sentinel-2 Data for Estimation of Crop Fraction of Absorbed
           Photosynthetically Active Radiation
    • Authors: Taifeng Dong;Jihua Meng;Jiali Shang;Jiangui Liu;Bingfang Wu;
      Pages: 4049 - 4059
      Abstract: In recent years, the impact of chlorophyll content on the estimation of the fraction of absorbed photosynthetically active radiation (FPAR) has attracted increased attention. In this study, chlorophyll-related vegetation indices (VIs) were selected and tested for their capability in crop FPAR estimation using simulated Sentinel-2 data. These indices can be categorized into four classes: 1) the ratio indices; 2) the normalized difference indices; 3) the triangular area-based indices; and 4) the integrated indices. Two crops, wheat and corn, with distinctive canopy and leaf structure were studied. Measured FPAR and Sentinel-2 reflectance simulated from field spectral measurements were used. The results showed that VIs using the nearinfrared and red-edge reflectance, including the modified Simple Ratio-2 (mSR2), the red-edge Simple Ratio (SR705), the RedEdge Normalized Difference Vegetation Index (ND705), MERIS Terrestrial Chlorophyll Index (MTCI), and the Revised Optimized Soil-Adjusted Vegetation Index (OSAVI[705, 750]), had a strong linear correlation with FPAR, especially in the high biomass range. When the red-edge reflectance was used, the ratio indices (e.g., mSR2 and SR705) had a stronger correlation with crop FPAR than the normalized difference indices (e.g., ND705). Sensitivity analysis showed that mSR2 had the strongest linear correlation with FPAR of the two crops across a growing season. Further analysis indicated that indices using the red-edge reflectance might be useful for developing FPAR retrieval algorithms that are independent of crop types. This suggests the potential for high resolution and high-quality mapping of FPAR for precision farming using the Sentinel-2 data.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Jointly Assimilating MODIS LAI and ET Products Into the SWAP Model for
           Winter Wheat Yield Estimation
    • Authors: Jianxi Huang;Hongyuan Ma;Wei Su;Xiaodong Zhang;Yanbo Huang;Jinlong Fan;Wenbin Wu;
      Pages: 4060 - 4071
      Abstract: Leaf area index (LAI) and evapotranspiration (ET) are two crucial biophysical variables related to crop growth and grain yield. This study presents a crop model-data assimilation framework to assimilate the 1-km moderate resolution imaging spectroradiometer (MODIS) LAI and ET products (MCD15A3 and MOD16A2, respectively) into the soil water atmosphere plant (SWAP) model to assess the potential for estimating winter wheat yield at field and regional scales. Since the 1-km MODIS products generally underestimate LAI or ET values in fragmented agricultural landscapes due to scale effects and intrapixel heterogeneity, we constructed a new cost function by comparing the generalized vector angle between the observed and modeled LAI and ET time series during the growing season. We selected three parameters (irrigation date, irrigation depth, and emergence date) as the reinitialized parameters to be optimized by minimizing the cost function using the shuffled complex evolution method-University of Arizona (SCE-UA) optimization algorithm, and then used the optimized parameters as inputs into the SWAP model for winter wheat yield estimation. We used four data-assimilation schemes to estimate winter wheat yield at field and regional scales. We found that jointly assimilating MODIS LAI and ET data improved accuracy (R2 = 0.43, RMSE = 619 kg · ha-1) than assimilating MODIS LAI data (R2 = 0.28, RMSE = 889 kg · ha-1) or ET data (R2 = 0.36, RMSE = 1561 kg·ha-1) at the county level, which indicates that the proposed estimation method is reliable and applicable at a county scale.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • A Comparison of Open-Source LiDAR Filtering Algorithms in a Mediterranean
           Forest Environment
    • Authors: Montealegre; A.L.;Lamelas, M.T.;de la Riva, J.;
      Pages: 4072 - 4085
      Abstract: Light detection and ranging (LiDAR) is an emerging remote-sensing technology with potential to assist in mapping, monitoring, and assessment of forest resources. Despite a growing body of peer-reviewed literature documenting the filtering methods of LiDAR data, there seems to be little information about qualitative and quantitative assessment of filtering methods to select the most appropriate to create digital elevation models with the final objective of normalizing the point cloud in forestry applications. Furthermore, most algorithms are proprietary and have high purchase costs, while a few are openly available and supported by published results. This paper compares the accuracy of seven discrete return LiDAR filtering methods, implemented in nonproprietary tools and software in classification of the point clouds provided by the Spanish National Plan for Aerial Orthophotography (PNOA). Two test sites in moderate to steep slopes and various land cover types were selected. The classification accuracy of each algorithm was assessed using 424 points classified by hand and located in different terrain slopes, cover types, point cloud densities, and scan angles. MCC filter presented the best overall performance with an 83.3% of success rate and a Kappa index of 0.67. Compared to other filters, MCC and LAStools balanced quite well the error rates. Sprouted scrub with abandoned logs, stumps, and woody debris and terrain slopes over 15° were the most problematic cover types in filtering. However, the influence of point density and scan-angle variables in filtering is lower, as morphological methods are less sensitive to them.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Contribution to Lightning Parameters Study Based on Some American Tropical
           Regions Observations
    • Authors: Torres; H.;Perez, E.;Younes, C.;Aranguren, D.;Montana, J.;Herrera, J.;
      Pages: 4086 - 4093
      Abstract: This paper presents a recent characterization review of three cloud-to-ground lightning parameters [lightning peak current, ground flash density, and keraunic level (KL)] used in engineering applications based on available data from studies conducted in some tropical countries of Central and South America (Brazil, Colombia, Costa Rica, and Venezuela), considering seasonal and spatial variation aspects. There are some differences between the behaviors of the analyzed parameters in tropical areas in comparison with those published in the literature for temperate ones. The most significant conclusion is that historical data suggest that the highest ground flash density are located between latitude of 8° and 10° north. This value is much higher than the highest values reported for countries located in temperate regions. It is seen from the KL analysis that this parameter varies depending on the latitude with values up to 200 thunderstorm days (TDs).
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Validation Strategies for Satellite-Based Soil Moisture Products Over
           Argentine Pampas
    • Authors: Grings; F.;Bruscantini, C.A.;Smucler, E.;Carballo, F.;Dillon, M.E.;Collini, E.A.;Salvia, M.;Karszenbaum, H.;
      Pages: 4094 - 4105
      Abstract: In this paper, an evaluation strategy for two-candidate satellite-derived SM products is presented. In particular, we analyze the performance of two candidate algorithms [soil moisture ocean salinity (SMOS)-based soil moisture (SM) and advanced scatterometer (ASCAT)-based SM] to monitor SM in Pampas Plain. The difficulties associated with commonly used evaluation techniques are addressed, and techniques that do not require ground-based observations are presented. In particular, we introduce comparisons with a land-surface model (GLDAS) and SM anomalies and triple collocation analyses. Then, we discuss the relevance of these analyses in the context of end-users requirements, and propose an extreme events-detection analysis based on anomalies of the standardized precipitation index (SPI) and satellite-based SM anomalies. The results show that: 1) both ASCAT and SMOS spatial anomalies data are able to reproduce the expected SM spatial patterns of the area; 2) both ASCAT and SMOS temporal anomalies are able to follow the measured in situ SM temporal anomalies; and 3) both products were able to monitor large SPI extremes at specific vegetation conditions.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Optimizing Total Energy–Mass Flux (TEMF) Planetary Boundary Layer
           Scheme for Intel’s Many Integrated Core (MIC) Architecture
    • Authors: Mielikainen; J.;Huang, B.;Huang, H.-L.A.;
      Pages: 4106 - 4119
      Abstract: In order to make use of the ever-improving microprocessor performance, the applications must be modified to take advantage of the parallelism of today's microprocessors. One such application that needs to be modernized is the weather research and forecasting (WRF) model, which is designed for numerical weather prediction and atmospheric research. The WRF software infrastructure consists of several components such as dynamic solvers and physics schemes. Numerical models are used to resolve the large-scale flow. However, subgrid-scale parameterizations are for an estimation of small-scale properties (e.g., boundary layer turbulence and convection, clouds, radiation). Those have a significant influence on the resolved scale due to the complex nonlinear nature of the atmosphere. For the cloudy planetary boundary layer (PBL), it is fundamental to parameterize vertical turbulent fluxes and subgrid-scale condensation in a realistic manner. A parameterization based on the total energy-mass flux (TEMF) that unifies turbulence and moist convection components produces a better result than other PBL schemes. Thus, we present our optimization results for the TEMF PBL scheme. Those optimizations included vectorization of the code to utilize multiple vector units inside each processor code. The optimizations improved the performance of the original TEMF code on Xeon Phi 7120P by a factor of 25.9×. Furthermore, the same optimizations improved the performance of the TEMF on a dual socket configuration of eight-core Intel Xeon E5-2670 CPUs by a factor of 8.3× compared to the original TEMF code.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Validation and Intercomparison of SARAL/AltiKa and PISTACH-Derived Coastal
           Wave Heights Using In-Situ Measurements
    • Authors: Hithin; N.K.;Remya, P.G.;Balakrishnan Nair, T.M.;Harikumar, R.;Kumar, R.;Nayak, S.;
      Pages: 4120 - 4129
      Abstract: SARAL/AltiKa, the first Ka-band altimeter, now provides an opportunity to study wave characteristics in the world's coastal ocean with improved accuracy. In the present work, AltiKa-derived significant wave heights (Hs) in the coastal ocean and inland water bodies have been analyzed using in-situ measurements. Analysis shows that AltiKa measured Hs agree well with the in-situ measurements with high correlation (0.98), low bias (6 cm), and low RMSE (19 cm) in the coastal ocean, and the performance is highly consistent across different coastal zones in the three tropical oceans. AltiKa performance is found to be very good (RMSE = 24 cm and correlation = 0.94) near to the coast (
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Feasibility of Code-Level Altimetry Using Coastal BeiDou Reflection
           (BeiDou-R) Setups
    • Authors: Yun Zhang;Luman Tian;Wanting Meng;Qiming Gu;Yanling Han;Zhonghua Hong;
      Pages: 4130 - 4140
      Abstract: With the development of the Chinese BeiDou satellite navigation system, the applications of BeiDou-reflected (BeiDou-R) signals will play a key role in Global Navigation Satellite System-reflected (GNSS-R) signals. In this paper, we describe the theory of code-level ocean surface altimetry using BeiDou-R signals. Two BeiDou-R coastal experiments (lake and ocean experiments in China) were performed using direct right-handed circularly polarized (D-RHCP) antenna, reflected left-handed circularly polarized (R-LHCP) antenna, and reflected right-handed circularly polarized (R-RHCP) antenna. This is the first research on BeiDou-R ocean altimetry performance analysis. The lake experiment demonstrated the potential availability of water surface altimetry using BeiDou-R signals. We found that the resulting error (0.11 m) from the BeiDou geostationary Earth orbit (GEO) satellite signals was much smaller than that (1.61 m) from the inclined geosynchronous orbit (IGSO) satellite signals, and thus verified that R-LHCP signals from high-elevation satellites were more suitable for altimetry. The ocean surface altimetry was performed on China East Sea for 28 h. The predicted results of ocean surface height using R-LHCP signals from BeiDou GEO satellites were in good agreement with the field measured data, and the root-mean squared (rms) height precision can reach 0.37 m. A better performance of GEO observations compared to IGSO observations was found for coastal setups. In case of airborne setups with different multipath settings, the result may be different.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Solar Lab Notebook (SLN): An Ultra-Portable Web-Based System for
           Heliophysics and High-Security Labs
    • Authors: Tsalaportas; P.G.;Kapinas, V.M.;Karagiannidis, G.K.;
      Pages: 4141 - 4150
      Abstract: This paper introduces the solar lab notebook (SLN), an electronic lab notebook (ELN) for improving the process of recording and sharing solar related digital information in an organized manner. SLN is a pure web-based application (available online: that runs client-side only, employing a clean and very friendly graphical user interface (GUI) design, and thus providing a true cross-platform user experience. Furthermore, SLN leverages unique technologies offered by modern web browsers, such as the FileReader API, the Blob interface, and Local Storage mechanism; it is coded entirely using HTML5, CSS3, and JavaScript, and powered by the extremely well-documented extensible markup language (XML) file format. For high-security labs, it can be utilized as an ultra-portable and secure digital notebook solution, since it is functionally self-contained, and does not require any server-side process running on either the local or a remote system. Finally, the W3C XML Schema language is used to define a list of rules, namely a data standard, that an SLN file must conform to, in order to be valid. In this way, developers are able to implement their own validation functions in their projects, or use one of the freely available tools to check if a data file is properly structured. Similarly, scientific groups at different labs can easily share information, being confident about the integrity of the exchanged data.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Natural Color Satellite Image Mosaicking Using Quadratic Programming in
           Decorrelated Color Space
    • Authors: Cresson; R.;Saint-Geours, N.;
      Pages: 4151 - 4162
      Abstract: Generating mosaics of orthorectified remote sensing images is a challenging task because of the colorimetric differences between adjacent images introduced by land use, surface illumination, atmospheric conditions, and sensor. Most of the existing color correction methods involve pairwise techniques, which are limited when the collection of images is large with numerous overlaps. Besides, available techniques do not operate in a color space suited for true-color processing. This paper presents a simple and robust method to perform the global colorimetric harmonization of multiple overlapping remote sensing images in natural colors (RGB). Our parameter-free method deals simultaneously with any number of images, with any spatial layout, and without any single reference image. It is based on the resolution of a quadratic programming (QP) optimization problem. It operates in the lαβ decorrelated color space, which is well suited for human vision of natural scenes. The results obtained from the mosaicking of 132 RapidEye color orthoimages over mainland France demonstrate good potential for performing colorimetric harmonization automatically and effectively.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Intercomparison of Operational Land Surface Temperature Products Derived
           From MSG-SEVIRI and Terra/Aqua-MODIS Data
    • Authors: Si-Bo Duan;Zhao-Liang Li;
      Pages: 4163 - 4170
      Abstract: Accuracy assessment of land surface temperature (LST) products is critical to facilitate their use in various studies. As an alternative method for assessing the accuracy of LST products, a new satellite LST product is compared with a heritage LST product to validate and determine the uncertainties in the satellite-derived LST approach. In this study, we propose a method for the intercomparison of the Meteosat second generation-spinning enhanced visible and infrared imager (MSG-SEVIRI) and Terra/Aqua-moderate resolution imaging spectroradiometer (MODIS) LST products. The intercomparison was performed by verifying the collocation in space, temporal concurrence, viewing geometry alignment, and spatial homogeneity between the two LST products. The discrepancies between the SEVIRI and MODIS LST products were investigated over different seasons, times of day, and surface types. SEVIRI LST values are generally higher than MODIS LST values, with positive biases during daytime (approximately 2-4 K) and nighttime (approximately 1-2 K). Significant variability of the daytime LST discrepancies with season, time of day, and surface type is observed. Compared with the daytime LST discrepancies, the nighttime LST discrepancies are less dependent on season, time of day, and surface type.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Using Remote Sensing to Track Variation in Phosphorus and Its Interaction
           With Chlorophyll-a and Suspended Sediment
    • Authors: Changchun Huang;Yulong Guo;Hao Yang;Yunmei Li;Jun Zou;Mingli Zhang;Heng Lyu;Axing Zhu;Tao Huang;
      Pages: 4171 - 4180
      Abstract: Treatment of eutrophication and algal blooms in large shallow lakes has been constrained by the endogenetic release of nutrients from sediment resuspension despite the wellcontrolled input of nutrients from surrounding land in Taihu Lake, China. In this study, we propose a method to simplify regionally empirical algorithms for total suspended matter (CTSM), chlorophyll-a (CChl-a), and phosphorus concentration (Cp) for the Geostationary Ocean Color Imager (GOCI) for Taihu Lake. The results show that the GOCI-derived CTSM, CChl-a, and Cp match well with the in situ measured data. Based on the validated synchronous and timely observation data (CTSM, CChl-a and Cp) from GOCI level-1b data, the interaction of phosphorus with algae and suspended sediment were analyzed from August 6 to August 9, 2013. The results indicate that phosphorus released from sediment resuspension is significant in Taihu Lake, with a high spatial-temporal variation. The effect of the restriction of nutrients (nitrogen and phosphorus) on algal growth varied temporally and spatially with the hydrodynamic characteristics of the lake. In most cases, restricted phosphorus in the lake is the primary reason for the algal growth, especially in open regions such as Center Lake (CL), Northwestern Lake (NWL), and Southwestern Lake (SWL). Both nitrogen and phosphorus are the restrictive factors to algal growth in Meiliang and Gonghu Bays. More attention should thus be focused on the endogenetic release of phosphorus in Taihu Lake when treating eutrophication and algal blooms in addition to controlling the input of nitrogen and phosphorus from surrounding land.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Reconstruction of Satellite-Derived Sea Surface Temperature Data Based on
           an Improved DINEOF Algorithm
    • Authors: Bo Ping;Fenzhen Su;Yunshan Meng;
      Pages: 4181 - 4188
      Abstract: An improved data interpolating empirical orthogonal function (I-DINEOF) algorithm was proposed in this study. Compared with the ordinary DINEOF algorithm, in the I-DINEOF algorithm, the existing data are not necessary to be selected for cross-validation and the initial matrix is directly used for reconstruction. Instead of using single EOF to reconstruct the whole spatio-temporal matrix, the initial matrix is divided into several subareas and each subarea is reconstructed by the most suitable EOF. To validate the accuracy of the I-DINEOF algorithm, a real sea surface temperature (SST) data set and three synthetic data sets with different missing data percentage are reconstructed by using the DINEOF and I-DINEOF algorithms. Four parameters (Pearson correlation coefficient, signal-to-noise ratio, root-mean-square error, and mean absolute difference) are used as a measure of reconstructed accuracy. Compared with the DINEOF algorithm, the I-DINEOF algorithm is less affected by the missing data and can significantly enhance the accuracy of reconstruction.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Atmospheric Correction of AISA Measurements Over the Florida Keys
           Optically Shallow Waters: Challenges in Radiometric Calibration and
           Aerosol Selection
    • Authors: Minwei Zhang;Chuanmin Hu;English; D.;Carlson, P.;Muller-Karger, F.E.;Toro-Farmer, G.;Herwitz, S.R.;
      Pages: 4189 - 4196
      Abstract: An Airborne Imaging Spectrometer for Applications (AISA) hyperspectral imager was deployed on a manned aircraft flown at 1305-m altitude to collect data over optically shallow waters in the Florida Keys with the ultimate goal of mapping water quality and benthic habitats. As a first step, we developed a practical atmospheric correction (AC) approach to derive surface remote-sensing reflectance (Rrs) from AISA measurements using radiative transfer simulations and constraints obtained from field spectral Rrs measurements. Unlike previously published method, the AC approach removes the surface Fresnel reflection and accounts for aircraft altitude and nonzero near-infrared (NIR) reflectance through iteration over the pre-established lookup tables (LUTs) based on MODTRAN calculations. Simulations and comparison with concurrent in situ Rrs measurements show the feasibility of the approach in deriving surface Rrs with acceptable uncertainties. The possibility of errors in the radiometric calibration of AISA is demonstrated, although a definitive assessment cannot be made due to lack of enough concurrent in situ measurements. The need for noise reduction and the difficulty in carrying out a vicarious calibration are also discussed to help advance the design of future AISA missions.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Bag-of-Words and Object-Based Classification for Cloud Extraction From
           Satellite Imagery
    • Authors: Yi Yuan;Xiangyun Hu;
      Pages: 4197 - 4205
      Abstract: Automatic cloud extraction from satellite imagery is an important task for many applications in remote sensing. Humans can easily identify various clouds from satellite images based on the visual features of cloud. In this study, a method of automatic cloud detection is proposed based on object classification of image features. An image is first segmented into superpixels so that the descriptor of each superpixel can be computed to form a feature vector for classification. The support vector machine algorithm is then applied to discriminate cloud and noncloud regions. Thereafter, the GrabCut algorithm is used to extract more accurate cloud regions. The key of the method is to deal with the highly varying patterns of clouds. The bag-of-words (BOW) model is used to construct the compact feature vectors from densely extracted local features, such as dense scale-invariant feature transform (SIFT). The algorithm is tested using 101 RapidEye and 86 Landsat images with many cloud patterns. These images achieve 89.2% of precision, 87.8% of recall for RapidEye, 85.8% of precision, and 83.9% of recall for Landsat. The experiments show that the method is insensitive to the number of codewords in the codebook construction of the BOW.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • Scene Learning for Cloud Detection on Remote-Sensing Images
    • Authors: Zhenyu An;Zhenwei Shi;
      Pages: 4206 - 4222
      Abstract: Cloud detection plays a major role for remote-sensing image processing. To accomplish the task, a novel automatic supervised approach based on the “scene-learning” scheme is proposed in this paper. Scene learning aims at training and applying a cloud detector on the whole image scenes. The cloud detector herein is a special classifier that is used to separate clouds from the backgrounds. Concretely, scene learning regards each pixel of scenes in training image as a sample, and uses it to train a cloud detector. Accordingly, the detecting process is also implemented on each pixel of testing image using the trained detector. Generally, scene-learning scheme contains two modules: feature data simulating and cloud detector learning and applying. We first simulate a kind of cubic structural data (also named feature data) by stacking different fundamental image features, including color, statistical information, texture, and structure. Such data synthesize different image features, and it is used for cloud detector training and applying. Cloud detector is designed based on minimizing the residual error between the feature data and its labels. The detector is easy to be trained because of its closed-form. Applying the detector and some necessary cloud refinement methods to the testing images, we could finally detect clouds. We also theoretically analyze the influence of feature number and prove that more features lead to better performance of scene learning under certain circumstance. Comparisons of qualitative and quantitative analyses of the experimental results are implemented. Results indicate the efficacy of the proposed method.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • how can you get your idea to market first
    • Pages: 4223 - 4223
      Abstract: Advertisement, IEEE.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
  • IEEE membership can help you reach your personal goals
    • Pages: 4224 - 4224
      Abstract: Advertisement, IEEE.
      PubDate: Aug. 2015
      Issue No: Vol. 8, No. 8 (2015)
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