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  Subjects -> ELECTRONICS (Total: 153 journals)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 1)
Advances in Electronics     Open Access   (Followers: 1)
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: 71)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 11)
Annals of Telecommunications     Hybrid Journal   (Followers: 4)
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: 9)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 16)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 14)
Biomedical Instrumentation & Technology     Full-text available via subscription   (Followers: 5)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 6)
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: 9)
Consumer Electronics Times     Open Access   (Followers: 4)
Control Systems     Hybrid Journal   (Followers: 24)
Electronic Design     Partially Free  
Electronic Markets     Hybrid Journal   (Followers: 5)
Electronic Materials Letters     Hybrid Journal   (Followers: 3)
Electronics     Open Access   (Followers: 8)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 5)
Electronics Letters     Hybrid Journal   (Followers: 19)
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 22)
Energy Harvesting and Systems : Materials, Mechanisms, Circuits and Storage     Hybrid Journal   (Followers: 1)
EPJ Quantum Technology     Open Access  
EURASIP Journal on Embedded Systems     Open Access   (Followers: 8)
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Foundations and TrendsĀ® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and TrendsĀ® in Signal Processing     Full-text available via subscription   (Followers: 4)
Frequenz     Full-text available via subscription   (Followers: 2)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 2)
Geoscience and Remote Sensing, IEEE Transactions on     Hybrid Journal   (Followers: 21)
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 4)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 15)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 14)
IEEE Consumer Electronics Magazine     Full-text available via subscription   (Followers: 17)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 12)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 2)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 6)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 10)
IEEE Transactions on Audio, Speech, and Language Processing     Hybrid Journal   (Followers: 12)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 26)
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)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 8)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 7)
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 7)
IET Power Electronics     Hybrid Journal   (Followers: 13)
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: 13)
Industry Applications, IEEE Transactions on     Hybrid Journal   (Followers: 5)
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: 11)
International Journal of Antennas and Propagation     Open Access   (Followers: 8)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 1)
International Journal of Biomedical Nanoscience and Nanotechnology     Hybrid Journal   (Followers: 7)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 4)
International Journal of Computer & Electronics Research     Full-text available via subscription   (Followers: 2)
International Journal of Control     Hybrid Journal   (Followers: 13)
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: 6)
International Journal of Nanoscience     Hybrid Journal   (Followers: 1)
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: 2)
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: 8)
International Journal on Electrical and Power Engineering     Full-text available via subscription   (Followers: 11)
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: 2)

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Journal Cover   Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
  [SJR: 1.632]   [H-I: 19]   [19 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  [176 journals]
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote
           Sensing Information for Authors
    • Abstract: Presents information for authors publishing in this journal.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • IEEE Transactions on Geoscience and Remote Sensing institutional listings
    • PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote
           Sensing publication information
    • PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Front cover
    • Abstract: Presents the front cover for this issue of the publication.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Table of Contents
    • Pages: 941 - 942
      Abstract: Presents the table of contents for this issue of the publication.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Urban Area SAR Image Man-Made Target Extraction Based on the Product Model
           and the Time–Frequency Analysis
    • Authors: Wenjin Wu;Huadong Guo;Xinwu Li;
      Pages: 943 - 952
      Abstract: This paper proposed an innovative framework to almost automatically extract man-made target from a high-resolution (HR) polarimetric SAR (PolSAR) image of an urban area. The core part of this framework is a new PolSAR image feature extraction method, which is developed by combining the spherically invariant random vector (SIRV) product model with the time-frequency (TF) analysis technology. The SIRV product model can better characterize HR SAR images, and the TF analysis will assist the classification by taking advantages of the anisotropic property to avoid the confusion of natural and man-made targets. Therefore, using this kind of extracted features, man-made targets can be easily discriminated with a simple unsupervised K-means classifier. Experimental results demonstrate the effectiveness of the proposed framework, in which man-made targets are extracted with clear contours, and natural surfaces are very continuous and homogenous. In addition, plenty of interesting targets with special scattering performances are highlighted in several rare classes. Their features are worth studying. Above all, because of barely requiring prior knowledge, the framework should be promising in a wide spectrum of applications by providing the rapid man-made target information acquisition of urban areas.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Automatic Feature-Based Geometric Fusion of Multiview TomoSAR Point Clouds
           in Urban Area
    • Authors: Yuanyuan Wang;Xiao Xiang Zhu;
      Pages: 953 - 965
      Abstract: Interferometric synthetic aperture radar (InSAR) techniques, such as persistent scatterer interferometry (PSI) or SAR tomography (TomoSAR), deliver three-dimensional (3-D) point clouds of the scatterers' positions together with their motion information relative to a reference point. Due to the SAR side-looking geometry, minimum of two point clouds from cross-heading orbits, i.e., ascending and descending, are required to achieve a complete monitoring over an urban area. However, these two point clouds are usually not coregistered due to their different reference points with unknown 3-D positions. In general, no exact identical points from the same physical object can be found in such two point clouds. This article describes a robust algorithm for fusing such two point clouds of urban areas. The contribution of this paper is finding the theoretically exact point correspondence, which is the end positions of façades, where the two point clouds close. We explicitly define this algorithm as “L-shape detection and matching,” in this paper, because the façades commonly appear as L-shapes in InSAR point cloud. This algorithm introduces a few important features for a reliable result, including point density estimation using adaptive directional window for better façade points detection and L-shape extraction using weighed Hough transform. The algorithm is fully automatic. Its accuracy is evaluated using simulated data. Furthermore, the proposed method is applied on two TomoSAR point clouds over Berlin with ascending and descending geometry. The result is compared with the first PSI point cloud fusion method (S. Gernhardt and R. Bamler, “Deformation monitoring of single buildings using meter-resolution SAR data in PSI,” ISPRS J. Photogramm. Remote Sens., vol. 73, pp. 68-79, 2012.) for urban area. Submeter consistency is achieved.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Exploitation of the COSMO-SkyMed SAR System for GMTI Applications
    • Authors: Pastina; D.;Turin, F.;
      Pages: 966 - 979
      Abstract: The focus of this paper is on the exploitation of COSMO-SkyMed spotlight SAR images for Ground Moving Target Indication (GMTI). To this purpose, a two-step processing chain is proposed: the first step performs stationary clutter removal, whereas the second step performs moving targets detection. Both the steps are based on the use of a bank of focusing filters, each one matched to a different relative speed between the radar antenna and the target, here implemented as Chirp Scaling Algorithms in order to keep low the computational burden. The performance of the proposed technique is investigated by applying it to COSMO-SkyMed Single Look Complex spotlight SAR images and compared to theoretical performance: the analysis shows the effectiveness of the proposed technique in suppressing the stationary clutter and providing a high gain in signal to background power ratio, thus allowing subclutter visibility despite the single-channel nature of COSMO-SkyMed data. Moreover, the information provided by the bank is used to estimate the target motion and, by using a knowledge-based approach, relocate in along-track direction the detected movers. The shown results prove the feasibility of a GMTI mode for the COSMO-SkyMed SAR system and more in general for single-channel spaceborne systems.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Ground-Based Polarimetric SAR Interferometry for the Monitoring of Terrain
           Displacement Phenomena–Part I: Theoretical Description
    • Authors: Iglesias; R.;Aguasca, A.;Fabregas, X.;Mallorqui, J.J.;Monells, D.;Lopez-Martinez, C.;Pipia, L.;
      Pages: 980 - 993
      Abstract: Ground-based synthetic aperture radar (SAR) (GB-SAR) sensors represent an effective solution for the monitoring of ground displacement episodes. Initially, the most GB-SAR sensors were based on vector network analyzers (VNA). This type of solution, characterized by a slow scanning time comparable to the decorrelation of the troposphere medium, compromised in many cases the quality of final products for the application of persistent scatterer interferomerty (PSI) techniques. The development of GB-SAR sensors based on the use of stepped linear frequency modulated continuous wave (SLFMCW) signals has led to significant improvements during the last years. They have allowed fulfilling the need of temporal homogeneity of the troposphere during the acquisition time and, moreover, they have favored the acquisition of reliable polarimetric SAR (PolSAR) measurements without drastically increasing the scanning time. This fact has boosted the inclusion of polarimetric SAR interferometry (PolInSAR) algorithms in PSI processing chains, which are demonstrating to outperform classical single-polarimetric performances. The objective of this paper is twofold. On the one hand, a general overview of the polarimetric RiskSAR sensor, developed by the Universitat Politècnica de Catalunya (UPC), is put forward as an example of SLFMCW GB-SAR system implementation. On the other hand, a complete theoretical description of ground-based SAR (GB-SAR) interferometry (GB-InSAR) techniques for PSI purposes is widely discussed. The adaptation of the Coherent Pixels Technique to obtain the linear and nonlinear components of ground displacement phenomena is proposed. In the second part of this paper, the displacement maps and time series over two very different scenarios are presented in order to show the feasibility of GB-SAR sensors for terrain displacement monitoring applications.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Ground-Based Polarimetric SAR Interferometry for the Monitoring of Terrain
           Displacement Phenomena–Part II: Applications
    • Authors: Iglesias; R.;Aguasca, A.;Fabregas, X.;Mallorqui, J.J.;Monells, D.;Lopez-Martinez, C.;Pipia, L.;
      Pages: 994 - 1007
      Abstract: Urban subsidence and landslides are among the greatest hazards for people and infrastructure safety and they require an especial attention to reduce their associated risks. In this framework, ground-based synthetic aperture radar (SAR) interferometry (GB-InSAR) represents a cost-effective solution for the precise monitoring of displacements. This work presents the application of GB-InSAR techniques, particularly with the RiskSAR sensor and its processing chain developed by the Remote Sensing Laboratory (RSLab) of the Universitat Politècnica de Catalunya (UPC), for the monitoring of two different types of ground displacement. An example of urban subsidence monitoring over the village of Sallent, northeastern of Spain, and an example of landslide monitoring in El Forn de Canillo, located in the Andorran Pyrenees, are presented. In this framework, the key processing particularities for each case are deeply analyzed and discussed. The linear displacement maps and time series for both scenarios are showed and compared with in-field data. For the study, fully polarimetric data acquired at X-band with a zero-baseline configuration are employed in both scenarios. The displacement results obtained demonstrate the capabilities of GB-SAR sensors for the precise monitoring of ground displacement phenomena.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Estimation of Key Dates and Stages in Rice Crops Using Dual-Polarization
           SAR Time Series and a Particle Filtering Approach
    • Authors: De Bernardis; C.G.;Vicente-Guijalba, F.;Martinez-Marin, T.;Lopez-Sanchez, J.M.;
      Pages: 1008 - 1018
      Abstract: Information of crop phenology is essential for evaluating crop productivity. In a previous work, we determined phenological stages with remote sensing data using a dynamic system framework and an extended Kalman filter (EKF) approach. In this paper, we demonstrate that the particle filter is a more reliable method to infer any phenological stage compared to the EKF. The improvements achieved with this approach are discussed. In addition, this methodology enables the estimation of key cultivation dates, thus providing a practical product for many applications. The dates of some important stages, as the sowing date and the day when the crop reaches the panicle initiation stage, have been chosen to show the potential of this technique.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Performance Analysis and Validation of Waterline Extraction Approaches
           Using Single- and Dual-Polarimetric SAR Data
    • Authors: Xianwen Ding;Nunziata; F.;Xiaofeng Li;Migliaccio, M.;
      Pages: 1019 - 1027
      Abstract: In this study, the performance of two waterline extraction approaches is analyzed using dual-polarization Cosmo-SkyMed (CSK) Synthetic Aperture Radar (SAR) data and ancillary ground truth information. The single-polarization approach is based on multiscale normalized cuts segmentation; while, the dual-polarization one exploits the inherent peculiarities of the CSK PING PONG incoherent dual-polarimetric imaging mode together with a tailored scattering model to perform land/sea discrimination. The two approaches are applied to the actual CSK SAR data collected over the coastal area of Shanghai, China. To provide a detailed and complete validation of the two approaches, we carried out several field surveys collecting in situ ancillary information including Global Positioning System (GPS) data and tidal information. Experimental results show that 1) both approaches provide satisfactory results in extracting waterline from CSK SAR data in the intertidal flat under low-to-moderate wind conditions and under a very broad range of incidence angles; 2) the accuracy of the waterline extracted by both approaches decreases in case of water within the intertidal flat; 3) the single-polarization approach is unsupervised when the land/sea contrast ratio is high. However, it needs manual supervision to correct the extracted waterline when the land/sea contrast is low or in complex areas. A typical CSK scene is processed in about 25 min; 4) the dual-polarization approach is unsupervised and very effective: a typical CSK SAR scene is processed in seconds.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • A Simple RVoG Test for PolInSAR Data
    • Authors: Ballester-Berman; J.D.;Vicente-Guijalba, F.;Lopez-Sanchez, J.M.;
      Pages: 1028 - 1040
      Abstract: In this paper, we present a simple algorithm for assessing the validity of the RVoG model for PolInSAR-based inversion techniques. This approach makes use of two important features characterizing a homogeneous random volume over a ground surface, i.e., the independence on polarization states of wave propagation through the volume and the structure of the polarimetric interferometric coherency matrix. These two features have led to two different methods proposed in the literature for retrieving the topographic phase within natural covers, i.e., the well-known line fitting procedure and the observation of the (1, 2) element of the polarimetric interferometric coherency matrix. We show that differences between outputs from both approaches can be interpreted in terms of the PolInSAR modeling based on the Freeman-Durden concept, and this leads to the definition of a RVoG/non-RVoG test. The algorithm is tested with both indoor and airborne data over agricultural and tropical forest areas.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Adaptive Anisotropic Diffusion Method for Polarimetric SAR Speckle
    • Authors: Xiaoshuang Ma;Huanfeng Shen;Liangpei Zhang;Jie Yang;Hongyan Zhang;
      Pages: 1041 - 1050
      Abstract: In this paper, we present an adaptive anisotropic diffusion (AD) method for the speckle filtering of polarimetric synthetic aperture radar (PolSAR) images. One of the main innovations of our work is that we employ a likelihood-ratio test method to measure the equality of two polarimetric covariance matrices to control the diffusivity, and thus consider the full polarimetric information and the statistical traits of PolSAR data in the diffusion process. Meanwhile, to overcome the drawback of the conventional AD methods, we integrate the local homogeneity information into the diffusion model to adaptively control the generosity of the filtering. Experiments were conducted on a simulated image and two airborne PolSAR images to illustrate the filtering performance, and the results show that the proposed method effectively reduces speckle, retains edges, and targets, and preserves the polarimetric scattering mechanisms.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • A Four-Component Decomposition Model for PolSAR Data Using Asymmetric
           Scattering Component
    • Authors: Bin Zou;Yan Zhang;Ning Cao;Nghia Pham Minh;
      Pages: 1051 - 1061
      Abstract: This paper describes a polarimetric information extraction method using PolSAR data. The proposed method is based on the covariance matrix and intended to be applicable to the general nonreflection symmetric scattering case that the copolar and cross-polar correlations are not close to zero. Asymmetric scattering term, which can entirely represent the asymmetric information of PolSAR data, is proposed to describe the nonreflection symmetric scattering caused by complicated shape targets or man-made structures in urban areas. Using this asymmetric scattering term, together with surface, double-bounce, and volume scattering terms, the new four-component scattering power decomposition method is then proposed, which can fully utilize all the parameters contained in the PolSAR data. It is found that asymmetric scattering is predominant in urban areas and close to zero in natural distributed areas. Although designed for nonreflection symmetric scattering case, the decomposition method can also deal with the reflection symmetry case, since it automatically becomes Freeman three-component decomposition method in natural areas. The E-SAR L-band full-polarized data acquired over Oberpfaffenhofen area in Germany and the CONVAIR-SAR C-band data acquired over Ottawa area in Canada are applied to validate the proposed decomposition method. The results of the experiments show that the proposed method has better performance than the four-component decomposition model in distinguishing different types of terrains.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • On the Use of Simulated Airborne Compact Polarimetric SAR for
    • Authors: Collins; M.J.;Denbina, M.;Minchew, B.;Jones, C.E.;Holt, B.;
      Pages: 1062 - 1077
      Abstract: Compact polarimetry (CP) synthetic aperture radar (SAR) is a form of coherent dual-pol SAR that has been shown to have great potential for maritime surveillance applications such as ship and ice detection. In this paper, we demonstrate the potential of CP data for oil spill characterization. As the availability of CP data is limited at this time, we simulate CP image data from UAVSAR L-Band quad-polarized images. We reconstruct quad-pol SAR data (termed pseudo-quad) from these simulated CP SAR data, and calculate an oil-water mixing index, termed Mdex. We show that the differences between the pseudo-quad and quad-pol Mdex maps are negligible. This contributes to the case that CP SAR has great potential for multiple applications in maritime surveillance.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Multipath Ghosts in Radar Imaging: Physical Insight and Mitigation
    • Authors: Gennarelli; G.;Soldovieri, F.;
      Pages: 1078 - 1086
      Abstract: Most algorithms commonly exploited for radar imaging are based on linear models that describe only direct scattering events from the targets in the investigated scene. This assumption is rarely verified in practical scenarios where the objects to be imaged interact with each other and with surrounding environment producing undesired multipath signals. These signals manifest in radar images as “ghosts" that usually impair the reliable identification of the targets. The recent literature in the field is attempting to provide suitable techniques for multipath suppression from one side and from the other side is focusing on the exploitation of the additional information conveyed by multipath to improve target detection and localization. This work addresses the first problem with a specific focus on multipath ghosts caused by target-to-target interactions. In particular, the study is performed with regard to metallic scatterers by means of the linearized inverse scattering approach based on the physical optics (PO) approximation. A simple model is proposed in the case of point-like targets to gain insight into the ghosts problem so as to devise possible measurement and processing strategies for their mitigation. Finally, the effectiveness of these methods is assessed by reconstruction results obtained from full-wave synthetic data.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Asymptotic Statistical Performance of Local Polynomial Wigner Distribution
           for the Parameters Estimation of Cubic-Phase Signal With Application in
           ISAR Imaging of Ship Target
    • Authors: Yong Wang;Bin Zhao;Jian Kang;
      Pages: 1087 - 1098
      Abstract: The parameters estimation of cubic-phase signal based on local polynomial Wigner distribution (LPWD) was proposed in the author's previous paper, and it outperforms the traditional algorithms in inverse synthetic aperture radar (ISAR) imaging of maneuvering target. The contribution of this paper is that the asymptotic statistical performance of LPWD for the parameters estimation of cubic-phase signal is analyzed theoretically, and the asymptotic statistical results are derived for all the estimated parameters via the first-order perturbation principle. Then, the LPWD is used in ISAR imaging of ship target with complex motion, and the high-quality instantaneous ISAR images can be obtained.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Application of RADAR Corner Reflectors for the Detection of Small Vessels
           in Synthetic Aperture Radar
    • Authors: Stastny; J.;Cheung, S.;Wiafe, G.;Agyekum, K.;Greidanus, H.;
      Pages: 1099 - 1107
      Abstract: Detection of vessels from space-based synthetic aperture radar (SAR) data is an important area of research with many applications, including fisheries monitoring, counter-piracy, and maritime border security. The detection of vessels on the ocean surface in SAR imagery requires that the vessel has sufficiently high radar cross section (RCS). In general, the RCS of an object is a function of the object's material, size, and shape, as well as RADAR parameters such as center frequency. Even, two objects of the same size may have different RCSs based on construction materials (i.e., wood versus metal). In Ghana, as in much of the Gulf of Guinea, wooden canoes 6-25 m in length represent a significant percentage of maritime traffic. These canoes are not easy to detect and track in coastal RADAR, nor are they easily detected in SAR imagery. These vessels may represent a significant risk to maritime safety and security. Here, we describe one possible solution for the problem described-above based on inexpensive, versatile corner reflectors with high RCS. Specifically, we describe the design and construction of high RCS corner reflectors and results from a series of experiments in which corner reflectors were installed on wooden canoes. During the experiments, canoes were deployed to specific locations off the coast of Ghana at specific times, corresponding to the acquisition of space-based SAR imagery. We present results from these experiments, which indicate that wooden canoes with these corner reflectors can be detected in space-based SAR imagery.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Radar High-Speed Target Detection Based on the Scaled Inverse Fourier
    • Authors: Jibin Zheng;Tao Su;Wentao Zhu;Xuehui He;Qing Huo Liu;
      Pages: 1108 - 1119
      Abstract: In this paper, by employing the symmetric autocorrelation function and the scaled inverse Fourier transform (SCIFT), a coherent detection algorithm is proposed for high-speed targets. This coherent detection algorithm is simple and can be easily implemented by using complex multiplications, the fast Fourier transform (FFT) and the inverse FFT (IFFT). Compared to the Hough transform and the keystone transform, this coherent detection algorithm can detect high-speed targets without the brute-force searching of unknown motion parameters and achieve a good balance between the computational cost and the antinoise performance. Through simulations and analyses for synthetic models and the real data, we verify the effectiveness of the proposed coherent detection algorithm.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Acceleration Model Analyses and Imaging Algorithm for Highly Squinted
           Airborne Spotlight-Mode SAR with Maneuvers
    • Authors: Shiyang Tang;Linrang Zhang;Ping Guo;Gaogao Liu;Guang-Cai Sun;
      Pages: 1120 - 1131
      Abstract: Synthetic aperture radar (SAR) imaging is usually performed along a straight path. In practice, variations from the ideal caused by maneuvers with acceleration are inevitable. The main problem is the complex signal processing, particularly in the highly squinted spotlight mode. In this paper, acceleration model is analyzed in more details. Impacts are obtained how the acceleration influences the Doppler parameters and space-variant terms, including the SAR resolution and azimuth bandwidth. According to the special signal properties of the acceleration case, an approximation of the range history is made to avoid using the method of series reversion (MSR) to obtain an accurate spectrum. Based on the high-accurate spectrum, a spotlight algorithm with a modified two-step approach is given. Simulation results show the effectiveness of the modified algorithm.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Imaging Modes for Ground Penetrating Radar and Their Relation to Detection
    • Authors: Paglieroni; D.W.;Chambers, D.H.;Mast, J.E.;Bond, S.W.;Beer, N.R.;
      Pages: 1132 - 1144
      Abstract: The focus of this paper is an empirical study conducted to determine how imaging modes for ground penetrating radar (GPR) affect buried object detection performance. GPR data were collected repeatedly over lanes whose buried objects were mostly nonmetallic. This data were collected and processed with a GPR antenna array, system hardware, and processing software developed by the authors and their colleagues. The system enables GPR data to be collected, imaged, and processed in real-time on a moving vehicle. The images are focused by applying multistatic and synthetic aperture imaging techniques either separately or jointly to signal scans acquired by the GPR antenna array. An image-based detection statistic derived from the ratio of buried object energy in the foreground to energy of soil in the background is proposed. Detection-false alarm performance improved significantly when the detection algorithm was applied to focused multistatic synthetic aperture radar (SAR) images rather than to unfocused GPR signal scans.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Interference Removal for Autofocusing of GPR Data From RC Bridge Decks
    • Authors: Xiangmin Wei;Ying Zhang;
      Pages: 1145 - 1151
      Abstract: Strong interferences can substantially deteriorate the performance of autofocusing techniques in ground penetrating radar (GPR) data analysis for reinforced concrete (RC) bridge deck evaluation. In this paper, we propose a new approach based on F-K dip filtering to remove interferences, including direct waves and cross rebar reflections. Different from previously related work, the surface roughness and uneven cross rebar reflections resulted from GPR signals propagating through rough surface and inhomogeneous medium are carefully modeled as reflectors with small dipping angles, and hence dip relaxations are introduced in the F-K dip filtering to remove strong interferences. The mechanism of the F-K filter without dip relaxation and the correctness of the rebar modeling are first illustrated using simulation data. Then its effectiveness with adequate dip relaxation is demonstrated by both experimental and field data. Additionally, the performance of the F-K dip filter with adequate dip relaxation is also compared with that of the background subtraction (BS) method that is commonly used for direct wave removal in GPR data processing for RC bridge deck evaluation.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Development and Validation of a Robust Algorithm for Retrieving Aerosol
           Optical Depth Over Land From MODIS Data
    • Authors: Guanghui Huang;Chunlin Huang;Zhengqiang Li;Hao Chen;
      Pages: 1152 - 1166
      Abstract: Due to the limitation of surface “dark-target,” in some regions and over certain surface types, Moderate Resolution Imaging Spectroradiometer (MODIS) standard aerosol algorithm does not work very well. In this paper, we developed and validated a robust algorithm, which combines the revised minimum reflectance technique and the technique of the synergy of Terra and Aqua MODIS to eliminate the dependence on surface conditions. The rationale of our algorithm is to first identify the “clearest” day observations in certain temporal window, assume that the aerosol optical depth (AOD) does not change during the limited period (0-3 h) between Terra and Aqua overpass in this day, subsequently obtain the relationships between visible bands and 2.1 μm band surface reflectance, and finally retrieve the AOD of all observations in the temporal window. The algorithm was validated using year 2006 measurements from 13 Aerosol Robotic Network (AERONET) sites distributed in North China, Central Asia, eastern United States, and Western Europe. For AOD, 65.5% and 72.7% of retrievals within MOD04 expected error envelope for all levels of quality assurance confidence (QAC) and QAC = 3, respectively, R2 of 0.87 and a less amount of gaps are found. In comparison to the MODIS aerosol products, the new algorithm on the whole shows similar accuracy over dark land surface, but gives a larger amount of retrievals over bright land surface. This indicates that the new algorithm can provide a more steady inversion for a variety of surface types. Especially over urban surface, such as Beijing in China, the inverted AOD is clearly better than that from MODIS aerosol products. Therefore, the new algorithm can provide an alternative way for AOD retrieving over regions where the standard dark target algorithm does not work well or higher spatial resolution is imperative.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • A Novel Aerosol Load Index Using MODIS Visible Bands: Applied to
           South-West Part of Iran
    • Authors: Shams; S.B.;Mohammadzadeh, A.;
      Pages: 1167 - 1175
      Abstract: Because of the existence of some gaps, uncertainties, and coarse spatial resolution in global aerosol optical depth (AOD) data over south-west part of Iran as the study area, a novel aerosol load index is proposed. As no AERONET station is available in the study area, an index is needed that does not use particle properties. The proposed algorithm has several steps: cloud masking, Rayleigh path reflectance, surface reflectance database, aerosol reflectance, and aerosol load index. Surface reflectance database of 0.05° latitude × 0.05° longitude resolution is calculated by improved minimum reflectance technique (IMRT) for spring season of 2005. The correlation of IMRT surface reflectance at 0.47 μm wavelength with MOD09 is increased in comparison with minimum reflectance technique (MRT), R = 0.75. Aerosol reflectance is obtained through radiation transfer equation, Rayleigh path reflectance, and surface reflectance database. The proposed load index is based on reducing the geometry dependency; hence normalized aerosol reflectance by accounting for solar/view slant path is used. The aerosol load index is verified for dust contamination. The suggested algorithm is applied over study area in spring 2005 using moderate resolution imaging spectroradiometer (MODIS) level L1B calibrated reflectance MOD02Hkm on Terra spacecraft. The spatial resolution of final aerosol load index is 500 m. For validation, the resultant load index is compared with dark-target and Deep Blue retrieved AOD of MOD/MYD04 and correlations of R = 0.82 and R = 0.71 are found at 0.47 μm wavelength, respectively. In comparison with ground base dust particle concentration, correlation of R = 0.72 is achieved correspondingly.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Remote Sensing of Spatiotemporal Variation of Apparent Optical Properties
           in Bohai Sea
    • Authors: Minwei Zhang;Qing Dong;Tingwei Cui;Jing Ding;
      Pages: 1176 - 1184
      Abstract: It has been presented in this study, the evaluation of remote sensing reflectance (Rrs) derived from the atmospheric correction of Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua satellite. A switching algorithm was developed for the atmospheric correction. The evaluation shows that MODIS measured Rrs at visible bands compare reasonably well with in situ Rrs, with the mean ratios ranging from 0.955 to 1.374. The spatiotemporal variation of Rrs in Bohai sea is characterized using MODIS data from July 2002 to June 2014. It is noted from the time series of monthly mean Rrs and wind speed a time lag for the response of Rrs to wind. Significant linear relationship is found between the monthly mean Rrs and wind speed, with the correlation coefficients much higher than those between the annual mean Rrs and total river discharge, indicating that wind plays a more important role than river discharge in determining the variation of Rrs in Bohai sea. Strong seasonal variation is observed in the monthly mean Rrs, which is the lowest during July and August and increases to the maximum in January-February and then decreases. Using the entire archive of MODIS/Aqua data over Bohai sea, this study documents the apparent optical properties which serve as an indicator of sediment transport, providing a low-cost and efficient way for monitoring the marine environmental change and for demonstrating the effect from sediment transport on coastal morphology and ecosystem.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • South America Land Use and Land Cover Assessment and Preliminary Analysis
           of Their Impacts on Regional Atmospheric Modeling Studies
    • Authors: Capucim; M.N.;Brand, V.S.;Machado, C.B.;Martins, L.D.;Allasia, D.G.;Homann, C.T.;de Freitas, E.D.;Da Silva Dias, M.A.F.;Andrade, M.F.;Martins, J.A.;
      Pages: 1185 - 1198
      Abstract: Data provided by two important sources of information on land use and land cover (LULC), MODIS-2009 and GLOBCOVER-2009, were analyzed for South America in order to assess differences related to their application in numerical modeling studies. Even though on a South American basis, the two databases showed a Pearson correlation coefficient above 85%, on a regional analysis, the correlation stayed within the range of 0%-100%, depending on the territorial unit analyzed. Significant differences were observed in most of the land cover classes, with only forested areas presenting a good level of agreement. In terms of territorial units, only areas in the Amazon region, where forest cover is predominant, showed significant correlation levels. Crops and urban classes presented the greatest differences between the two analyzed files. Results of meteorological simulations indicated that such observed discrepancies are able to cause strong impacts on modeling scenarios and important bias on simulated variables, being a crucial feature for weather and climate forecast and diagnostic.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Quantifying Tidal Mud Flat Elevations From Fixed-Platform Long-Wave
           Infrared Imagery
    • Authors: Puleo; J.A.;Pieterse, A.;McKenna, T.E.;
      Pages: 1199 - 1207
      Abstract: A procedure for estimating tidal mud flat topography from fixed-platform, long-wave infrared imagery is presented. Shallow water and low bearing capacity on many mud flats hinder traditional surveying methods by water craft, walking, or land vehicle. The approach utilizes identification of the intersection of water with the surface of the mud flat through a rising tide. Waterlines on mud flats are often indistinguishable to the naked eye and in visible-band imagery. Long-wave infrared imagery, relying on emitted radiance, provides a more distinct delineation between an exposed mud flat and water. The waterline is identified via an image intensity threshold and transferred to real-world coordinates using a geometrical transformation model that accounts for potential imager sway. Elevation estimates, interpolated to a uniform grid, show excellent agreement (absolute error generally less than 0.02 m) with ground truth elevations obtained using a sled-mounted global positioning survey system.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Land Surface Temperature Retrieval Using Nighttime Mid-Infrared Channels
           Data From Airborne Hyperspectral Scanner
    • Authors: Yong-Gang Qian;En-Yu Zhao;Caixia Gao;Ning Wang;Lingling Ma;
      Pages: 1208 - 1216
      Abstract: Compared with thermal infrared (8-14 μm) spectrum, mid-infrared (MIR) spectrum is less sensitive to land surface emissivity (LSE) for estimating land surface temperature (LST). This work addressed the retrieval of LST from two adjacent MIR (3-5 μm) night-time airborne hyperspectral imager (AHS) simulated data with a split-window method, which can be expressed as a linear combination of the brightness temperature measured in two adjacent MIR channels with coefficients depending on LSE, view zenith angle (VZA), and water vapor content (WVC). Meanwhile, the LST retrieval accuracy for various channel combination was investigated and it was noted that the AHS channels 66 (3.5-4.25 μm) and 68 (4.25-5.0 μm) were the optimal channels for LST retrieval with a root-mean-square error (RMSE) less than 0.4 K for dry atmosphere and less than 0.5 K for wet atmosphere. Finally, the sensitivity analysis in terms of the instrumental noise, the uncertainties of LSE, and WVC were performed. It is worth noting that the combination of CH66 and CH68 performed well, and the LST retrieval errors were less than 0.5, 0.2, and 0.3 K caused by an noise equivalent delta temperature (NEΔT) of 0.33 K, WVC error of 20%, and LSE error of 0.01, respectively.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Poverty Evaluation Using NPP-VIIRS Nighttime Light Composite Data at the
           County Level in China
    • Authors: Bailang Yu;Kaifang Shi;Yingjie Hu;Chang Huang;Zuoqi Chen;Jianping Wu;
      Pages: 1217 - 1229
      Abstract: Poverty has appeared as one of the long-term predicaments facing development of human society during the 21st century. Estimation of regional poverty level is a key issue for making strategies to eliminate poverty. This paper aims to evaluate the ability of the nighttime light composite data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB) carried by the Suomi National Polar-orbiting Partnership (NPP) Satellite in estimating poverty at the county level in China. Two major experiments are involved in this study, which include 1) 38 counties of Chongqing city and 2) 2856 counties of China. The first experiment takes Chongqing as an example and combines 10 socioeconomic variables into an integrated poverty index (IPI). IPI is then used as a reference to validate the accuracy of poverty evaluation using the average light index (ALI) derived from NPP-VIIRS data. Linear regression and comparison of the class ranks have been employed to verify the correlation between ALI and IPI. The results show a good correlation between IPI and ALI, with a coefficient of determination (R2) of 0.8554, and the class ranks of IPI and API show relative closeness at the county level. The second experiment examines all counties in China and makes a comparison between ALI values and national poor counties (NPC). The comparison result shows a general agreement between the NPC and the counties with low ALI values. This study reveals that the NPP-VIIRS data can be a useful tool for evaluating poverty at the county level in China.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Validating and Mapping Surface Water Temperatures in Lake Taihu: Results
           From MODIS Land Surface Temperature Products
    • Authors: Gang Liu;Weixin Ou;Yunlin Zhang;Tingfeng Wu;Guangwei Zhu;Kun Shi;Boqiang Qin;
      Pages: 1230 - 1244
      Abstract: Data from four in situ high-frequency monitoring sites in Lake Taihu, China were used to 1) assess the accuracy of MODIS land surface temperature (LST) products; 2) characterize the spatial and temporal variability in lake surface water temperature (LSWT) with Aqua MODIS thermal-infrared imagery; and 3) explore the causes of these variations. The validation showed that MODIS-derived LSWTs and in situ water temperatures were significantly correlated, with a coefficient of determination higher than 0.96 and a root mean square error between 1.2°C and 1.8°C. These results indicate MODIS LST products can be used to assess the spatial and temporal thermal behavior of Lake Taihu. A spatial analysis of daytime LSWT showed different thermal zones along the lake due to the differential heat storage capacity between the deep and shallow regions of the lake, such as the littoral and East Lake Taihu. In contrast, the nighttime LSWT showed little variation, and there was a uniform surface water temperature. Following a change in solar radiation, the annual cycle of the average LSWT (with a nearly 24°C range) started to increase in January and peaked in July. In Lake Taihu, the mean nighttime LSWT from July to September rapidly warmed over the period of 2002-2013 at an average rate of 0.059 ± 0.053°C/year. Our study promotes the use of MODIS LST products in limnology through a validation using a large amount of real-time synchronous water temperature data based on high-frequency observations, which were seldom used in previous studies.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Regression-Kriging Technique to Downscale Satellite-Derived Land Surface
           Temperature in Heterogeneous Agricultural Landscape
    • Authors: Mukherjee; S.;Joshi, P.K.;Garg, R.D.;
      Pages: 1245 - 1250
      Abstract: The study introduces regression-kriging technique to downscale land surface temperature (LST) over a heterogeneous landscape of India and compares it with other models. All models are initially tested on aggregated 960 m Landsat LST and downscaled to 240 m (RMSE = 0.45°C) and 120 m (RMSE = 0.68°C) resolution. Finally, the MODIS LST is downscaled to 250 m (RMSE = 0.7°C) resolution. The proposed model outperformed compared to other models. The qualitative assessment reveals appearance of box-like structure is not seen in the proposed model-derived LST due to reconstruction of residual.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Estimation of Heat Content and Mean Temperature of Different Ocean Layers
    • Authors: Jagadeesh; P.S.V.;Suresh Kumar, M.;Ali, M.M.;
      Pages: 1251 - 1255
      Abstract: Oceans are reservoirs of heat energy represented by the heat content or the mean temperature, and are the source of energy for the atmospheric processes. Which process of the atmosphere interacts with the energy of which layer of the ocean is not clear, primarily, because of the nonavailability of oceanic heat energy of different layers on a required temporal and spatial scales. Realizing this requirement, we compute the ocean heat content (OHC) and the ocean mean temperature (OMT) from surface to 50, 100, 150, 200, 300, 500, 700 m and upto 26 °C isotherm depth. Thus, we computed altogether 16 variables from satellite observations of sea surface height anomaly (SSHA), sea surface temperature (SST), and the climatological values of the above 16 variables through an artificial neural network (ANN). The model is developed using 11472 in situ and satellite collocated observations and is validated using 2479 independent values that are not used for developing the model. These estimations have a strong Pearson correlation coefficient, r, of more than 0.90 (at 99% confidence level) between the estimated and in situ values. These parameters are provided on near real time daily basis at a spatial resolution of 0.25° at the Bhuvan website of National Remote Sensing Centre, Indian Space Research Organisation, which can be downloaded by a researcher for further ocean-atmosphere interaction investigations.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • OBIA System for Identifying Mesoscale Oceanic Structures in SeaWiFS and
           MODIS-Aqua Images
    • Authors: Vidal-Fernandez; E.;Piedra-Fernandez, J.A.;Almendros-Jimenez, J.M.;Canton-Garbin, M.;
      Pages: 1256 - 1265
      Abstract: The ocean covers over 70% of the surface of our planet and plays a key role in the global climate. Most ocean circulation is mesoscale (scales of 50-500 km and 10-100 days), and the energy in mesoscale circulation is at least one order of magnitude greater than general circulation; therefore, the study of mesoscale oceanic structures (MOS) is crucial to ocean dynamics, making it especially useful for analyzing global changes. The detection of MOS, such as upwellings or eddies, from satellites images is significant for marine environmental studies and coastal resource management. In this paper, we present an object-based image analysis (OBIA) system which segments and classifies regions contained in sea-viewing field-of-view sensor (SeaWiFS) and Moderate Resolution Imaging Spectro-radiometer (MODIS)-Aqua sensor satellite images into MOS. After color clustering and hierarchical data format (HDF) file processing, the OBIA system segments images and extracts image descriptors, producing primary regions. Then, it merges regions, recalculating image descriptors for MOS identification and definition. First, regions are labeled by a human-expert, who identifies MOS: upwellings, eddies, cool, and warm eddies. Labeled regions are then classified by learning algorithms (i.e., decision tree, Bayesian network, artificial neural network, genetic algorithm, and near neighbor algorithm) from selected features. Finally, the OBIA system enables images to be queried from the user interface and retrieved by means of fuzzy descriptors and oceanic structures. We tested our system with images from the Canary Islands and the North West African coast.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • An Improved Empirical Model for Retrieving Bottom Reflectance in Optically
           Shallow Water
    • Authors: Chaoyu Yang;Dingtian Yang;
      Pages: 1266 - 1273
      Abstract: Satellite remote sensing has become an essential observing system to obtain comprehensive information on the status of coastal habitats. However, a significant challenge in remote sensing of optically shallow water is to correct the effects of the water column. This challenge becomes particularly difficult due to the spatial and temporal variability of water optical properties. In order to model the light distribution for optically shallow water and retrieve the bottom reflectance, a parameterized model was proposed by introducing an important adjusted factor g. The synthetic data sets generated by HYDROLIGHT were utilized to train a neural network (NN) and then to derive the adjustable parameter values. The parameter g was found to vary with water depth, water optical properties, and bottom reflectance. Specifically, it revealed two obvious patterns among the different benthic habitat types. In coral reef, seagrass, and macrophyte habitats, g exhibited a remarkable peak at about 550 nm. The peak has a value of about 2.47-2.49. In white sand or hardpan habitats, g spectra are relatively flat. The semi-empirical model was applied to calculate the bottom reflectance from the new weighting factor, the downward diffuse attenuation coefficient, and the irradiance reflectance just below the sea surface collected in Sanya Bay in 2008 and 2009. Good agreement between the predicted and measured values demonstrated that the weighting factor g is an effective tool to modify the model for interpreting and predicting bottom reflectance without the need for any localized input (R2 > 0.79).
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Edge-Tree Correction for Predicting Forest Inventory Attributes Using
           Area-Based Approach With Airborne Laser Scanning
    • Authors: Packalen; P.;Strunk, J.L.;Pitkanen, J.A.;Temesgen, H.;Maltamo, M.;
      Pages: 1274 - 1280
      Abstract: We describe a novel method to improve the correspondence between field and airborne laser scanning (ALS) measurements in an area-based approach (ABA) forest inventory framework. An established practice in forest inventory is that trees with boles falling within a fixed border field measurement plot are considered “in” trees; yet their crowns may extend beyond the plot border. Likewise, a tree bole may fall outside of a plot, but its crown may extend into a plot. Typical ABA approaches do not recognize these discrepancies between the ALS data extracted for a given plot and the corresponding field measurements. In the proposed solution, enhanced ABA (EABA), predicted tree positions, and crown shapes are used to adjust plot and grid cell boundaries and how ALS metrics are computed. The idea is to append crowns of “in” trees to a plot and cut down “out” trees, then EABA continues in the traditional fashion as ABA. The EABA method requires higher density ALS data than ABA because improvement is obtained by means of detecting individual trees. When compared to typical ABA, the proposed EABA method decreased the error rate (RMSE) of stem volume prediction from 23.16% to 19.11% with 127 m2 plots and from 19.08% to 16.95% with 254 m2 plots. The greatest improvements were obtained for plots with the largest residuals.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Framework for Evaluating Visual and Geometric Quality of Three-Dimensional
    • Authors: Liang Cheng;Wen Zhang;Lishan Zhong;Peijun Du;Manchun Li;
      Pages: 1281 - 1294
      Abstract: Three-dimensional (3-D) models require a quality evaluation prior to their use in specific applications, regardless of whether the modeling process is automatic or manual. A comprehensive framework to evaluate visual and geometric quality of 3-D models is proposed in this study for use in various applications. To evaluate the visual quality, we propose a new concept that we call a fuzzy realistic index, which is based on fuzzy set theory and information entropy methods. Geometric accuracy is determined by deconstructing a 3-D model into the elements of point, line, and plane. The campus of Nanjing University, China, is the experimental area for this study, consisting of 106 3-D building models having various styles and complexity. In this experiment of visual quality, we selected 30 models and invited 100 participants in order to illustrate the power of the proposed fuzzy realistic index. Furthermore, with the support of the proposed framework, this study analyzes the influence of building complexity and of the perceptions of different people upon the quality of constructed 3-D models. Results of these experiments reveal the applicability of the proposed framework in evaluating the quality of 3-D models.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Dune Height Estimation on Titan Exploiting Pairs of Synthetic Aperture
           Radar Images With Different Observation Angles
    • Authors: Callegari; M.;Casarano, D.;Mastrogiuseppe, M.;Poggiali, V.;Notarnicola, C.;
      Pages: 1295 - 1306
      Abstract: Widespread longitudinal dunes have been identified on Titan thanks to the 2.2-cm wavelength Cassini Synthetic Aperture Radar (SAR) instrument. Understanding the properties of these surface features, such as material composition and dune height, is very important for giving new clues about the Titan geology and climate. One of the major difficulties in the estimation of dune heights using SAR occurs when the material composition of the dunes is heterogeneous. In this paper, we propose a novel method for dune height estimation, which takes into account material heterogeneity, and in particular, the case in which the interdune exhibits different dielectric properties with respect to the remaining part of the dune. Paired data acquisitions with orthogonal observations are considered for separating the dielectric from the geometric effect on the backscattering coefficients in order to retrieve the slope and thus the height of the dunes. The results for a test area located in the Fensal region indicate that the slopes of the dune faces are generally lower than 5° and the heights range between 40 and 110 m.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Quality Assessment of Preclassification Maps Generated From
           Spaceborne/Airborne Multispectral Images by the Satellite Image
           Automatic Mapper
    and Atmospheric/Topographic
           Correction-Spectral Classification
    Software Products: Part
    • Authors: Baraldi; A.;Humber, M.L.;
      Pages: 1307 - 1329
      Abstract: In compliance with the Quality Assurance Framework for Earth Observation (QA4EO) guidelines, the goal of this paper is to provide a theoretical comparison and an experimental quality assessment of two operational (ready-for-use) expert systems (prior knowledge-based nonadaptive decision trees) for automatic near real-time preattentional classification and segmentation of spaceborne/airborne multispectral (MS) images: the Satellite Image Automatic Mapper™ (SIAM™) software product and the Spectral Classification of surface reflectance signatures (SPECL) secondary product of the Atmospheric/Topographic Correction™ (ATCOR™) commercial software toolbox. For the sake of simplicity, this paper is split into two: Part 1-Theory, presented herein, and Part 2-Experimental results, already published elsewhere. The main theoretical contribution of the present Part 1 is threefold. First, it provides the published Part 2 with an interdisciplinary terminology and a theoretical background encompassing multiple disciplines, such as philosophical hermeneutics, machine learning, artificial intelligence, computer vision, human vision, and remote sensing (RS). Second, it highlights the several degrees of novelty of the ATCOR-SPECL and SIAM deductive preliminary classifiers (preclassifiers) at the four levels of abstraction of an information processing system, namely, system design, knowledge/information representation, algorithms, and implementation. Third, the present Part 1 requires the experimental Part 2 to collect a minimum set of complementary statistically independent metrological quality indicators (QIs) of operativeness (QIOs), in compliance with the QA4EO guidelines and the principles of statistics. In particular, sample QIs are required to be: 1) statistically significant, i.e., provided with a degree of uncertainty in measurement; and 2) statistically valid (consistent), i.e., representative of the entire population being sampled, which requir- s the implementation of a probability sampling protocol. Largely overlooked by the RS community, these sample QI requirements are almost never satisfied in the RS common practice. As a consequence, to date, QIOs of existing RS image understanding systems (RS-IUSs), including thematic map accuracy, remain largely unknown in statistical terms. The conclusion of the present Part 1 is that the proposed comparison of the two alternative ATCOR-SPECL and SIAM prior knowledge-based preclassifiers in operating mode, accomplished in the Part 2, can be considered appropriate, well-timed, and of potential interest to a large portion of the RS readership.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • The Dynamic Assessment Model for Monitoring Cadmium Stress Levels in Rice
           Based on the Assimilation of Remote Sensing and the WOFOST Model
    • Authors: Feng Liu;Xiangnan Liu;Liting Zhao;Chao Ding;Jiale Jiang;Ling Wu;
      Pages: 1330 - 1338
      Abstract: Monitoring of heavy metal stress in crops is vital for food security and agricultural production management. Traditional remote sensing methods focus on the stress-induced changes to the aerial organs of plants, whereas roots are considered to be more directly and severely stressed. In this study, the dry weight of rice roots (WRT) was used as an indicator for monitoring cadmium (Cd) stress levels in rice tissues. The World Food Study (WOFOST) model is a widely used analysis tool for describing the fundamental processes of crop growth, and has been tested for similar applications. We used this model to incorporate a Cd stress factor (fCd), allowing us to simulate the WRT values more accurately. Then, an optimized method of assimilating remotely sensed leaf area index (LAI) into the modified WOFOST model was used to optimize the simulation process and obtain the optimum value of fCd. Thus, the dynamic simulation of WRT under Cd stress was adjusted. Based on the WRT values of two sample plots with different soil Cd concentrations, the ratio between them (WRTStress/WRTSafe) was calculated subsequently. The variation in the ratio curve generally reflected the stress mechanism in time scale, indicating that the dynamic simulation of WRT was reliable. This study suggests that the method of assimilating remote sensing data into the crop growth model is applicable for simulating crop growth under Cd stress on spatial-time scale, providing a reference for dynamically monitoring heavy metal contamination in rice tissues.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Land Cover Change Detection at Subpixel Resolution With a Hopfield Neural
    • Authors: Qunming Wang;Wenzhong Shi;Atkinson; P.M.;Zhongbin Li;
      Pages: 1339 - 1352
      Abstract: In this paper, a new subpixel resolution land cover change detection (LCCD) method based on the Hopfield neural network (HNN) is proposed. The new method borrows information from a known fine spatial resolution land cover map (FSRM) representing one date for subpixel mapping (SPM) from a coarse spatial resolution image on another, closer date. It is implemented by using the thematic information in the FSRM to modify the initialization of neuron values in the original HNN. The predicted SPM result was compared to the original FSRM to achieve subpixel resolution LCCD. The proposed method was compared with the original unmodified HNN method as well as six state-of-the-art methods for LCCD. To explore the effect of uncertainty in spectral unmixing, which mainly originates from spectral separability in the input, coarse image, and the point spread function (PSF) of the sensor, a set of synthetic multispectral images with different class separabilities and PSFs was used in experiments. It was found that the proposed LCCD method (i.e., HNN with an FSRM) can separate more real changes from noise and produce more accurate LCCD results than the state-of-the-art methods. The advantage of the proposed method is more evident when the class separability is small and the variance in the PSF is large, that is, the uncertainty in spectral unmixing is large. Furthermore, the utilization of an FSRM can expedite the HNN-based processing required for LCCD. The advantage of the proposed method was also validated by applying to a set of real Landsat-Moderate Resolution Imaging Spectroradiometer (MODIS) images.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Soft-Computing Methodologies for Precipitation Estimation: A Case Study
    • Authors: Shamshirband; S.;Gocic, M.;Petkovic, D.;Saboohi, H.;Herawan, T.;Mat Kiah, L.;Akib, S.;
      Pages: 1353 - 1358
      Abstract: The current paper presents an investigation of the accuracy of soft-computing techniques in precipitation estimation. The monthly precipitation data from 29 synoptic stations in Serbia from 1946 to 2012 are used as a case study. Despite a number of mathematical functions having been proposed for modeling precipitation estimation, the models still have disadvantages such as being very demanding in terms of calculation time. Soft computing can be used as an alternative to the analytical approach, as it offers advantages such as no required knowledge of internal system parameters, compact solutions for multivariable problems, and fast calculation. Because precipitation prediction is a crucial problem, a process which simulates precipitation with two soft-computing techniques was constructed and presented in this paper, namely, adaptive neurofuzzy inference (ANFIS) and support vector regression (SVR). In the current study, polynomial, linear, and radial basis function (RBF) are applied as the kernel function of the SVR to estimate the probability of precipitation. The performance of the proposed optimizers is confirmed with the simulation results. The SVR results are also compared with the ANFIS results. According to the experimental results, enhanced predictive accuracy and capability of generalization can be achieved with the ANFIS approach compared to SVR estimation. The simulation results verify the effectiveness of the proposed optimization strategies.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Cloud- and Agent-Based Geospatial Service Chain: A Case Study of Submerged
           Crops Analysis During Flooding of the Yangtze River Basin
    • Authors: Xicheng Tan;Liping Di;Meixia Deng;Aijun Chen;Fang Huang;Chao Peng;Meng Gao;Yayu Yao;Zongyao Sha;
      Pages: 1359 - 1370
      Abstract: More intelligent construction of geospatial service chains and more efficient execution of such service chains remain major challenges in distributed geospatial analysis. This study addresses these challenges using a Cloud- and agent-based approach for automatic and intelligent construction of a geospatial service chain in the Cloud environment. A spatial agent infrastructure comprising fundamental services and an agent interface is designed, implemented, and deployed. Our approach involves a strategy for selecting and aggregating appropriate agents and Web-processing services (WPS) by evaluating their availability. This strategy ensures successful construction of a geospatial service chain in the Cloud environment, even when there is a lack of requisite geospatial services in the system. Moreover, the method can significantly increase the speed of a service chain in distributed environments and retains high stability when more requests are submitted over various network conditions. This is because the computing mobility and intelligence of the agent help to avoid transfer of large volumes of spatial data and keep the load balanced during construction and execution of the service chain. A prototype system for analysis of submerged crops during flooding of the Yangtze River basin demonstrates the advantages of our approach over existing methods.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Spatial-Contextual Supervised Classifiers Explored: A Challenging Example
           of Lithostratigraphy Classification
    • Authors: Cracknell; M.J.;Reading, A.M.;
      Pages: 1371 - 1384
      Abstract: Spatial-contextual classifiers exploit characteristics of spatially referenced data and account for random noise that contributes to spatially inconsistent classifications. In contrast, standard global classifiers treat inputs as statistically independent and identically distributed. Spatial-contextual classifiers have the potential to improve visualization, analysis, and interpretation: fundamental requirements for the subsequent use of classifications representing spatially varying phenomena. We evaluate random forests (RF) and support vector machine (SVM) spatial-contextual classifiers with respect to a challenging lithostratigraphy classification problem. Spatial-contextual classifiers are divided into three categories aligned with the supervised classification work flow: 1) data preprocessing-transformation of input variables using focal operators; 2) classifier training-using proximal training samples to train multiple localized classifiers; and 3) postregularization (PR)-reclassification of outputs. We introduce new variants of spatial-contextual classifier that employ self-organizing maps to segment the spatial domain. Segments are used to train multiple localized classifiers from k neighboring training instances and to represent spatial structures that assist PR. Our experimental results, reported as mean (n = 10) overall accuracy ±95% confidence intervals, indicate that focal operators (RF 0.754 ±0.010, SVM 0.683 ±0.010) and PR majority filters (RF 0.705 ±0.010, SVM 0.607 ±0.010 for 11 × 11 neighborhoods) generate significantly more accurate classifications than standard global classifiers (RF 0.625 ±0.011, SVM 0.581 ±0.011). Thin and discontinuous lithostratigraphic units were best resolved using non-preprocessed variables, and segmentation coupled with postregularized RF classifications (0.652 ±0.011). These methods may be used to improve the accuracy of classifications across a wid- variety of spatial modeling applications.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
  • Locality Preserving Composite Kernel Feature Extraction for Multi-Source
           Geospatial Image Analysis
    • Authors: Yuhang Zhang;Prasad; S.;
      Pages: 1385 - 1392
      Abstract: Multi-source data, either from different sensors or disparate features extracted from the same sensor, are valuable for geospatial image analysis due to their potential for providing complementary features. In this paper, a composite-kernel-based feature extraction method is proposed for multi-source remote sensing data classification. Features from different sources are first fused via a weighted composite kernel mapping, and then projected to a lower-dimensional subspace in which kernel local Fisher discriminant analysis (KLFDA) is used to extract the most discriminative information. We hypothesize that after such a projection, multi-source data would have better class separability between classes, and an efficient linear classification model-multinomial logistic regression (MLR) would be suitable for classification. The efficacy of the proposed method is demonstrated via experiments using two different sets of multi-source geospatial data. For feature fusion, the raw spectral data and extended multi-attribute profiles (EMAPs) derived from the hyperspectral image are used as a testbed for multi-source image analysis. The second multi-source testbed used for validation involves sensor fusion, in which the hyperspectral and light detection and ranging (LiDAR) data are utilized. Experimental results show that composite kernel local Fisher's discriminant analysis when combined with MLR based classifier (CKLFDA-MLR) is very effective at feature extraction and classification of multi-source geospatial images.
      PubDate: March 2015
      Issue No: Vol. 8, No. 3 (2015)
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