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  Subjects -> ELECTRONICS (Total: 152 journals)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 1)
Advances in Electronics     Open Access   (Followers: 3)
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: 86)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 12)
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: 10)
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     Hybrid Journal   (Followers: 5)
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: 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: 9)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 5)
Electronics Letters     Hybrid Journal   (Followers: 19)
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 23)
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: 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: 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: 3)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 6)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 11)
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: 4)
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: 9)
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: 4)
Journal of Electrical Bioimpedance     Full-text available via subscription   (Followers: 2)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (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]   [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  [176 journals]
  • 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: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • IEEE Transactions on Geoscience and Remote Sensing institutional listings
    • Abstract: Provides a listing of the editors, board members, and current staff for this issue of the publication.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (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: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Front cover
    • Abstract: Presents the front cover for this issue of the publication.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Table of Contents
    • Pages: 1393 - 1394
      Abstract: Presents the table of contents for this issue of the publication.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Discriminating Native and Nonnative Grasses in the Dry Mixedgrass Prairie
           With MODIS NDVI Time Series
    • Authors: McInnes; W.S.;Smith, B.;McDermid, G.J.;
      Pages: 1395 - 1403
      Abstract: Separating native grasses from tame pastures is an important mapping exercise that assists in the assessment of biodiversity, delineation of species' habitat, and appraisal of rangeland health. However, native grasslands (primarily naturally occurring species) and tame pastures (primarily nonnative grasses planted for hay, pasture, or seed) are spectrally similar and therefore difficult to differentiate with traditional remote sensing techniques and with air-photo interpretation. We used seasonal profiles of the normalized difference vegetation index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments to examine the separability of native grasslands and tame pastures (where both types employ the C3 photosynthetic pathway) in the Dry Mixedgrass natural subregion of Alberta, Canada. The two classes were found to have different rates of spring green up at the pixel level that allowed for separation with a simple linear discriminant function. We achieved an overall accuracy of 73% (n = 100 independent test cases) with the MODIS time series-a statistically significant improvement of the photo-interpretation-based Grassland Vegetation Inventory (52%): the current standard for vegetation information in Alberta's agricultural zone. We also found that the multitemporal method was able to select dates for single-date classifications that provided relatively high classification accuracies (up to 71% overall). In addition to achieving higher levels of overall accuracy than more conventional methods, the MODIS time series produced much more reliable identification of abandoned pastures: formerly planted rangelands that lack many of the visual cues used by photo interpreters.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • MODIS NBAR Time Series Modeling With Two Statistical Methods and
           Application to Leaf Area Index Recursive Estimation
    • Authors: Li Tian;Jindi Wang;Hongmin Zhou;Xiao; Z.;
      Pages: 1404 - 1412
      Abstract: The inconsistent data quality of remote sensing observation, which is largely a result of atmospheric conditions, presents problems in the application of these data. Pixel reflectance in remote sensing observation varies with the type of land cover and the observation time. For land cover types that cycle yearly, such as vegetation, the variations in surface reflectance usually have dynamic periodic characteristics. In this study, we modeled the temporal feature of Moderate-Resolution Imaging Spectroradiometer (MODIS) Nadir BRDF-adjusted reflectance (NBAR) time series data of typical forest and cropland areas using two statistical methods: season-trend and seasonal autoregressive (AR) integrated moving average (SARIMA). The fitting values of these models were used in the recursive estimation of leaf area index (LAI) time series based on a nonlinear AR exogenous (NARX) neural network. This suppressed interferences from observational data noise and missing values. The results from 6 years (2008-2013) of MODIS NBAR modeling indicate that the two statistical methods are effective to model the NBAR time series of the vegetation surface; the season-trend model can extract both seasonal and trend components of long time series, and the SARIMA model has a good fitting capacity for general time series data. The NARX neural network performs well with the improved NBAR time series input, and the estimated LAI time series is more continuous than the MODIS LAI. Comparison with field data reveals the reliability of the estimated LAI values.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Estimation of Canopy and Woody Components Clumping Indices at Three Mature
           Picea crassifolia Forest Stands
    • Authors: Jie Zou;Guangjian Yan;Ling Chen;
      Pages: 1413 - 1422
      Abstract: Many previous studies have shown that the underestimation of the plant area index (PAI) by traditional optical instruments is mainly due to the clumping effects of forest canopies. However, the evaluation of the clumping effects of canopy (leaves, stems, branches, fruits, and flowers) and woody components (stems and branches) within forest canopies is still a challenging task for current indirect instruments and algorithms. In this study, two key issues of the gap size distribution algorithm (CC) were discussed first, such as the stop conditions of the gap-removal procedure and gap-removing methods. Four types of gap-removing schemes were compared and their impacts to the estimation of canopy and woody components clumping indices (Ωe and Ωw) were analyzed. Obvious discrepancies were found between the estimates of Ωe and Ωw from the four gap-removing schemes at each zenith angle. A new gap-removal scheme was proposed subsequently. After that, a solution was presented to estimate Ωe and Ωw at multiple zenithal and azimuthal directions in three mature Picea crassifolia forest stands. These estimates were retrieved based on multispectral canopy imager (MCI) equipment and CC algorithm. The estimates from the MCI equipment were later compared with those from the TRAC instrument. Small differences were found between the Ωe estimates from the MCI and TRAC instruments, indicating that the MCI instrument was effective for evaluating the clumping effects of forest canopies at multiple zenithal and azimuthal directions. Results showed that both of Ωe and Ωw change with the zenithal and azimuthal directions.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • GOST2: The Improvement of the Canopy Reflectance Model GOST in Separating
           the Sunlit and Shaded Leaves
    • Authors: Weiliang Fan;Jing Li;Qinhuo Liu;
      Pages: 1423 - 1431
      Abstract: Accurately simulating the area ratios of the sunlit and shaded foliage in multiple-view angles presents a challenge in developing a geometric-optical (GO) model. GOST model by Fan et al.[1] proposed a high computationally demanding ray tracing method on this issue. In order to relax the computational restriction, a new hybrid canopy reflectance model GOST2 based on GOST is developed with a “ray tracing + GO” method, which is used for simulating the area ratios of the sunlit and shaded foliage. GOST2 shows the explicitly physical mechanism and has the capability in modeling the area ratios of the sunlit and shaded foliage on slopes. The area ratios of the four scene components of the five GO models, such as GOST2, GOST, the Li-Strahler model, the four-scale model, and Unified, are quantitatively evaluated. The canopy reflectances by the five GO models and the three-dimensional virtual canopy model are validated by the observed reflectance. It indicates that GOST2 is both reliable and computationally undemanding canopy reflectance model.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Estimating Tree Height Distribution Using Low-Density ALS Data With and
           Without Training Data
    • Authors: Mehtatalo; L.;Virolainen, A.;Tuomela, J.;Packalen, P.;
      Pages: 1432 - 1441
      Abstract: This study applies an approach based on stochastic geometry for retrieval of forest characteristics from airborne laser scanning (ALS) in two situations: 1) without ground-measured training data and 2) with training data. The applied model treats the ALS echo heights as an outcome of a random process, expressing the observed heights of canopy envelope as a function of stand density, the parameters of the tree height distribution, and the shape of the individual tree crown. The model was applied to a eucalyptus plantation dataset with known spacing, where the main interest was to estimate the plot-specific tree height distribution. Estimation without training data resulted in RMSEs of 2.9 and 0.9 m for mean and dominant heights, respectively. Estimation using training data resulted in RMSE's of 1.4 and 0.8 m, respectively. In both cases, the estimates of dominant height were more accurate than with the reference method, but the estimates of mean height were less accurate (area-based approach; RMSEs 1.1 and 0.9 m, respectively). The model-based method was robust to substantial decrease in echo density from 1.4 echoes/m2 to 0.14 echoes/m2.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Discrimination of Vegetation Height Categories With Passive Satellite
           Sensor Imagery Using Texture Analysis
    • Authors: Petrou; Z.I.;Manakos, I.;Stathaki, T.;Mucher, C.A.;Adamo, M.;
      Pages: 1442 - 1455
      Abstract: Vegetation height is a crucial factor in environmental studies, landscape analysis, and mapping applications. Its estimation may prove cost and resource demanding, e.g., employing light detection and ranging (LiDAR) data. This study presents a cost-effective framework for height estimation, built around texture analysis of a single very high-resolution passive satellite sensor image. A number of texture features are proposed, based on local variance, entropy, and binary patterns. Their potential in discriminating among classes in a wide range of height values used for habitat mapping (from less than 5 cm to 40 m) is tested in an area with heath, tree, and shrub vegetation. A number of missing data handling, outlier removal, and data normalization methods are evaluated to enhance the proposed framework. Its performance is tested with different classifiers, including single and ensemble tree ones and support vector machines. Furthermore, dimensionality reduction (DR) is applied to the full feature set (192 features), through both data transformation and filter feature selection methods. The proposed approach was tested in two WorldView-2 images, representing the peak and the decline of the vegetative period. Vegetation height categories were accurately distinguished, reaching accuracies of over 90% for six height classes, using the images either individually or in synergy. DR achieved similarly high, or higher, accuracies with even a 3% feature subset, increasing the processing efficiency of the framework, and favoring its use in height estimation applications not requiring particularly high spatial resolution data, as a cost-effective surrogate of more expensive and resource demanding approaches.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Optical Sensing of Vegetation Water Content: A Synthesis Study
    • Authors: Ying Gao;Walker; J.P.;Allahmoradi, M.;Monerris, A.;Dongryeol Ryu;Jackson, T.J.;
      Pages: 1456 - 1464
      Abstract: Vegetation water content (VWC) plays an important role in parameterizing the vegetation influence on microwave soil moisture retrieval. During the past decade, relationships have been developed between VWC and vegetation indices from satellite optical sensors, in order to create large-scale VWC maps based on these relationships. Among existing vegetation indices, the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI) have been most frequently used for estimating VWC. This work compiles and inter-compares a number of equations developed for VWC derivation from NDVI and NDWI using satellite data and ground samples collected from field campaigns carried out in the United States, Australia, and China. Four vegetation types are considered: corn, cereal grains, legumes, and grassland. While existing equations are reassessed against the entire compiled data sets, new equations are also developed based on the entire data sets. Comparing with existing equations, results show superiorities for the new equations based on statistical analysis against the entire data set. NDWI1640 and NDVI are found to be the preferred indices for VWC estimation based on the availability and the error statistics of the compiled data sets. It is recommended that the new equations can be applied in the future global remote sensing application for VWC map retrieval.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Assessment of a Remote Sensing Energy Balance Methodology (SEBAL) Using
           Different Interpolation Methods to Determine Evapotranspiration in a
           Citrus Orchard
    • Authors: Jimenez-Bello; M.A.;Castel, J.R.;Testi, L.;Intrigliolo, D.S.;
      Pages: 1465 - 1477
      Abstract: A surface energy balance algorithm for land (SEBAL) for estimating evapotranspiration (ET) has been parameterized and tested in a 400-ha drip irrigated citrus orchard. Simultaneously, during three growing seasons, energy fluxes were measured using Eddy Covariance. Instantaneous fluxes obtained with SEBAL using 10 images from Landsat-5 were compared with the measured fluxes. The Perrier function was the best method for properly estimating the roughness momentum length for discontinuous canopies, as in citrus orchards. Crop height was estimated using LIDAR data. In general, SEBAL performed well for net radiation estimation but failed in soil heat flux estimation. Latent heat estimations from the SEBAL model had a relative root mean square error (rRMSE) of 0.06 when compared with measurements obtained by Eddy Covariance. Three procedures were tested for up-scaling the instantaneous ET estimates from SEBAL to daily ET values: 1) assuming the fraction between the actual ET and the reference ET is constant throughout the day; 2) using actual local crop coefficient curves; and 3) using an up-scaling factor where the fraction of hourly ET to daily ET equals the ratio of hourly to daily global solar radiation. This last method gave acceptable results for daily ET estimations (rRMSE = 0.09) and for 15day ET (rRMSE = 0.19), and its main advantage is that no local data are required. It is concluded that the SEBAL methodology can be successfully applied for determining actual ET, even in discontinuous citrus canopies. However, additional parameterizations of momentum roughness length were needed in order to obtain reliable ET determinations.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Multiscale Validation of the 8-day MOD16 Evapotranspiration Product Using
           Flux Data Collected in China
    • Authors: Ronglin Tang;Kun Shao;Zhao-Liang Li;Hua Wu;Bo-Hui Tang;Guoqing Zhou;Li Zhang;
      Pages: 1478 - 1486
      Abstract: Accurate estimates of terrestrial evapotranspiration (ET) are critical and significant to the field for modeling water and energy transfer between the land surface and atmosphere. This paper evaluates the 8-day MOD16 actual ET product using the ground-based eddy covariance (EC) system and large aperture scintillometer (LAS) measurements collected from 2008 to 2011 at seven sites in North and Northwest China. Overall, the 8-day MOD16 ET reproduces the temporal patterns of both the LAS and EC measurements but tends to underestimate and overestimate these measurements at high and low ET levels, respectively. It is also of limited use when surface is irrigated because under such condition significant underestimation is observed. Using the LAS measurements that also include a large source area does not generate a better agreement than using the EC measurements which comprise a small source area. The 8-day MOD16 ET averaged over ${3} times {3;km}^{{2}}$ MODIS pixels agree better with both the EC and LAS measurements than that extracted at the ${1} times {1};{km}^{{2}}$ MODIS pixel. For the EC validation, the relative bias and the relative root-mean-square error (RMSE) vary between 5% and $- 59% $ and between 35% and 120%, respectively, for the LAS validation, the relative bias and the relative RMSE vary between 6% and $- 69% $ and between 55% and 108%, respectively. The agreement between one site and another is not consistent and varies greatly. More validation work is recommended to testing the general applicability of the MOD16 ET product at a large number of sites worldwide.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • A Two-Level Approach for Species Identification of Coniferous Trees in
           Central Ontario Forests Based on Multispectral Images
    • Authors: Jili Li;Baoxin Hu;Woods; M.;
      Pages: 1487 - 1497
      Abstract: This study aims to provide detailed spatial information of valuable tree species to support improved management of winter habitat of white-tailed deer. To achieve this, we proposed a novel approach using information from two spatial scales and a suite of methods for analysis and classification of remotely sensed data. High-spatial resolution, multispectral images were employed to test the proposed method. A new structure-based remote sensing feature [local binary pattern (LBP) index] was developed and proved to be effective for species classification. A simple but effective fusion approach based on information entropy theory was proposed to incorporate features derived from different methods and their uncertainties. Based on tenfold cross validation, an overall accuracy (OA) of 77% was obtained for the classification of three tree species groups. The proposed approach has high potential to improve species mapping for operational ecological modeling.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Inverse Retrieval of Chlorophyll From Reflected Spectra for Assimilating
           Branches of Drought-Tolerant Tamarix ramosissima
    • Authors: Sinan Zhang;Quan Wang;
      Pages: 1498 - 1505
      Abstract: Leaf chlorophyll content is a critical indicator for the better understanding of the featured carbon cycle and ecosystem functions in arid regions. The potential applicability of the inverse retrieval of chlorophyll via the radiative transfer model PROSPECT has been intensively examined in this study for a dominant species in desert ecosystems, Tamarix ramosissima, in central Asia, which has distinct structural features of xeromorphism and its young twig functioned as “assimilating organisms.” This study revealed that the performance of the inverse retrieval based on the original version of PROSPECT-4 was poor with very low accuracy. As a comparison, its calibrated version was capable of accurate retrieval of chlorophyll content, which recorded an R2 (coefficient of determination) of 0.47 with a root mean square error (RMSE) of 28.79 mg/m2, over the entire measured chlorophyll range, from 57.37 to 202.27 mg/m2. The model calibration is not considered to be overfitting since the tenfold cross-validation shows a close RMSE value of 26.19 mg/m2. The effects of the percentage of training dataset for calibration and the number of calibration repeats have also been intensively investigated in this study. Despite some inherent defects of applying broadleaforiented PROSPECT on assimilating branches, it remains a feasible selection to inversely retrieve the chlorophyll content from the reflectance and thus provides a base for investigating the chlorophyll content of desert plants using hyperspectral remote sensing.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Modeling Land Surface Reflectance Coupled BRDF for HJ-1/CCD Data of Rugged
           Terrain in Heihe River Basin, China
    • Authors: Jianguang Wen;Qiang Liu;Yong Tang;Baocheng Dou;Dongqin You;Qing Xiao;Qinhuo Liu;Xiaowen Li;
      Pages: 1506 - 1518
      Abstract: Rugged terrain significantly affects the Huan Jing (HJ)-1/CCD reflectance at the earth's surface because the sloping surfaces change the sun-surface-sensor geometry. It is necessary to consider the land surface directional reflectance and reduce topographic effects to obtain the correct reflectance. An atmospheric model 6S (second simulation of the satellite signal in the solar spectrum) coupled with bidirectional reflectance distribution function (BRDF) shape, which is well suited to estimate the HJ-1/CCD land surface reflectance of rugged terrain and flat surface (BRATC, BRDF-based atmospheric and topographic correction), is reformulated in this paper. The BRDF shape, a statistics-based MODIS (moderate-resolution imaging spectroradiometer) BRDF prior-knowledge look-up table (LUT) stored in this algorithm, is applied to the HJ-1/CCD reflectance estimation that covers Heihe River Basin, China. The results of the indirect validation of the visual image and the linear relationship between the reflectance and the cosine of the solar relative incident angle show that the algorithm effectively reduces topographic effects. Compared with three land cover field measurement reflectances, the HJ-1/CCD-corrected reflectance is consistently good with an overall RMSE as low as 0.0128. The proposed method could be designed for an operational system of HJ-1/CCD reflectance products.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Performance and Scalability of the JCSDA Community Radiative Transfer
           Model (CRTM) on NVIDIA GPUs
    • Authors: Mielikainen; J.;Bormin Huang;Huang, H.-L.A.;Lee, T.;
      Pages: 1519 - 1527
      Abstract: An atmospheric radiative transfer model calculates radiative transfer of electromagnetic radiation through earth's atmosphere. The community radiative transfer model (CRTM) is a fast radiative transfer model for calculating the satellite infrared (IR) and microwave (MW) radiances of a given state of the Earth's atmosphere and its surface. The CRTM takes into account the radiance emission and absorption of various atmospheric gasses as well as the emission and the reflection of various surface types. Two different transmittance algorithms are currently available in the CRTM OPTRAN: optical depth in absorber space (ODAS) and optical depth in pressure space (ODPS). ODAS in the current CRTM allows two variable absorbers (water vapor and ozone). In this paper, we examine the feasibility of using graphics processing units (GPUs) to accelerate the CRTM with the ODAS transmittance model. Using commodity GPUs for accelerating CRTM means that the hardware costs of adding high-performance accelerators to computation hardware configuration are significantly reduced. Our results show that GPUs can provide significant speedup over conventional processors for the 8461-channel IASI sounder. In particular, a GPU on the dual-GPU NVIDIA GTX 590 card can provide a speedup 375x for the single-precision version of the CRTM ODAS compared to its single-threaded Fortran counterpart running on Intel i7 920 CPU, whereas the speedup for 1 CPU socket with respect to 1 CPU core is only 6.3x. Furthermore, two NVIDIA GTX 590s provided speedups of 201x and 1367x for double precision and single precision versions of ODAS compared to single threaded Fortran code.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Evaluation of the Effects of Surface Roughness on the Relationship Between
           Soil BRF Data and Broadband Albedo
    • Authors: Cierniewski; J.;Kazmierowski, C.;Krolewicz, S.;
      Pages: 1528 - 1533
      Abstract: This paper reports a preliminary study on correctness of the broadband albedo (αb) of cultivated soils that could be calculated by their narrowband bidirectional reflectance factors (BRF) measured from many directions with a prototype goniometric device in a laboratory on their samples with similar roughness, as these soils revealed in the field. The correctness was tested on examples of Phaeozem, Luvisol, and Albeluvisol with roughness formed by a plow, disk harrow, pulverizing harrow, and smoothing harrow. The αb values of the soils calculated using the equation proposed here were not affected by the root mean square error higher than 0.01 as compared to the data measured in the field if the BRF data were obtained on the soil samples with a sufficiently low roughness. It was found that the roughness of those soil samples should be sufficiently low to ensure that the values of their height standard deviation along the length of the minor axis of a sensor field of view area are greater than 15.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Estimation of Spruce Needle-Leaf Chlorophyll Content Based on DART and
           PARAS Canopy Reflectance Models
    • Authors: Yanez-Rausell; L.;Malenovsky, Z.;Rautiainen, M.;Clevers, J.G.P.W.;Lukes, P.;Hanus, J.;Schaepman, M.E.;
      Pages: 1534 - 1544
      Abstract: Needle-leaf chlorophyll content (Cab) of a Norway spruce stand was estimated from CHRIS-PROBA images using the canopy reflectance simulated by the PROSPECT model coupled with two canopy reflectance models: 1) discrete anisotropic radiative transfer model (DART); and 2) PARAS. The DART model uses a detailed description of the forest scene, whereas PARAS is based on the photon recollision probability theory and uses a simplified forest structural description. Subsequently, statistically significant empirical functions between the optical indices ANCB670-720 and ANMB670-720 and the needle-leaf Cab content were established and then applied to CHRIS-PROBA data. The Cab estimating regressions using ANMB670_720 were more robust than using ANCB670-720 since the latter was more sensitive to LAI, especially in case of PARAS. Comparison between Cab estimates showed strong linear correlations between PARAS and DART retrievals, with a nearly perfect one-to-one fit when using ANMB670-720 (slope = 1.1, offset = 11 μg · cm-2). Further comparison with Cab estimated from an AISA Eagle image of the same stand showed better results for PARAS (RMSE = 2.7 μg · cm-2 for ANCB670-720; RMSE = 9.5 μg · cm-2 for ANMB670_720) than for DART (RMSE = 7.5 μg · cm-2 for ANCB670-720; RMSE = 23 μg · cm-2 for ANMB670-720). Although these results show the potential for simpler models like PARAS in estimating needle-leaf Cab from satellite imaging spectroscopy data, further analyses regarding parameterization of radiative transfer models are recommended.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • A Modified Semianalytical Algorithm for Remotely Estimating Euphotic Zone
           Depth in Turbid Inland Waters
    • Authors: Wei Yang;Matsushita; B.;Yoshimura, K.;Jin Chen;Fukushima, T.;
      Pages: 1545 - 1554
      Abstract: Euphotic zone depth (Zeu), defined as the depth where photosynthetic available radiation (PAR) is 1% of its surface value, is of great importance in studies of water biogeochemical processes. Satellite remote sensing is a powerful technique to obtain Zeu, as it can cover large areas at very frequent intervals. Several remote-sensing algorithms for estimating Zeu have been developed for oceanic water bodies; however, remote estimation of Zeu is still a challenging task for inland waters. In this study, an existing semianalytical algorithm (named as Lee07 in this study) was modified for remotely estimating Zeu in turbid inland waters by replacing the original quasi-analytical algorithm (QAA) by QAA_Turbid, an algorithm specially developed for remotely estimating total absorption and backscattering coefficients in turbid waters. Performance of the modified algorithm was evaluated using in situ radiometric data collected in Japan's Lake Kasumigaura, known to be turbid. Results showed that yielded acceptable estimation accuracy for Zeu (ranging from 1.15 to 2.26 m) with root-mean-square error (RMSE) of 0.12 m, normalized root-mean-square error (NRMS) of 8.01%, and mean normalized bias (MNB) of -1.84%, significantly outperforming the original version as well as three other Zeu retrieval algorithms. These results indicate its great potential for accurately estimating Zeu over widespread turbid inland waters from satellite images.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Automatic Identification of Oceanic Multieddy Structures From Satellite
           Altimeter Datasets
    • Authors: Jiawei Yi;Yunyan Du;Chenghu Zhou;Fuyuan Liang;May Yuan;
      Pages: 1555 - 1563
      Abstract: Very few of current eddy detection algorithms are capable of identifying multieddy structures resulted from interactions among eddies. In this study, we improve our previous hybrid detection (HD) algorithm by incorporating a new criterion to better identify multieddy structures from satellite altimeter data. The criterion defines an aspect ratio to determine if eddies have vortex overlaps and, as such, result in a composite structure of multiple eddies (a.k.a. multieddy structures). Compared with two previous studies on observed eddy-eddy interactions in eddy mergers from altimeter data, the improved HD algorithm not only successfully captures multieddy structures but also shows how eddies interact and evolve, including merging, splitting, and partial vorticity exchange. Tests of the improved HD algorithm on a series of sea-level anomaly maps in the South China Sea (SCS) from 1993 to 2012 show that single eddies, in contrast to eddies with composite structures, appear more concentrated in northwest of the Luzon and southeast of Vietnam. Tracking dual-eddy structures reveals several processes of eddy interactions in the SCS. The study demonstrates the potential value of the new HD algorithm in helping scientists to investigate characteristics of eddy-eddy interactions from satellite observations.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • On the Investigation of the Sea-Level Variability in Coastal Zones Using
           SWOT Satellite Mission: Example of the Eastern English Channel (Western
    • Authors: Turki; I.;Laignel, B.;Chevalier, L.;Costa, S.;Massei, N.;
      Pages: 1564 - 1569
      Abstract: The future mission of surface water and ocean topography (SWOT), launched in 2020 over a period of 3-5 years, will be designated to address the issue of combining surface water hydrology with physical oceanography aiming to present new perspectives of applications for coastal areas. The extent to which the synthetic SWOT measurements can reproduce the temporal variability of the sea level was investigated. The eastern English Channel (NW France) was considered as a case of application. The hourly sea-level records were filtered from the aliased harmonic tides by classic harmonic analyses to obtain the nontidal residual. This residual was used to simulate synthetically the satellite samples based on the number of overpasses per repeat cycle at each geographical station. Both real and synthetic SWOT measurements were compared by the use of different approaches of inference statistics and wavelets. The statistical behavior, deduced from the functions of probability density (pdf) and cumulative distribution (cdf), shows correlations between 65% and 75% for hourly measurements, which increase to 85% for monthly average ones. The frequency of positive and negative extreme values is under-estimated with an order less than 25%. The potential use of SWOT depends on the number of measurements and the sampling interval between SWOT overpasses per repeat orbit. In the time- frequency domain, the wavelet multiresolution analysis of the nontidal sea level displays four components: 1) 1 year; 2) ~4-7 month; 3) ~2-3 month; and 4)
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • 3-D Point Cloud Object Detection Based on Supervoxel Neighborhood With
           Hough Forest Framework
    • Authors: Hanyun Wang;Cheng Wang;Huan Luo;Peng Li;Yiping Chen;Li; J.;
      Pages: 1570 - 1581
      Abstract: Object detection in three-dimensional (3-D) laser scanning point clouds of complex urban environment is a challenging problem. Existing methods are limited by their robustness to complex situations such as occlusion, overlap, and rotation or by their computational efficiency. This paper proposes a high computationally efficient method integrating supervoxel with Hough forest framework for detecting objects from 3-D laser scanning point clouds. First, a point cloud is over-segmented into spatially consistent supervoxels. Each supervoxel together with its first-order neighborhood is grouped into one local patch. All the local patches are described by both structure and reflectance features, and then used in the training stage for learning a random forest classifier as well as the detection stage to vote for the possible location of the object center. Second, local reference frame and circular voting strategies are introduced to achieve the invariance to the azimuth rotation of objects. Finally, objects are detected at the peak points in 3-D Hough voting space. The performance of our proposed method is evaluated on real-world point cloud data collected by the up-to-date mobile laser scanning system. Experimental results demonstrate that our proposed method outperforms state-of-the-art 3-D object detection methods with high computational efficiency.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • A Random Forest Model Based on Lidar and Field Measurements for
           Parameterizing Surface Roughness in Coastal Modeling
    • Authors: Medeiros; S.C.;Hagen, S.C.;Weishampel, J.F.;
      Pages: 1582 - 1590
      Abstract: A novel technique for parameterizing surface roughness in coastal inundation models using airborne laser scanning (lidar) data is presented. Two important parameters to coastal overland flow dynamics, Manning's n (bottom friction) and effective aerodynamic roughness length (wind speed reduction), are computed based on a random forest (RM) regression model trained using field measurements from 24 sites in Florida fused with georegistered lidar point cloud data. The lidar point cloud for each test site is separated into ground and nonground classes and the z-dimensional (height or elevation) variance from the least squares regression plane is computed, along with the height of the nonground regression plane. These statistics serve as the predictor variables in the parameterization model. The model is then tested using a bootstrap subsampling procedure consisting of removal without replacement of one record and using the surviving records to train the model and predict the surface roughness parameter of the removed record. When compared with the industry standard technique of assigning surface roughness parameters based on published land use/land cover type, the RM regression models reduce the parameterization error by 93% (0.086-0.006) and 53% (1.299-0.610 m) for Manning's n and effective aerodynamic roughness length, respectively. These improvements will improve water level and velocity predictions in coastal models.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Estimation of Improvement in Indian Summer Monsoon Circulation by
           Assimilation of Satellite Retrieved Temperature Profiles in WRF Model
    • Authors: Raju; A.;Parekh, A.;Sreenivas, P.;Chowdary, J.S.;Gnanaseelan, C.;
      Pages: 1591 - 1600
      Abstract: This study estimates the improvement in the simulation of Indian summer monsoon (ISM) circulation in the weather research and forecasting (WRF) model by assimilating temperature profiles from atmospheric infrared sounder. Two experiments are carried out from 1st May to 1st October during 2003-2011. In the first experiment control (CTRL), National Centers for Environmental Prediction final analysis forcing is used; whereas the second one (WRFAIRS) is same as CTRL but temperature profiles are assimilated. The improvements in the simulation are quantified using different statistical scores. Overall, the assimilation has improved the spatial and temporal distribution of various fields associated with ISM. Some of the major improvements are 1) elimination of asymmetric (north-south) SLP bias; 2) larger error reduction in winds; 3) reduction in the temperature biases at boundary layer and midtroposphere; 4) improvement in the vertical wind shear; 5) reduction in the water vapor mixing ratio errors by 0.3-0.6 g · Kg-1; and 6) improved simulation of monsoon circulation indices. Further improvements are noticed in dynamic and thermodynamic fields over different convective regions. This study advocates that accurate representation of the thermal structure in WRF is crucial for the simulation of realistic monsoon circulation. It may further pave way for developing/improving convective parameterization schemes for the model.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • SVM-Based Sea Ice Classification Using Textural Features and Concentration
           From RADARSAT-2 Dual-Pol ScanSAR Data
    • Authors: Huiying Liu;Huadong Guo;Lu Zhang;
      Pages: 1601 - 1613
      Abstract: An approach to sea ice classification using dual polarization RADARSAT-2 ScanSAR data is presented in this paper. It is based on support vector machine (SVM). In addition to backscatter coefficients and gray-level cooccurrence matrix (GLCM) texture features, sea ice concentration was introduced as a classification basis. To better analyze the backscatter information of sea ice types, we considered two steps that could improve the ScanSAR image quality, the noise floor stripe reduction and the incidence angle normalization. Then, effective GLCM texture characteristics from both polarizations were selected using the proper parameters. The third type of information, sea ice concentration, was extracted from the initial SVM classification result after the optimal SVM model was achieved from the training. The final result was generated by implementing the SVM twice and the decision tree once. Using this method, the classification was improved in two aspects, both of which were related to sea ice concentration. The results showed that the sea ice concentration parameter was effective in dealing with open water and in discriminating pancake ice from old ice. Finally, the maximum likelihood (ML) was run as a comparative test. In conclusion, the sea ice concentration parameter could play a role in SVM classification, and the whole process provided an effective way to classify sea ice using dual polarization ScanSAR data.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Local Isotropy Indicator for SAR Image Filtering: Application to
           Envisat/ASAR Images of the Doñana Wetland (November 2014)
    • Authors: Marti-Cardona; B.;Lopez-Martinez, C.;Dolz-Ripolles, J.;
      Pages: 1614 - 1622
      Abstract: This paper explores a geometrical and computationally simple operator, named Ds, for local isotropy assessment on SAR images. It is assumed that isotropic intensity distributions in natural areas, either textured or nontextured, correspond to a single cover class. Ds is used to measure isotropy in processing neighborhoods and decide if they can be considered as belonging to a unique cover class. The speckle statistical properties are used to determine suitable Ds thresholds for discriminating heterogeneous targets from isotropic cover types at different window sizes. An assessment of Ds as an edge detector showed sensitivities similar to those of the ratio edge operator for straight, sharp boundaries, centered in the processing window, but significantly better sensitivity for detecting heterogeneities during the window expansion in multiresolution filtering. Furthermore, Ds presents the advantage versus the ratio edge coefficient of being rotationally invariant, and its computation indicates the direction of the main intensity gradient in the processing window. The Ds operator is used in a multiresolution fashion for filtering ASAR scenes of the Doñana wetland. The intensities in isotropic areas are averaged in order to flatten fluctuations within cover types and facilitate a subsequent land cover classification. The results show high degree of smoothing within textured cover classes, plus effective spatial adaptation to gradients and irregular boundaries, substantiating the usefulness of this operator for filtering SAR data of natural areas with the purpose of classification.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Parametric and Nonparametric Methods for SAR Patch Scene Categorization
    • Authors: Gleich; D.;Singh, J.;Planinsic, P.;
      Pages: 1623 - 1634
      Abstract: This paper presents synthetic aperture radar (SAR) image categorization based on feature descriptors within the discrete wavelet transform (DWT) domain using nonparametric and parametric features. The first and second moments, Kolmogorov Sinai entropy and coding gain, are used for the nonparametric features within an oriented dual tree complex wavelet transform (2D ODT$mathbb{C}$WT). A Gauss-Markov random field (GMRF), triplet Markov random field (TMRF), and autobinomial model (ABM) are used for feature extraction using a parametric approach within an image domain. A single parameter of GMRF, TMRF, or ABM is used for characterizing an entire patch; therefore, higher model orders (MOs) are used. A database with 2000 images representing 20 different classes with 100 images per class is used for estimating classification efficiency. A supervised learning stage is implemented within a support vector machine (SVM) using 10% and 20% of the test images per class. The experimental results showed that the nonparametric features achieved better results when compared to the parametric features.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Information Content of Very-High-Resolution SAR Images: Semantics,
           Geospatial Context, and Ontologies
    • Authors: Dumitru; C.O.;Shiyong Cui;Schwarz, G.;Datcu, M.;
      Pages: 1635 - 1650
      Abstract: Currently, the amount of collected Earth Observation (EO) data is increasing considerably with a rate of several Terabytes of data per day. As a consequence of this increasing data volume, new concepts for exploration and information retrieval are urgently needed. To this end, we propose to explore satellite image data via an image information mining (IIM) approach in which the main steps are feature extraction, classification, semantic annotation, and interactive query processing. This leads to a new process chain and a robust taxonomy for the retrieved categories capitalizing on human interaction and judgment. We concentrated on land cover categories that can be retrieved from high-resolution synthetic aperture radar (SAR) images of the spaceborne TerraSAR-X instrument, where we annotated different urban areas all over the world and defined a taxonomy element for each prevailing surface cover category. The annotation resulted from a test dataset comprising more than 100 scenes covering diverse areas of Africa, Asia, Europe, the Middle East, and North and South America. The scenes were grouped into several collections with similar source areas and each collection was processed separately in order to discern regional characteristics. In the first processing step, each scene was tiled into patches. Then the features were extracted from each patch by a Gabor filter bank and a support vector machine with relevance feedback classifying the feature sets into user-oriented land cover categories. Finally, the categories were semantically annotated using Google Earth for ground truthing. The annotation followed a multilevel approach that allowed the fusion of information being visible on different resolution levels. The novelty of this paper lies in the fact that a semantic annotation was performed with a large number of high-resolution radar images that allowed the definition of more than 850 surface cover categories. This opens the way toward an automated identification - nd classification of urban areas, infrastructure (e.g., airports), geographic objects (e.g., mountains), industrial installations, military compounds, vegetation, and agriculture. Applications that may result from this work can be a semantic catalog of urban images to be used in crisis situations or after a disaster. In addition, the proposed taxonomies can become a basis for building a semantic catalog of satellite images. Finally, we defined four powerful types of high-level queries. Querying on such high levels provides new opportunities for users to search an image database for specific parameters or semantic relationships.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • SAR Image Reconstruction From Undersampled Raw Data Using Maximum
           A Posteriori Estimation
    • Authors: Xiao Dong;Yunhua Zhang;
      Pages: 1651 - 1664
      Abstract: A method for synthetic aperture radar (SAR) imaging using maximum a posteriori (MAP) estimation based on multiplicative speckle model is presented. The new method uses the total variation (TV) minimization to regularize the solution. The reconstruction of SAR image is formulated as a biconvex optimization problem, which is solved by the alternate convex search (ACS) method. Experiments on Radarsat-1 raw data show that the proposed method can recover most of the structural and texture details of the imaged scene using only a half of raw data. Compared with regular regularization methods for SAR imaging with incomplete data, the proposed method performs much better on less sparse scenes.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Technical Framework of Feature Extraction Based on Pixel-Level SAR Image
           Time Series
    • Authors: Liang Cheng;Yafei Wang;Lishan Zhong;Peijun Du;Manchun Li;
      Pages: 1665 - 1681
      Abstract: This study proposes a novel technical framework of feature extraction based on pixel-level synthetic aperture radar (SAR) image time series, to exploit the application potential of SAR image data with low and medium spatial resolution. This framework comprises three key parts: 1) construction of the pixel-level SAR image time series using a new matching technique based on progressive binary partition; 2) pixel-level similarity measurement via dynamic time warping (DTW); and 3) a new spatiotemporal similarity analysis method that improves feature extraction by considering both the similarity of a feature's pixel-level time series and its spatial correlation. Two locations, covered by 31 low-resolution (150 m) and 26 medium-resolution (30 m) ENVISAT ASAR images, respectively, were selected as test cases to validate the proposed framework. Results show that the framework can identify features with a high level of accuracy, completeness, and correctness, outperforming methods using multitemporal images, as well as the time series-only (nonspatial) method, and other methods of spatiotemporal similarity analysis that use alternative similarity measures.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Patch Ordering-Based SAR Image Despeckling Via Transform-Domain Filtering
    • Authors: Bin Xu;Yi Cui;Zenghui Li;Bin Zuo;Jian Yang;Jianshe Song;
      Pages: 1682 - 1695
      Abstract: In this paper, we propose a synthetic aperture radar (SAR) image despeckling method based on patch ordering and transform-domain filtering. Logarithmic transformation with bias correction is applied to the original SAR image to transform the multiplicative noise model into the additive model. Then, we adopt a two-stage filtering strategy. The first stage is coarse filtering which can suppress speckle effectively. In this stage, we extract the sliding patches from the logarithmic SAR image, and order them in a smooth way by a simplified patch ordering algorithm specially for SAR images. The ordered patches are filtered by learned simultaneous sparse coding (SSC), a technology recently advanced in image processing. Then, the coarse filtering result is reconstructed from the filtered patches via inverse permutation and subimage averaging. The second stage is refined filtering which can eliminate small artifacts generated by the coarse filtering. In this stage, the sliding patches are extracted from the coarse filtering result and ordered in the same way. Then, we apply 2-D wavelet hard-thresholding to the ordered patches and reconstruct the refined filtering result. The final result is obtained by taking exponential transformation to the refined filtering result. An algorithm based on the proposed strategy is presented in detail and the parameters are selected for fast and effective realization. Experimental results with both simulated images and real SAR images demonstrate that the proposed method achieves state-of-the-art despeckling performance in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM) index, equivalent number of looks (ENLs), and ratio image.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Very-High-Resolution SAR Images and Linked Open Data Analytics Based on
    • Authors: Espinoza-Molina; D.;Nikolaou, C.;Dumitru, C.O.;Bereta, K.;Koubarakis, M.;Schwarz, G.;Datcu, M.;
      Pages: 1696 - 1708
      Abstract: In this paper, we deal with the integration of multiple sources of information such as Earth observation (EO) synthetic aperture radar (SAR) images and their metadata, semantic descriptors of the image content, as well as other publicly available geospatial data sources expressed as linked open data for posing complex queries in order to support geospatial data analytics. Our approach lays the foundations for the development of richer tools and applications that focus on EO image analytics using ontologies and linked open data. We introduce a system architecture where a common satellite image product is transformed from its initial format into to actionable intelligence information, which includes image descriptors, metadata, image tiles, and semantic labels resulting in an EO-data model. We also create a SAR image ontology based on our EO-data model and a two-level taxonomy classification scheme of the image content. We demonstrate our approach by linking high-resolution TerraSAR-X images with information from CORINE Land Cover (CLC), Urban Atlas (UA), GeoNames, and OpenStreetMap (OSM), which are represented in the standard triple model of the resource description frameworks (RDFs).
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Speckle Tracking and Interferometric Processing of TerraSAR-X TOPS Data
           for Mapping Nonstationary Scenarios
    • Authors: Scheiber; R.;Jager, M.;Prats-Iraola, P.;De Zan, F.;Geudtner, D.;
      Pages: 1709 - 1720
      Abstract: Terrain observation by progressive scan (TOPS) antenna beam steering is utilized for European Space Agency's (ESA's) Sentinel-1 synthetic aperture radar (SAR) sensor for the interferometric wide swath (IW) and extra wide swath (EW) modes. As a consequence of the azimuth steering, the resulting signal characteristics have to be accounted for in SAR interferometric (InSAR) processing. This paper assesses the performance of speckle tracking and spectral diversity (SD) [also referred to as split spectrum or multi-aperture interferometry (MAI)] when applied to TOPS data acquired over nonstationary scenarios, such as glaciers. The characteristics of the TOPS signal, especially the azimuth-variant Doppler centroid, are discussed with particular consideration of along-track surface motion between the interferometric acquisitions. The TOPS specific coregistration requirements are formulated, followed by an analysis of the theoretical estimation accuracy as a function of the estimation window size. A refined adaptive coregistration approach based on SD is suggested. Experimental TerraSAR-X TOPS data acquired over the Lambert glacier, Antarctica, are used to validate the proposed speckle tracking and SD methodologies.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • MOCO for High-Resolution ScanSAR via Full-Aperture Processing
    • Authors: Ning Li;Wang; R.;Yunkai Deng;Jiaqi Chen;Yabo Liu;Zhimin Zhang;Fengjun Zhao;
      Pages: 1721 - 1726
      Abstract: In this paper, a novel Doppler rate (DR) estimation-based two-dimensional (2-D) subaperture motion compensation (MOCO) approach is proposed for high-resolution scanning synthetic aperture radar (ScanSAR) mode. It can estimate space-variant phase errors in different subswaths simultaneously by exploiting data of multiple subswaths. High-resolution ScanSAR images, produced by full-aperture processing algorithm, are often defocused by uncompensated phase errors. As a result of the periodic gapped data in each subswath in ScanSAR mode, the performance of the commonly used stripmap MOCO approaches will be degraded or even not work when using full-aperture processing algorithm. The effectiveness of the proposed approach is demonstrated by an airborne ScanSAR real data set containing different types of terrain, with a high geometric resolution of about 3.5 m (mid or far range) or 5 m (near range) in azimuth working at C band.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Nonlocal Adaptive Multilooking in SAR Multipass Differential
    • Authors: Sica; F.;Reale, D.;Poggi, G.;Verdoliva, L.;Fornaro, G.;
      Pages: 1727 - 1742
      Abstract: Filtering of interferometric synthetic aperture radar (InSAR) data has been the object of a growing number of papers, in recent years, aimed at improving the quality of differential InSAR (DInSAR) and tomography products based on multibaseline/multitemporal data. In this work, we investigate the potential of nonlocal adaptive multilooking (AML) techniques for the filtering of interferometric stacks. Nonlocal filtering has been already successfully applied to SAR data in many contexts, including the restoration of single interferograms. We propose several workflows, with different solutions for the data preprocessing and for the estimation of similarity, at the core of all nonlocal methods. Experiments on simulated and real data, the latter both at low and high spatial resolution, prove the proposed methods to provide significant improvements over nonadaptive multilooking in terms of both resolution and detail preservation, allowing for the generation of better interferometric products.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • An Improvement of Multiple-Aperture SAR Interferometry Performance in the
           Presence of Complex and Large Line-of-Sight Deformation
    • Authors: Hyung-Sup Jung;Sang-Ho Yun;Min-Jeong Jo;
      Pages: 1743 - 1752
      Abstract: Synthetic Aperture Radar Interferometry (InSAR) provides one-dimensional measurements on ground displacement in the radar line-of-sight (LOS) direction. Multiple-Aperture Interferometry (MAI) technique has been successfully used to measure along-track ground displacement. However, the technique occasionally shows filtering boundary artifacts along the boundary of incoherent areas and a loss of MAI coherence in the presence of large and complex LOS deformation. In this study, we propose an efficient MAI processing method to mitigate them and improve computational efficiencies as well. We validated the performance of the proposed MAI method using ALOS PALSAR interferometric pair acquired from the ascending orbits on June 12, 2007 and August 2, 2009. The test pair includes large and complex LOS deformation signals accumulated from several dike intrusions and fissure eruptions. Through the proposed MAI processing method, we have generated the InSAR and MAI interferograms with the pixel spacing of about 45 and 40 m in ground range and azimuth directions, respectively. Close to surface rupture, we found that our proposed method improved the MAI coherence from 0.33 to 0.96 and reduced the filtering boundary artifacts from 0.068 to 0.040 rad. The results demonstrate the potential of the proposed method to measure along-track ground displacement in regions of decorrelation.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Early Warning GBInSAR-Based Method for Monitoring Volterra (Tuscany,
           Italy) City Walls
    • Authors: Pratesi; F.;Nolesini, T.;Bianchini, S.;Leva, D.;Lombardi, L.;Fanti, R.;Casagli, N.;
      Pages: 1753 - 1762
      Abstract: Ground-based synthetic aperture radar interferometry (GBInSAR) remote sensing technique has been repeatedly proved an effective tool for monitoring built environment affected by structural and geological criticalities. In this paper, it is described how this technique can be successfully applied for early-warning procedures and detection of ongoing deterioration processes on archeological and cultural heritage sites. An integrated approach of GBInSAR and terrestrial laser scanner (TLS) technologies was performed on Volterra test site (Tuscany, Italy), where a sudden collapse of a 35-m wide section of city walls occurred on January 31, 2014. The installed early-warning monitoring system is capable of an accurate and focused real-time displacement detection of the south-western side of the city including walls, buildings, and monuments, thus allowing prompt interventions for citizens safety and conservation purposes. The effectiveness of this alert technique became evident when the precursors of a second impressive wall collapse were clearly detected. From the beginning of the GBInSAR monitoring, we measured a constant displacement velocity of 0.1 mm/h in correspondence to a 15-m high wall sustaining the Acropolis and lying an underground parking. After a sudden increase of velocity values up to 1.7 mm/h, the local authorities were alerted so that they had time to interdict the area to citizens and to take adequate safety countermeasures two days before the collapse.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • A DInSAR Investigation of the Ground Settlement Time Evolution of
           Ocean-Reclaimed Lands in Shanghai
    • Authors: Qing Zhao;Pepe; A.;Wei Gao;Zhong Lu;Bonano, M.;He, M.L.;Jun Wang;Xi Tang;
      Pages: 1763 - 1781
      Abstract: Reclaimed lands are seriously affected by ground settlement episodes, which are primarily caused by unconsolidated soils, and could result in severe damage to buildings and public infrastructures. In this work, we present a differential synthetic aperture radar (DInSAR) analysis of the ground displacement that impacts the ocean-reclaimed areas of the Nanhui New City of Shanghai (China), based on jointly exploiting persistent scatterers (PS) and small baseline (SB) approaches. The mean line of sight displacement velocity maps and the corresponding interferometric time-series of deformation were initially cross-compared to assess the accuracy of both DInSAR techniques in regions subject to long-lasting land reclamation processes. By exploiting a set of 31 SAR images collected by the ASAR/ENVISAT sensor from February 2007 to May 2010, we found the average difference between PS and SB velocity maps at 1.2 mm/year, with a root mean square difference of 5 mm for single measurements. Despite the increased levels of noise in the interferograms, due to the extremely time-varying electromagnetic and geometrical characteristics of the SAR scenes in correspondence to reclamation platforms, these results suggest that during first stages of reclamation processes both DInSAR methods are able to correctly identify points that preserve high level of accuracy. We have thus predicted the forthcoming time evolution of ground displacement over reclaimed platforms by combining DInSAR measurements and geotechnical-derived models, suggesting that approximately 90% of the settlements occur within about 15 years.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Research on Spatial Resolution of One-Stationary Bistatic Ultrahigh
           Frequency Ultrawidebeam–Ultrawideband SAR Based on Scattering
           Target Wavenumber Domain Support
    • Authors: Hongtu Xie;Daoxiang An;Xiaotao Huang;Zhimin Zhou;
      Pages: 1782 - 1798
      Abstract: Compared with the traditional one-stationary bistatic narrowbeam-narrowband (NB) synthetic aperture radar (SAR), the coupling between the azimuth and range wavenumbers for the one-stationary bistatic ultrahigh frequency (UHF) ultrawidebeam-ultrawideband (UWB) SAR is much larger due to the large fractional signal bandwidth and wide antenna beamwidth, which may affect the behavior of spatial resolutions. Considering the wavenumber coupling, the more accurate spatial resolutions for the one-stationary bistatic UHF UWB SAR are proposed based on the wavenumber domain support of the scattering target in this paper. First, the one-stationary bistatic SAR imaging geometry is provided, and then the spatial wavenumber of the scattering target for the one-stationary bistatic UHF UWB SAR is analyzed. Second, based on the spatial wavenumber spectrum, spatial resolutions of the one-stationary bistatic UHF UWB SAR are derived in detail. In addition, the squint angles of radars are considered in the derivation of the spatial resolutions. Besides, the narrowing/broadening factors defined as the ratio of the proposed spatial resolutions to traditional spatial resolutions are presented, which describe the effects of the fractional bandwidth and associated integration angle on the spatial resolutions. Finally, simulation results are given to prove the correctness and validity of the proposed resolutions.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • A Comparison Between High-Resolution EO-Based and Ice Analyst-Assigned Sea
           Ice Concentrations
    • Authors: Karvonen; J.;Vainio, J.;Marnela, M.;Eriksson, P.;Niskanen, T.;
      Pages: 1799 - 1807
      Abstract: In the 4th Ice Analyst Workshop 2014, ice analysts made ice concentration (IC) analysis based on two synthetic aperture radar (SAR) images over the Gulf of Bothnia located in the northern Baltic sea. The ice analysts were divided into five work groups and each group assigned ICs to predefined polygons. This exercise gave us a good opportunity to compare the analysis performed by the work groups with the results produced by our dualpol-SAR IC estimation algorithm. The ice analyzes were performed and the algorithm was run in a resolution of 100 m. For reference, we also included the polygon median values produced by the ARTIST sea ice (ASI) radiometer-based algorithm producing the ICs in a 3.125-km grid. This kind of comparisons are very important to evaluate the automated algorithms with respect to the human interpretation. Human interpretation available in the ice charts is currently considered as the best available IC information.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • A Novel Preprocessing Scheme to Improve the Prediction of Sand Fraction
           From Seismic Attributes Using Neural Networks
    • Authors: Chaki; S.;Routray, A.;Mohanty, W.K.;
      Pages: 1808 - 1820
      Abstract: This paper presents a novel preprocessing scheme to improve the prediction of sand fraction from multiple seismic attributes such as seismic impedance, amplitude, and frequency using machine learning and information filtering. The available well logs along with the three-dimensional (3-D) seismic data have been used to benchmark the proposed preprocessing stage using a methodology that primarily consists of three steps: 1) preprocessing; 2) training; and 3) postprocessing. An artificial neural network (ANN) with conjugate-gradient learning algorithm has been used to model the sand fraction. The available sand fraction data from the high-resolution well logs have far more information content than the low-resolution seismic attributes. Therefore, regularization schemes based on Fourier transform (FT), wavelet decomposition (WD), and empirical mode decomposition (EMD) have been proposed to shape the high-resolution sand fraction data for effective machine learning. The input data sets have been segregated into training, testing, and validation sets. The test results are primarily used to check different network structures and activation function performances. Once the network passes the testing phase with an acceptable performance in terms of the selected evaluators, the validation phase follows. In the validation stage, the prediction model is tested against unseen data. The network yielding satisfactory performance in the validation stage is used to predict lithological properties from seismic attributes throughout a given volume. Finally, a postprocessing scheme using 3-D spatial filtering is implemented for smoothing the sand fraction in the volume. Prediction of lithological properties using this framework is helpful for reservoir characterization (RC).
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • EnOI Optimization for SMOS Soil Moisture Over West Africa
    • Authors: Ju Hyoung Lee;Pellarin; T.;Kerr, Y.H.;
      Pages: 1821 - 1829
      Abstract: In land surface or numerical weather prediction (NWP) models, a soil moisture initialization scheme is important not to drift the prognostic variables to errors. We propose a novel approach for a stationary data assimilation scheme of ensemble optimal interpolation (EnOI) effective for Soil Moisture and Ocean Salinity (SMOS) soil moisture initialization. For the optimization of EnOI, the satellite retrieval error specification was conducted rather than ensemble evolution. As combining two ensembles generated from a satellite retrieval and a land surface model, this approach is termed as “two-step EnOI” in this study: (first step) the SMOS soil moisture retrieval ensembles (i.e., errors in brightness temperature, landscape, and geophysical parameters) were merged with SMOS L3 data; (second step) the data assimilation result from the first step was further used for the observations of the EnOI. This two-step EnOI was compared with a sequential ensemble Kalman filter (EnKF) evolving model state ensembles over time but assuming global constant a priori random errors for the SMOS observations. The point-scale comparison results showed that two-step EnOI was better matched with the field measurements than the SMOS L3 data and a sequential ensemble KF scheme. On meso-scale, a spatial average of two-step EnOI reached that of a sequential ensemble KF with the significantly reduced ensemble size. These results suggest that the performance of two-step EnOI is comparable to a sequential ensemble KF but computationally more effective. From this, it is illustrated that appropriate error specification of satellite retrieval is more important than a sequential evolution of model state ensembles, and brightness temperature ensemble mean can reduce the SMOS retrieval biases without sequential evolution.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Target Detection Based on Random Forest Metric Learning
    • Authors: Yanni Dong;Bo Du;Liangpei Zhang;
      Pages: 1830 - 1838
      Abstract: Target detection is aimed at detecting and identifying target pixels based on specific spectral signatures, and is of great interest in hyperspectral image (HSI) processing. Target detection can be considered as essentially a binary classification. Random forests have been effectively applied to the classification of HSI data. However, random forests need a huge amount of labeled data to achieve a good performance, which can be difficult to obtain in target detection. In this paper, we propose an efficient metric learning detector based on random forests, named the random forest metric learning (RFML) algorithm, which combines semimultiple metrics with random forests to better separate the desired targets and background. The experimental results demonstrate that the proposed method outperforms both the state-of-the-art target detection algorithms and the other classical metric learning methods.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Capturing the Signature of Severe Weather Events in Australia Using GPS
    • Authors: Kefei Zhang;Manning; T.;Suqin Wu;Rohm, W.;Silcock, D.;Choy, S.;
      Pages: 1839 - 1847
      Abstract: Rapid developments in satellite positioning, navigation, and timing have revolutionized surveying and mapping practice and significantly influenced the way people live and society operates. The advent of new generation global navigation satellite systems (GNSS) has heralded an exciting future for not only the GNSS community, but also many other areas that are critical to our society at large. With the rapid advances in space-based technologies and new dedicated space missions, the availability of large scale and dense contemporary GNSS networks such as regional continuously operating reference station (CORS) networks and the developments of new algorithms and methodologies, the ability of using space geodetic techniques to remotely sense the atmosphere (i.e., the troposphere and ionosphere) has dramatically improved. Real time GNSS-derived atmospheric variables with a high spatio-temporal resolution have become an important new source of measurements for meteorology, particularly for extreme weather events since water vapour (WV), as the most abundant element of greenhouse gas and accounting for ~70% of global warming, is under-sampled in current meteorological and climate observing systems. This study investigates the emerging area of GNSS technology for near real-time monitoring and forecasting of severe weather and climate change research. This includes both ground-based global positioning system (GPS)-derived precipitable water vapour (PWV) estimation and four-dimensional (4-D) tomographic modeling for wet refractivity fields. Two severe weather case studies were used to investigate the signature of GPS-derived PWV and wet refractivity derived from the 4-D GPS tomographic model under the influence of severe mesoscale convective systems (MCSs). GPS observations from the Victorian state-wide CORS network, i.e., GPSnet, in Australia were used. Results showed strong spatial and temporal correlations between the variations in the ground-based GPS-derived PWV and the- passage of the severe MCS. This indicates that the GPS method can complement conventional meteorological observations for the studying, monitoring, and potentially predicting of severe weather events. The advantage of using the ground-based GPS technique is that it can provide continuous observations for the storm passage with high temporal and spatial resolution. Results from these two case studies also suggest that GPS-derived PWV can resolve the synoptic signature of the dynamics and offer precursors to severe weather, and the tomographic technique has the potential to depict the three-dimensional (3-D) signature of wet refractivity for the convective and stratiform processes evident in MCS events. This research reveals the potential of using GNSS-derived PWV to strengthen numerical weather prediction (NWP) models and forecasts, and the potential for GNSS-derived PWV and wet refractivity fields to enhance early detection and sensing of severe weather.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Spectral Decomposition Modeling Method and Its Application to EM
           Scattering Calculation of Large Rough Surface With SSA Method
    • Authors: Wang-Qiang Jiang;Min Zhang;Peng-Bo Wei;Ding Nie;
      Pages: 1848 - 1854
      Abstract: The small slope approximation (SSA) method is a practical method to calculate the electromagnetic (EM) scattering from rough surfaces. However, the SSA method requires that the interval for sampling surfaces must be small enough, such as less than one-tenth of incident wavelength. This constraint condition will cause the problem of huge memory consumption and insufficient memory when the EM scattering of large rough surfaces is calculated. Although the hard disk has large space to keep data and can solve the insufficient memory problem, its read/write speed is still too slow. In addition, massive data transmission will reduce the computational efficiency for the compute unified device architecture (CUDA) parallel computation under some conditions. In this paper, the main idea of the spectral decomposition modeling method is that the whole spectrum of rough surface is divided into several parts and these parts can be used to generate different-scale rough surfaces. Then, by analyzing the different-scale rough surfaces, the large rough surface can be achieved and applied to the calculation of EM scattering with the SSA method. Due to the small memory consumption of different-scale rough surfaces, it takes less time to translate data for the different-scale rough surfaces than that for the standard large surface. Thus, the spectral decomposition modeling method could readily be applied to CUDA parallel computation.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Application of Remote Sensing Technologies to Map the Structural Geology
           of Central Region of Kenya
    • Authors: Mwaniki; M.W.;Matthias, M.S.;Schellmann, G.;
      Pages: 1855 - 1867
      Abstract: Advancements of digital image processes (DIP) and availability of multispectral and hyperspectral remote sensing data have greatly benefited mineral investigation, structure geology mapping, fault pattern, and landslide studies: site-specific landslide assessment and landslide quantification. The main objective of this research was to map the geology of the central region of Kenya using remote-sensing techniques to aid rainfall-induced landslide quantification. The study area is prone to landslides geological hazards and, therefore, it was necessary to investigate geological characteristics in terms of structural pattern, faults, and river channels in a highly rugged mountainous terrain. The methodology included application of PCA, band rationing, intensity hue saturation (IHS) transformation, ICA, false color composites (FCC), filtering applications, and thresholding, and performing knowledge-based classification on Landsat ETM + imagery. PCA factor loading facilitated the choice of bands with the most geological information for band rationing and FCC combination. Band ratios (3/2, 5/1, 5/4, and 7/3) had enhanced contrast on geological features and were the input variables in a knowledge-based geological classification. This was compared to a knowledge-based classification using PCs 2, 5, and IC1, where the band ratio classification performed better at representing geology and matched FCC [IC1, PC5, saturation band of IHS (5,7,3)]. Fault and lineament extraction was achieved by filtering and thresholding of pan-band8 and ratio 5/1 and overlaid on the geology map. However, the best visualization of lineaments and geology was in the FCC [IC1, PC5, saturation band of IHS (5,7,3)], where volcanic extrusions, igneous, sedimentary rocks (eolian and organic), and fluvial deposits were well discriminated.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
  • Open Access
    • Pages: 1868 - 1868
      Abstract: Advertisement, IEEE.
      PubDate: April 2015
      Issue No: Vol. 8, No. 4 (2015)
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