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IEEE transactions on geoscience and remote sensing... 54건

  1. [해외논문]   Estimation of Doppler Profile Using Multiparameter Cost Function Method   SCI SCIE

    Sinha, Swati , Sarma, Tummalapalli Venkata Chandrasekhar , Regeena, Mary Lourde
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 932 - 942 , 2017 , 0196-2892 ,

    초록

    Wind profilers (WPs) are a special category of ground-based radar instruments used to obtain 3-D profile of wind velocity along the altitude in atmosphere. They transmit radio wave pulses in very high frequency (VHF) or ultrahigh frequency (UHF) bands in vertical and near-vertical directions. The Doppler frequency shift and the time of flight of the echo signals from each beam are measured. These data are analyzed to get the radial velocities of atmospheric targets at all the ranges. The data must be processed from at least three noncoplanar beam directions together to estimate 3-D wind profile. The signal-to-noise ratio is very low for the higher range target echoes. Also, echoes are often contaminated by nonatmospheric signals like clutter, radio frequency interference, and so on. Determining accurate wind profile, especially at higher heights, becomes a challenging task due to these factors. This paper presents a novel algorithm for the estimation of radial velocity profile by processing the set of Doppler power spectra of all range bins. The algorithm identifies prospective atmospheric echoes components. Then it forms velocity profile trails connecting five range bins. The program rejects the profile trails that show velocity change higher than a predefined limit. The remaining trails are evaluated using a specially designed multiparameter cost function (MPCF). The trails with maximum cost are selected and then connected to construct the complete Doppler profile or the radial velocity profile. The key innovation in this method is an improvised function that is created by weighted addition of two terms. The first term is proportional to the signal power, and the second term is a nonlinear function of differential wind shear. This algorithm has been tried on multiple sets of the Indian mesosphere–stratosphere–troposphere radar data and the lower atmospheric WP radar data. The performance of this method is compared with other methods, namely, the adaptive moment estimation method and fuzzy logic approach. It has been observed that the new method shows excellent consistency in extracting the Doppler profile from the power spectral data. This method requires at least 30% lesser computations compared with other methods. The results of the MPCF method showed a very good match with the data obtained from concurrently operated Global Positioning System sonde, an independent wind profiling method. This paper also shows the results on the performance improvement using power spectra from the symmetrical beams. This algorithm shows a great promise as a tool for automatic Doppler profile tracing.

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  2. [해외논문]   Modeling Sea Ice Surface Emissivity at Microwave Frequencies: Impact of the Surface Assumptions and Potential Use for Sea Ice Extent and Type Classification   SCI SCIE

    Hermozo, Laura , Eymard, Laurence , Karbou, Fatima
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 943 - 961 , 2017 , 0196-2892 ,

    초록

    In this paper, the surface emissivity is retrieved over the Arctic sea ice/open seas using observations from the advanced microwave sounding unit window channels during the year 2009. The emissivity computation is performed using two contrasted surface assumptions: specular and Lambertian assumptions. The obtained sea ice surface emissivities are studied in this paper with a focus on the effect of the surface assumption. Some factors of variability of the obtained emissivities are analyzed: variability in space, in time, with the zenith angle, and with respect to the frequency. We show that the near-nadir surface emissivity and emissivity difference (obtained using two contrasted surface assumptions) could be used as an excellent proxy to detect ice/no ice regions. We also show that near-nadir sea ice emissivity at some selected frequencies and the combination of both high and low window frequencies could also be very useful to better characterize sea ice surface physical properties and provide additional information for existing sea ice classifications, as they bring relevant information about first year and multiyear sea ice properties and their seasonal evolution.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  3. [해외논문]   Automatic Enhancement and Detection of Layering in Radar Sounder Data Based on a Local Scale Hidden Markov Model and the Viterbi Algorithm   SCI SCIE

    Carrer, Leonardo , Bruzzone, Lorenzo
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 962 - 977 , 2017 , 0196-2892 ,

    초록

    Radar sounders are unique instruments for subsurface investigation in both terrestrial and space applications. They are widely employed for monitoring changes to the polar ice sheets and for the study of planetary bodies (e.g., Mars). The analysis of the very large amount of data produced by such systems requires the development of automatic techniques for an objective, accurate, and fast extraction of relevant information from radargrams. In this paper, we propose a novel technique for the automatic detection of layer boundaries based on a local scale hidden Markov model (HMM), which models the radar response in the presence of a layer boundary, and the Viterbi algorithm (VA, which performs the inference step). The proposed technique is based on a divide and conquer strategy that executes the VA using the observation data and the HMM to infer the most likely layer boundary location within a small radargram portion. Finally, a detection strategy is defined to chain together the inferred local layer locations. Furthermore, a novel radargram enhancement and denoising technique tailored to support the detection step is presented. The effectiveness of the proposed technique has been confirmed by testing it on different radargrams acquired by shallow radar over the north pole of Mars. The results obtained point out the superiority of the proposed method in retrieving the position of each layer boundary (and thus of the related intensity and geometric properties) with respect to the state-of-the-art techniques.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  4. [해외논문]   DEM Estimation for LASAR Based on Variational Model   SCI SCIE

    Jun, Shi (University of Electronic Science and Technology of China, Chengdu, China ) , Zuoyong, Peng (University of Electronic Science and Technology of China, Chengdu, China ) , Congyue, Ren (University of Electronic Science and Technology of China, Chengdu, China) , Ling, Fan , Xiaoling, Zhang
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 978 - 995 , 2017 , 0196-2892 ,

    초록

    This paper discusses the digital elevation model (DEM) estimation problem for the linear array synthetic aperture radar based on the variational model. Compared with the sparse recovery model, the one-to-one mapping between the horizontal grid nodes and the elevations is preserved explicitly, which is important for the topographic surveying and mapping mission. During the research, we find that since the mean square error criterion is insensitive to the amount of the elevation offsets, the numerical method by solving the Euler-Lagrange equation is unreliable and the global optimization method is necessary to solve the variational problem. With the ambiguity function localization and the sliding-window architecture, the global optimal path can be obtained by solving a series of local optimization problems provided that the observation matrix is row full rank. Furthermore, the local optimization problem can be relaxed as a sparse recovery problem and can be solved by a modified orthogonal matching pursuit (OMP) method (named as Var-OMP), whose computational cost is acceptable for the actual data processing. By a series of numerical experiments, we show that the performance of Var-OMP is influenced by both the resolution enhancement factor (L) and the signal-to-noise ratio (SNR). The larger the SNR is, the better the performance is; the smaller L is, the more stable and faster the Var-OMP algorithm is. Compared with the sparse recovery methods, the variational model and the Var-OMP algorithm are more suitable for the DEM estimation application in the face of all kinds of terrains.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  5. [해외논문]   Road Curb Extraction From Mobile LiDAR Point Clouds   SCI SCIE

    Xu, Sheng , Wang, Ruisheng , Zheng, Han
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 996 - 1009 , 2017 , 0196-2892 ,

    초록

    Automatic extraction of road curbs from uneven, unorganized, noisy, and massive 3-D point clouds is a challenging task. Existing methods often project 3-D point clouds onto 2-D planes to extract curbs. However, the projection causes loss of 3-D information, which degrades the performance of the detection. This paper presents a robust, accurate, and efficient method to extract road curbs from 3-D mobile LiDAR point clouds. Our method consists of two steps: 1) extracting candidate points of curbs based on the proposed novel energy function and 2) refining candidate points using the proposed least cost path model. We evaluated the method on a large scale of residential area (16.7 GB, 300 million points) and an urban area (1.07 GB, 20 million points) mobile LiDAR point clouds. Results indicate that the proposed method is superior to the state-of-the-art methods in terms of robustness, accuracy, and efficiency. The proposed curb extraction method achieved a completeness of 78.62% and a correctness of 83.29%. Experiments demonstrate that our method is a promising solution to extract road curbs from mobile LiDAR point clouds.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  6. [해외논문]   An Efficient Undersampled High-Resolution Radon Transform for Exploration Seismic Data Processing   SCI SCIE

    Latif, Arbab , Mousa, Wail A.
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 1010 - 1024 , 2017 , 0196-2892 ,

    초록

    Radon transforms have been widely utilized for exploration seismic data processing. They have been part of the seismic data processing workflow for the last few decades. They are robust, easy to compute, and mathematically well established. This paper suggests a new method for obtaining an undersampled high-resolution Radon transform. The proposed method is based on a nonlinear sampling technique known as compressive sensing, which assumes that seismic data is sparse in a certain domain. The Radon transform domain can be sparse for exploration seismic data. The proposed method was applied for different seismic data processing applications including: 1) attenuation of multiple reflections; 2) first-arrival picking; and 3) seismic denoising. The method was tested on synthetic as well as real seismic data. Additionally, it was compared with existing methods for low- and high-resolution Radon transforms. From the simulation results, it is clear that the proposed method not only reduces the number of measurements needed but also produces high-resolution Radon transforms with less computational time. Therefore, it is believed that the proposed method is an appropriate alternative to some of the existing methods for efficient high-resolution sparse Radon transform computation.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  7. [해외논문]   A Comprehensive Evaluation of Microwave Emissivity and Brightness Temperature Sensitivities to Soil Parameters Using Qualitative and Quantitative Sensitivity Analyses   SCI SCIE

    Ma, Chunfeng (College of Global Change and Earth System Science, Beijing Normal University, Beijing, China) , Li, Xin , Wang, Jing , Wang, Chen , Duan, Qingyun , Wang, Weizhen
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 1025 - 1038 , 2017 , 0196-2892 ,

    초록

    Passive microwave remote sensing has experienced significant success for soil moisture (SM) inversion. However, quantifying the uncertainties caused by soil parameter sensitivities has not attracted sufficient attention. Although local sensitivity analysis (SA) has been used to describe parameter sensitivity in the past, it fails to quantify parameter sensitivities, especially interactions, for nonlinear microwave emission models. This paper presents a comprehensive evaluation that combines physically based emission models and various global SA algorithms to evaluate parameter sensitivity. All the algorithms exhibit highly consistent sensitivity measures, which means a reliable SA result is obtained. The results indicate that the sums of the main sensitivity indices of SM and surface roughness parameters—root-mean-square height (RMSH) and correlation length—are greater than 0.92 and 0.95 for emissivity and brightness temperature (TB), respectively. Furthermore, we find that: 1) the parameter probability distributions have little effect on the sensitivity measures; 2) the SM sensitivity decreases and the RMSH sensitivity increases as the frequency increases and the incidence angle decreases; and 3) the SM is more sensitive on V-polarized than on H-polarized emissivity and TB, while the RMSH is much more sensitive on the polarization index. The presented global SA quantitatively explains the optimal frequency, incidence angle, and polarization for SM inversion and extends the parameter SA for microwave emission models to a more general framework, as well as provides an implication for bare soil emission modeling and SM inversion.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  8. [해외논문]   Severe Thunderstorm Detection by Visual Learning Using Satellite Images   SCI SCIE

    Zhang, Yu (AccuWeather Inc., State College, PA, USA ) , Wistar, Stephen (Department of Statistics, Eberly College of Science, Pennsylvania State University, State College, PA, USA ) , Li, Jia (AccuWeather Inc., State College, PA, USA) , Steinberg, Michael A. , Wang, James Z.
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 1039 - 1052 , 2017 , 0196-2892 ,

    초록

    Computers are widely utilized in today’s weather forecasting as a powerful tool to leverage an enormous amount of data. Yet, despite the availability of such data, current techniques often fall short of producing reliable detailed storm forecasts. Each year severe thunderstorms cause significant damage and loss of life, some of which could be avoided if better forecasts were available. We propose a computer algorithm that analyzes satellite images from historical archives to locate visual signatures of severe thunderstorms for short-term predictions. While computers are involved in weather forecasts to solve numerical models based on sensory data, they are less competent in forecasting based on visual patterns from both current and past satellite images. In our system, we extract and summarize important visual storm evidence from satellite image sequences in the way that meteorologists interpret the images. In particular, the algorithm extracts and fits local cloud motion from image sequences to model the storm-related cloud patches. Image data from the year 2008 have been adopted to train the model, and historical severe thunderstorm reports in continental U.S. from 2000 to 2013 have been used as the ground truth and priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing more accurate severe thunderstorm forecasts.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  9. [해외논문]   On the Accuracy of Topographic Residuals Retrieved by MTInSAR   SCI SCIE

    Du, Yanan , Zhang, Lei , Feng, Guangcai , Lu, Zhong , Sun, Qian
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 1053 - 1065 , 2017 , 0196-2892 ,

    초록

    Topographic residuals in differential interferometric synthetic aperture radar (InSAR) measurements are mainly caused by inaccurate external digital elevation model (DEM). Accurate separation of the phase component contributed by topographic residuals plays an important role in the retrieval of deformation time series from InSAR observations. Even though the residuals can be modeled and estimated in the framework of multitemporal SAR interferometry (MTInSAR), it is not clear what an optimal processing strategy is and how accurate the estimation can reach. We analyze here the factors that affect the accuracy of the retrieved DEM residuals by applying four commonly used MTInSAR methods in a series of simulated scenarios. The results indicate that besides the quality of interferometric observations, the thresholds of spatial and temporal baselines, the diversity of spatial baseline lengths, the connectivity of interferogram network, and improper deformation model also fluctuate the accuracy of the retrieved topographic residuals. According to these affecting factors, this paper sheds light on an optimal approach to reliably retrieve accurate topographic residuals under MTInSAR framework.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  10. [해외논문]   Multitemporal Backscattering Logistic Analysis for Intertidal Bathymetry   SCI SCIE

    Catalao, J. , Nico, G.
    IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society v.55 no.2 ,pp. 1066 - 1073 , 2017 , 0196-2892 ,

    초록

    A new methodology for the mapping of intertidal terrain morphology is presented. It is based on the use of synthetic aperture radar (SAR) images and the temporal correlation between the SAR backscatter intensity and the water level on the intertidal zone. The proposed methodology does not require manual editing, providing a set of geolocated pixels that can be used to generate a digital elevation model of the intertidal zone. The methodology is validated using TerraSAR-X SAR images acquired over Tagus estuary. This methodology can be useful for the regular updating of intertidal bathymetric models useful for both flood hazard mitigation and morphodynamics modeling.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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