# IEEE Transactions on Geoscience and Remote Sensing

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Displaying Results 1 - 25 of 52
• ### Front Cover

Publication Year: 2017, Page(s): C1
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• ### IEEE Transactions on Geoscience and Remote Sensing publication information

Publication Year: 2017, Page(s): C2
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Publication Year: 2017, Page(s):4837 - 5424
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• ### Facet Segmentation-Based Line Segment Extraction for Large-Scale Point Clouds

Publication Year: 2017, Page(s):4839 - 4854
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As one of the most common features in the man-made environments, straight lines play an important role in many applications. In this paper, we present a new framework to extract line segments from large-scale point clouds. The proposed method is fast to produce results, easy for implementation and understanding, and suitable for various point cloud data. The key idea is to segment the input point ... View full abstract»

• ### A Novel GNSS Technique for Predicting Boreal Forest Attributes at Low Cost

Publication Year: 2017, Page(s):4855 - 4867
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One of the biggest challenges in forestry research is the effective and accurate measuring and monitoring of forest variables, as the exploitation potential of forest inventory products largely depends on the accuracy of estimates and on the cost of data collection. This paper presented a novel computational method of low-cost forest inventory using global navigation satellite system (GNSS) signal... View full abstract»

• ### Critical Analysis of Model-Based Incoherent Polarimetric Decomposition Methods and Investigation of Deorientation Effect

Publication Year: 2017, Page(s):4868 - 4877
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This paper critically analyzes several incoherent model-based decomposition methods for assessing the effect of deorientation in characterization of various land covers. It has been found that even after performing decomposition, ambiguity still occurs in scattering response from various land covers, such as urban and vegetation. Researchers introduced the concept of deorientation to remove this a... View full abstract»

• ### Commercial Off-the-Shelf Digital Cameras on Unmanned Aerial Vehicles for Multitemporal Monitoring of Vegetation Reflectance and NDVI

Publication Year: 2017, Page(s):4878 - 4886
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This paper demonstrates the ability to generate quantitative remote sensing products by means of an unmanned aerial vehicle (UAV) equipped with one unaltered and one near infrared-modified commercial off-the-shelf (COTS) camera. Radiometrically calibrated orthomosaics were generated for 17 dates, from which digital numbers were corrected to surface reflectance and to normalized difference vegetati... View full abstract»

• ### Band Subset Selection for Anomaly Detection in Hyperspectral Imagery

Publication Year: 2017, Page(s):4887 - 4898
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This paper presents a new approach, called band subset selection (BSS)-based hyperspectral anomaly detection (AD), which selects multiple bands simultaneously as a band subset rather than selecting multiple bands one at a time as the tradition band selection (BS) does, referred to as sequential multiple BS (SQMBS). Its idea is to first use virtual dimensionality (VD) to determine the number of mul... View full abstract»

• ### Soil Moisture Estimation by SAR in Alpine Fields Using Gaussian Process Regressor Trained by Model Simulations

Publication Year: 2017, Page(s):4899 - 4912
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In this paper, we address the problem of retrieving soil moisture over a grassland alpine area from Synthetic Aperture Radar (SAR) data using a statistical algorithm trained by simulations of a physical model. A time series of C-band VV-polarized Wide Swath images acquired by Envisat Advanced SAR (ASAR) in the snow-free periods of 2010 and 2011 was simulated using a discrete radiative transfer mod... View full abstract»

• ### A Novel Bayesian Spatial–Temporal Random Field Model Applied to Cloud Detection From Remotely Sensed Imagery

Publication Year: 2017, Page(s):4913 - 4924
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With the fast advancement of remote sensing platforms and sensors, remotely sensed imagery (RSI) is increasingly being characterized by both high spatial resolution and high temporal resolution. How to efficiently use the rich spatial and temporal information in RSI for highly accurate object detection and classification is an important research question. Nevertheless, there is still a lack of a p... View full abstract»

• ### A Stepwise Analytical Projected Gradient Descent Search for Hyperspectral Unmixing and Its Code Vectorization

Publication Year: 2017, Page(s):4925 - 4943
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We present, in this paper, a new methodology for spectral unmixing, where a vector of fractions, corresponding to a set of endmembers (EMs), is estimated for each pixel in the image. The process first provides an initial estimate of the fraction vector, followed by an iterative procedure that converges to an optimal solution. Specifically, projected gradient descent (PGD) optimization is applied t... View full abstract»

• ### Correntropy Maximization via ADMM: Application to Robust Hyperspectral Unmixing

Publication Year: 2017, Page(s):4944 - 4955
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In hyperspectral images, some spectral bands suffer from low signal-to-noise ratio due to noisy acquisition and atmospheric effects, thus requiring robust techniques for the unmixing problem. This paper presents a robust supervised spectral unmixing approach for hyperspectral images. The robustness is achieved by writing the unmixing problem as the maximization of the correntropy criterion subject... View full abstract»

• ### An Effective Fuzzy Feature Selection and Prediction Method for Modeling Tidal Current: A Case of Persian Gulf

Publication Year: 2017, Page(s):4956 - 4961
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This paper develops a new two-stage approach for accurate modeling and prediction of tidal current. The proposed method makes use of a novel fuzzy feature selection to extract the most preferable features from the tidal current speed and direction data set. The selected features are further used to train a support vector regression for accurate prediction. The setting parameters of the proposed mo... View full abstract»

• ### Recurrent Neural Networks to Correct Satellite Image Classification Maps

Publication Year: 2017, Page(s):4962 - 4971
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While initially devised for image categorization, convolutional neural networks (CNNs) are being increasingly used for the pixelwise semantic labeling of images. However, the proper nature of the most common CNN architectures makes them good at recognizing but poor at localizing objects precisely. This problem is magnified in the context of aerial and satellite image labeling, where a spatially fi... View full abstract»

• ### A Theoretical Study of Velocity SAR Imaging of a Moving, Nonstationary Scene

Publication Year: 2017, Page(s):4972 - 4988
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The concept of the “velocity synthetic aperture radar” (VSAR)-a multiaperture sensor capable of measuring radial velocities in the scene and utilizing this information to correct motion-induced imaging distortions inherent to SAR-was proposed two decades ago. Lately, with the emergence of truly multichannel systems featuring antenna arrays with dozens of elements, the approach has be... View full abstract»

• ### Sea Ice Detection Using U.K. TDS-1 GNSS-R Data

Publication Year: 2017, Page(s):4989 - 5001
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A sea ice detection algorithm developed using the U.K. TechDemoSat-1 (U.K. TDS-1) global navigation satellite systems (GNSSs)-reflectometry data over the Arctic and Antarctic regions is presented. It is based on measuring the similarity of the received GNSS reflected waveform or delay Doppler map (DDM) to the coherent reflection model waveform. Over the open ocean, the scattered signal has a diffu... View full abstract»

• ### Using Landsat Surface Reflectance Data as a Reference Target for Multiswath Hyperspectral Data Collected Over Mixed Agricultural Rangeland Areas

Publication Year: 2017, Page(s):5002 - 5014
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Low-cost flight-based hyperspectral imaging systems have the potential to provide important information for ecosystem and environmental studies as well as aide in land management. To realize this potential, methods must be developed to provide large-area surface reflectance data allowing for temporal data sets at the mesoscale. This paper describes a bootstrap method of producing a large-area, rad... View full abstract»

• ### The Influence of Different Spatial Resolutions on the Retrieval Accuracy of Sea Surface Wind Speed With C-2PO Models Using Full Polarization C-Band SAR

Publication Year: 2017, Page(s):5015 - 5025
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This paper presents a comparison strategy for investigating the influence of spatial resolutions on sea surface wind speed retrieval accuracy with cross-polarized synthetic aperture radar images. First, for wind speeds retrieved from vertical transmitting-vertical receiving (VV)-polarized images, the optimal geophysical C-band model (CMOD) function was selected among four CMOD functions. Second, t... View full abstract»

• ### Polarimetric SAR Image Factorization

Publication Year: 2017, Page(s):5026 - 5041
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This paper reformulates the problem of polarimetric incoherent target decomposition as a general image factorization which aims to simultaneously estimate a dictionary of meaningful atom scatterers and their corresponding spatial distribution maps. Both model-based and eigenanalysis-based decompositions can be seen as special cases of image factorization under specific constraints. The inverse pro... View full abstract»

• ### The Application of PCRTM Physical Retrieval Methodology for IASI Cloudy Scene Analysis

Publication Year: 2017, Page(s):5042 - 5056
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This paper applies a physical inversion approach to retrieve geophysical properties from the single instrumental field-of-view (FOV) spectral radiances measured by the Infrared Atmospheric Sounding Interferometer (IASI) under all-sky conditions. We demonstrate the use of a principal-component-based radiative transfer model (PCRTM) and a physical inversion methodology to simultaneously retrieve clo... View full abstract»

• ### A Novel Adaptive Fuzzy Local Information $C$ -Means Clustering Algorithm for Remotely Sensed Imagery Classification

Publication Year: 2017, Page(s):5057 - 5068
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This paper presents a novel adaptive fuzzy local information c-means (ADFLICM) clustering approach for remotely sensed imagery classification by incorporating the local spatial and gray level information constraints. The ADFLICM approach can enhance the conventional fuzzy c-means algorithm by producing homogeneous segmentation and reducing the edge blurring artifact simultaneously. The major contr... View full abstract»

• ### Soil Moisture Estimation Using Differential Radar Interferometry: Toward Separating Soil Moisture and Displacements

Publication Year: 2017, Page(s):5069 - 5083
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Differential interferometric synthetic aperture radar (DInSAR) measurements are sensitive to displacements, but also to soil moisture mν changes. Here, we analyze whether soil moisture can be estimated from three DInSAR observables without making any assumptions about its complex spatio-temporal dynamics, with the goal of removing its contribution from the displacement estimates.... View full abstract»

• ### An Automatic Algorithm to Retrieve Wave Height From X-Band Marine Radar Image Sequence

Publication Year: 2017, Page(s):5084 - 5092
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A new method is proposed to retrieve wave height from an X-band marine radar image sequence, without external measurements for reference. The X-band marine radar image sequence is first decomposed by empirical orthogonal function (EOF), and then the sea surface height profile is reconstructed and scaled from the first EOF mode. The radial profiles that are close to the peak wave direction are used... View full abstract»

• ### A Subpixel Target Detection Approach to Hyperspectral Image Classification

Publication Year: 2017, Page(s):5093 - 5114
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Hyperspectral image classification faces various levels of difficulty due to the use of different types of hyperspectral image data. Recently, spectral-spatial approaches have been developed by jointly taking care of spectral and spatial information. This paper presents a completely different approach from a subpixel target detection view point. It implements four stage processes, a preprocessing ... View full abstract»

• ### Automatic Ice Surface and Bottom Boundaries Estimation in Radar Imagery Based on Level-Set Approach

Publication Year: 2017, Page(s):5115 - 5122
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Accelerated loss of ice from Greenland and Antarctica has been observed in recent decades. The melting of polar ice sheets and mountain glaciers has considerable influence on sea level rise in a changing climate. Ice thickness is a key factor in making predictions about the future of massive ice reservoirs. The ice thickness can be estimated by calculating the exact location of the ice surface and... View full abstract»

## Aims & Scope

IEEE Transactions on Geoscience and Remote Sensing (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.

Full Aims & Scope

Editor-in-Chief
Antonio J. Plaza