# IEEE Geoscience and Remote Sensing Letters

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Displaying Results 1 - 25 of 32
• ### Front Cover

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

Publication Year: 2017, Page(s): C2
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Publication Year: 2017, Page(s):1 - 2
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• ### Remote Sensing Image Registration With Modified SIFT and Enhanced Feature Matching

Publication Year: 2017, Page(s):3 - 7
Cited by:  Papers (18)
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The scale-invariant feature transform algorithm and its many variants are widely used in feature-based remote sensing image registration. However, it may be difficult to find enough correct correspondences for remote image pairs in some cases that exhibit a significant difference in intensity mapping. In this letter, a new gradient definition is introduced to overcome the difference of image inten... View full abstract»

• ### Dielectric Response of Corn Leaves to Water Stress

Publication Year: 2017, Page(s):8 - 12
Cited by:  Papers (5)
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Radar backscatter from a vegetated surface is sensitive to direct backscatter from the canopy and two-way attenuation of the signal as it travels through the canopy. Both mechanisms are affected by the dielectric properties of the individual elements of the canopy, which are primarily a function of water content. Leaf water content of corn can change considerably during the day and in response to ... View full abstract»

• ### RFI Mitigation in Aperture Synthesis Radiometers Using a Modified CLEAN Algorithm

Publication Year: 2017, Page(s):13 - 17
Cited by:  Papers (1)
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For aperture synthesis radiometers, sparse samplings on the $u$ -$v$ frequency plane cause undesirable sidelobes in the synthesized beam. Through these sidelobes, artificial sources emitting in the protected 1400-1427 MHz band contaminate the retrievals of the soil moisture and ocean salinity (SMOS) from MIRAS measurements. One effective way to correct the artificial interferences is to create a s... View full abstract»

• ### Multiple-Reflection Noise Attenuation Using Adaptive Randomized-Order Empirical Mode Decomposition

Publication Year: 2017, Page(s):18 - 22
Cited by:  Papers (22)
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We propose a novel approach for removing noise from multiple reflections based on an adaptive randomized-order empirical mode decomposition (EMD) framework. We first flatten the primary reflections in common midpoint gather using the automatically picked normal moveout velocities that correspond to the primary reflections and then randomly permutate all the traces. Next, we remove the spatially di... View full abstract»

• ### Region-of-Interest Coding Based on Saliency Detection and Directional Wavelet for Remote Sensing Images

Publication Year: 2017, Page(s):23 - 27
Cited by:  Papers (13)
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With growing contradiction between the high-speed acquisition of remote sensing data and the low-speed data storage and transmission, the advantages of giving higher priority to a region of interest (ROI) in compression have become prominent. Previous research focused on ROI coding, rather than automatic ROI extraction. However, accurate ROI extraction can significantly improve coding efficiency. ... View full abstract»

• ### Semiautomatic Registration of Terrestrial Laser Scanning Data Using Perspective Intensity Images

Publication Year: 2017, Page(s):28 - 32
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Point cloud registration is an important procedure for terrestrial laser scanning data processing. Artificial targets are usually used in practice to guarantee a robust registration. However, installing and locating targets are labor-intensive for large surveying and mapping project. A methodology for semiautomatic registration of terrestrial point clouds using perspective intensity images is pres... View full abstract»

• ### Exponential Discriminative Locality Alignment for Hyperspectral Image Classification

Publication Year: 2017, Page(s):33 - 37
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Metric learning algorithms have been widely applied for hyperspectral image (HSI) dimensionality reduction and classification. One of the metric learning algorithms proposed recently is discriminative locality alignment (DLA). The DLA attacks the distribution nonlinearity of samples, and preserves the discriminative ability. However, the DLA needs to manually adjust a parameter called scaling fact... View full abstract»

• ### Drone Classification Using Convolutional Neural Networks With Merged Doppler Images

Publication Year: 2017, Page(s):38 - 42
Cited by:  Papers (20)
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We propose a drone classification method based on convolutional neural network (CNN) and micro-Doppler signature (MDS). The MDS only presents Doppler information in time domain. The frequency domain representation of MDS is called as cadence-velocity diagram (CVD). To analyze the Doppler information of drone in time and frequency domain, we propose a new image by merging MDS and CVD, as merged Dop... View full abstract»

• ### A New Sparse Subspace Clustering Algorithm for Hyperspectral Remote Sensing Imagery

Publication Year: 2017, Page(s):43 - 47
Cited by:  Papers (11)
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Robust techniques such as sparse subspace clustering (SSC) have been recently developed for hyperspectral images (HSIs) based on the assumption that pixels belonging to the same land-cover class approximately lie in the same subspace. In order to account for the spatial information contained in HSIs, SSC models incorporating spatial information have become very popular. However, such models are of... View full abstract»

• ### Distortion Magnetic Field Compensation of Geomagnetic Vector Measurement System Using a 3-D Helmholtz Coil

Publication Year: 2017, Page(s):48 - 51
Cited by:  Papers (3)
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The magnetic interferential fields, such as soft-iron and hard-iron interferences, will seriously affect the accuracy of geomagnetic vector measurement system, and thus should be compensated. In this letter, a new compensation method using a 3-D Helmholtz coil is proposed. As a first step, the geomagnetic vector measurement system is exposed to different directions and the magnitudes of magnetic f... View full abstract»

• ### Rough-Set-Based Color Channel Selection

Publication Year: 2017, Page(s):52 - 56
Cited by:  Papers (5)
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Color channel selection is essential for accurate segmentation of sky and clouds in images obtained from ground-based sky cameras. Most prior works in cloud segmentation use threshold-based methods on color channels selected in an ad hoc manner. In this letter, we propose the use of rough sets for color channel selection in visible-light images. Our proposed approach assesses color channels with r... View full abstract»

• ### Errors-in-Variables Anisotropic Extended Orthogonal Procrustes Analysis

Publication Year: 2017, Page(s):57 - 61
Cited by:  Papers (1)
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This letter presents a novel total least squares (TLS) solution of the anisotropic row-scaling Procrustes problem. The ordinary LS Procrustes approach finds the transformation parameters between origin and destination sets of observations minimizing errors affecting only the destination one. In this letter, we introduce the errors-in-variables model in the anisotropic Procrustes analysis problem a... View full abstract»

• ### An Efficient Approach for Filling Gaps in Landsat 7 Satellite Images

Publication Year: 2017, Page(s):62 - 66
Cited by:  Papers (4)
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Landsat 7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery presents an important data source for many applications related to remote sensing. However, the scan line corrector (SLC) failure has seriously limited the scientific applications of ETM+ data since SLC failed permanently on May 31, 2003, resulting in about 22% of the image data missing in each scene. In this letter, we propose to ap... View full abstract»

• ### An Improved Azimuth Reconstruction Method for Multichannel SAR Using Vandermonde Matrix

Publication Year: 2017, Page(s):67 - 71
Cited by:  Papers (1)
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To overcome the contradiction between wide swath and high resolution in synthetic aperture radar systems, a multichannel azimuth reconstruction method is investigated to unambiguously recover the Doppler spectrum. The proposed method is derived from the least squares principle by exploiting a Vandermonde component of the system matrix. The Vandermonde matrix is Doppler independent and data indepen... View full abstract»

• ### The Assessment of Ground-Based Weather Radar Data by Comparison With TRMM PR

Publication Year: 2017, Page(s):72 - 76
Cited by:  Papers (4)
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The Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission satellite has already provided reliable observations for more than 15 years. There is a potential possibility to assess long-term data of ground-based radar (GR) in the China new generation weather radar network through comparison between PR and GR. In this letter, stratiform precipitation above and below bright bands is used ... View full abstract»

• ### Interpreting Temporal Changes of Atmospheric CO2Over Fire Affected Regions Based on GOSAT Observations

Publication Year: 2017, Page(s):77 - 81
Cited by:  Papers (2)
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The carbon dioxide (CO2) emissions released from biomass burning significantly affect the temporal variations of atmospheric CO2concentrations. Based on a longterm (July 2009-June 2015) retrieved data sets by the greenhouse gases observing satellite (GOSAT), the seasonal cycle and interannual variations of column-averaged volume mixing ratios of atmospheric carbon dioxide (XC... View full abstract»

• ### Supervised Feature Extraction of Hyperspectral Images Using Partitioned Maximum Margin Criterion

Publication Year: 2017, Page(s):82 - 86
Cited by:  Papers (2)
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Dimensionality reduction is an important task where the aim is to reduce the number of features and make the system less time consuming for classification. Here, the drawbacks of Fisher's linear-discriminant-analysis-based feature extraction (FE) methods are addressed and a proposal is made to overcome it as well as to reduce the Hughes phenomenon and computational complexity of the system. The pr... View full abstract»

• ### Block Kriging With Measurement Errors: A Case Study of the Spatial Prediction of Soil Moisture in the Middle Reaches of Heihe River Basin

Publication Year: 2017, Page(s):87 - 91
Cited by:  Papers (1)
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Block kriging (BK) is a common method of predicting the true value at the pixel scale when validating remote sensing retrieval products. However, measurement errors (MEs) increase the prediction uncertainty. In this letter, an extended interpolation technique - BK with MEs (BKMEs) - is developed. The properties of BKME are proven through derivation and demonstrated in a case study of soil moisture... View full abstract»

• ### Extension of the QuikSCAT Sea Ice Extent Data Set With OSCAT Data

Publication Year: 2017, Page(s):92 - 96
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The Ku-band Oceansat-2 Scatterometer (OSCAT) is very similar to the Quick Scatterometer (QuikSCAT), which operated from 1999 to 2009. OSCAT continues the Ku-band scatterometer data record through 2014 with an overlap of 19 days with QuikSCAT's mission in 2009. This letter discusses a particular climate application of the time series for sea ice extent observation. In this letter, a QuikSCAT sea ic... View full abstract»

• ### Deep Learning With Grouped Features for Spatial Spectral Classification of Hyperspectral Images

Publication Year: 2017, Page(s):97 - 101
Cited by:  Papers (9)
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This letter presents a novel deep learning algorithm for feature extraction from the hyperspectral images. The proposed method takes advantage of the knowledge that the features of the spatial-spectral data naturally fall into an array of groups with respect to different spectral bands. Aiming to reduce the influence of redundant spectral bands adaptively using unlabeled hyperspectral data, we inc... View full abstract»

• ### Accurate Reconstruction and Suppression for Azimuth Ambiguities in Spaceborne Stripmap SAR Images

Publication Year: 2017, Page(s):102 - 106
Cited by:  Papers (2)
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In this letter, an accurate mathematical model for azimuth ambiguity in stripmap synthetic aperture radar (SAR) images is first constructed, with an azimuth ambiguity factor (AAF) defined as the residual amplitude and phase terms of ambiguities. Next, a novel framework for reconstructing and suppressing azimuth ambiguity is proposed based on the analysis of the AAF. In this framework, azimuth ambi... View full abstract»

• ### Downscaling of Land Surface Temperature Using Airborne High-Resolution Data: A Case Study on Aprilia, Italy

Publication Year: 2017, Page(s):107 - 111
Cited by:  Papers (2)
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A regression-based downscaling of land surface temperature was developed over the heterogeneous urban area of Aprilia, Central Italy, using high resolution (HR) airborne data. Airborne sensors provided thermal and visible-near infrared (VNIR) measurements at 2-m pixel size. Coarse resolution images at 40, 30, and 20 m, upscaled by aggregation from the native airborne data, were sharpened to the fi... View full abstract»

## Aims & Scope

IEEE Geoscience and Remote Sensing Letters (GRSL) is a monthly publication for short papers (maximum length 5 pages) addressing new ideas and formative concepts in remote sensing as well as important new and timely results and concepts.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Alejandro C. Frery