# IEEE Geoscience and Remote Sensing Letters

## Issue 2 • Feb. 2018

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## Filter Results

Displaying Results 1 - 25 of 36

Publication Year: 2018, Page(s): C1
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• ### IEEE Geoscience and Remote Sensing Letters publication information

Publication Year: 2018, Page(s): C2
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Publication Year: 2018, Page(s):161 - 162
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• ### Atmospheric Humidity Sounding Using Differential Absorption Radar Near 183 GHz

Publication Year: 2018, Page(s):163 - 167
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A tunable G-band frequency-modulated continuous-wave radar system has been developed and used to perform differential absorption atmospheric humidity measurements for the first time. The radar's transmitter uses high- power-handling GaAs Schottky diodes to generate between 15-23 dBm over a 10-GHz bandwidth near 183 GHz. By virtue of a high-isolation circular polarization duplexer, the monostatic r... View full abstract»

• ### Object Tracking in Satellite Videos by Fusing the Kernel Correlation Filter and the Three-Frame-Difference Algorithm

Publication Year: 2018, Page(s):168 - 172
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Object tracking is a popular topic in the field of computer vision. The detailed spatial information provided by a very high resolution remote sensing sensor makes it possible to track targets of interest in satellite videos. In recent years, correlation filters have yielded promising results. However, in terms of dealing with object tracking in satellite videos, the kernel correlation filter (KCF... View full abstract»

• ### Semantic Segmentation of Aerial Images With Shuffling Convolutional Neural Networks

Publication Year: 2018, Page(s):173 - 177
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Semantic segmentation of aerial images refers to assigning one land cover category to each pixel. This is a challenging task due to the great differences in the appearances of ground objects. Many attempts have been made during the past decades. In recent years, convolutional neural networks (CNNs) have been introduced in the remote sensing field, and various solutions have been proposed to realiz... View full abstract»

• ### Improving TMPA 3B43 V7 Data Sets Using Land-Surface Characteristics and Ground Observations on the Qinghai–Tibet Plateau

Publication Year: 2018, Page(s):178 - 182
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The accurate knowledge of precipitation information over the Qinghai-Tibet Plateau, where the rain gauge networks are limited, is vital for various applications. While satellite-based precipitation estimates provide high spatial resolution (0.25°), large uncertainties and systematic anomalies still exist over this critical area. To derive more accurate monthly precipitation estimates, a spa... View full abstract»

• ### Scene Classification Based on Two-Stage Deep Feature Fusion

Publication Year: 2018, Page(s):183 - 186
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In convolutional neural networks (CNNs), higher layer information is more abstract and more task specific, so people usually concern themselves with fully connected (FC) layer features, believing that lower layer features are less discriminative. However, a few researchers showed that the lower layers also provide very rich and powerful information for image representation. In view of these study ... View full abstract»

• ### Spectral Unmixing With Multiple Dictionaries

Publication Year: 2018, Page(s):187 - 191
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Spectral unmixing aims at recovering the spectral signatures of materials, called endmembers, mixed in a hyperspectral image (HSI) or multispectral image, along with their abundances. A typical assumption is that the image contains one pure pixel per endmember, in which case spectral unmixing reduces to identifying these pixels. Many fully automated methods have been proposed in recent years, but ... View full abstract»

• ### Development and Assessment of a Data Set Containing Frame Images and Dense Airborne Laser Scanning Point Clouds

Publication Year: 2018, Page(s):192 - 196
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This letter describes the main features of a data set that contains aerial images acquired with a medium format digital camera and point clouds collected using an airborne laser scanning unit, as well as ground control points and direct georeferencing data. The flights were performed in 2014 over an urban area in Presidente Prudente, São Paulo, Brazil, using different flight heights. These... View full abstract»

• ### One-Dimensional Mirrored Aperture Synthesis With Rotating Reflector

Publication Year: 2018, Page(s):197 - 201
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In this letter, 1-D mirrored aperture synthesis with a rotating reflector (1-D MAS-R) is proposed to improve the spatial resolution and reduce the number of required antennas for passive microwave remote sensing. The principle of the 1-D MAS-R with an antenna array is given, and from the principle, the 1-D MAS-R with only one antenna can also reconstruct the image of the scene. Simulation results ... View full abstract»

• ### Mapping the Spatiotemporal Dynamics of Europe’s Land Surface Temperatures

Publication Year: 2018, Page(s):202 - 206
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The land surface temperature (LST) drives many terrestrial biophysical processes and varies rapidly in space and time primarily due to the earth's diurnal and annual cycles. Models of the diurnal and annual LST cycle retrieved from satellite data can be reduced to several gap-free parameters that represent the surface's thermal characteristics and provide a generalized characterization of the LST ... View full abstract»

• ### A CFCC-LSTM Model for Sea Surface Temperature Prediction

Publication Year: 2018, Page(s):207 - 211
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Sea surface temperature (SST) prediction is not only theoretically important but also has a number of practical applications across a variety of ocean-related fields. Although a large amount of SST data obtained via remote sensor are available, previous work rarely attempted to predict future SST values from history data in spatiotemporal perspective. This letter regards SST prediction as a sequen... View full abstract»

• ### Semisupervised Hyperspectral Image Classification Based on Generative Adversarial Networks

Publication Year: 2018, Page(s):212 - 216
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Because the collection of ground-truth labels is difficult, expensive, and time-consuming, classifying hyperspectral images (HSIs) with few training samples is a challenging problem. In this letter, we propose a novel semisupervised algorithm for the classification of hyperspectral data by training a customized generative adversarial network (GAN) for hyperspectral data. The GAN constructs an adve... View full abstract»

• ### Moving Point Target Detection Based on Higher Order Statistics in Very Low SNR

Publication Year: 2018, Page(s):217 - 221
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This letter presents an approach for the detection of moving point targets on high-frame-rate image sequences with low spatial resolution and low SNR based on higher order statistical theory. We propose a novel method for analyzing the time-domain evolution of image data for distinguishing between the background and the target in situations when the spatial signal of the target is swamped by noise... View full abstract»

• ### Noise Performance Comparison Between Continuous Wave and Stroboscopic Pulse Ground Penetrating Radar

Publication Year: 2018, Page(s):222 - 226
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Although stroboscopic pulse (SP) ground penetrating radar (GPR) is the most popular and widespread equipment for subsoil investigation, continuous-wave (CW) radar has better performance in terms of noise, system dynamic range, and penetration depth, at the expense of greater complexity and cost of the components. The aim of this letter is a direct comparison between SP GPR and CW GPR through an ex... View full abstract»

• ### Micro-Doppler Mini-UAV Classification Using Empirical-Mode Decomposition Features

Publication Year: 2018, Page(s):227 - 231
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In this letter, we propose an empirical-mode decomposition (EMD)-based method for automatic multicategory mini-unmanned aerial vehicle (UAV) classification. The radar echo signal is first decomposed into a set of oscillating waveforms by EMD. Then, eight statistical and geometrical features are extracted from the oscillating waveforms to capture the phenomenon of blade flashes. After feature norma... View full abstract»

• ### Remote Sensing Image Registration Using Convolutional Neural Network Features

Publication Year: 2018, Page(s):232 - 236
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Successful remote sensing image registration is an important step for many remote sensing applications. The scale-invariant feature transform (SIFT) is a well-known method for remote sensing image registration, with many variants of SIFT proposed. However, it only uses local low-level information, and loses much middle- or high-level information to register. Image features extracted by a convoluti... View full abstract»

• ### Quantification of the Relationship Between Sea Surface Roughness and the Size of the Glistening Zone for GNSS-R

Publication Year: 2018, Page(s):237 - 241
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A formulation of the relationship between sea-surface roughness and extension of the glistening zone (GZ) of a Global Navigation Satellite System Reflectometry (GNSS-R) system is presented. First, an analytical expression of the link between GZ area, viewing geometry, and surface mean square slope (MSS) is derived. Then, a strategy for retrieval of surface roughness from the delay-Doppler map (DDM... View full abstract»

• ### PSOSAC: Particle Swarm Optimization Sample Consensus Algorithm for Remote Sensing Image Registration

Publication Year: 2018, Page(s):242 - 246
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Image registration is an important preprocessing step for many remote sensing image processing applications, and its result will affect the performance of the follow-up procedures. Establishing reliable matches is a key issue in point matching-based image registration. Due to the significant intensity mapping difference between remote sensing images, it may be difficult to find enough correct matc... View full abstract»

• ### Localization of Multiple Underwater Objects With Gravity Field and Gravity Gradient Tensor

Publication Year: 2018, Page(s):247 - 251
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We present a novel algorithm to locate multiple underwater objects in real time using gravity field vector and gravity gradient tensor signals. This algorithm formulates the task of localization of multiple underwater objects into a regularized nonlinear problem, which is solved with the standard Levenberg–Marquardt algorithm. The regularization parameters are estimated by cross validation.... View full abstract»

• ### Optimal and Suboptimal Velocity Estimators for ArcSAR With Distributed Target

Publication Year: 2018, Page(s):252 - 256
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Two new methods of radial velocity estimation for distributed targets in arc-scanning synthetic aperture radar (ArcSAR) systems, namely, the maximum-likelihood estimator (MLE) and the suboptimal method based on the least squares estimation (LSE), are proposed, derived, and analyzed. To this end, we establish that $n$ scattere... View full abstract»

• ### DropBand: A Simple and Effective Method for Promoting the Scene Classification Accuracy of Convolutional Neural Networks for VHR Remote Sensing Imagery

Publication Year: 2018, Page(s):257 - 261
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The dropout and data augmentation techniques are widely used to prevent a convolutional neural network (CNN) from overfitting. However, the dropout technique does not work well when applied to the input channels of neural networks, and data augmentation is usually employed along the image plane. In this letter, we present DropBand, which is a simple and effective method of promoting the classifica... View full abstract»

• ### Integration of Contextual Knowledge in Unsupervised Subpixel Classification: Semivariogram and Pixel-Affinity Based Approaches

Publication Year: 2018, Page(s):262 - 266
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This letter investigates the use of coarse-image features for predicting class labels at a given finer spatial scale. In this regard, two unsupervised subpixel mapping approaches, a semivariogram method, and a pixel-affinity based method are proposed. Furthermore, segmentation-based spectral unmixing is explored so as to address the spectral variability and nonconvexity of classes. In addition, th... View full abstract»

• ### Spectral Clustering of Straight-Line Segments for Roof Plane Extraction From Airborne LiDAR Point Clouds

Publication Year: 2018, Page(s):267 - 271
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This letter presents a novel approach to automated extraction of roof planes from airborne light detection and ranging data based on spectral clustering of straight-line segments. The straight-line segments are derived from laser scan lines, and 3-D line geometry analysis is employed to identify coplanar line segments so as to avoid skew lines in plane estimation. Spectral analysis reveals the spe... 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