# IEEE Transactions on Geoscience and Remote Sensing

## Issue 1 • Jan. 2019

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## Filter Results

Displaying Results 1 - 25 of 53
• ### [Front cover]

Publication Year: 2019, Page(s): C1
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• ### IEEE Transactions on Geoscience and Remote Sensing publication information

Publication Year: 2019, Page(s): C2
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Publication Year: 2019, Page(s):1 - 624
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• ### GETNET: A General End-to-End 2-D CNN Framework for Hyperspectral Image Change Detection

Publication Year: 2019, Page(s):3 - 13
Cited by:  Papers (8)
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Change detection (CD) is an important application of remote sensing, which provides timely change information about large-scale Earth surface. With the emergence of hyperspectral imagery, CD technology has been greatly promoted, as hyperspectral data with high spectral resolution are capable of detecting finer changes than using the traditional multispectral imagery. Nevertheless, the high dimensi... View full abstract»

• ### Class Signature-Constrained Background- Suppressed Approach to Band Selection for Classification of Hyperspectral Images

Publication Year: 2019, Page(s):14 - 31
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In hyperspectral image classification (HSIC), background (BKG) is generally excluded from consideration due to the fact that obtaining complete knowledge of BKG is nearly impossible in reality. Unfortunately, BKG has significant impact on classification and band selection (BS). This paper investigates both issues and presents a novel approach called class signature-constrained BKG suppression (CSC... View full abstract»

• ### Earth’s Energy Imbalance Measured From Space

Publication Year: 2019, Page(s):32 - 45
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The direct measurement of earth’s energy imbalance (EEI) is one of the greatest challenges in climate research. The global mean EEI represents the integrated value of global warming and is tightly linked to changes in hydrological cycle and the habitability of our planet. Current space-born radiometers measure the individual radiative components of the energy balance with unprecedented stability, ... View full abstract»

• ### Tensorized Principal Component Alignment: A Unified Framework for Multimodal High-Resolution Images Classification

Publication Year: 2019, Page(s):46 - 61
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High-resolution (HR) remote sensing (RS) imaging opens the door to very accurate geometrical analysis for objects. However, it is difficult to simultaneous use massive HR RS images in practical applications, because these HR images are often collected in different multimodal conditions (multisource, multiarea, multitemporal, multiresolution, and multiangular) and learning method trained for one si... View full abstract»

• ### DeepDetect: A Cascaded Region-Based Densely Connected Network for Seismic Event Detection

Publication Year: 2019, Page(s):62 - 75
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Automatic event detection from time series signals has broad applications. Traditional detection methods detect events primarily by the use of similarity and correlation in data. Those methods can be inefficient and yield low accuracy. In recent years, machine learning techniques have revolutionized many sciences and engineering domains. In particular, the performance of object detection in a 2-D ... View full abstract»

• ### A Growth-Model-Driven Technique for Tree Stem Diameter Estimation by Using Airborne LiDAR Data

Publication Year: 2019, Page(s):76 - 92
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Diameter at breast height (DBH) is one of the most important tree parameter for forest inventory. In this paper, we present a novel method for the adaptive and the accurate DBH estimation of trees characterized by small and large stems. The method automatically discriminates among different tree growth models by means of a data-driven technique based on a clustering procedure. First, the method de... View full abstract»

• ### Full-Wave Removal of Internal Antenna Effects and Antenna–Medium Interactions for Improved Ground-Penetrating Radar Imaging

Publication Year: 2019, Page(s):93 - 103
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Antenna effects alter the detection of buried objects during ground-penetrating radar (GPR) surveys. In this paper, we propose a novel approach based on full-wave inversion to filter out antenna effects from GPR data. The approach, which is exact for locally planar layered media, resorts to a recently developed electromagnetic model that takes advantage of an intrinsic, closed-form solution of Max... View full abstract»

• ### A Robust Framework for Covariance Classification in Heterogeneous Polarimetric SAR Images and Its Application to L-Band Data

Publication Year: 2019, Page(s):104 - 119
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In this paper, an automatic classification approach for polarimetric covariance structure is derived and assessed. It extends the framework of Pallotta et al. “Detecting Covariance Symmetries in Polarimetric SAR Images” to the heterogeneous environment, where the pixels of the polarimetric image share the same covariance structure but different power levels. The Principle of Invar... View full abstract»

• ### Fast Modeling and Practical Inversion of Laterolog-Type Downhole Resistivity Measurements

Publication Year: 2019, Page(s):120 - 127
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In this paper, we present a fast modeling and practical inversion scheme for the laterolog-type measurements that includes dual-laterolog and array laterolog methods. A modified domain decomposition finite-element method (DDFEM) is proposed to implement the fast modeling of the laterolog-type measurements in 2-D cylindrical coordinates. This method enables the simulation of the tool’s responses at... View full abstract»

• ### A Nonlinear Regression Application via Machine Learning Techniques for Geomagnetic Data Reconstruction Processing

Publication Year: 2019, Page(s):128 - 140
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The integrity of geomagnetic data is a critical factor in understanding the evolutionary process of Earth’s magnetic field, as it provides useful information for near-surface exploration, unexploded explosive ordnance detection, and so on. Aimed to reconstruct undersampled geomagnetic data, this paper presents a geomagnetic data reconstruction approach based on machine learning techniques. The tra... View full abstract»

• ### Variational Learning of Mixture Wishart Model for PolSAR Image Classification

Publication Year: 2019, Page(s):141 - 154
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The phase difference, amplitude product, and amplitude ratio between two polarizations are important discriminators for terrain classification, which derives a significant statistical-distribution-based polarimetric synthetic aperture radar (PolSAR) image classification. Traditionally, statistical-distribution-based PolSAR image classification models pay attention to two aspects: searching for a s... View full abstract»

• ### Machine Learning-Assisted Analysis of Polarimetric Scattering From Cylindrical Components of Vegetation

Publication Year: 2019, Page(s):155 - 165
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Reliable and efficient analysis of electromagnetic scattering by cylindrical components of vegetation is important for microwave remote sensing of vegetated terrain. In this paper, we proposed a machine learning (ML) scheme for the analysis of polarimetric bistatic scattering from a finite dielectric cylinder. A deep neural network architecture is adopted in the hope that with increased depth of t... View full abstract»

• ### Total Variation Regularized Collaborative Representation Clustering With a Locally Adaptive Dictionary for Hyperspectral Imagery

Publication Year: 2019, Page(s):166 - 180
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Clustering is a very challenging task for hyperspectral imagery (HSI) because of the complex spectral–spatial structures found in such data. Recently, the sparse recovery-based approaches have been introduced to deal with hyperspectral clustering, and have achieved state-of-the-art performances. Several recent works have shown that it is the collaborative representation mechanism over all the dict... View full abstract»

• ### Coarse-to-Fine Extraction of Small-Scale Lunar Impact Craters From the CCD Images of the Chang’E Lunar Orbiters

Publication Year: 2019, Page(s):181 - 193
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Lunar impact craters form the basis for lunar geological stratigraphy, and small-scale craters further enrich the basic statistical data for the estimation of local geological ages. Thus, the extraction of lunar impact craters is an important branch of modern planetary studies. However, few studies have reported on the extraction of small-scale craters. Therefore, this paper proposes a coarse-to-f... View full abstract»

• ### Spectral Unmixing With Perturbed Endmembers

Publication Year: 2019, Page(s):194 - 211
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We consider the problem of supervised spectral unmixing with a fully-perturbed linear mixture model where the given endmembers, as well as the observations of the spectral image, are subject to perturbation due to noise, error, or model mismatch. We calculate the Fisher information matrix and the Cramer–Rao lower bound associated with the estimation of the abundance matrix in the considered fully-... View full abstract»

• ### Geometric Modeling of the Z-Surface and Z-Curve of GNSS Signals and Their Solution Techniques

Publication Year: 2019, Page(s):212 - 223
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This paper presents a novel geometric model to characterize the zero-crossing surface ( $z$ -surface) and its z-curve for signals emitted by a pair of Global Navigation Satellite System satellites ( ${\mathcal{A}}$ , View full abstract»

• ### Intrinsic Image Recovery From Remote Sensing Hyperspectral Images

Publication Year: 2019, Page(s):224 - 238
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In this paper, a novel reflectance model is proposed to recover intrinsic images from remote sensing hyperspectral images (HSIs). Intrinsic image recovery is a well-known challenging and underconstrained problem in computer vision, and it becomes even more severely illposed for HSIs. To reduce the uncertainties and improve the recovery accuracy, two kinds of priors are introduced: 1) shading prior... View full abstract»

• ### Multiobjective-Based Sparse Representation Classifier for Hyperspectral Imagery Using Limited Samples

Publication Year: 2019, Page(s):239 - 249
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Recent studies about hyperspectral imagery (HSI) classification usually focus on extracting more representative features or combining joint spectral–spatial information. However, besides feature extraction, developing more powerful classifiers can also contribute to the accuracies of HSI classification. In this paper, we propose a multiobjective-based sparse representation classifier (MSRC) for HS... View full abstract»

• ### Fast Narrowband RFI Suppression Algorithms for SAR Systems via Matrix-Factorization Techniques

Publication Year: 2019, Page(s):250 - 262
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A synthetic aperture radar (SAR) system is severely affected by radio frequency systems, such as TV and cellular networks. Previous studies showed that narrowband radio frequency interference (RFI) is low rank and used the nuclear norm as a low-rank regularization to extract the RFI from the received signal. However, the nuclear norm is not an appropriate approximation of the true rank function. H... View full abstract»

• ### Estimation of Thin-Ice Thickness and Discrimination of Ice Type From AMSR-E Passive Microwave Data

Publication Year: 2019, Page(s):263 - 276
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Detection of thin-ice thickness with microwave radiometers, such as the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), is very effective for the estimation of sea-ice production, which causes dense water driving ocean thermohaline circulation. In previous thin-ice thickness algorithms, ice thickness is estimated by utilizing a negative correlation between ice thickness and... View full abstract»

• ### Improving the Spatial Bias Correction Algorithm in SMOS Image Reconstruction Processor: Validation of Soil Moisture Retrievals With In Situ Data

Publication Year: 2019, Page(s):277 - 290
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SMOS is a space mission led by the European Space Agency and designed to provide global maps of Soil Moisture and Ocean salinity, two important geophysical parameters for understanding the water cycle variations and climate change. The SMOS payload is a 2-D interferometer operating at L-band that consists of 69 elementary antennas located along a Y-shaped structure. Important spatial biases persis... View full abstract»

• ### Toward Mitigating Stratified Tropospheric Delays in Multitemporal InSAR: A Quadtree Aided Joint Model

Publication Year: 2019, Page(s):291 - 303
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Tropospheric delays (TDs) in differential interferometric synthetic aperture radar (InSAR) measurements are mainly caused by spatial and temporal variation of pressure, temperature, and humidity between SAR acquisitions. These delays are described as one of the primary error sources in InSAR observations. Although independent atmospheric measurements have been used to correct TDs, their sparse spa... View full abstract»

## Aims & Scope

IEEE Transactions on Geoscience and Remote Sensing (TGRS) s 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. This journal publishes technical papers disclosing new and significant research.  The technical content of papers must be both new and significant. Experimental data must be complete and include sufficient description of experimental apparatus, methods, and relevant experimental conditions.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Simon H. Yueh
Jet Propulsion Laboratory