IEEE Geoscience and Remote Sensing Letters最新文献_第9页

Late Winter Observations of Sea Ice Pressure Ridge Sail Height 晚冬海冰气压脊帆高观测

IF 4.8 3区地球科学

IEEE Geoscience and Remote Sensing Letters Pub Date : 2019-01-10 DOI: 10.1002/essoar.10500429.1

K. Duncan, S. Farrell, J. Hutchings, J. Richter-Menge

{"title":"Late Winter Observations of Sea Ice Pressure Ridge Sail Height","authors":"K. Duncan, S. Farrell, J. Hutchings, J. Richter-Menge","doi":"10.1002/essoar.10500429.1","DOIUrl":"https://doi.org/10.1002/essoar.10500429.1","url":null,"abstract":"Analysis of high-resolution imagery acquired by the Digital Mapping System during annual, late-winter NASA Operation IceBridge surveys of Arctic sea ice between 2010 and 2018 reveals that pressure ridge sail heights (<inline-formula> <tex-math notation=\"LaTeX\">${H} _{mathbf {S}}$ </tex-math></inline-formula>) vary regionally and interannually. We find distinct differences in <inline-formula> <tex-math notation=\"LaTeX\">${H} _{mathbf {S}}$ </tex-math></inline-formula> distributions between the central Arctic (CA) and the Beaufort/Chukchi Seas region. Our results show that differences with respect to ice type occur within the tails of the <inline-formula> <tex-math notation=\"LaTeX\">${H} _{mathbf {S}}$ </tex-math></inline-formula> distributions and that the 95th and 99th percentiles of <inline-formula> <tex-math notation=\"LaTeX\">${H} _{mathbf {S}}$ </tex-math></inline-formula> are strong indicators of the predominant ice type in which the pressure ridge formed. During the first part of the study period <inline-formula> <tex-math notation=\"LaTeX\">${H} _{mathbf {S}}$ </tex-math></inline-formula> increased, with the largest sails observed in the winters of 2015 and 2016, after which <inline-formula> <tex-math notation=\"LaTeX\">${H} _{mathbf {S}}$ </tex-math></inline-formula> declined, suggesting that the most heavily deformed sea ice may have drifted beyond the area surveyed and exited the CA. Our analysis of the interannual and regional variability in sea ice deformation in the western Arctic during the last decade provides an improved understanding of sail height that will help advance ridge parameterizations in sea ice models.","PeriodicalId":13046,"journal":{"name":"IEEE Geoscience and Remote Sensing Letters","volume":"18 1","pages":"1525-1529"},"PeriodicalIF":4.8,"publicationDate":"2019-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/essoar.10500429.1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48221682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Notice to the reader 读者须知

IF 4.8 3区地球科学

IEEE Geoscience and Remote Sensing Letters Pub Date : 2019-01-01 DOI: 10.1109/lgrs.2013.2256414

引用次数: 109

Nuclear Magnetic Resonance Spectrum Inversion Based on the Residual Hybrid

$l_{1}$

/

$l_{2}$

基于残差混合$l_{1}$ / $l_{2}$的核磁共振谱反演

IF 4.8 3区地球科学

IEEE Geoscience and Remote Sensing Letters Pub Date : 2018-08-01 DOI: 10.1109/lgrs.2018.2835457

Y. Zou, R. Xie, Mi Liu, Jiangfeng Guo, G. Jin

引用次数: 1

Moving Target Refocusing Algorithm in 2-D Wavenumber Domain After BP Integral BP积分后二维波数域运动目标重聚焦算法

IF 4.8 3区地球科学

IEEE Geoscience and Remote Sensing Letters Pub Date : 2018-01-01 DOI: 10.1109/LGRS.2017.2777494

Qi Dong, M. Xing, X. Xia, Sheng Zhang, Guangcai Sun

引用次数: 12

Interference Mitigation for Automotive Radar Using Orthogonal Noise Waveforms 基于正交噪声波形的汽车雷达干扰抑制

IF 4.8 3区地球科学

IEEE Geoscience and Remote Sensing Letters Pub Date : 2018-01-01 DOI: 10.1109/LGRS.2017.2777962

Zhihuo Xu, Quan Shi

引用次数: 42

Semisupervised Classification of Polarimetric SAR Image via Superpixel Restrained Deep Neural Network 基于超像素约束深度神经网络的极化SAR图像半监督分类

IF 4.8 3区地球科学

IEEE Geoscience and Remote Sensing Letters Pub Date : 2018-01-01 DOI: 10.1109/LGRS.2017.2777450

Jie Geng, Xiaorui Ma, Jianchao Fan, Hongyu Wang

{"title":"Semisupervised Classification of Polarimetric SAR Image via Superpixel Restrained Deep Neural Network","authors":"Jie Geng, Xiaorui Ma, Jianchao Fan, Hongyu Wang","doi":"10.1109/LGRS.2017.2777450","DOIUrl":"https://doi.org/10.1109/LGRS.2017.2777450","url":null,"abstract":"The classification of polarimetric synthetic aperture radar (PolSAR) image is of crucial significance for SAR applications. In this letter, a superpixel restrained deep neural network with multiple decisions (SRDNN-MDs) is proposed for PolSAR image classification, which not only extracts effective superpixel spatial features and degrades the influence of speckle noises but also deals with the limited training samples. First, the polarimetric features of coherency matrix and Yamaguchi decomposition are extracted as initial features, and superpixel segmentation is conducted on the Pauli color-coded image to acquire the superpixel averaged features. Then, an SRDNN based on sparse autoencoders is proposed to capture superpixel correlative features and reduce speckle noises. After that, MDs, including nonlocal decision and local decision, are developed to select credible testing samples. Finally, our deep network is updated by the extended training set to yield the final classification map. Experimental results demonstrate that the proposed SRDNN-MD yields higher accuracies compared with other related approaches, which indicate that the proposed method is able to capture superpixel correlative information and adds the information of unlabeled samples to improve the classification performance.","PeriodicalId":13046,"journal":{"name":"IEEE Geoscience and Remote Sensing Letters","volume":"4 1","pages":"122-126"},"PeriodicalIF":4.8,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LGRS.2017.2777450","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62471947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 41

Time–Frequency Analysis of Seismic Data Using a Three Parameters S Transform 基于三参数S变换的地震资料时频分析

IF 4.8 3区地球科学

IEEE Geoscience and Remote Sensing Letters Pub Date : 2018-01-01 DOI: 10.1109/LGRS.2017.2778045

Naihao Liu, Jing-Hua Gao, Bo Zhang, Fangyu Li, Qian Wang

引用次数: 62

Inversion-Driven Attenuation Compensation Using Synchrosqueezing Transform 利用同步压缩变换的逆驱动衰减补偿

IF 4.8 3区地球科学

IEEE Geoscience and Remote Sensing Letters Pub Date : 2018-01-01 DOI: 10.1109/LGRS.2017.2777598

Guowei Zhang, Jinghuai Gao

{"title":"Inversion-Driven Attenuation Compensation Using Synchrosqueezing Transform","authors":"Guowei Zhang, Jinghuai Gao","doi":"10.1109/LGRS.2017.2777598","DOIUrl":"https://doi.org/10.1109/LGRS.2017.2777598","url":null,"abstract":"Attenuation is a fundamental mechanism as seismic wave propagates through the earth. The loss of high-frequency energy and concomitant phase distortion can be compensated by inverse <inline-formula> <tex-math notation=\"LaTeX\">${Q}$ </tex-math></inline-formula> filtering to enhance the resolution of seismic data. Since the attenuation process depends on time and frequency, it is routinely performed in the time–frequency domain. The synchrosqueezing transform (SST), which provides highly localized time–frequency representations for the nonstationary signals due to reduced spectral smearing, is applied to implement the inverse <inline-formula> <tex-math notation=\"LaTeX\">${Q}$ </tex-math></inline-formula> filtering scheme. However, the amplitude compensation process is unstable because energy amplification is involved. To stabilize it, the amplitude compensation is regarded as an inverse problem with an L1-norm regularization term in the SST domain. The iteratively reweighted least-squares algorithm is used to solve the regularized inverse problem. Synthetic and real data examples illustrate the stability and effectiveness of the proposed method.","PeriodicalId":13046,"journal":{"name":"IEEE Geoscience and Remote Sensing Letters","volume":"15 1","pages":"132-136"},"PeriodicalIF":4.8,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LGRS.2017.2777598","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62472023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Persistent Scatter Identification and Look-Angle Error Estimation Using Similar Time-Series Interferometric Pixels 基于相似时间序列干涉像元的持续散射识别和视角误差估计

IF 4.8 3区地球科学

IEEE Geoscience and Remote Sensing Letters Pub Date : 2018-01-01 DOI: 10.1109/LGRS.2017.2778421

Avadh Bihari Narayan, A. Tiwari, R. Dwivedi, O. Dikshit

{"title":"Persistent Scatter Identification and Look-Angle Error Estimation Using Similar Time-Series Interferometric Pixels","authors":"Avadh Bihari Narayan, A. Tiwari, R. Dwivedi, O. Dikshit","doi":"10.1109/LGRS.2017.2778421","DOIUrl":"https://doi.org/10.1109/LGRS.2017.2778421","url":null,"abstract":"Persistent scatterer (PS) pixels contain highly coherent information, which is used in the estimation of geophysical parameters of interest. Conventionally, PS pixels are selected on the basis of the estimated noise present in the spatially uncorrelated phase component along with look-angle error. The phase history of selected PS pixels is corrected for the look-angle error followed by phase unwrapping and extraction of spatially correlated nuisance phase component leading to displacement estimation. In this letter, a novel PS selection method, which is based on a new index called the similar time-series interferometric pixels (STIPs) representing the number of neighborhood pixels with similar phase history, is proposed. In this approach, apart from PS selection, corresponding set of STIP is also used in refining look-angle error estimation. The efficiency of the proposed InSAR processing chain is demonstrated for the Sentinel-1A single look complex images of Rajmahal, Jharkhand, India, predominantly a coal mines area. Results, when compared with the conventional PS processing technique, reveal substantial improvement in terms of extracting more number of reliable PS with enhanced density.","PeriodicalId":13046,"journal":{"name":"IEEE Geoscience and Remote Sensing Letters","volume":"15 1","pages":"147-150"},"PeriodicalIF":4.8,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LGRS.2017.2778421","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62472131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Simultaneous Estimation of Multiple Land-Surface Parameters From VIIRS Optical-Thermal Data 利用VIIRS光热数据同时估算多个地表参数

IF 4.8 3区地球科学

IEEE Geoscience and Remote Sensing Letters Pub Date : 2018-01-01 DOI: 10.1109/LGRS.2017.2779040

Han Ma, S. Liang, Zhiqiang Xiao, Dongdong Wang

{"title":"Simultaneous Estimation of Multiple Land-Surface Parameters From VIIRS Optical-Thermal Data","authors":"Han Ma, S. Liang, Zhiqiang Xiao, Dongdong Wang","doi":"10.1109/LGRS.2017.2779040","DOIUrl":"https://doi.org/10.1109/LGRS.2017.2779040","url":null,"abstract":"Traditional methods for estimating land-surface parameters from remotely sensed data generally focus on a single parameter with a specific spectral region, resulting in physical and spatiotemporal inconsistencies in current satellite products. We recently proposed a unified inversion scheme to estimate a suite of parameters simultaneously from both visible and near-infrared and thermal-infrared MODIS data. In this letter, we implemented this scheme to estimate six time-series parameters [leaf area index, fraction of absorbed photosynthetically active radiation, surface albedo, land-surface emissivity, land-surface temperature (LST), and upwelling longwave radiation (LWUP)] from the Visible Infrared Imaging Radiometer Suite (VIIRS) data. Several components of these schemes are refined, including the incorporation of a snow bidirectional reflectance distribution function model, determination of the best band combination, and better estimation of the snow-covered surface emissivity by accounting for the snow-cover fraction. Validation using the measurements at 12 sites of SURFRAD, CarboEuropeIP, and FLUXNET, and intercomparisons with MODIS and Global Land-Surface Satellite products, are carried out: the retrieved albedo, LST, and LWUP achieved accuracies ( $R^{2}$ ) of 0.77, 0.96, and 0.95, root mean square errors of 0.06, 2.9 K, and 18.3 W/m2, and biases of 0.01, 0.09 K, and −0.08 W/m2, respectively. The retrieved parameters can achieve comparable or higher accuracy than existing products, which indicates that the unified algorithm can be applied effectively to the VIIRS data with high physical and temporal consistency and accuracy.","PeriodicalId":13046,"journal":{"name":"IEEE Geoscience and Remote Sensing Letters","volume":"15 1","pages":"156-160"},"PeriodicalIF":4.8,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LGRS.2017.2779040","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62472164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12