IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society最新文献_第2页

A Unified Framework for Bridging the Data Gap Between GRACE/GRACE-FO for Both Greenland and Antarctica 弥合格陵兰和南极洲GRACE/GRACE- fo数据差距的统一框架

IF 4.4

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2025-09-04 DOI: 10.1109/LGRS.2025.3605913

Zhuoya Shi;Zemin Wang;Baojun Zhang;Nicholas E. Barrand;Manman Luo;Shuang Wu;Jiachun An;Hong Geng;Haojian Wu

{"title":"A Unified Framework for Bridging the Data Gap Between GRACE/GRACE-FO for Both Greenland and Antarctica","authors":"Zhuoya Shi;Zemin Wang;Baojun Zhang;Nicholas E. Barrand;Manman Luo;Shuang Wu;Jiachun An;Hong Geng;Haojian Wu","doi":"10.1109/LGRS.2025.3605913","DOIUrl":"https://doi.org/10.1109/LGRS.2025.3605913","url":null,"abstract":"The 11-month data gap between gravity recovery and climate experiment (GRACE) and GRACE Follow-On (GRACE-FO) hinders monitoring long-term ice mass change and its further analysis. While many attempts have been made to bridge water storage gaps, few unified frameworks exist to bridge the ice mass change gaps for both Greenland ice sheet (GrIS) and Antarctic ice sheet (AIS). This study combined partial least squares regression (PLSR) and the Sparrow Search Algorithm optimized back propagation (SSA-BP) to fill this gap in GrIS and AIS. During this process, seasonal autoregressive integrated moving average (MA) with exogenous variables (SARIMAX) and multiple linear regression (MLR) were introduced as comparison. PSLR is utilized to select key variables for constructing predictive models. We found SSA-BP outperformed SARIMAX and MLR, with correlation coefficients (CCs) and root mean square error (RMSE) at 0.99 and 39.22 Gt for GrIS, and 0.95 and 189.85 Gt for AIS within the testing period. SSA-BP demonstrated a reasonable mass change trend with less noise than other methods. SSA-BP reconstructed result shows superiority than other researches. Moreover, the reconstructed seasonal signals highlight the importance of filling the gap, showing decreased mass loss for GrIS and continuous mass loss acceleration for AIS post-2016.","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":4.4,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Graph-Aware Hybrid Encoding for Hyperspectral Image Classification 基于图感知的高光谱图像分类混合编码

IF 4.4

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2025-09-04 DOI: 10.1109/LGRS.2025.3605916

Yuquan Gan;Siyu Wu;Xingyu Li;Zhijie Xu;Yushan Pan

引用次数: 0

A Test Statistic for Block-Diagonal Covariance Matrix Structure in polSAR Data polSAR数据中块对角协方差矩阵结构的检验统计量

IF 4.4

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2025-09-04 DOI: 10.1109/LGRS.2025.3605978

Allan A. Nielsen;Henning Skriver;Knut Conradsen

{"title":"A Test Statistic for Block-Diagonal Covariance Matrix Structure in polSAR Data","authors":"Allan A. Nielsen;Henning Skriver;Knut Conradsen","doi":"10.1109/LGRS.2025.3605978","DOIUrl":"https://doi.org/10.1109/LGRS.2025.3605978","url":null,"abstract":"We report on a complex Wishart distribution-based test statistic <inline-formula> <tex-math>$boldsymbol {Q}$ </tex-math></inline-formula> for block-diagonality in Hermitian matrices such as the ones analyzed in polarimetric synthetic aperture radar (polSAR) image data in the covariance matrix formulation. We also give an improved probability measure <inline-formula> <tex-math>$boldsymbol {P}$ </tex-math></inline-formula> associated with the test statistic. This is used in a case with simulated data to demonstrate the superiority of the new expression for <inline-formula> <tex-math>$boldsymbol {P}$ </tex-math></inline-formula> and to illustrate the dependence of results on the choice of covariance matrix, its dimensionality, the equivalent number of looks, and two parameters in the improved <inline-formula> <tex-math>$boldsymbol {P}$ </tex-math></inline-formula> measure. We also give two cases with acquired data. One case is with airborne F-SAR polarimetric data, where we test for reflection symmetry, another case is with (spaceborne) dual-pol Sentinel-1 data, where we test if the data are diagonal-only. The absence of block-diagonal structure occurs mostly for man-made objects. In the example with Sentinel-1 data, some objects (e.g., buildings, cars, aircraft, and ships) are detected, others (e.g., some bridges) are not.","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":4.4,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145061854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Potential Impacts of 3-D Polarized GPR Data on Full-Waveform Inversion 三维极化GPR数据对全波形反演的潜在影响

IF 4.4

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2025-09-03 DOI: 10.1109/LGRS.2025.3605792

Siyuan Ding;Xun Wang;Deshan Feng;Cheng Chen;Dianbo Li

{"title":"Potential Impacts of 3-D Polarized GPR Data on Full-Waveform Inversion","authors":"Siyuan Ding;Xun Wang;Deshan Feng;Cheng Chen;Dianbo Li","doi":"10.1109/LGRS.2025.3605792","DOIUrl":"https://doi.org/10.1109/LGRS.2025.3605792","url":null,"abstract":"Ground penetrating radar (GPR) is a powerful tool for exploring the shallow subsurface due to its effective and noninvasive features. Recently, the accurate and high-resolution characterization of subsurface properties in 3-D GPR investigations calls for a quantitative and high-resolution imaging approach. However, the full-waveform inversion (FWI) method for GPR data was performed mostly in 2-D and rarely discussed the polarizations. To fully utilize 3-D GPR polarization data, this letter proposes a frequency-domain FWI algorithm for simultaneous inversion of both the co-polarized and cross-polarized data. Detail derivations and vital processes in our inversion workflow were described in detail, before applying it to the numerical experiments and analyzing the potential impacts of the polarizations on inversion results with a synthetic model. Results showed that the cross-polarized data are more sensitive than the co-polarized data in inversion, and the behaviors in the inversion of the multipolarized data with different values in the weighting matrix suggest that larger weights for co-polarized data are of benefit to a better inversion result.","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":4.4,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

First Implementation of GPD+ Wet Tropospheric Correction on SWOT Side 1 and Side 2 Radiometer Tracks 在SWOT侧1和侧2辐射计轨道上首次实施GPD+湿对流层校正

IF 4.4

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2025-09-03 DOI: 10.1109/LGRS.2025.3605854

Isabel Cardoso;Clara Lázaro;Telmo Vieira;M. Joana Fernandes

{"title":"First Implementation of GPD+ Wet Tropospheric Correction on SWOT Side 1 and Side 2 Radiometer Tracks","authors":"Isabel Cardoso;Clara Lázaro;Telmo Vieira;M. Joana Fernandes","doi":"10.1109/LGRS.2025.3605854","DOIUrl":"https://doi.org/10.1109/LGRS.2025.3605854","url":null,"abstract":"The Surface Water and Ocean Topography (SWOT) satellite provides high-resolution observations of the ocean surface topography and elevation of inland waters. Measurements from the two onboard Advanced Microwave Radiometers (AMRs) are used to compute the wet tropospheric correction (WTC), accounting for the radar signal delay due to water vapor and cloud liquid water content in the troposphere. This study presents the first implementation of the Global Navigation Satellite System (GNSS)-derived Path Delay Plus (GPD+) algorithm for SWOT to estimate the WTC when AMR observations are absent or invalid. Using the first 15 science-phase cycles between 50°N and 50°S, GPD+ retrieves the WTC for approximately 7% of points per cycle that would otherwise be excluded. Retrieval rates per cycle range from less than 5% of the points in passes mostly over open ocean, where the WTC derived from the radiometers is usually preserved, to up to 15% in passes including coastal zones. These results indicate that GPD+ can recover WTC values otherwise unavailable from SWOT’s radiometers, increasing the availability of valid WTC for SWOT measurements, in particular over coastal regions. Further refinements will focus on improving the accuracy of the WTC along the KaRIn swath and the Poseidon-3C nadir track.","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":4.4,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distant-to-Close Novel View Synthesis for Asteroid Surface Imaging 小行星表面成像的远近新视点合成

IF 4.4

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2025-09-03 DOI: 10.1109/LGRS.2025.3605777

Xiaodong Wei;Linyan Cui;Xinyu Zhao;Gangzheng Ai;Jihao Yin

{"title":"Distant-to-Close Novel View Synthesis for Asteroid Surface Imaging","authors":"Xiaodong Wei;Linyan Cui;Xinyu Zhao;Gangzheng Ai;Jihao Yin","doi":"10.1109/LGRS.2025.3605777","DOIUrl":"https://doi.org/10.1109/LGRS.2025.3605777","url":null,"abstract":"Predictively synthesizing high-quality, close-range asteroid surface views from distant optical remote sensing imagery is critical for mission planning and landing-site selection in asteroid exploration missions. However, distant observations inherently lack sufficient resolution and surface detail, limiting the existing novel view synthesis (NVS) methods. To address this, we introduce, to the best of our knowledge, the first framework for distant-to-close NVS, tailored for asteroid surface imaging. Our method features two key innovations. First, a 3-D Gaussian splatting (3D-GS) super-resolution (SR) module applies 2-D SR to generate high-resolution virtual close-range views from distant images, enriching the 3-D scene model with finer details. Second, an entropy-driven residual refinement strategy adaptively emphasizes structurally complex regions by assigning higher loss weights based on residual image entropy. This strategy triggers targeted subdivisions of 3-D Gaussians in the areas of high structural complexity. Experiments conducted on datasets from Hayabusa (Itokawa), Dawn (Vesta), Rosetta (67P/Churyumov-Gerasimenko), Hayabusa2 (Ryugu), and OSIRIS-REx (Bennu) missions demonstrate substantial improvements over baseline methods in quantitative metrics, such as peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and learned perceptual image patch similarity (LPIPS).","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":4.4,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of Optical Multiangle Multispectral Reflectance in Land Cover Classification 光学多角度多光谱反射率在土地覆盖分类中的应用

IF 4.4

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2025-09-02 DOI: 10.1109/LGRS.2025.3605331

Fan Ye;Xiaoning Zhang;Zhengjie Wang;Yifei Wang;Zhaoyang Peng;Tengying Fu;Ziti Jiao;Yanxuan Wu;Yue Wang

{"title":"Application of Optical Multiangle Multispectral Reflectance in Land Cover Classification","authors":"Fan Ye;Xiaoning Zhang;Zhengjie Wang;Yifei Wang;Zhaoyang Peng;Tengying Fu;Ziti Jiao;Yanxuan Wu;Yue Wang","doi":"10.1109/LGRS.2025.3605331","DOIUrl":"https://doi.org/10.1109/LGRS.2025.3605331","url":null,"abstract":"Considering the simplicity of flight route planning, orthorectified images obtained from nadir observations are widely used in remote sensing. However, they are always insufficient to represent the anisotropic reflectance and 3-D structural information of objects. Therefore, multiangle observation information can enhance target information and potentially improve the accuracy of target classification and recognition. In this study, we investigated the potential of anisotropic reflectance information in land cover classification. By employing the DJI P4M multispectral observation system, multiangle multispectral reflectance images for five land cover types were captured at bare soil, concrete roads, grassland, apricot tree, and red broom cypress areas. Subsequently, the anisotropic flat index (AFX)-based bidirectional reflectance distribution function (BRDF) archetypes model and the kernel-driven model were used to reconstruct the BRDF. Finally, land cover classification was performed using three types of machine learning algorithm considering different BRDF features and band combinations. The results indicate that, compared to nadir directional reflectance, multiangle feature sets can improve the overall classification accuracy up to 24%. Compared to using single-band information, band combinations can also improve that up to 54%. The overall accuracy using the feature set of kernel-driven model parameters and nadir reflectance was also enhanced significantly, which can reach 86% using green-red-near infrared band combinations. This work demonstrates the contribution of multiangle multispectral information to natural and artificial land cover classification.","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":4.4,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145021449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LMG-Net: A Lightweight Remote Sensing Change Detection Network With Multilevel Global Features LMG-Net：一种具有多层次全局特征的轻型遥感变化检测网络

IF 4.4

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2025-09-01 DOI: 10.1109/LGRS.2025.3604651

Yutian Li;Wei Liu;Erzhu Li;Lianpeng Zhang;Xing Li

{"title":"LMG-Net: A Lightweight Remote Sensing Change Detection Network With Multilevel Global Features","authors":"Yutian Li;Wei Liu;Erzhu Li;Lianpeng Zhang;Xing Li","doi":"10.1109/LGRS.2025.3604651","DOIUrl":"https://doi.org/10.1109/LGRS.2025.3604651","url":null,"abstract":"Remote sensing change detection (RSCD) is a key tool for environmental monitoring and resource management, playing a significant role in monitoring dynamic surface changes. In practical applications, RSCD often requires high precision and efficient detection methods. However, traditional methods tend to involve high technical complexity and a large number of parameters and are susceptible to interference from complex background noise, leading to poor performance in detecting change areas. To address these issues, this letter proposes a lightweight RSCD network, LMG-Net. The model uses a lightweight encoder and incorporates a hierarchical transformer module (HTF) to suppress background noise and minimize parameter increase, effectively extracting multilevel global features. Additionally, this letter introduces a multidimensional cooperative attention guidance (MAG) mechanism, further enhancing the ability to detect boundary changes. The model has only 3.29 M parameters and a computational load of 3.89G, demonstrating its high applicability, particularly for real-time applications in resource-constrained environments. Experimental results show that LMG-Net achieves the state-of-the-art (SOTA) <inline-formula> <tex-math>${F}1$ </tex-math></inline-formula> scores and IoU values on the WHU-CD, SYSU-CD, and LEVIR-CD+ datasets: (94.79%, 90.09%), (82.29%, 69.90%), and (84.30%, 71.14%).","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":4.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting Martian Regolith Permittivity Using Deep Learning Methods—Revisiting Southern Utopia Planitia 利用深度学习方法预测火星风化层介电常数——重访南部乌托邦平原

IF 4.4

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2025-08-29 DOI: 10.1109/LGRS.2025.3604251

Qinfen Cai;Feng Zhou;Iraklis Giannakis;Sijing Liu;Xiangyun Hu

{"title":"Predicting Martian Regolith Permittivity Using Deep Learning Methods—Revisiting Southern Utopia Planitia","authors":"Qinfen Cai;Feng Zhou;Iraklis Giannakis;Sijing Liu;Xiangyun Hu","doi":"10.1109/LGRS.2025.3604251","DOIUrl":"https://doi.org/10.1109/LGRS.2025.3604251","url":null,"abstract":"China’s first Mars mission [Tianwen-1 (TW-1)] successfully touched down in the Utopia Planitia of Mars with a rover subsurface penetrating radar (RoPeR) carried for exploring the regolith dielectric properties. Hyperbolic fitting is a conventional method to infer the subsurface material relative permittivity from ground penetrating radar (GPR) data. However, it is difficult to directly extract valid hyperbolas from the RoPeR data. Inspired by the recently developed deep learning-based geophysical inversion method to estimate the subsurface wave velocities through GPR data, an improved deep learning architecture is proposed to infer the Martian regolith relative permittivity from the RoPeR data, with self-attention (SA) and cascade modules are introduced into the network. The improved cascade and SA modules can improve the inversion efficiency and mitigate the scatter-diffraction effect of the predicted results. The inverted relative permittivity from the first 60 ns of the RoPeR data demonstrates an approximate line with a mean value of 4.73 in the regolith of interest. The very limited fluctuation of relative permittivity implies that no explicit stratification existing in the investigated regolith, agreeing with the previous studies.","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":4.4,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing Change Detection With Edge-Guided Difference Modeling in Remote Sensing Imagery 利用边缘引导差分建模增强遥感图像变化检测

IF 4.4

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2025-08-29 DOI: 10.1109/LGRS.2025.3604110

Pengkai Wang;Fuchao Cheng;Yuan Yao;Liang Liu;Jianwei Zhang;Abdelaziz Bouras;D. Narasimhan;Ling Qin;Shaohua Wang;Chang Liu

引用次数: 0