IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing最新文献_第10页

Rethinking Scanning Strategies With Vision Mamba in Semantic Segmentation of Remote Sensing Imagery: An Experimental Study 利用 Vision Mamba 在遥感图像语义分割中重新思考扫描策略：实验研究

IF 4.7 2区地球科学

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2024-10-02 DOI: 10.1109/JSTARS.2024.3472296

Qinfeng Zhu;Yuan Fang;Yuanzhi Cai;Cheng Chen;Lei Fan

{"title":"Rethinking Scanning Strategies With Vision Mamba in Semantic Segmentation of Remote Sensing Imagery: An Experimental Study","authors":"Qinfeng Zhu;Yuan Fang;Yuanzhi Cai;Cheng Chen;Lei Fan","doi":"10.1109/JSTARS.2024.3472296","DOIUrl":"https://doi.org/10.1109/JSTARS.2024.3472296","url":null,"abstract":"Deep learning methods, especially convolutional neural networks (CNNs) and vision transformers (ViTs), are frequently employed to perform semantic segmentation of high-resolution remotely sensed images. However, CNNs are constrained by their restricted receptive fields, while ViTs face challenges due to their quadratic complexity. Recently, the Mamba model, featuring linear complexity and a global receptive field, has gained extensive attention for vision tasks. In such tasks, images need to be serialized to form sequences compatible with the Mamba model. Numerous research efforts have explored scanning strategies to serialize images, aiming to enhance the Mamba model's understanding of images. However, the effectiveness of these scanning strategies remains uncertain. In this research, we conduct a comprehensive experimental investigation on the impact of mainstream scanning directions and their combinations on semantic segmentation of remotely sensed images. Through extensive experiments on the LoveDA, ISPRS Potsdam, ISPRS Vaihingen, and UAVid datasets, we demonstrate that no single scanning strategy outperforms others, regardless of their complexity or the number of scanning directions involved. A simple, single scanning direction is deemed sufficient for semantic segmentation of high-resolution remotely sensed images. Relevant directions for future research are also recommended.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"17 ","pages":"18223-18234"},"PeriodicalIF":4.7,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703181","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142452721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Refinement Analysis of Real Dihedral and Trihedral CR-InSAR Based on TerraSAR-X and Sentinel-1A Images 基于 TerraSAR-X 和 Sentinel-1A 图像的真实二面体和三面体 CR-InSAR 精细化分析

IF 4.7 2区地球科学

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2024-10-02 DOI: 10.1109/JSTARS.2024.3472220

Hui Liu;Bochen Zhou;Changwei Miao;Shihuan Li;Lei Xu;Ke Zheng;Geshuang Li;Shiji Yang;Mengyuan Zhu

{"title":"Refinement Analysis of Real Dihedral and Trihedral CR-InSAR Based on TerraSAR-X and Sentinel-1A Images","authors":"Hui Liu;Bochen Zhou;Changwei Miao;Shihuan Li;Lei Xu;Ke Zheng;Geshuang Li;Shiji Yang;Mengyuan Zhu","doi":"10.1109/JSTARS.2024.3472220","DOIUrl":"https://doi.org/10.1109/JSTARS.2024.3472220","url":null,"abstract":"This study creatively invented a new type of turnbuckle adjustable corner reflector (CR), which greatly enhances the flexible adjustment ability of CR in both vertical and horizontal directions through a unique positive and negative screw structure design, significantly improving the convenience of on-site deployment. Based on the performance of dihedral CR and trihedral CR installed in the South-to-North Water Diversion Channel using back-to-back design on TerraSAR-X and Sentinel-1A images, the performance of different structures of CR in complex environments, especially under heavy precipitation conditions, was deeply analyzed. The experimental results show that the trihedral CR can still maintain stable monitoring efficiency when encountering extreme weather conditions with precipitation exceeding 10 mm. The monitoring effect of traditional dihedral CR drops sharply and is almost ineffective in such environments. At the same time, the combination of theoretical radar cross section (RCS) and measured RCS values confirms the decisive impact of CR geometry and deployment strategy on improving monitoring stability and accuracy. Further precise comparison between CR-InSAR monitoring results and the second-order leveling measurement results shows that the system's average error is controlled within the range of 2–3 mm using trihedral CR. Compared with the results of dihedral CR and InSAR without CR, a significant improvement in accuracy has been achieved. This study provides strong theoretical support and practical guidance for the optimization design and practical application of CR systems, and has important scientific value and application prospects.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"17 ","pages":"18739-18750"},"PeriodicalIF":4.7,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10702605","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142517954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

GNSS-R Snow Depth Inversion Study Based on SNR-SVR 基于 SNR-SVR 的 GNSS-R 雪深反演研究

IF 4.7 2区地球科学

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2024-10-02 DOI: 10.1109/JSTARS.2024.3470508

Yuan Hu;Jingxin Wang;Wei Liu;Xintai Yuan;Jens Wickert

{"title":"GNSS-R Snow Depth Inversion Study Based on SNR-SVR","authors":"Yuan Hu;Jingxin Wang;Wei Liu;Xintai Yuan;Jens Wickert","doi":"10.1109/JSTARS.2024.3470508","DOIUrl":"https://doi.org/10.1109/JSTARS.2024.3470508","url":null,"abstract":"The global navigation satellite system reflectometry (GNSS-R) technology has shown significant potential in retrieving snow depth using signal-to-noise ratio (SNR) data. However, compared to traditional in situ snow depth measurement techniques, we have observed that the accuracy and performance of GNSS-R can be significantly impacted under certain conditions, particularly when the elevation angle increases. This is due to the attenuation of the multipath effect, which is particularly evident during snow-free periods and under low-snow conditions where snow depths are below 50 cm. To address these limitations, we propose a snow depth inversion method that integrates SNR signals with the support vector regression algorithm, utilizing SNR sequences as feature inputs. We conducted studies at stations P351 and P030, covering elevation angles ranging from 5° to 20°, 5° to 25°, and 5° to 30°. The experimental results show that the root-mean-square error at both the stations decreased by 50% or more compared to traditional methods, demonstrating an improvement in inversion accuracy across different elevation angles. More importantly, the inversion accuracy of our method does not significantly lag behind that at lower elevation angles, indicating its excellent performance under challenging conditions. These findings highlight the contribution of our method in enhancing the accuracy of snow depth retrieval and its potential to drive further advancements in the field of GNSS-R snow depth inversion.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"17 ","pages":"18025-18037"},"PeriodicalIF":4.7,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703113","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Method for Assessing the Lake Trophic Status Using Hyperspectral Reflectance (400–900 nm) Measured Above Water 利用水上测量的高光谱反射率（400-900 纳米）评估湖泊营养状况的方法

IF 4.7 2区地球科学

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2024-10-01 DOI: 10.1109/JSTARS.2024.3472021

Nguyen Thi Thu Ha;Pham Quang Vinh;Nguyen Thien Phuong Thao;Pham Ha Linh;Michael Parsons;Nguyen Van Manh

{"title":"A Method for Assessing the Lake Trophic Status Using Hyperspectral Reflectance (400–900 nm) Measured Above Water","authors":"Nguyen Thi Thu Ha;Pham Quang Vinh;Nguyen Thien Phuong Thao;Pham Ha Linh;Michael Parsons;Nguyen Van Manh","doi":"10.1109/JSTARS.2024.3472021","DOIUrl":"https://doi.org/10.1109/JSTARS.2024.3472021","url":null,"abstract":"The effective monitoring of eutrophication in inland water bodies is crucial for environmental management and pollution prevention. This study conducts a comprehensive analysis of in situ hyperspectral reflectance data (400–900 nm) and the trophic state index (TSI) obtained from 365 points across ten lakes and reservoirs in Northern Vietnam to propose a trophic classification based on water reflectance spectra features and a TSI estimation model for diagnosis and assessment of lake trophic status. By analyzing the quantity of reflectance peaks and their heights, our study identifies three distinct water reflectance spectra classes corresponding to three trophic levels: mesotrophic to lightly eutrophic, highly eutrophic, and hypertrophic. This classification enables the quick identification of trophic levels directly at the in situ radiometric measurement sites. Our study demonstrates that a logarithmic function of the band ratio, \u0000<inline-formula><tex-math>${{mathbf{R}}_{mathbf{rs}}}( {715} )/{{mathbf{R}}_{mathbf{rs}}}( {560} )$</tex-math></inline-formula>\u0000, is robust for estimating TSI (\u0000<inline-formula><tex-math>${{{bm{R}}}^2}$</tex-math></inline-formula>\u0000 = 0.85 and 0.94; root-mean-square error = 5.0 and 3.7 in calibration and validation, respectively), particularly in algal-dominated waters. These findings represent a practical application of hyperspectral remote sensing for effective eutrophication management. They also highlight the potential use of multispectral optical imagery for monitoring eutrophication in tropical regions.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"17 ","pages":"17890-17902"},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10702456","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MSARG-Net: A Multimodal Offshore Floating Raft Aquaculture Area Extraction Network for Remote Sensing Images Based on Multiscale SAR Guidance MSARG-Net：基于多尺度合成孔径雷达制导的多模式近海浮筏水产养殖区提取网络

IF 4.7 2区地球科学

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2024-10-01 DOI: 10.1109/JSTARS.2024.3471925

Haomiao Yu;Fangxiong Wang;Yingzi Hou;Junfu Wang;Jianfeng Zhu;Jianke Guo

{"title":"MSARG-Net: A Multimodal Offshore Floating Raft Aquaculture Area Extraction Network for Remote Sensing Images Based on Multiscale SAR Guidance","authors":"Haomiao Yu;Fangxiong Wang;Yingzi Hou;Junfu Wang;Jianfeng Zhu;Jianke Guo","doi":"10.1109/JSTARS.2024.3471925","DOIUrl":"https://doi.org/10.1109/JSTARS.2024.3471925","url":null,"abstract":"Accurately extracting offshore floating raft aquaculture (FRA) areas from remotely sensed images is the key to rationally managing aquaculture resources. Currently, deep learning-based methods perform well in FRA area extraction tasks but are limited by the shortcomings of single-modality remote sensing data, which affect their extraction accuracies. To solve this problem, we constructed a multimodal dataset called CHN-YS3-FRA for FRA area extraction using heterogeneous Sentinel-1/-2 remote sensing image data and proposed a new multiscale synthetic aperture radar (SAR) guidance network (MSARG-Net) for performing FRA area extraction on multimodal remote sensing images. In this network, we designed a global-local Poolformer block to model the local and global relationships of FRA areas to more comprehensively learn the semantic features of these areas. In addition, we designed a multiscale SAR-guided attention block to efficiently fuse the semantic information acquired from different modalities. The experimental results obtained on the CHN-YS3-FRA dataset show that MSARG-Net could robustly extract offshore FRA regions with F1 scores, intersection-over-union and kappa coefficient values of 91.46%, 84.26%, and 89.69%, respectively. Compared with the latest remote sensing-based semantic segmentation methods, MSARG-Net has achieved significant quantitative and qualitative improvements and has significant potential for mapping and monitoring large-scale offshore FRA areas.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"17 ","pages":"18319-18334"},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10700976","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142452701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Location-Guided Dense Nested Attention Network for Infrared Small Target Detection 用于红外小目标探测的位置引导密集嵌套注意力网络

IF 4.7 2区地球科学

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2024-10-01 DOI: 10.1109/JSTARS.2024.3472041

Huinan Guo;Nengshuang Zhang;Jing Zhang;Wuxia Zhang;Congying Sun

{"title":"Location-Guided Dense Nested Attention Network for Infrared Small Target Detection","authors":"Huinan Guo;Nengshuang Zhang;Jing Zhang;Wuxia Zhang;Congying Sun","doi":"10.1109/JSTARS.2024.3472041","DOIUrl":"https://doi.org/10.1109/JSTARS.2024.3472041","url":null,"abstract":"Infrared small target (IST) detection involves identifying objects that occupy fewer than 81 pixels in a 256 × 256 image. Because the target is small and lacks texture, structure, and shape information on its surface, this task is highly challenging. CNN-based methods can extract rich features of the target. However, overly deep network structures may increase the risk of losing small targets. In addition, pixel-level positional deviations can also reduce the detection accuracy of IST. To address these challenges, we propose the location-guided dense nested attention network for IST detection. The proposed network consists of a pixel attention guided feature extraction module (PAG-FEM), a channel attention guided feature fusion module (CAG-FFM), and a detection module. First, the PAG-FEM utilizes the DNIM dense nested blocks from the DNANet as the backbone, integrating both channel and pixel attention mechanisms. This method focuses on the semantic and positional information of the targets, yielding semantic features that emphasize the positions of small targets. Second, the CAG-FFM employs upsampling and convolution operations to align the feature sizes, while utilizing the channel attention mechanism to obtain effective channel information. Then, these features are fused through stacking, addition, and averaging operations to obtain more discriminative features. Finally, the detection module uses eight-connected neighborhood clustering method to obtain the centroid coordinates of the targets for subsequent detection evaluation. Three datasets are utilized to verify our method, and experimental results show that our method performs better than other advanced methods.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"17 ","pages":"18535-18548"},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10702466","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142517959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FDGSNet: A Multimodal Gated Segmentation Network for Remote Sensing Image Based on Frequency Decomposition FDGSNet：基于频率分解的遥感图像多模态门控分割网络

IF 4.7 2区地球科学

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2024-10-01 DOI: 10.1109/JSTARS.2024.3471638

Jian Cui;Jiahang Liu;Yue Ni;Jinjin Wang;Manchun Li

{"title":"FDGSNet: A Multimodal Gated Segmentation Network for Remote Sensing Image Based on Frequency Decomposition","authors":"Jian Cui;Jiahang Liu;Yue Ni;Jinjin Wang;Manchun Li","doi":"10.1109/JSTARS.2024.3471638","DOIUrl":"https://doi.org/10.1109/JSTARS.2024.3471638","url":null,"abstract":"Multiple modal data fusion can provide valuable and diverse information for remote sensing image segmentation. However, the existing fusion methods often lead to feature loss during the fusion of various modal data, and the complementarity among multimodal features is insufficient. To address these problems, we propose a multimodal gated segmentation network for remote sensing images based on the frequency decomposition. Complementary information from multimodal features is extracted by establishing a long-distance correlation between the low-frequency components of different modal data. In addition, high-frequency detailed features of different modal data are preserved by residual connection. The adaptive gated fusion method is then used to control the information flow between the complementary information and each modality feature map, enabling adaptive fusion between multimodal features. These operations can effectively improve the adaptability of the proposed method in various scenarios and data changes. Extensive experiments demonstrate that the proposed method has good effectiveness, robustness, and generalization and achieved state-of-the-art performance in several remote sensing image semantic segmentation tasks.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"17 ","pages":"19756-19770"},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10700993","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Collaborative Estimation of Aboveground Forest Biomass Using P-Band and X-Band Interferometric Synthetic Aperture Radar Based on Feature Optimization 基于特征优化的 P 波段和 X 波段干涉合成孔径雷达地面森林生物量协同估算

IF 4.7 2区地球科学

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2024-10-01 DOI: 10.1109/JSTARS.2024.3472096

Yunmei Ma;Lei Zhao;Erxue Chen;Zengyuan Li;Yaxiong Fan;Kunpeng Xu;Han Wang

{"title":"Collaborative Estimation of Aboveground Forest Biomass Using P-Band and X-Band Interferometric Synthetic Aperture Radar Based on Feature Optimization","authors":"Yunmei Ma;Lei Zhao;Erxue Chen;Zengyuan Li;Yaxiong Fan;Kunpeng Xu;Han Wang","doi":"10.1109/JSTARS.2024.3472096","DOIUrl":"https://doi.org/10.1109/JSTARS.2024.3472096","url":null,"abstract":"Accurate estimation of forest aboveground biomass (AGB) is crucial for research on terrestrial carbon cycling and global climate change. In this study, we introduce an improved approach for estimating forest AGB combining P-band and X-band interferometric synthetic aperture radar (InSAR) data. Forest AGB was estimated by combining unbiased forest height and volume backscatter intensity. For forest height, a multilayer model and subaperture decomposition technology were used to remove the penetration bias of the X-band and reduce the effects of forest scatterers on the extraction of a pure understory terrain phase based on P-band, respectively. For volume backscatter intensity, a ground cancellation algorithm based on P-band InSAR was used to eliminate ground scattering contributions unrelated to forest AGB. The proposed method was validated using airborne P-band InSAR data and spaceborne X-band InSAR data gathered over the study area on the Saihanba Forest Farm in Hebei, China. The unbiased forest height and volume backscatter intensity had stronger correlations with forest AGB than estimates derived from unimproved features. The proposed method returned high-precision estimates of forest AGB with an accuracy of 83.73%, an improvement of 8.80% over an estimate derived from unoptimized features. Additionally, AGB estimates combined with forest height and backscatter intensity were greater than those based on a single feature, with the contribution of the former is greater than that of the latter.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"17 ","pages":"17876-17889"},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10702464","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detection of Seismic Microwave Radiation Anomalies in Snow-Covered Mountainous Terrain: Insights From Two Recent Earthquakes in the Pamir–Tien Shan Region 在积雪覆盖的山区地形中探测地震微波辐射异常：帕米尔-天山地区最近两次地震的启示

IF 4.7 2区地球科学

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2024-10-01 DOI: 10.1109/JSTARS.2024.3472045

Feng Jing;Meng Jiang;Ramesh P. Singh

{"title":"Detection of Seismic Microwave Radiation Anomalies in Snow-Covered Mountainous Terrain: Insights From Two Recent Earthquakes in the Pamir–Tien Shan Region","authors":"Feng Jing;Meng Jiang;Ramesh P. Singh","doi":"10.1109/JSTARS.2024.3472045","DOIUrl":"https://doi.org/10.1109/JSTARS.2024.3472045","url":null,"abstract":"When earthquakes occur in high-mountain areas during the winter season, the epicentral region is often covered by a snow layer, which can be either thin or thick. The presence of snow and/or ice layers affects the detection of thermal anomalies associated with seismic signals. Taking into account the penetration capabilities of microwaves, microwave brightness temperature data were analyzed by using the index of microwave radiation anomaly to study the response of the epicentral region associated with two recent strong earthquakes in Central Asia, which occurred in snow-covered mountainous areas. Increased microwave radiation was observed within one week prior to the earthquakes. By conducting a comparative analysis of different frequencies and a comprehensive examination of meteorological parameters, we distinguished anomalies caused by tectonic activity from those induced by atmospheric water vapor. A robustness analysis from the periods of seismic tranquility and seismic disturbance has been conducted to validate our results. Our findings suggest that regions with less snow cover or shallow snow depth may exhibit high sensitivity to seismic microwave radiation anomalies in high-altitude mountainous areas during the cold season, which can be detected through passive microwave remote sensing. Combined with a further analysis from microwave polarization difference index and distribution of regional lithology, we proposed that the theory of positive holes may be the dominant mechanism for enhanced microwave radiation.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"17 ","pages":"18156-18166"},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10702460","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142452754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Kriging-Based Atmospheric Phase Screen Compensation Incorporating Time-Series Similarity in Ground-Based Radar Interferometry 基于克里金法的大气相位屏补偿，在地基雷达干涉测量中纳入时间序列相似性

IF 4.7 2区地球科学

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2024-10-01 DOI: 10.1109/JSTARS.2024.3469158

Yuta Izumi;Giovanni Nico;Othmar Frey;Simone Baffelli;Irena Hajnsek;Motoyuki Sato

引用次数: 0