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A 3-D scattering centre model-based SAR target recognition method using multi-level region matching 基于三维散射中心模型的合成孔径雷达目标识别方法（使用多级区域匹配
IF 2.3 4区 地球科学
Remote Sensing Letters Pub Date : 2024-02-07 DOI: 10.1080/2150704x.2024.2313609
Baiyuan Ding, Ao Zhang, Rui Li
{"title":"A 3-D scattering centre model-based SAR target recognition method using multi-level region matching","authors":"Baiyuan Ding, Ao Zhang, Rui Li","doi":"10.1080/2150704x.2024.2313609","DOIUrl":"https://doi.org/10.1080/2150704x.2024.2313609","url":null,"abstract":"A 3-D scattering centre model-based synthetic aperture radar (SAR) automatic target recognition (ATR) method is proposed. Multi-level dominant scattering areas (DSAs) are generated from the test sa...","PeriodicalId":49132,"journal":{"name":"Remote Sensing Letters","volume":"13 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139772684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 0
Hyperspectral image classification using a double-branch hierarchical partial convolution network 使用双分支分层部分卷积网络进行高光谱图像分类
IF 2.3 4区 地球科学
Remote Sensing Letters Pub Date : 2024-02-06 DOI: 10.1080/2150704x.2024.2311784
Zijian Sheng, Guo Cao, Hao Shi, Youqiang Zhang
{"title":"Hyperspectral image classification using a double-branch hierarchical partial convolution network","authors":"Zijian Sheng, Guo Cao, Hao Shi, Youqiang Zhang","doi":"10.1080/2150704x.2024.2311784","DOIUrl":"https://doi.org/10.1080/2150704x.2024.2311784","url":null,"abstract":"Recently, convolutional neural network (CNN) and Transformer have been successfully applied in hyperspectral image (HSI) classification. Despite their success, some challenges persist. Popular HSI ...","PeriodicalId":49132,"journal":{"name":"Remote Sensing Letters","volume":"22 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139772675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 0
Comparative analysis of bias correction methods for IMERG V06 precipitation products: case study in Guangxi, China IMERG V06 降水产品纠偏方法比较分析：中国广西案例研究
IF 2.3 4区 地球科学
Remote Sensing Letters Pub Date : 2024-02-01 DOI: 10.1080/2150704x.2024.2307321
Meiqing Yang, Qian Ni, Xiang Diao, Qiang Xiong
{"title":"Comparative analysis of bias correction methods for IMERG V06 precipitation products: case study in Guangxi, China","authors":"Meiqing Yang, Qian Ni, Xiang Diao, Qiang Xiong","doi":"10.1080/2150704x.2024.2307321","DOIUrl":"https://doi.org/10.1080/2150704x.2024.2307321","url":null,"abstract":"This study investigates the effectiveness of three bias correction methods: linear scaling (LS), local intensity scaling (LOCI), and quantile mapping (QM) in correcting the bias of Integrated Multi...","PeriodicalId":49132,"journal":{"name":"Remote Sensing Letters","volume":"16 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139668912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 0
Range current retrieval fromsentinel-1 SAR ocean product based on deep learning 基于深度学习的圣天诺-1 号合成孔径雷达海洋产品范围海流检索
IF 2.3 4区 地球科学
Remote Sensing Letters Pub Date : 2024-01-27 DOI: 10.1080/2150704x.2024.2305176
Weizeng Shao, Yuhang Zhou, Yuyi Hu, Yan Li, Yashi Zhou, Qingjun Zhang
{"title":"Range current retrieval fromsentinel-1 SAR ocean product based on deep learning","authors":"Weizeng Shao, Yuhang Zhou, Yuyi Hu, Yan Li, Yashi Zhou, Qingjun Zhang","doi":"10.1080/2150704x.2024.2305176","DOIUrl":"https://doi.org/10.1080/2150704x.2024.2305176","url":null,"abstract":"In this study, the feasibility of current retrieval from Sentinel-1 (S-1) synthetic aperture radar (SAR) in the radar look/range direction is investigated. S-1 Ocean (OCN) products acquired in inte...","PeriodicalId":49132,"journal":{"name":"Remote Sensing Letters","volume":"16 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139584369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 0
EMAFF-Net: an enhanced multi-scale attentive feature fusion network for building extraction from VHR remote sensing images EMAFF-Net：用于从 VHR 遥感图像中提取建筑物的增强型多尺度注意特征融合网络
IF 2.3 4区 地球科学
Remote Sensing Letters Pub Date : 2024-01-25 DOI: 10.1080/2150704x.2024.2305624
Lakshmi Vijayan, Akshara Preethy Byju
{"title":"EMAFF-Net: an enhanced multi-scale attentive feature fusion network for building extraction from VHR remote sensing images","authors":"Lakshmi Vijayan, Akshara Preethy Byju","doi":"10.1080/2150704x.2024.2305624","DOIUrl":"https://doi.org/10.1080/2150704x.2024.2305624","url":null,"abstract":"Automated building extraction is imperative for several geospatial applications such as monitoring disaster-affected buildings and urban planning. Existing deep learning (DL)-based building extract...","PeriodicalId":49132,"journal":{"name":"Remote Sensing Letters","volume":"218 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139584267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 0
Observations of water optical properties during red tide outbreaks off southeast Hokkaido by GCOM-C/SGLI: implications for the development of red tide algorithms 全球海洋观测系统-C/SGLI 对北海道东南部赤潮爆发期间海水光学特性的观测：对赤潮算法开发的影响
IF 2.3 4区 地球科学
Remote Sensing Letters Pub Date : 2024-01-18 DOI: 10.1080/2150704x.2024.2302948
Eko Siswanto, Jutarak Luang-on, Kazunori Ogata, Hiroto Higa, Mitsuhiro Toratani
{"title":"Observations of water optical properties during red tide outbreaks off southeast Hokkaido by GCOM-C/SGLI: implications for the development of red tide algorithms","authors":"Eko Siswanto, Jutarak Luang-on, Kazunori Ogata, Hiroto Higa, Mitsuhiro Toratani","doi":"10.1080/2150704x.2024.2302948","DOIUrl":"https://doi.org/10.1080/2150704x.2024.2302948","url":null,"abstract":"A severe red tide event, caused primarily by dinoflagellate Karenia selliformis, occurred during the autumn of 2021 in the waters off southeast Hokkaido and resulted in damage of $70 million to fis...","PeriodicalId":49132,"journal":{"name":"Remote Sensing Letters","volume":"32 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139506483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 0
Adaptive multimodal feature fusion with frequency domain gate for remote sensing object detection 利用频域门进行自适应多模态特征融合，用于遥感物体探测
IF 2.3 4区 地球科学
Remote Sensing Letters Pub Date : 2024-01-17 DOI: 10.1080/2150704x.2024.2305177
Xu Sun, Yinhui Yu, Qing Cheng
{"title":"Adaptive multimodal feature fusion with frequency domain gate for remote sensing object detection","authors":"Xu Sun, Yinhui Yu, Qing Cheng","doi":"10.1080/2150704x.2024.2305177","DOIUrl":"https://doi.org/10.1080/2150704x.2024.2305177","url":null,"abstract":"Fusing complementary information of visible and infrared radiation modalities can improve object detection performance for unmanned aerial vehicle (UAV) remote sensing images under insufficient ill...","PeriodicalId":49132,"journal":{"name":"Remote Sensing Letters","volume":"8 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139481788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 0
A discriminatory groups-based supervised band selection technique for hyperspectral image classification 用于高光谱图像分类的基于组的判别监督波段选择技术
IF 2.3 4区 地球科学
Remote Sensing Letters Pub Date : 2024-01-10 DOI: 10.1080/2150704x.2024.2302939
S. N. Chaudhri, S. K. Roy
{"title":"A discriminatory groups-based supervised band selection technique for hyperspectral image classification","authors":"S. N. Chaudhri, S. K. Roy","doi":"10.1080/2150704x.2024.2302939","DOIUrl":"https://doi.org/10.1080/2150704x.2024.2302939","url":null,"abstract":"","PeriodicalId":49132,"journal":{"name":"Remote Sensing Letters","volume":"46 2","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139440949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 0
Vertical structure of tropical cyclone precipitation over the North Indian Ocean: a spaceborne precipitation radar perspective 北印度洋热带气旋降水的垂直结构：空间降水雷达视角
IF 2.3 4区 地球科学
Remote Sensing Letters Pub Date : 2024-01-02 DOI: 10.1080/2150704x.2024.2302349
S. Prakash, M. Mohapatra
{"title":"Vertical structure of tropical cyclone precipitation over the North Indian Ocean: a spaceborne precipitation radar perspective","authors":"S. Prakash, M. Mohapatra","doi":"10.1080/2150704x.2024.2302349","DOIUrl":"https://doi.org/10.1080/2150704x.2024.2302349","url":null,"abstract":"","PeriodicalId":49132,"journal":{"name":"Remote Sensing Letters","volume":"60 8","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139452598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 0
A hybrid CNN–vision transformer structure for remote sensing scene classification 用于遥感场景分类的混合 CNN 视觉变换器结构
IF 2.3 4区 地球科学
Remote Sensing Letters Pub Date : 2024-01-02 DOI: 10.1080/2150704x.2024.2302348
Nan Li, Siyuan Hao, Kun Zhao
{"title":"A hybrid CNN–vision transformer structure for remote sensing scene classification","authors":"Nan Li, Siyuan Hao, Kun Zhao","doi":"10.1080/2150704x.2024.2302348","DOIUrl":"https://doi.org/10.1080/2150704x.2024.2302348","url":null,"abstract":"","PeriodicalId":49132,"journal":{"name":"Remote Sensing Letters","volume":"135 31","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139453050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 0
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