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Better, Not Just More: Data-centric machine learning for Earth observation 更好，不仅仅是更多：以数据为中心的地球观测机器学习
IF 14.6 1区 地球科学
IEEE Geoscience and Remote Sensing Magazine Pub Date : 2024-10-31 DOI: 10.1109/mgrs.2024.3470986
Ribana Roscher, Marc Russwurm, Caroline Gevaert, Michael Kampffmeyer, Jefersson A. Dos Santos, Maria Vakalopoulou, Ronny Hänsch, Stine Hansen, Keiller Nogueira, Jonathan Prexl, Devis Tuia
{"title":"Better, Not Just More: Data-centric machine learning for Earth observation","authors":"Ribana Roscher, Marc Russwurm, Caroline Gevaert, Michael Kampffmeyer, Jefersson A. Dos Santos, Maria Vakalopoulou, Ronny Hänsch, Stine Hansen, Keiller Nogueira, Jonathan Prexl, Devis Tuia","doi":"10.1109/mgrs.2024.3470986","DOIUrl":"https://doi.org/10.1109/mgrs.2024.3470986","url":null,"abstract":"","PeriodicalId":48660,"journal":{"name":"IEEE Geoscience and Remote Sensing Magazine","volume":null,"pages":null},"PeriodicalIF":14.6,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142561943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
EarthNets: Empowering artificial intelligence for Earth observation EarthNets：增强地球观测人工智能的能力
IF 14.6 1区 地球科学
IEEE Geoscience and Remote Sensing Magazine Pub Date : 2024-10-23 DOI: 10.1109/mgrs.2024.3466998
Zhitong Xiong, Fahong Zhang, Yi Wang, Yilei Shi, Xiao Xiang Zhu
{"title":"EarthNets: Empowering artificial intelligence for Earth observation","authors":"Zhitong Xiong, Fahong Zhang, Yi Wang, Yilei Shi, Xiao Xiang Zhu","doi":"10.1109/mgrs.2024.3466998","DOIUrl":"https://doi.org/10.1109/mgrs.2024.3466998","url":null,"abstract":"","PeriodicalId":48660,"journal":{"name":"IEEE Geoscience and Remote Sensing Magazine","volume":null,"pages":null},"PeriodicalIF":14.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142488499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Remote Sensing-Based Algorithms for Estimating Evapotranspiration in Agricultural Systems: A systematic literature review 基于遥感的农业系统蒸散量估算算法：系统性文献综述
IF 14.6 1区 地球科学
IEEE Geoscience and Remote Sensing Magazine Pub Date : 2024-10-15 DOI: 10.1109/mgrs.2024.3469182
Wendel Kaian Mendonça Oliveira, Marcio Furlan Maggi, Luan Peroni Venancio, Claudio Leones Bazzi, Lúcia Helena Pereira Nóbrega, Adriane Silva De Mendonça Oliveira, Erivelto Mercante, Kelyn Schenatto
{"title":"Remote Sensing-Based Algorithms for Estimating Evapotranspiration in Agricultural Systems: A systematic literature review","authors":"Wendel Kaian Mendonça Oliveira, Marcio Furlan Maggi, Luan Peroni Venancio, Claudio Leones Bazzi, Lúcia Helena Pereira Nóbrega, Adriane Silva De Mendonça Oliveira, Erivelto Mercante, Kelyn Schenatto","doi":"10.1109/mgrs.2024.3469182","DOIUrl":"https://doi.org/10.1109/mgrs.2024.3469182","url":null,"abstract":"","PeriodicalId":48660,"journal":{"name":"IEEE Geoscience and Remote Sensing Magazine","volume":null,"pages":null},"PeriodicalIF":14.6,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142440013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
The High-Resolution Synthetic Aperture Radar System and Signal Processing Techniques: Current progress and future prospects 高分辨率合成孔径雷达系统和信号处理技术：当前进展与未来展望
IF 14.6 1区 地球科学
IEEE Geoscience and Remote Sensing Magazine Pub Date : 2024-10-01 DOI: 10.1109/mgrs.2024.3456444
YUNKAI DENG, WEIDONG YU, PEI WANG, DENGJUN XIAO, WEI WANG, KAIYU LIU, HENG ZHANG
{"title":"The High-Resolution Synthetic Aperture Radar System and Signal Processing Techniques: Current progress and future prospects","authors":"YUNKAI DENG, WEIDONG YU, PEI WANG, DENGJUN XIAO, WEI WANG, KAIYU LIU, HENG ZHANG","doi":"10.1109/mgrs.2024.3456444","DOIUrl":"https://doi.org/10.1109/mgrs.2024.3456444","url":null,"abstract":"","PeriodicalId":48660,"journal":{"name":"IEEE Geoscience and Remote Sensing Magazine","volume":null,"pages":null},"PeriodicalIF":14.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142362843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 Systematic Review and Assessment of Inverse Crop Parameter Modeling Based on Synthetic Aperture Radar Data: Research advances, existing problems, and future directions 基于合成孔径雷达数据的反作物参数建模系统回顾与评估》：研究进展、现有问题和未来方向
IF 14.6 1区 地球科学
IEEE Geoscience and Remote Sensing Magazine Pub Date : 2024-09-30 DOI: 10.1109/mgrs.2024.3454317
Rongkun Zhao, Shangrong Wu, Yun Shao, Mengdao Xing, Zhiqu Liu, Xuexiao Wu, Hong Cao, Peng Yang, Huajun Tang
{"title":"A Systematic Review and Assessment of Inverse Crop Parameter Modeling Based on Synthetic Aperture Radar Data: Research advances, existing problems, and future directions","authors":"Rongkun Zhao, Shangrong Wu, Yun Shao, Mengdao Xing, Zhiqu Liu, Xuexiao Wu, Hong Cao, Peng Yang, Huajun Tang","doi":"10.1109/mgrs.2024.3454317","DOIUrl":"https://doi.org/10.1109/mgrs.2024.3454317","url":null,"abstract":"","PeriodicalId":48660,"journal":{"name":"IEEE Geoscience and Remote Sensing Magazine","volume":null,"pages":null},"PeriodicalIF":14.6,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142360472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
Letter From the President [President’s Message] 总统致辞
IF 14.6 1区 地球科学
IEEE Geoscience and Remote Sensing Magazine Pub Date : 2024-09-24 DOI: 10.1109/mgrs.2024.3437791
Mariko Burgin
{"title":"Letter From the President [President’s Message]","authors":"Mariko Burgin","doi":"10.1109/mgrs.2024.3437791","DOIUrl":"https://doi.org/10.1109/mgrs.2024.3437791","url":null,"abstract":"","PeriodicalId":48660,"journal":{"name":"IEEE Geoscience and Remote Sensing Magazine","volume":null,"pages":null},"PeriodicalIF":14.6,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142317090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
GRSS Awards Presented at the IGARSS 2024 Banquet [Conference Reports] 2024 年 IGARSS 晚宴上颁发的 GRSS 奖项 [会议报告］
IF 14.6 1区 地球科学
IEEE Geoscience and Remote Sensing Magazine Pub Date : 2024-09-23 DOI: 10.1109/mgrs.2024.3438611
Francesca Bovolo, Jaya Sreevalsan-Nair, Antonio Plaza, Hanwen Yu, Alberto Moreira
{"title":"GRSS Awards Presented at the IGARSS 2024 Banquet [Conference Reports]","authors":"Francesca Bovolo, Jaya Sreevalsan-Nair, Antonio Plaza, Hanwen Yu, Alberto Moreira","doi":"10.1109/mgrs.2024.3438611","DOIUrl":"https://doi.org/10.1109/mgrs.2024.3438611","url":null,"abstract":"Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.","PeriodicalId":48660,"journal":{"name":"IEEE Geoscience and Remote Sensing Magazine","volume":null,"pages":null},"PeriodicalIF":14.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142313816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
The Fourth China International Synthetic Aperture Radar Symposium [Conference Reports] 第四届中国国际合成孔径雷达研讨会[会议报告]
IF 14.6 1区 地球科学
IEEE Geoscience and Remote Sensing Magazine Pub Date : 2024-09-23 DOI: 10.1109/mgrs.2024.3371933
Hui Wang, Yongqi Wang, Shaohui Mei, Zhaokai Pan, Hanwen Yu, Qiang Zhao
{"title":"The Fourth China International Synthetic Aperture Radar Symposium [Conference Reports]","authors":"Hui Wang, Yongqi Wang, Shaohui Mei, Zhaokai Pan, Hanwen Yu, Qiang Zhao","doi":"10.1109/mgrs.2024.3371933","DOIUrl":"https://doi.org/10.1109/mgrs.2024.3371933","url":null,"abstract":"Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.","PeriodicalId":48660,"journal":{"name":"IEEE Geoscience and Remote Sensing Magazine","volume":null,"pages":null},"PeriodicalIF":14.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142313817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
HexaLCSeg: A historical benchmark dataset from Hexagon satellite images for land cover segmentation [Software and Data Sets] HexaLCSeg：来自 Hexagon 卫星图像的历史基准数据集，用于土地覆被分割 [软件和数据集]
IF 14.6 1区 地球科学
IEEE Geoscience and Remote Sensing Magazine Pub Date : 2024-09-23 DOI: 10.1109/mgrs.2024.3394248
Elif Sertel, Mustafa Erdem Kabadayi, Gafur Semi Sengul, Ilay Nur Tumer
{"title":"HexaLCSeg: A historical benchmark dataset from Hexagon satellite images for land cover segmentation [Software and Data Sets]","authors":"Elif Sertel, Mustafa Erdem Kabadayi, Gafur Semi Sengul, Ilay Nur Tumer","doi":"10.1109/mgrs.2024.3394248","DOIUrl":"https://doi.org/10.1109/mgrs.2024.3394248","url":null,"abstract":"Historical land cover (LC) maps are significant geospatial data sources used to understand past land characteristics and accurately determine the long-term land changes that provide valuable insights into the interactions between human activities and the environment over time. This article introduces a novel open LC benchmark dataset generated from very high spatial resolution historical Hexagon (KH-9) reconnaissance satellite images to be used in deep learning (DL)-based image segmentation tasks. This new benchmark dataset, which includes very high-resolution (VHR) mono-band Hexagon images of several Turkish and Bulgarian territories from the 1970s and 1980s, covers a large geographic area. Our dataset includes eight LC classes inspired by the European Space Agency (ESA) WorldCover project except for the tree class, which we divided into subclasses, namely agricultural fruit trees and other trees. We implemented widely used U-Net++ and DeepLabv3+ segmentation architectures with appropriate hyperparameters and backbone structures to demonstrate the versatility and impact of our HexaLCSeg dataset and to compare the performance of these models for accurate and fast LC mapping of past terrain conditions. We achieved the highest accuracy using U-Net++ with an SE-ResNeXt50 backbone and obtained an F1-score of 0.8804. The findings of this study can be applied to different geographical regions with similar Hexagon images, providing valuable contributions to the field of remote sensing and LC mapping. Our dataset, related source codes, and pretrained models are available at <uri xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/RSandAI/HexaLCSeg</uri> and <uri xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://doi.org/10.5281/zenodo.11005344</uri>\u0000.","PeriodicalId":48660,"journal":{"name":"IEEE Geoscience and Remote Sensing Magazine","volume":null,"pages":null},"PeriodicalIF":14.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142313818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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
IEEE Tech RXIV: Share Your Preprint Research with the world! IEEE Tech RXIV：与世界分享您的预印本研究成果！
IF 14.6 1区 地球科学
IEEE Geoscience and Remote Sensing Magazine Pub Date : 2024-09-23 DOI: 10.1109/mgrs.2024.3455659
{"title":"IEEE Tech RXIV: Share Your Preprint Research with the world!","authors":"","doi":"10.1109/mgrs.2024.3455659","DOIUrl":"https://doi.org/10.1109/mgrs.2024.3455659","url":null,"abstract":"","PeriodicalId":48660,"journal":{"name":"IEEE Geoscience and Remote Sensing Magazine","volume":null,"pages":null},"PeriodicalIF":14.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142313499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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