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Why Does GRSM Require the Submission of White Papers? [From the Editor] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-07-12 Paolo Gamba
As you have already guessed from the title, and in line with my editorial in the March 2023 issue, I will use my space here to address two different points. First, the reader will find a summary of the contents of this issue, which is useful to those who would like to quickly navigate the issue and read only what they are interested in. The second part of this editorial will be devoted instead to better
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Letter From the President [President’s Message] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-07-13 Mariko Burgin
Hello and nice to see you again! My name is Mariko Burgin, and I am the IEEE Geoscience and Remote Sensing Society (GRSS) President. You can reach me at president@ieee-grss.org and @GRSS_President on Twitter.
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Taking Artificial Intelligence Into Space Through Objective Selection of Hyperspectral Earth Observation Applications: To bring the “brain” close to the “eyes” of satellite missions IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-07-12 Agata M. Wijata, Michel-François Foulon, Yves Bobichon, Raffaele Vitulli, Marco Celesti, Roberto Camarero, Gianluigi Di Cosimo, Ferran Gascon, Nicolas Longépé, Jens Nieke, Michal Gumiela, Jakub Nalepa
Recent advances in remote sensing hyperspectral imaging and artificial intelligence (AI) bring exciting opportunities to various fields of science and industry that can directly benefit from in-orbit data processing. Taking AI into space may accelerate the response to various events, as massively large raw hyperspectral images (HSIs) can be turned into useful information onboard a satellite; hence
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Onboard Information Fusion for Multisatellite Collaborative Observation: Summary, challenges, and perspectives IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-07-12 Gui Gao, Libo Yao, Wenfeng Li, Linlin Zhang, Maolin Zhang
Onboard information fusion for multisatellites, which is based on spatial computing mode, can improve the satellites’ capability, such as the spatial–temporal coverage, detection accuracy, recognition confidence, position precision, and prediction precision for disaster monitoring, maritime surveillance, and other emergent or continuous persistent observing situations. First, we analyze the necessity
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AI Security for Geoscience and Remote Sensing: Challenges and future trends IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-07-12 Yonghao Xu, Tao Bai, Weikang Yu, Shizhen Chang, Peter M. Atkinson, Pedram Ghamisi
Recent advances in artificial intelligence (AI) have significantly intensified research in the geoscience and remote sensing (RS) field. AI algorithms, especially deep learning-based ones, have been developed and applied widely to RS data analysis. The successful application of AI covers almost all aspects of Earth-observation (EO) missions, from low-level vision tasks like superresolution, denoising
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Generative Artificial Intelligence and Remote Sensing: A perspective on the past and the future [Perspectives] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-07-12 Nirav Patel
The first phase of 2023 has been marked with an explosion of interest around generative AI systems, which generate content. This type of machine learning promises to enable the creation of synthetic data and outputs in many different modalities. OpenAI’s ChatGPT has certainly taken the world by storm and opened discourse on how the technology should be used.
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Analysis-Ready Data and FAIR-AI—Standardization of Research Collaboration and Transparency Across Earth-Observation Communities [Technical Committees] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-07-12 Dalton Lunga, Silvia Ullo, Ujjwal Verma, George Percivall, Fabio Pacifici, Ronny Hänsch
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
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REACT: A New Technical Committee for Earth Observation and Sustainable Development Goals [Technical Committees] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-07-12 Irena Hajnsek, Subit Chakrabarti, Andrea Donnellan, Rabia Munsaf Khan, Carlos López-Martínez, Ryo Natsuaki, Anthony Milne, Avik Bhattacharya, Praveen Pankajakshan, Pooja Shah, Muhammad Adnan Siddique
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
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Computer Vision for Earth Observation—The First IEEE GRSS Image Analysis and Data Fusion School [Technical Committees] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-07-12 Gemine Vivone, Dalton Lunga, Francescopaolo Sica, Gülşen Taşkin, Ujjwal Verma, Ronny Hänsch
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
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Not the Usual Editorial [From the Editor] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-03-31 Paolo Gamba
Readers of this magazine know that the IEEE Geoscience and Remote Sensing Magazine ( GRSM ) editorial usually summarizes the content of the issue, providing hints to the interested researchers and practitioners to make it easier to find the articles or topics they are looking for. Since this is my first editorial, however, I will ask for your patience because I would like to introduce myself and a
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Letter From the President [President’s Message] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-04-03 Mariko Burgin
Hello and nice to meet you! My name is Mariko Burgin and I am the incoming IEEE Geoscience and Remote Sensing Society (GRSS) president. You can reach me at president@ieee-grss.org and @GRSS_President on Twitter.
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The IEEE GRSS IDEA Committee: Championing Diversity in Adversity [Women in GRSS] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-03-31 Stephanie Tumampos, Shawn C. Kefauver
After more than two years of hard lockdowns and restricted mobility, the whole world carefully returns to normalcy. With this, the IEEE Geoscience and Remote Sensing Society (GRSS) Inspire, Develop, Empower, and Advance (IDEA) Committee took the opportunity to attend two conferences in person, continuing its campaign for inclusivity and diversity.
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MapInWild: A remote sensing dataset to address the question of what makes nature wild [Software and Data Sets] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-03-31 Burak Ekim, Timo T. Stomberg, Ribana Roscher, Michael Schmitt
The advancement in deep learning (DL) techniques has led to a notable increase in the number and size of annotated datasets in a variety of domains, with remote sensing (RS) being no exception [1] . Also, an increase in Earth observation (EO) missions and the easy access to globally available and free geodata have opened up new research opportunities. Although numerous RS datasets have been published
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The Third China International Synthetic Aperture Radar Symposium [Conference Reports] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-03-31 Hui Wang, Yushan Guo, Qiang Zhao
From 2 to 4 November 2022, the third China International Synthetic Aperture Radar (SAR) Symposium (CISS), sponsored by the Shanghai Institute of Satellite Engineering, was successfully held at the Jinjiang Metropolo Hotel Minhang, Shanghai. The CISS is an international academic conference with extensive authority, knowledge, and interaction. The symposium aims to build a high-level and international
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Geoinformation Harvesting From Social Media Data: A community remote sensing approach IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-02-20 Xiao Xiang Zhu, Yuanyuan Wang, Mrinalini Kochupillai, Martin Werner, Matthias Häberle, Eike Jens Hoffmann, Hannes Taubenböck, Devis Tuia, Alex Levering, Nathan Jacobs, Anna Kruspe, Karam Abdulahhad
As unconventional sources of geoinformation, massive imagery and text messages from open platforms and social media form a temporally quasi-seamless, spatially multiperspective stream, but with unknown and diverse quality. Due to its complementarity to remote sensing (RS) data, geoinformation from these sources offers promising perspectives, but harvesting is not trivial due to its data characteristics
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Introducing the December Issue [From the Editor] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-02-20 James L. Garrison
Welcome to the December 2022 issue of IEEE Geoscience and Remote Sensing Magazine with the theme of “Radar and Data: New Techniques and Algorithms.” This is my last issue as editor-in-chief. I have thoroughly enjoyed serving the Society in this capacity over the last five years and take great pride in what the magazine has become. The latest Journal Citation Reports, for example, gives us an impact
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Strengthening Connections Within GRSS [President’s Message] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-02-20 David Kunkee
I believe the past year has been a very important and transformative one for the IEEE Geoscience and Remote Sensing Society (GRSS). The Society continues to expand its influence in several ways, including Society initiatives, membership growth, journal submissions, and outreach. But perhaps the most important transformation has been the many in-person events we have been able to have in 2022 compared
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Report on the IEEE GRSS Workshop on Remote Sensing Data Management Technologies in Geoscience 2022 [Technical Committees] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-02-20 Dai-Hai Ton That, Priya Deshpande, Khalid Belhajjame, Muthukumaran Ramasubramanian, Vishal Perekadan, Nishan Pantha, Todd Mahood, Kesheng Wu
In recognition of emerging new data management technologies, the IEEE Earth Science Informatics (ESI) Technical Committee (TC) recently formed a new Working Group on Databases in Remote Sensing (DBRS). This is a report about the first workshop organized by the DBRS-WG to gather information about technologies that could effectively store, query, search, and analyze remote sensing data. This workshop
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Protection of Earth Observation Satellites From Radio-Frequency Interference: Policies and practices [Perspectives] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-02-20 Luis Pedro, Manuel Sá, Rui Fernandes, Flávio Jorge, Sandro Mendonça
Carrying onboard remote sensing systems, Earth observation (EO) satellites provide unique global, systematic, and consistent space-based measurements of natural and man-made phenomena. Measurements can be produced on atmospheric, surface, and subsurface characteristics, properties, and constituents as well as other indicators and related data, enabling comparisons in time and across different parts
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Explainable, Physics-Aware, Trustworthy Artificial Intelligence: A paradigm shift for synthetic aperture radar IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-02-03 Mihai Datcu, Zhongling Huang, Andrei Anghel, Juanping Zhao, Remus Cacoveanu
The recognition or understanding of the scenes observed with a synthetic aperture radar (SAR) system requires a broader range of cues beyond the spatial context. These encompass but are not limited to the imaging geometry, imaging mode, properties of the Fourier spectrum of the images, or behavior of the polarimetric signatures. In this article, we propose a change of paradigm for explainability in
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Tensor Decompositions for Hyperspectral Data Processing in Remote Sensing: A comprehensive review IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-02-02 Minghua Wang, Danfeng Hong, Zhu Han, Jiaxin Li, Jing Yao, Lianru Gao, Bing Zhang, Jocelyn Chanussot
Owing to the rapid development of sensor technology, hyperspectral (HS) remote sensing (RS) imaging has provided a significant amount of spatial and spectral information for the observation and analysis of Earth’s surface at a distance of data acquisition devices. The recent advancement and even revolution of HS RS techniques offer opportunities to realize the potential of various applications while
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Unmanned Aerial Vehicle Remote Sensing for Antarctic Research: A review of progress, current applications, and future use cases IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2023-01-18 Yanjun Li, Gang Qiao, Sergey Popov, Xiangbin Cui, Igor V. Florinsky, Xiaohan Yuan, Lijuan Wang
Antarctica has been significantly influenced by global climate change. Owing to the spatiotemporal limitations of existing datasets, budgetary constraints, logistical challenges, and adverse temperature and climatic conditions of Antarctica, researchers face great challenges. Unmanned aerial vehicles (UAVs) have helped to solve this issue because they can collect high-resolution spatiotemporal data
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Sparse Synthetic Aperture Radar Imaging From Compressed Sensing and Machine Learning: Theories, applications, and trends IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-12-01 Gang Xu, Bangjie Zhang, Hanwen Yu, Jianlai Chen, Mengdao Xing, Wei Hong
Synthetic aperture radar (SAR) image formation can be treated as a class of ill-posed linear inverse problems, and the resolution is limited by the data bandwidth for traditional imaging techniques via matched filter (MF). The sparse SAR imaging technology using compressed sensing (CS) has been developed for enhanced performance, such as superresolution, feature enhancement, etc. More recently, sparse
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FSSCat: The Federated Satellite Systems 3Cat Mission: Demonstrating the capabilities of CubeSats to monitor essential climate variables of the water cycle [Instruments and Missions] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-11-30 Adriano Camps, Joan Francesc Munoz-Martin, Joan Adrià Ruiz-de-Azua, Lara Fernandez, Adrian Perez-Portero, David Llavería, Christoph Herbert, Miriam Pablos, Alessandro Golkar, Antonio Gutiérrez, Carlos António, Jorge Bandeiras, Jorge Andrade, David Cordeiro, Simone Briatore, Nicola Garzaniti, Fabio Nichele, Raffaele Mozzillo, Alessio Piumatti, Margherita Cardi, Marco Esposito, Chris van Dijk, Nathan
The Federated Satellite Systems/ 3 Cat-5 (FSSCat) mission was the winner of the European Space Agency (ESA) Sentinel Small Satellite (S 3 ) Challenge and overall winner of the 2017 Copernicus Masters competition. It consisted of two six-unit CubeSats. The Earth observation payloads were 1) the Flexible Microwave Payload 2 (FMPL-2) onboard 3 Cat-5/A, an L-band microwave radiometer and GNSS reflectometer
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Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised Learning [Technical Committees] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-11-21 Ronny Hänsch, Claudio Persello, Gemine Vivone, Javiera Castillo Navarro, Alexandre Boulch, Sebastien Lefevre, Bertrand Le Saux
The Image Analysis and Data Fusion (IADF) Technical Committee (TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) has been organizing the annual Data Fusion Contest (DFC) since 2006. The contest promotes the development of methods for extracting geospatial information from large-scale, multisensor, multimodal, and multitemporal data. It aims to propose new problem settings that are challenging
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Earth Observation and Artificial Intelligence: Understanding emerging ethical issues and opportunities IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-11-18 Mrinalini Kochupillai, Matthias Kahl, Michael Schmitt, Hannes Taubenböck, Xiao Xiang Zhu
Ethics is a central and growing concern in all applications utilizing artificial intelligence (AI). Earth observation (EO) and remote sensing (RS) research relies heavily on both big data and AI or machine learning (ML). While this reliance is not new, with increasing image resolutions and the growing number of EO/RS use cases that have a direct impact on governance, policy, and the lives of people
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Front cover IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-11-02
Presents the front cover for this issue of the publication.
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Table of Contents IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-11-02
Presents the table of contents for this issue of the publication.
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Staff list IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-11-02
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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To Travel or Not to Travel: The Hybrid Conference Era [President’s Message] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-11-02 David Kunkee
This year it is nice to once again be writing the September message having just returned from the annual IEEE Geoscience and Remote Sensing Society (GRSS) flagship conference, the IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IGARSS was held in Kuala Lumpur, Malaysia, at the Kuala Lumpur Conference Center, where we enjoyed a week of technical sessions held both in person and
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Welcome to the September 2022 Issue of IEEE Geoscience and Remote Sensing Magazine! [From the Guest Editors] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-11-02 James L. Garrison
I have just returned from Malaysia, where I attended the 2022 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), my first international travel since 2019. Although the conference was presented in hybrid form and had significant online participation, I very much appreciated the opportunity to see talks “live” and interact with colleagues. For more on IGARSS, and future directions for
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IGARSS 2022 in Kuala Lumpur, Malaysia: Impressions of the First Days [Conference Reports] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-11-02 Alberto Moreira, Jasmeet Judge, Francesca Bovolo, Antonio Plaza
Presents information on the above named conference.
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Investigating Different Data-Traceability Approaches to Prevent Data Swamps [Perspectives] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-11-02 Rahul Ramachandran, Manil Maskey, Chris Lynnes, Arun John, Tathagata Mukherjee
Science users typically obtain data from authoritative or trusted sources referred to as repositories . An authoritative source is defined as an entity that is approved by a legal entity to develop or manage data for a specific purpose [4] , [5] . Different government agencies generating Earth observation (EO) data are one example. An authoritative source can also be an actively managed repository
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TechRxiv: Share Your Preprint Research With the World! IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-11-02
Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
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Digital Beamforming for Spaceborne Reflector-Based Synthetic Aperture Radar, Part 2: Ultrawide-swath imaging mode IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-10-28 Marwan Younis, Felipe Queiroz De Almeida, Michelangelo Villano, Sigurd Huber, Gerhard Krieger, Alberto Moreira
Utilizing digital beamforming (DBF) techniques in conjunction with the feed array of large deployable reflector antennas can boost the performance of synthetic aperture radar (SAR) systems. Multichannel SAR overcomes the constraints of classical single-channel SAR, allowing for wide-swath imaging at fine azimuth resolution. Part 1 of this tutorial provided an introduction to the instrument structure
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Subsurface Propagation Velocity Estimation Methods in Ground-Penetrating Radar: A review IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-09-26 Swarna Laxmi Panda, Subrata Maiti, Upendra Kumar Sahoo
Velocity estimation is one of the most crucial tasks in ground-penetrating radar (GPR) surveys. It is an integral part of GPR data analysis for interpreting GPR-generated images of subsurface media. Error in velocity estimation leads to wrong interpretations of underground scenarios. Since the beginning of GPR development, researchers have proposed various velocity estimation procedures. In this article
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State of the Art: High-Performance and High-Throughput Computing for Remote Sensing Big Data IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-09-22 Sheng Zhang, Yong Xue, Xiran Zhou, Xiaopeng Zhang, Wenhao Liu, Kaiyuan Li, Runze Liu
In recent years, with the increasing number of Earth observation satellites and the popularization and application of various sensors, remote sensing data have shown a rapid growth trend and present typical big data characteristics. The continuous enrichment of remote sensing data has provided large information resources for Earth science research and promoted the wide application of remote sensing
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Self-Supervised Learning in Remote Sensing: A review IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-09-05 Yi Wang, Conrad M. Albrecht, Nassim Ait Ali Braham, Lichao Mou, Xiao Xiang Zhu
In deep learning research, self-supervised learning (SSL) has received great attention, triggering interest within both the computer vision and remote sensing communities. While there has been big success in computer vision, most of the potential of SSL in the domain of Earth observation remains locked. In this article, we provide an introduction to and a review of the concepts and latest developments
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Deep Learning-Based Object Tracking in Satellite Videos: A comprehensive survey with a new dataset IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-09-02 Yuxuan Li, Licheng Jiao, Zhongjian Huang, Xin Zhang, Ruohan Zhang, Xue Song, Chenxi Tian, Zixiao Zhang, Fang Liu, Shuyuan Yang, Biao Hou, Wenping Ma, Xu Liu, Lingling Li
As a fundamental task for research in satellite videos (SVs), object tracking is used to track the target of interest in traffic evaluation, military security, and so forth. The current satellite technology in the remote sensing field makes it possible to track moving targets with a relatively high frame rate and image resolution. However, objects under this special view are often small and blurry
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Phase Synchronization Techniques for Bistatic and Multistatic Synthetic Aperture Radar: Accounting for frequency offset IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-08-03 Da Liang, Heng Zhang, Kaiyu Liu, Dacheng Liu, Robert Wang
Bistatic synthetic aperture radar (BiSAR) and multistatic (MuSAR) systems with a separated transmitter and receiver have been widely used for remote sensing. However, frequency deviation among different oscillators will cause a modulated phase error on the echo signal. Therefore, phase synchronization is one of the most critical problems to be addressed in BiSAR/MuSAR systems. In this article, we review
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Machine Learning in Pansharpening: A benchmark, from shallow to deep networks IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-07-28 Liang-jian Deng, Gemine Vivone, Mercedes E. Paoletti, Giuseppe Scarpa, Jiang He, Yongjun Zhang, Jocelyn Chanussot, Antonio Plaza
Machine learning (ML) is influencing the literature in several research fields, often through state-of-the-art approaches. In the past several years, ML has been explored for pansharpening, i.e., an image fusion technique based on the combination of a multispectral (MS) image, which is characterized by its medium/low spatial resolution, and higher-spatial-resolution panchromatic (PAN) data. Thus, ML
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Compact Polarimetric Synthetic Aperture Radar for Target Detection: A review IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-07-20 Linlin Zhang, Gui Gao, Chao Chen, Sheng Gao, Libo Yao
In recent years, compact polarimetric (CP) SAR has been widely used for Earth target detection as a means to balance system resources and target information. Although there has been a large number of related researches, an in-depth review of CP SAR, from basic principles to target detection methods, is lacking. This article aims to provide a review of this area. In this article, we review the historical
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Front cover IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-07-13
Presents the front cover for this issue of the publication.
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TOC IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-07-13
Presents the table of contents for this issue of the publication.
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Staff list IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-07-13
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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Introducing the June Issue [From the Editor] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-07-13 James L. Garrison
Welcome to the June 2022 issue of IEEE Geoscience and Remote Sensing Magazine (GRSM)! Our theme for this issue is “Building Upon a Legacy of Remote Sensing to Advance Our Future.” Supporting this theme, the 12 features in this issue cover instruments and techniques that build upon the long heritage of societal benefits from remote sensing as well as introduce some new and innovative ideas taking the
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GRSS Community Engagement [President’s Message] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-07-13 David Kunkee
On behalf of the IEEE Geoscience and Remote Sensing Society (GRSS), I would like to invite you to participate in IGARSS 2022, our annual International Geoscience and Remote Sensing Symposium. This year’s symposium will be held in Kuala Lumpur, Malaysia, from 17 to 22 July using a hybrid conference format. The theme for this year’s meeting will focus on “Preserving Our Heritage, Enabling Our Future
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Coupling Model- and Data-Driven Methods for Remote Sensing Image Restoration and Fusion: Improving physical interpretability IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-07-13 Huanfeng Shen, Menghui Jiang, Jie Li, Chenxia Zhou, Qiangqiang Yuan, Liangpei Zhang
In the fields of image restoration and image fusion, model- and data-driven methods are the two representative frameworks. However, both approaches have their respective advantages and disadvantages. Model-driven techniques consider the imaging mechanism, which is deterministic and theoretically reasonable; however, they cannot easily model complicated nonlinear problems. Data-driven schemes have a
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Reimagining the Surface Water and Ocean Topography Mission as the “Landsat” of Surface Water [Perspective] IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-07-13 Faisal Hossain
The Surface Water Ocean Topography (SWOT) mission, jointly developed by NASA and French Space Agency (CNES) with contributions from the Canadian and U.K. space agencies, and planned for launch in 2022, is designed to provide a spatially distributed and high-frequency measurement of water elevation data for the hydrology and oceanography communities for the first time [1], [2]. By virtue of its novel
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Remote Sensing for Subsurface and Deeper Oceans: An overview and a future outlook IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-07-11 Lingsheng Meng, Xiao-Hai Yan
The oceans are an important component of Earth’s system and play a crucial role in climate change through the coupled atmosphere–ocean process. Observations are fundamental for studying and understanding the oceans. While in situ measurements are limited, satellites can remotely monitor oceans continuously for extended periods, with broad spatial coverages. These sustained in situ and remotely sensed
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Close-Range Remote Sensing of Forests: The state of the art, challenges, and opportunities for systems and data acquisitions IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-06-16 Xinlian Liang, Antero Kukko, Ivan Balenović, Ninni Saarinen, Samuli Junttila, Ville Kankare, Markus Holopainen, Martin Mokroš, Peter Surový, Harri Kaartinen, Luka Jurjević, Eija Honkavaara, Roope Näsi, Jingbin Liu, Markus Hollaus, Jiaojiao Tian, Xiaowei Yu, Jie Pan, Shangshu Cai, Juho-Pekka Virtanen, Yunsheng Wang, Juha Hyyppä
Remote sensing-based forest investigation and monitoring have become more affordable and applicable in the past few decades. The current bottleneck limiting practical use of the vast volume of remote sensing data lies in the lack of affordable, reliable, and detailed field references, which are required for necessary calibrations of satellite and aerial data and calibrations of relevant allometric
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Deep Learning for Downscaling Remote Sensing Images: Fusion and super-resolution IEEE Geosci. Remote Sens. Mag. (IF 14.6) Pub Date : 2022-06-02 Maria Sdraka, Ioannis Papoutsis, Bill Psomas, Konstantinos Vlachos, Konstantinos Ioannidis, Konstantinos Karantzalos, Ilias Gialampoukidis, Stefanos Vrochidis
The past few years have seen an accelerating integration of deep learning (DL) techniques into various remote sensing (RS) applications, highlighting their power to adapt and achieving unprecedented advancements. In the present review, we provide an exhaustive exploration of the DL approaches proposed specifically for the spatial downscaling of RS imagery. A key contribution of our work is the presentation