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

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.

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

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

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

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.

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

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

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.

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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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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

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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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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Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

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

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

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

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

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

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

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

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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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

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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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

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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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

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

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