Presents the front cover for this issue of the publication.

Advertisement.

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Welcome to the September 2021 issue of IEEE Geoscience and Remote Sensing Magazine ( GRSM )! We have a number of feature articles in this issue, covering topics ranging from a tutorial on synthetic aperture radar (SAR) beamforming, to a review of the Earth-observation constellation, to several articles on techniques for processing various types of remote sensing data. These will be followed by a report

Advertisement.

About this time, I expected to be returning from the IEEE International Geoscience and Remote Sensing Symposium (IGARSS) that was to be held in Brussels, Belgium, with many stories about the trip and thinking about discussions I had with colleagues. However, once again, we found ourselves attending the conference online and, in many cases, recording presentations that originally were intended to be

Presents information on the GRSS society IGARSS 2021 Symposium.

Presents information on the GRSS echnical Committee on Image Analysis and Data Fusion.

Reports on GRSS society chapter activities and meetings.

This article presents the multimodal BigEarthNet (BigEarthNet-MM) benchmark archive consisting of 590,326 pairs of Sentinel-1 and Sentinel-2 image patches to support deep learning (DL) studies in multimodal, multilabel remote sensing (RS) image retrieval and classification. Each pair of patches in BigEarthNet-MM is annotated with multilabels provided by the CORINE Land Cover (CLC) map of 2018 based

Advertisement.

Advertisement.

Advertisement.

In past years, we have witnessed the fields of geosciences and remote sensing and artificial intelligence (AI) become closer. Thanks to the massive availability of observational data, improved simulations, and algorithmic advances, these disciplines have found common objectives and challenges to help advance the modeling and understanding of the Earth system. Despite such great opportunities, we have

Presents information on the GRSS Remote Sensing Code Library (RSCL).

The articles in this special section focus on recent progress in developing artificial intelligence and machine learning methodologies.

Presents information on the work of the GRSS Instrumentation and Future Technologies Technical Committee Working Groups.

Presents information on the work of the GRSS Instrumentation and Future Technologies Technical Committee Working Groups.

Reports on the journal impact factor for the IEEE Geoscience and Remote Sensing Magazine.

Presents the front cover for this issue of the publication.

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Presents the introductory editorial for this issue of the publication.

Presents the President’s message for this issue of the publication.

We discuss best practices for developing multilanguage remote sensing training. Our discussion is based on the approach developed by the NASA-funded Applied Remote Sensing Training (ARSET) program for Spanish-speaking countries. Best practices include incorporating Spanish language at all phases of the training cycle, from outreach activities to program evaluation, and full integration of Spanish-speaking

In this era of environmental challenges, such as global climate change and local and regional air pollution, it is increasingly important that students develop skills to understand and address interdisciplinary scientific issues related to atmospheric studies. Involving students in optical remote sensing research projects is a high-impact educational strategy that can foster student interest and persistence

Reports on GRSS society summer schools in 2020.

Presents information on various GRSS Society chapters.

Tracking the movement of natural surface features across the time intervals between successive images has gained widespread acceptance for mapping ocean surface currents (OSCs). The 500-m and 1-h spatiotemporal resolutions of the Geostationary Ocean Color Imager (GOCI), launched in 2010, are ideal for observing the dynamics of mesoscale eddies and the diurnal changes dominated by tides. All reported

The global Earth-observing satellite constellation (EOSC) is a major international asset that has developed since 1960 with a dramatic growth in size and complexity in the recent past. This high-level review article takes stock and summarizes, from a meteorological perspective, the current constellation’s capabilities, in order to increase awareness, document the value chain of satellite data from

Synthetic aperture radar (SAR) images are affected by a spatially correlated and signal-dependent noise called speckle, which is very severe and may hinder image exploitation. Despeckling is an important task that aims to remove such noise so as to improve the accuracy of all downstream image processing tasks. The first despeckling methods date back to the 1970s, and several model-based algorithms

Interferometric synthetic aperture radar (InSAR) is a radar technique widely used in geodesy and remote sensing applications, e.g., topography reconstruction and subsidence estimation. Phase unwrapping (PU) is one of the key procedures of InSAR signal processing. Artificial intelligence (AI) techniques have proven to be potentially powerful in many fields and have been introduced into the PU domain

Deployable reflector antennas illuminated by a digital feed array enable spaceborne synthetic aperture radar (SAR) systems to image an ultrawide, continuous swath at a fine azimuth resolution. This is facilitated by the use of dedicated imaging modes and by multidimensional digital beamforming (DBF) techniques. This article is part 1 of a tutorial trilogy, where a focus is put on the required onboard

Hyperspectral (HS) imaging, also known as image spectrometry, is a landmark technique in geoscience and remote sensing (RS). In the past decade, enormous efforts have been made to process and analyze these HS products, mainly by seasoned experts. However, with an ever-growing volume of data, the bulk of costs in manpower and material resources poses new challenges for reducing the burden of manual

Presents the front cover for this issue of the publication.

Presents a call for nominations for the GRSS Administrative Committee.

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Advertisement.

Reports on the impact factor for this publication.

Recounts the career and contributions of David Landgrebe.

Morphological attribute profiles (APs) are among the most prominent methods for spatial–spectral pixel analysis of remote sensing images. Since their introduction a decade ago to tackle land cover classification, many studies have been contributed to the state of the art, focusing not only on their application to a wider range of tasks but also on their performance improvement and extension to more

A hyperspectral image (HSI) is a collection of several narrow-band images that span a wide spectral range. Each band reflects the same scene, composed of various objects imaged at different wavelengths; the spatial information, however, remains generally consistent across bands. Both types of information, spectral and spatial, can be leveraged to identify and classify objects. Recently, the use of

Remotely sensed land surface temperature (LST) with spatial continuity and high spatiotemporal resolution (hereafter referred to as high resolution ) is a crucial parameter for studying the thermal environment and has important applications in many fields. However, adverse atmospheric conditions, sensor malfunctioning, and scanning gaps between orbits frequently introduce spatial discontinuities into

This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name

The advent of lidar has revolutionized the way we observe and measure vegetation structure from the ground and from above and represents a major advance toward the quantification of 3D ecological observations. Developments in lidar hardware systems and data processing algorithms have greatly improved the accessibility and ease of use of lidar observations in ecological studies. A wide range of studies

Presents the front cover for this issue of the publication.

Reports on the GRS society journals and their impact factors.

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Advertisement.

Presents the introductory editorial for this issue of the publication.

Presents the President’s message for this issue of the publication.

This article considers the tremendous potential for satellite remote sensing information delivered via mobile digital applications to improve decision making in emerging agricultural economies. Earth observations have been available for use in weather and other models to support decision making since the late 1970s, with the launch of the advanced very-high-resolution radiometer and the Landsat sensors

Recounts the career and contributions of Josa Manuel Bioucas-Dias.

Recounts the career and contributions of Jakob van Zyl.

The Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) has organized the annual Data Fusion Contest (DFC) since 2006. The contest aims to establish new benchmarks for scientific challenges in remote sensing image analysis by promoting the use of multimodal data, leveraging new sensors as well as big data, and facilitating the emergence

Reports on GRSS society Chapter activities in Brazil.

Advertisement.