Welcome to the IEEE Geoscience and Remote Sensing Society (GRSS) in 2024! I am delighted to serve one more year as the GRSS president and hope we can accomplish great things together. I welcome your thoughts at president@grss-ieee.org, so don’t hesitate to reach out, even just to say hello.

A carbon nanotube (CNT) has been used as electronic materials for functional electronic devices such as transistors, transparent electrodes, sensors, and Joule heating devices owing to their unique properties and high aspect ratios. However, the CNT network is randomly aligned on sheets fabricated by the spreading of a CNT suspension. In order to fabricate directional CNT network, we demonstrate the

On 17–21 July 2023, more than 3,000 engineers, geoscientists, and remote sensing enthusiasts from around the world congregated in Pasadena, California, for the 2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). The Inspire, Develop, Empower, and Advance (IDEA) Committee led a series of impactful events throughout the week-long conference, centering on themes of driving transformation

A carbon nanotube (CNT) has been used as electronic materials for functional electronic devices such as transistors, transparent electrodes, sensors, and Joule heating devices owing to their unique properties and high aspect ratios. However, the CNT network is randomly aligned on sheets fabricated by the spreading of a CNT suspension. In order to fabricate directional CNT network, we demonstrate the

A carbon nanotube (CNT) has been used as electronic materials for functional electronic devices such as transistors, transparent electrodes, sensors, and Joule heating devices owing to their unique properties and high aspect ratios. However, the CNT network is randomly aligned on sheets fabricated by the spreading of a CNT suspension. In order to fabricate directional CNT network, we demonstrate the

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.

The book SAR Image Analysis—A Computational Statistics Approach: With R Code, Data, and Applications stands out as an exceptional resource dedicated to statistical methodologies to extract information from synthetic aperture radar (SAR) imagery, all within a computational framework using R programming language. The book covers a wide range of topics in 183 pages and seven chapters, including a detailed

Let me start this editorial by announcing that I am stepping down from my position of editor-in-chief (EIC) of IEEE Geoscience and Remote Sensing Magazine (GRSM) soon. I will provide a short summary of my term in the “From the Editor” column in the next (and my last) GRSM issue. Today, I simply want to highlight that the search for a new EIC is underway, and all the details are available on the webpage

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.

Shallow aquifers are the largest freshwater bodies in the North African Sahara and the Arabian Peninsula. Their groundwater dynamics and response to climatic variability and anthropogenic discharge remain largely unquantified due to the absence of large-scale monitoring methods. Currently, the assessment of groundwater dynamics in these aquifer systems is made primarily from sporadic well logs that

Urban studies require a rich set of information sources and techniques that enable a comprehensive depiction of urban environments. Remote sensing captures physical characteristics of urban landscapes, while social sensing collects data from social media and digital devices to reflect human activities. The combination of remote sensing and social sensing has been employed to investigate urban environments

With the rapid advancements in synthetic aperture radar (SAR) satellites and associated processing algorithms over recent decades, interferometric SAR (InSAR) has emerged as a routine method for monitoring large-scale ground deformation and interpreting geophysical processes. Statistical inference serves as a major component in InSAR technique developments and applications. This article provides an

In the last 40 years, remote sensing technology has evolved, significantly advancing ocean observation and catapulting its data into the big data era. How to efficiently and accurately process and analyze ocean big data and solve practical problems based on ocean big data constitute a great challenge. Artificial intelligence (AI) technology has developed rapidly in recent years. Numerous deep learning

Since you are reading this editorial, you are well aware that this journal is quite different than the other ones published by the IEEE Geoscience and Remote Sensing Society (GRSS). Indeed, it is a magazine, which implies that it has some specific features. In the past two issues I introduced how the technical contents of IEEE Geoscience and Remote Sensing Magazine (GRSM) are selected and how authors

How time flies! With the end of 2023 (and the first year of my presidency) approaching, it is an opportune time to reflect on 2023 and look ahead to 2024 (and the second [and last] year of my presidency).

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

The Instrumentation and Future Technologies Technical Committee’s (IFT-TC) second summer school took place in Auckland, New Zealand, from 30 January to 3 February 2023. The IFT Remote Sensing Summer Schools (IFT-R3S) aim to promote future research in remote sensing; connect Master students, junior Ph.D. students, recent graduates, and young professionals with research groups linked to the IFT-TC; and

Presents corrections to the paper, “Active learning for hyperspectral image classification: A comparative review”.

The Second International Soil Moisture School (ISMS2023) was conducted at the Indian Institute of Technology Bombay (IITB), India, during 15–17 March 2023, after the success of the first school held at the University of Massachusetts, Amherst, MA, USA. ISMSs aim to provide early career scientists with an understanding and utilization of remotely sensed soil moisture (SM) information from current and

CubeSats are now serving a wide range of applications beyond their original educational intent. Private companies are deploying large constellations for Earth observation and machine–to–machine communications. Their growing popularity and increased performance have raised the demand for reliability and costs. Today, it is becoming increasingly difficult to find subsystems providers, and the trend is

Synthetic aperture radar (SAR) imaging data in general have not been openly accessible for consumption to the general public in the past few decades, as mainly governments have led the development of such platforms, due to the commercial industry lacking the need of such data (with few exceptions).

Polarimetric radar, which can acquire full polarization information, has become mainstream in microwave remote sensing. However, radar target scattering responses are strongly orientation dependent, which makes applications such as target detection and recognition more difficult. Polarimetric roll-invariant features, which are independent of target orientations along the radar line of sight (LOS),

Today, remote sensing systems/technologies are one of the most essential requirements for civil and military sectors for various applications. This review article discusses the evolutionary developments of today’s remote sensing radar/optical/electronic warfare (EW) technologies, right from the telemobiloscope. This review article addresses the fundamentals of radar sensing techniques, top-level radar

Remote sensing object detection (RSOD), one of the most fundamental and challenging tasks in the remote sensing field, has received long-standing attention. In recent years, deep learning techniques have demonstrated robust feature representation capabilities and led to a big leap in the development of RSOD techniques. In this era of rapid technical evolution, this article aims to present a comprehensive

Real-time semantic segmentation of remote sensing imagery is a challenging task that requires a tradeoff between effectiveness and efficiency. It has many applications, including tracking forest fires, detecting changes in land use and land cover, crop health monitoring, and so on. With the success of efficient deep learning methods [i.e., efficient deep neural networks (DNNs)] for real-time semantic

The richness of hyperspectral imaging (HSI)-collected signals makes possible quantitative inference by the inverse problem-solving of the chemical and biophysical parameters of the imaged object. In this article, we first propose a classification of the large variety of literature on invertible physics-based hyperspectral signature models by analyzing their founding hypotheses and methodologies. All

The emerging field of vision–language models, which combines computer vision and natural language processing (NLP), has gained significant interest and exploration. This integration has opened up new research opportunities, particularly in remote sensing (RS), where it has the potential to enhance RS systems’ capabilities. In this context, this article presents a comprehensive review of more than 100

Visual data exploration is ubiquitous in nearly every industry and organization to support discovering data-driven actionable insights. However, unlocking those insights requires analysts to manually construct a prohibitively large number of aggregate queries and visually explore their results, looking for those valuable and insightful visualizations. Such a challenge naturally motivated the development

Hello again! My name is Mariko Burgin, and I am the IEEE Geoscience and Remote Sensing Society (GRSS) president. You can reach me at president@grss-ieee.org and @GRSS_President on X, formally known as Twitter.

The advent of high-throughput technologies has produced an increase in the dimensionality of omics datasets, which limits the application of machine learning methods due to the great unbalance between the number of observations and features. In this scenario, dimensionality reduction is essential to extract the relevant information within these datasets and project it in a low-dimensional space, and

Forest wildfires represent one of the catastrophic events that, over the last decades, have caused huge environmental and humanitarian damage. In addition to a significant amount of carbon dioxide emission, they are a source of risk to society in both short-term (e.g., temporary city evacuation due to fire) and long-term (e.g., higher risks of landslides) cases. Consequently, the availability of tools

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.