Remote Sensing, Volume 17, Issue 6

The finite-difference time-domain (FDTD) method is a robust numerical approach for the three-dimensional forward modeling of airborne ground-penetrating radar responses of complex geological structures, particularly landslides. However, standard FDTD...

This study aims to develop a forest landscape stability assessment framework that integrates structure, function, and resilience to assess forest landscape stability under different landform types on the Loess Plateau, and to propose differentiated o...

The rapid development of urban infrastructure has accelerated the construction of large foundation pit projects, posing challenges for deformation monitoring and safety. This study proposes a novel approach integrating time-series InSAR data with a m...

Although the traditional Carrier-to-Code Leveling (CCL) method can provide ideal slant total electron content (STEC) observables for establishing ionospheric models, it must rely on dual-frequency (DF) receivers, which results in high hardware costs....

In the field of weather forecasting, improving the accuracy of nowcasting is a highly researched topic, and radar echo extrapolation technology plays a crucial role in this process. Aiming to address the limitations of existing deep learning methods...

High-speed railway (HSR) has become a key infrastructure that shapes land use, specifically industrial distribution, and therefore affects urban industrial structure and regional economic patterns. This paper develops a new approach to examine the in...

The assessment of the jamming effect of Synthetic Aperture Radar (SAR) is the primary means to measure the reliability of the jamming, which can provide important guidance for the use of jamming strategies and patterns. This paper proposes a detectio...

In this study, we explored the occurrence of near-sunrise equatorial plasma bubbles (EPBs) and inhibition of dusk-time EPBs during the geomagnetic storm (SYM-Hmin= −139 nT) of 19–20 April 2024 using multi-instrument observations over the...

In the conventional PPP-RTK mode, the platform and users act only as the generator and the utilizer of ionospheric corrections, respectively. In sparse reference station networks or regions with an active ionosphere, high-precision modeling still fac...

In remote sensing via aperture synthesis, the complex gains of every elementary antenna have to be very well known for measuring accurate complex visibilities. The role of calibration is to estimate the instrumental and environmental variations that...

The Mw 7.0 Dingri earthquake, which occurred on 7 January 2025, occurred at the southern end of the Xainza-Dinggyê Fault Zone within the South Tibet Rift (STR) system, in the Dengmecuo graben. It is the largest normal-faulting event in the regi...

Deep metric learning combines deep learning with metric learning to explore the deep spectral space and distinguish between the target and background. Current target detection methods typically fail to accurately distinguish local differences between...

RGB-IR object detection provides a promising solution for complex scenarios, such as remote sensing and low-light environments, by leveraging the complementary strengths of visible and infrared modalities. Despite significant advancements, two key ch...

Synthetic aperture radar (SAR) is emerging as a valuable dataset for monitoring crops globally. Unlike optical remote sensing, SAR can provide earth observations regardless of solar illumination or atmospheric conditions. Several methods that utilize...

The rapid development of factory aquaculture not only brings economic benefits to coastal areas but also poses numerous ecological and environmental challenges. Therefore, understanding the distribution of coastal factory aquaculture is of great sign...

River channels are fundamental geomorphological and hydrological features that play a critical role in regulating the Earth’s water cycle and ecosystems and influencing human activities. This study utilized Digital Elevation Model (DEM) data an...

This paper proposes a pose estimation algorithm using INS and LiDAR for precise cooperative relative navigation between target and chaser spacecraft in a close docking mission scenario. Previous cooperative algorithms have proposed estimating positio...

Observing coal mining and reclamation activities using remote sensing avoids the need for physical site visits, which is important for environmental and land management. This study utilizes deep learning techniques with a U-Net and ResNet architectur...

Wetlands in the Yellow River Watershed of Inner Mongolia face significant reductions under future climate and land use scenarios, threatening vital ecosystem services and water security. This study employs high-resolution projections from NASA’...

Accurate soil pH prediction is critical for soil management and ecological environmental protection. Machine learning (ML) models have been widely applied in the field of soil pH prediction. However, when using these models, the spatial heterogeneity...

Urban nighttime lighting extends human activity hours and enhances safety but also wastes energy and causes light pollution. Influenced by building obstructions and surface reflections, light emissions exhibit significant anisotropy. Remote sensing c...

The accurate quantification of anthropogenic carbon dioxide (CO₂) emissions in urban areas is hindered by high uncertainties in emission inventories. We assessed the spatial distributions of three anthropogenic CO₂ emission inventories in Shanghai, C...

Evaluating the performance of irrigation water use is essential for efficient and sustainable water resource management. However, existing approaches often lack systematic quantification of irrigation water consumption and fail to differentiate betwe...

Failures in solar photovoltaic (PV) modules generate heat, leading to various hotspots observable in infrared images. Automated hotspot detection technology enables rapid fault identification in PV systems, while PV array detection, leveraging geomet...

Accurate cloud detection is critical for quantitative applications of satellite-based advanced imager observations, yet nighttime cloud detection presents challenges due to the lack of visible and near-infrared spectral information. Nighttime cloud d...

Rapid urbanization and the consequent alteration in land use and land cover (LULC) significantly change the natural landscape and adversely affect hydrological cycles, biological systems, and various ecosystem services, especially in the developing w...

In today’s world, where near-Earth space constitutes an increasingly congested and contested theater of economic, political, and military activities for the growing number of space-faring nations, the significance of actionable situational awar...

With the rapid advancement of unmanned aerial vehicles (UAVs) in recent years, UAV-based remote sensing has emerged as a highly efficient and practical tool for environmental monitoring. In vegetation remote sensing, UAVs equipped with hyperspectral...

Inverse Synthetic Aperture Radar (ISAR) serves as a valuable instrument for surveillance of space targets. There has been a great deal of research on space target identification using ISAR. However, the polarization characteristics of space target co...

In the field of remote sensing, super-resolution methods based on deep learning have made significant progress. However, redundant feature extraction and inefficient feature fusion can, respectively, result in excessive parameters and restrict the pr...

Enhancing the detection capabilities of rotated objects in aerial imagery is a vital aspect of the burgeoning field of remote sensing technology. The objective is to identify and localize objects oriented in arbitrary directions within the image. In...

Mangroves and tropical swamp forests are ecosystems that play a critical role in carbon sequestration, coastal protection, and biodiversity support. Accurately estimating aboveground biomass (AGB) in these forests is crucial for global carbon managem...

The purpose of this study is to provide a comprehensive resource for the selection of data representations for machine learning-oriented models and components in solar flare prediction tasks. Major solar flares occurring in the solar corona and helio...

This paper presents the technical design of the pathfinder Barcelona Raman LIDAR (pBRL) for the northern site of the Cherenkov Telescope Array Observatory (CTAO-N) located at the Roque de los Muchachos Observatory (ORM). The pBRL is developed for con...

Rising sea levels, warming ocean temperatures, and other climate change impacts threaten the German North Sea coast, making monitoring of this system even more critical. This study reviews the potential of remote sensing for the German North Sea coas...

Multimodal remote sensing image registration aims to achieve effective fusion and analysis of information by accurately aligning image data obtained by different sensors, thereby improving the accuracy and application value of remote sensing data in...

This paper examines the long-term morphological evolution of the Bevano River sand spit (Ravenna, Italy) after an artificial intervention carried out in 2006 that artificially relocated the river mouth to improve the hydraulic efficiency, preventing...

Monitoring inland waters is of critical importance for the effective and sustainable management of water resources, especially under climate change scenarios. This paper introduces a satellite-based approach for river monitoring using optical multisp...

Sparse Synthetic Aperture Radar (SAR) imaging has garnered significant attention due to its ability to suppress azimuth ambiguity in under-sampled conditions, making it particularly useful for high-resolution wide-swath (HRWS) SAR systems. Traditiona...

Equilibrating the supply and demand for ecosystem services (ESs) is essential for sustainable development. Nonetheless, elements like policy modifications, land utilization, and climate change are profoundly transforming the dynamics of ecosystem ser...

The solar radiation pressure (SRP) model, as a key factor affecting the precise orbit determination (POD) accuracy of navigation satellites, is related to the state and optical properties of the satellite surface. This study establishes a high-precis...

The Arctic Ocean has a uniquely complex system associated with tightly coupled ocean–ice–atmosphere–land interactions. The Arctic Ocean is considered to be highly susceptible to global climate change, with the potential for dramatic...

Forest health monitoring at scale requires high-spatial-resolution remote sensing images coupled with deep learning image analysis methods. However, high-quality large-scale datasets are costly to acquire. To address this challenge, we explored the p...

Aboveground biomass (AGB) is crucial in forest ecosystems and is intricately linked to the carbon cycle and global climate change dynamics. This study investigates the efficacy of synthetic aperture radar (SAR) data from the X, C, and L bands, combin...

Arid and semi-arid regions are highly sensitive and vulnerable to climate change and human activities. Clarifying their spatial distribution is of great significance for understanding regional drought dynamics. This research examines the Shendong min...

Frequency-modulated continuous wave (FMCW) and orthogonal frequency-division multiplexing (OFDM) technologies play significant roles in millimeter-wave radar and communication. Their combinations, however, are understudied in the literature. This pap...

Three-dimensional (3D) seismic data, essential for revealing subsurface structures and exploring oil and gas resources, are often contaminated by noise with an unknown prior distribution. Existing denoising research faces great challenges due to the...

This paper presents a comparison of different image fusion methods for matching visible-spectrum images with thermal-spectrum (far-infrared) images, aimed at enhancing person detection using convolutional neural networks (CNNs). While object detectio...

Ground-based global navigation satellite system (GNSS) and remote sensing interferometric synthetic aperture radar (InSAR) techniques have proven to be very useful for deformation monitoring. GNSS provides high-precision data but only at a limited nu...

This paper presents a technique based on Constellation Rotation Modulation (CRM) to enhance the communication bandwidth of Frequency-Hopping Multiple-Input Multiple-Output Dual-Function Radar and Communication (FH-MIMO DFRC) systems. The technique in...