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Due to error sources arising from undersampling of target signals and imperfections in background models, the single-pair satellite gravity missions equipped with the low-low satellite-to-satellite tracking technology ar...

Due to the limitation of lacking elevation resolution, ground-based interferometric radar suffers from serious layover problem when applied to building deformation monitoring. Ground-based tomographic arc-scanning synthe...

The design of a bistatic inverse synthetic aperture radar (ISAR) images simulator is described, as a response to the need of databases with classification purposes in bistatic radar scenarios characterized by numerous de...

Multimodal remote sensing image registration is a fundamental step for multisource data fusion and geospatial analysis. However, nonlinear radiometric, textural, and geometric discrepancies across modalities challenge in...

The NASA-ISRO Synthetic Aperture Radar (NISAR) mission will advance global soil moisture monitoring through high-resolution L-band observations. However, accurate fine-scale retrieval remains challenging due to the 12-da...

Sea-ice motion plays a pivotal role in the variability of the Antarctic climate system by modulating the atmosphere–ocean fluxes and the ocean freshwater budget. Due to the variability of the ice surface, snow&#x2...

Wildfires are natural hazards that threaten ecosystems, communities, and economies, and they have shown a significant increase in frequency and intensity in recent years. Accurate wildfire spread prediction is critical f...

Artificial intelligence (AI) models developed for Global Navigation Satellite System Reflectometry (GNSS-R) observations have demonstrated competitive performance in estimating geophysical parameters, especially ocean su...

Few-shot object detection (FSOD) recently garnered increasing attention in remote sensing images (RSIs). Although FSOD has achieved success in natural sense, the large size and complex backgrounds of RSIs make FSOD espec...

Infrared thermal radiation signals are highly susceptible to environmental interference, leading to dynamic fluctuations. Consequently, weak targets are frequently submerged in heavy clutter backgrounds under extreme sce...

With the rapid advancement of remote sensing technology, target detection in remote sensing imagery plays a crucial role in military reconnaissance, urban planning, and other fields. However, there are problems such as l...

The field of remote sensing change detection (RSCD) has witnessed remarkable progress. Most existing RSCD methods currently follow the encoder-feature interaction-decoder architecture. However, these methods often treat ...

This article presents an innovative technique for remote sensing-based mapping and predicting land degradation in the European frontier regions. The mapping is carried out by geospatial data fusion of relevant biophysica...

Driven by satellite remote sensing observations, deep learning models provide a promising solution for the rapid estimation of subsurface thermohaline structures. By learning from large-scale paired surface–subsur...

Terrestrial evaporation ($E$) plays a crucial role in the water, energy, and carbon cycles and modulates climate change through multiple feedback mechanisms. While process-based models estimate $E$ using satellite-derive...

As a key element of human settlements and fundamental features in maps, buildings play a critical role in urban planning and environmental monitoring. Automatically extracting buildings from remote sensing images is of s...

Measurements from global navigation satellite system reflectometry (GNSS-R) have proven effective for applications in sea surface height (SSH). Deep learning-based methods for spaceborne GNSS-R SSH retrieval can effectiv...

Recently, to enhance the ability of deployed models to adapt to continually changing environments, the continual test-time adaptation (CTTA) for urban scene image (USI) segmentation has been preliminarily studied. CTTA a...

Wildfires are among the most destructive natural disasters and pose significant risks to ecosystems, infrastructure, and human lives. This study focuses on wildfire susceptibility mapping in Los Angeles County, a region ...

High-quality lunar imaging is essential to terrain modeling, resource assessment, and landing navigation. However, due to the limited depth-of-field of lunar probe cameras, a single image cannot simultaneously capture cl...

With advances in aerospace technology, high-resolution optical imagery from satellites, such as China’s Gaofen series, is vital for climate monitoring and agriculture. However, cloud cover significantly impedes th...

Intelligent mining area detection is fundamental for ecological monitoring and sustainable development of mining areas. However, current remote sensing detection lacks high-quality multimineral rotated object detection d...

Remote sensing enables urban planners to gain macroscopic insights into urban structures and issues. Pan-sharpening plays a key role by merging multispectral and panchromatic images, combining high spatial resolution wit...

Degradation of images in ocean remote sensing is primarily due to light scattering, chromatic aberration, and stochastic noise. As a result, the quality of the image content has been significantly compromised. Most ocean...