Remote Sensing, Volume 17, Issue 3

Ultraviolet (UV) radiation effects on Earth’s ecosystems on a global scale can be assessed on a basis of satellite estimates of hyperspectral irradiance on the surface and in ocean waters and the spectral biological weighting functions. The sat...

Evapotranspiration (ET) is vital for global water balance, energy cycle, and biological processes, representing a key component of Earth systems interactions. However, how human activities affect regional ET is still unknown. This study identified a...

Rain backscatter corrupts Ku-band scatterometer wind retrieval by mixing with the signatures of the ${\sigma }^{\circ }$ (backscatter measurements) on the sea surface. The measurements are sensitive to rain clouds due to the short wavelength, and the rain-...

Resistance, resilience, and recovery time are critical for quantifying the stability of grasslands in response to drought disturbances. Few studies have simultaneously considered both drought intensity and duration to analyze the stability of differe...

The quantization process of synthetic aperture radar (SAR) images faces significant challenges due to their high dynamic range, resulting in notable quantization distortion. This not only degrades the visual quality of the quantized images but also s...

Ecological integrity is fundamental to human survival and development. However, rapid urbanization and population growth have significantly disrupted ecosystems. Despite the focus of the International Geosphere-Biosphere Programme (IGBP) on terrestri...

Integrating LiDAR and photogrammetry offers significant potential for ensuring the accuracy and completeness of the 3D models of existing structures, which are essential for several applications in the architectural, engineering, and construction (AE...

In dual-channel synthetic aperture radar (SAR) systems, the estimation of the four-dimensional motion parameters of the ground maneuvering target is a critical challenge. In particular, when spatial degrees of freedom are used to enhance the target&r...

The Aburrá Valley, located in the northwestern region of Colombia, has undergone significant land cover changes and urban expansion in recent decades, driven by rapid population growth and infrastructure development. This region, known for its...

Vegetation characteristics significantly influence the impact of wildfires on individual building structures, and these effects can be systematically analyzed using heat transfer modelling software. Close-range light detection and ranging (LiDAR) dat...

Soil sand content is an important characterization index of soil texture, which directly affects soil water regulation, nutrient cycling, and crop growth potential. Therefore, its high-precision spatial distribution information is of great importance...

Synthetic Aperture Radar (SAR) is extensively utilized in ship detection due to its robust performance under various weather conditions and its capability to operate effectively both during the day and at night. However, ships in SAR images exhibit v...

The present survey examines the role of big data analytics in advancing remote sensing and geospatial analysis. The increasing volume and complexity of geospatial data are driving the adoption of machine learning (ML) and artificial intelligence (AI)...

Monitoring mangrove phenology requires frequent, high-resolution remote sensing data, yet satellite imagery often suffers from coarse resolution and cloud interference. Traditional methods, such as denoising and spatiotemporal fusion, faced limitatio...

Sustainable urban growth is an important issue in urbanization. Existing studies mainly focus on urban growth from the two-dimensional morphology perspective due to limited data. Therefore, this study aimed to construct a framework for estimating lon...

Soil, a crucial natural resource and the cornerstone of agriculture, profoundly impacts crop growth, quality, and yield. However, soil degradation affects over one-third of global land, with topsoil loss emerging as a significant form of this degrada...

Precipitation is a key component of the water cycle. Different precipitation data sources have strengths and weaknesses. To combine these strengths and achieve accurate precipitation data, this study introduces a dual-layer neural network (D-ConvLSTM...

Accurate and objective regional landslide risk assessment is crucial for the precise prevention of regional disasters. This study proposes an integrated landslide risk assessment via a landslide susceptibility model based on intelligent optimization...

Underground monument preservation is tightly linked to geological risk. The geological risk management of underground structures typically relies on a preliminary site investigation phase. Engineering geological mapping—as a key site investigat...

To evaluate the potential of an upcoming large-swath satellite for estimating surface methane (CH₄) fluxes at a weekly scale, we report the results from a series of observing system simulation experiments (OSSEs) that use an established modelin...

Monitoring soil moisture (SM) on individual crop fields is of great interest for agricultural applications. Synthetic aperture radar (SAR) systems such as Sentinel-1 provide sensitivity to surface SM at a spatial resolution compatible with crop-field...

Significant progress has been made in the semantic segmentation of mobile laser scanning (MLS) point clouds based on deep learning. However, the segmentation classes of deep learning models depend on the label classes of the source point clouds used...

With the advancement of remote sensing technology, the acquisition of ultra-high-resolution remote sensing imagery has become a reality, opening up new possibilities for detailed research and applications of Earth’s surface. These ultra-high-re...

Of all meteorological events, Tropical Cyclones (TCs) are by far the costliest of natural hazards around the globe. They typically lose their strength quite rapidly once making landfall. Recent studies have revealed that TCs, even degrading below TC...

Aboveground biomass (AGB) is a sensitive indicator of grassland resource quality and ecological degradation. However, accurately estimating AGB at large scales to reveal long-term trends remains challenging. Here, single-factor parametric models, mul...

Early detection and monitoring of invasive forest pests are crucial for effective pest management, particularly in preventing large-scale damage, reducing eradication costs, and improving overall control effectiveness. This study investigates the pot...

Vegetation indices are important representatives of plant growth. Climate change and human activities seriously affect vegetation. This study focuses on the Huojitu mining area in the Shendong region, utilizing the kNDVI index calculated via the Goog...

The sensitivity of Global Navigation Satellite System (GNSS) receivers to ionospheric disturbances and their constant growth are nowadays resulting in an increased concern of GNSS users about the impacts of ionospheric disturbances at mid-latitudes....

Sulfur dioxide (SO₂) is sourced by degassing magma in the shallow crust; hence its monitoring provides information on the rates of magma ascent in the feeding conduit and the style and intensity of eruption, ultimately contributing to volcano monitor...

The efficiency of satellite altimetry in monitoring coastal areas and lakes is limited due to the contaminated waveform caused by non-water features included in the satellite footprint. Therefore, to mitigate these limitations, waveforms need to be r...

Lidar technology is pivotal for detecting and monitoring the atmospheric environment. However, maintaining optical path stability in complex environments poses significant challenges, especially regarding adaptability and cost efficiency. This study...

The observation of small to medium inland water targets with nadir radar altimeters is currently limited by the along-track resolution of UnFocused SAR (UFSAR) altimetry, which is approximately 300 $\mathrm{m}$ for Delay-Doppler processors. In this study, we an...

This study introduces methods for generating fused precipitation data by applying radial basis function (RBF) interpolation, which integrates radar reflectivity-based data with ground-based precipitation gauge measurements. Rain gauges provide direct...

Near-surface ozone is a secondary pollutant, and its high concentrations pose significant risks to human and plant health. Based on an Extra Tree (ET) model, this study estimated near-surface ozone concentrations with the high spatiotemporal resoluti...

The construction of accurate anisotropic velocity models is essential for effective microseismic monitoring in hydraulic fracturing. Ignoring anisotropy can result in significant distortions in microseismic event locations and their interpretation. A...

Plant phenology is an important driver of inter-annual variability in peatland carbon uptake. However, the use of traditional phenology datasets (e.g., manual surveys, satellite remote sensing) to quantify this link is hampered by their limited spati...

Water use efficiency (WUE) reflects the quantitative relationship between vegetation gross primary productivity (GPP) and surface evapotranspiration (ET), serving as a crucial indicator for assessing the coupling of carbon and water cycles in ecosyst...

To address the significant impact of noise on the target detection performance of borehole radar (BHR), a key type of ground-penetrating radar (GPR), a denoising scheme based on the whale optimization algorithm (WOA) for adaptive variational mode dec...

Climate change has led to an increase in global temperature and frequent intense precipitation, resulting in a rise in severe and intense urban flooding worldwide. This growing threat is exacerbated by rapid urbanization, impervious surface expansion...

Beach surface moisture (BSM) is crucial to studying coastal aeolian sand transport processes. However, traditional measurement techniques fail to accurately monitor moisture distribution with high spatiotemporal resolution. Remote sensing technologie...

In change detection tasks, seasonal variations in spectral characteristics and surface cover can negatively impact performance when comparing image pairs from different seasons. Many existing change detection methods do not specifically address the p...

Vegetation anomalies are frequently occurring and may greatly affect ecological functions. Many near-real-time (NRT) detection methods have been developed to detect these anomalies in a timely manner whenever a new satellite observation is available....

With advancements in phased array and cognitive technologies, the adaptability of modern multifunction radars (MFRs) has significantly improved, enabling greater flexibility in waveform parameters and beam scheduling. However, these enhancements have...

Cloud classification is fundamental to advancing climate research and improving weather forecasting. However, existing cloud classification models are constrained by several limitations. For instance, simple statistical methods depend heavily on prio...

Accurate and precise monitoring of species abundance is essential for determining population trends and responses to environmental change. Species, such as bats, that have slow life histories, characterized by extended lifespans and low reproductive...

Sea surface temperature (SST) plays a pivotal role in air–sea interactions, with implications for climate, weather, and marine ecosystems, particularly in regions like the Caribbean Sea, where upwelling and dynamic oceanographic processes signi...

Due to its miniature size and single-pass nature, Unmanned Aerial Vehicle (UAV)-borne array synthetic aperture radar (SAR) is capable of obtaining three-dimensional (3D) electromagnetic scattering information with a low cost and high efficiency, maki...

Wildfires in the United States have increased in frequency and severity over recent decades, driven by climate change, altered weather patterns, and accumulated flammable materials. Accurately forecasting the Fire Weather Index (FWI) is crucial for m...

With the widespread application of remote sensing technologies and UAV imagery in various fields, dense object detection has become a significant and challenging task in computer vision research. Existing end-to-end detection models, particularly tho...

This paper studies the performance of an interplanetary CubeSat equipped with a continuous-thrust primary propulsion system in a heliocentric mission scenario, which models a nodal flyby with a potential near-Earth asteroid. In particular, the mathem...