Remote Sensing, Volume 17, Issue 23

The accuracy of machine learning models in plant disease detection significantly relies on large volumes of knowledge-based labeled data; the acquisition of annotation remains a significant bottleneck in domain-specific research such as plant disease...

This study introduces a controlled laboratory setup for hyperspectral longwave infrared (LWIR) imaging of soils, designed to bridge the gap between laboratory measurements and remote sensing observations. A Fourier-transform hyperspectral LWIR imagin...

Wetlands provide critical ecological and socio-economic benefits, covering approximately 45% of the Athabasca Oil Sands Region in Alberta, Canada. However, open-pit oil sand mining has led to widespread wetland loss. While reclamation efforts are ong...

Ship detection in remote sensing imagery is hindered by cluttered backgrounds, large variations in scale, and random orientations, limiting the performance of detectors designed for natural images. We propose RSDB-Net, a Rotation-Sensitive Dual-Branc...

Leaf Area Index (LAI) is a key biophysical descriptor of crop canopies and is essential for growth monitoring and yield estimation. We present a physics-driven machine-learning framework for operational LAI retrieval and end-to-end uncertainty quanti...

Olea europaea L. is an economically and ecologically significant species, for which accurate biomass estimation provides critical insights for artificial propagation, yield forecasting, and carbon sequestration assessments. Currently, research on bio...

To address the urgent need for rapid detection and precise segmentation of oil spill incidents, a cascaded processing framework integrating the YOLOv11 model with an enhanced Northern Goshawk Optimization (NGO) algorithm is proposed. This method effe...

Land surface temperature (LST) is a key indicator of the urban heat island effect and is affected by multiple factors. However, existing research mainly focuses on the contributions of urban landscape and meteorology, and the impact of changes in atm...

The occurrence and duration of droughts have increased in recent years, reinforcing their role as a major climate risk. This study evaluates a remote sensing soil moisture-based drought index, the Standardized Soil Moisture Index (SSI), as a tool to...

Urban land subsidence poses a significant threat in rapidly urbanizing regions, threatening infrastructure integrity and sustainable development. This study focuses on Mandalay, Myanmar, and presents a novel clustering framework—Dynamic Time Wa...

We evaluated six global digital elevation DEMs at 1-arc-sec resolution: CopDEM and AW3D30, which are digital surface models (DSMs), and EDTM, GEDTM, FABDEM, and FathomDEM, which are digital terrain models (DTMs). We compared them to reference DTMs cr...

Accurate prediction of photosynthetic parameters is pivotal for precision viticulture, as it enables non-invasive monitoring of plant physiological status and informed management decisions. In this study, spectral reflectance data were used to predic...

In hyperspectral image classification (HSIC), each pixel contains information across hundreds of contiguous spectral bands; therefore, the ability to perform long-distance modeling that stably captures and propagates these long-distance dependencies...

Global increases in drought frequency and severity pose growing risks to forest resilience, particularly for long-lived endemic tree species such as kauri (Agathis australis). Building on prior leaf-level work, this study assessed the utility of mult...

The accurate estimation of grapevine biophysical parameters is important for decision support in precision viticulture. This study addresses the use of unmanned aerial vehicle (UAV) multispectral data and machine learning (ML) techniques to estimate...

In war and explosion scenarios, buildings often suffer varying degrees of damage characterized by complex, irregular, and fragmented spatial patterns, posing significant challenges for remote sensing–based change detection. Additionally, the sc...

Underground gas storage (UGS) facilities may cause ground displacements as a result of the cavern convergence or regular gas injection (alternate ground uplift and subsidence). The occurrence and scale of displacements are strongly dependent on the s...

Reliable geolocation of thermal hotspots, such as smoldering embers that can reignite after vegetation fire suppression, deep-seated peat fires, or underground coal seam fires, is critical to prevent fire resurgence, limit prolonged greenhouse gas em...

Detecting underwater debris is important for monitoring the marine environment but remains challenging due to poor image quality, visual noise, object occlusions, and diverse debris appearances in underwater scenes. This study proposes UDD-YOLO, a no...

Glaciers in High-Mountain Asia, the so-called “Third Pole,” are critical water sources but remain poorly monitored due to rugged topography and limited accessibility. We present an integrated approach that combines remote sensing with gro...

As a pivotal spatiotemporal infrastructure in the modern information society, satellite navigation provides global users with high-precision, all-weather, and round-the-clock Positioning, Navigation, and Timing (PNT) services [...]

Collecting accurate and reliable beach morphology data is essential for informed coastal management. The beach adjacent to the seawall on North Padre Island, Texas, USA has experienced increased erosion and disrupted natural processes. City ordinance...

Semantic change detection has become a key technology for monitoring the evolution of land cover and land use categories at the semantic level. However, existing methods often lack effective information interaction and fail to capture changes at mult...

With an abundance of data provided by satellite-based measurements, such as Synthetic Aperture Radar Interferometry (InSAR) or the Global Navigation Satellite System (GNSS), an interest has grown in training highly complex data-driven models for geop...

This study investigates a typical ozone pollution episode in Hong Kong from May 29 to 31, 2023. Based on the observations of a Differential Absorption Lidar (DIAL) system, both ozone and aerosols accumulated below 1.5 km during the pollution episode....

Since the late 1970s, satellite missions have monitored Total Solar Irradiance (TSI), providing a long-term record of solar variability. The Digital Absolute Radiometer (DARA), onboard the Chinese Fengyun-3E (FY3E) spacecraft since 4 July 2021, contr...

Ports pose distinctive monitoring challenges due to harsh marine conditions, mixed construction typologies, and heterogeneous ground conditions. These factors complicate the routine use of satellite InSAR, especially when medium-resolution scatterers...

Fourier transform spectrometers (FTSs) are cornerstone instruments in Earth observation space missions, effectively monitoring atmospheric gases in missions such as Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), and Infrared Atmos...

Hyperspectral image (HSI) classification is often challenged by cross-scene domain shifts and limited target annotations. Existing approaches relying on class-agnostic moment matching or confidence-based pseudo-labeling tend to blur decision boundari...

By combining the Maxwell–Garnett mixing rule, Mie scattering, and the four-stream discrete ordinates adding method, a snow albedo model with explicit consideration of water content was constructed, and the influence of snow water content on sno...

Aquaculture pond extraction based on remote sensing (RS) plays a pivotal role in coastal resource utilization and production management. However, most existing studies have focused on limited coastal aquaculture pond extraction and neglected the extr...

High-resolution above-ground biomass (AGB) data play a critical role in advancing low-carbon development strategies across cities. However, research on urban trees’ AGB largely relies on high-accuracy field measurements, which limits the feasib...

Maritime surveillance has become increasingly relevant due to the growth of shipping, illegal fishing, and the need to monitor remote oceanic regions. Synthetic Aperture Radar (SAR) imagery supports this task under day-and-night and almost all-weathe...

The precise identification of photovoltaic power stations is essential for advancing the assessment of energy infrastructure and for the efficient management of land resources. To address the need for spatially explicit data on photovoltaic (PV) deve...

Satellite and UAV-based remote sensing have been widely used for agricultural systems monitoring jointly. How to quantitatively optimize the efficiency of integrating these two techniques remains largely understudied. To address this gap, we, for the...

Accurate daily surface net radiation (R_n) estimation over the Tibetan Plateau’s complex and highly heterogeneous terrain is essential for advancing the understanding of land–atmosphere exchanges and regional climate processes. This study...

Reliable land surface temperature (LST) data are required for monitoring climate variability, hydrological processes, and land–atmosphere interactions. Yet existing satellite-derived LST products, such as those from thermal infrared (TIR) senso...

Monitoring oil spills on coastal beaches using satellite imagery has received limited attention, primarily due to the lack of characteristic spectral data as well as constraints in spatial or temporal resolution. In this study, we employ both reflect...

Understanding the sediment grain size distribution in riverbeds is essential for analyzing sediment transport, riverbed morphology, and ecological habitats. Previous studies have shown that riverbed grain size can be inferred from surface roughness u...

Frequent extreme climate events have intensified landslide hazards in mountainous regions, necessitating efficient identification and classification to understand movement mechanisms and mitigate risks. This study develops a novel, non-contact InSAR...

This article conducts a systematic review on the fine-grained interpretation of remote sensing images, delving deeply into its background, current situation, datasets, methodology, and future trends, aiming to provide a comprehensive reference framew...

Forestry is essential for environmental sustainability, biodiversity conservation, carbon sequestration, and renewable resource management. Traditional methods for forest inventory, particularly the manual measurement of diameter at breast height (DB...

Large-scale rainfed cropping systems (broadacre agriculture) face intensifying climate and resource stresses that undermine yield stability and farm livelihoods. Remote sensing (RS) offers critical tools for improving resilience by monitoring crop pe...

The target detection method based on a constant false alarm rate (CFAR) and feature space is commonly used in remote sensing for detecting maritime targets within sea clutter. However, the performance of traditional CFAR techniques heavily relies on...

Homography estimation of infrared and visible light images is a key visual technique that enables drones to perceive their environment and perform autonomous localization in low-altitude environments. Its potential lies in integration with edge compu...

Tidal flats play a vital role in coastal ecosystems by supporting biodiversity, mitigating natural hazards, and functioning as blue carbon reservoirs. However, monitoring their geomorphological changes remains challenging due to high turbidity, shall...

Three-dimensional (3D) reconstruction technology for space targets can provide information support such as target structures and dimensions for space missions including on-orbit services and fault diagnosis, which is crucial for maintaining the norma...

In remote sensing monitoring of forest fires, smoke and clouds exhibit similar spectral characteristics in satellite imagery, which can easily lead to clouds being misjudged as smoke. This incorrect discrimination may result in missed detections or f...

Debris-covered glaciers, with their intricate thermal dynamics and significant spatial heterogeneity, play a pivotal role in elucidating glacier ablation processes and their responses to climate change. However, existing research on their energy bala...

Synthetic Aperture Radar (SAR) imagery enables high-resolution observation regardless of weather conditions. However, it is difficult to interpret intuitively due to issues such as speckle noise. In contrast, optical imagery provides realistic visual...