2025 April-2 - 161 articles
By extending synthetic aperture technology from a microwave band to laser wavelength, the synthetic aperture ladar (SAL) achieves extremely high spatial resolution independent of the target distance in long-range imaging. Nonlinear phase correction i...
Accurate, real-time, and dynamic monitoring of crop planting distributions in hilly areas with complex terrain and frequent meteorological changes is highly important for agricultural production. Dual-polarization SAR has high application value in th...
Deep learning has significantly advanced synthetic aperture radar (SAR) ship detection in recent years. However, existing approaches predominantly rely on amplitude information while largely overlooking the critical phase component, limiting further...
Spatial disparities in rangeland conditions across Kazakhstan complicate field-based assessments of livestock-carrying capacity (LCC), a critical metric for the country’s food security and economic planning. This study developed a geospatial li...
Tiny object detection remains a formidable challenge in the field of computer vision. There are many factors that influence tiny object detection performance. In this paper, we focus primarily on the following two aspects. First, due to diminutive si...
Mid-wave infrared (MWIR) hyperspectral imaging integrates MWIR technology with hyperspectral remote sensing, enabling the capture of radiative information that is difficult to obtain in the visible spectrum, thus demonstrating significant value in ca...
Semi-supervised learning aims to improve the generalization performance of a model by exploiting the large quantity of unlabeled data together with limited labeled data during training. When applied to object detection in remote sensing images, semi-...
Three-dimensional models of trees can help simulate forest resource management, field surveys, and urban landscape design. With the advancement of Computer Vision (CV) and laser remote sensing technology, forestry researchers can use images and point...
Dust storms, as an important extreme weather event on Mars, have significant impacts on the Martian atmosphere and climate and the activities of Martian probes. Therefore, it is necessary to analyze and predict the activity trends of Martian dust sto...
Accurate cover crop biomass estimation is critical for evaluating their ecological benefits. Traditional methods, like destructive sampling, are labor-intensive and time-consuming. This study investigates the application of unmanned aerial vehicle (U...
Deep learning has shown significant potential in multi-band Polarimetric Synthetic Aperture Radar (PolSAR) land cover classification. However, the existing methods face two main challenges: accurately modeling the complex nonlinear relationships betw...
Mesoscale eddies play a crucial role as primary transporters of heat, salinity, and freshwater in oceanic systems. Utilizing the latest Surface Water and Ocean Topography (SWOT) dataset, this study employed the py-eddy-tracker (PET) algorithm to iden...
Accurately and timely estimating three-dimensional ocean states is crucial for improving operational ocean forecasting capabilities. Although satellite observations provide valuable evolutionary information, they are confined to surface-level variabl...
In the face of rapid infrastructure expansion and escalating anthropogenic activities, it becomes imperative to prioritize the examination of long-term transformations in land cover and ecological quality within the Greater Mekong Subregion (GMS). We...
The sea surface temperature (SST) is an important parameter reflecting the energy exchange between the ocean and the atmosphere, which has a key impact on climate change, marine ecology and fisheries. However, most of the existing SST fusion methods...
Object detection is a critical task in autonomous driving. Currently, 3D object detection methods for autonomous driving primarily rely on stereo cameras and LiDAR, which are susceptible to adverse weather conditions and low lighting, resulting in li...
The deployment of landslide intelligent recognition models in non-training regions encounters substantial challenges, primarily attributed to heterogeneous remote sensing acquisition parameters and inherent geospatial variability in factors such as t...
Aba Tibetan and Qiang Autonomous Prefecture (Aba Prefecture), located in Southwest China, has complex geological conditions and frequent seismic activity, facing an increasing landslide risk that threatens the safety of local communities. This study...
Remote Sensing Image Change Captioning (RSICC) has emerged as a cross-disciplinary technology that automatically generates sentences describing the changes in bi-temporal remote sensing images. While demonstrating significant potential for urban plan...
Deep learning-based hyperspectral image (HSI) classification methods, such as Transformers and Mambas, have attracted considerable attention. However, several challenges persist, e.g., (1) Transformers suffer from quadratic computational complexity d...
While groundwater-dependent ecosystems (GDEs) occupy only a small portion of the Earth’s surface, they hold significant ecological value by providing essential ecosystem services such as habitat for flora and fauna, carbon sequestration, and er...
The estimation and correction of antenna patterns are essential for ensuring the relative radiometric quality of SAR images. Traditional methods for antenna pattern estimation rely on artificial calibrators or specific stable natural scenes like the...
Light detection and ranging (LiDAR) has the advantage of simultaneous localization and mapping with high precision, making it one of the important sensors for intelligent robotics navigation, positioning, and perception. It is common knowledge that t...
HSI classification is essential for monitoring and analyzing the Earth’s surface, with methods utilizing convolutional neural networks (CNNs) and transformers rapidly gaining prominence and advancing in recent years. However, CNNs are limited b...
Impulse ultrawideband (UWB) synthetic aperture radar (SAR) combines high-azimuth-range resolution with robust penetration capabilities, making it ideal for applications such as through-wall detection and subsurface imaging. In such systems, the perfo...
Capturing real-world aerial images for vision-based navigation (VBN) is challenging due to limited availability and conditions that make it nearly impossible to access all desired images from any location. The complexity increases when multiple locat...
The rapid development of UAV-LiDAR and data processing capabilities is likely to enable accurate individual-tree inventories in the near future, requiring few on-ground calibration measurements. Using data collected from 20 radiata pine trials disper...
Using Planetscope imagery, we trained a random forest model to detect Callery pear (Pyrus calleryana) throughout a diverse urban landscape in Columbia, Missouri. The random forest model had a classification accuracy of 89.78%, a recall score of 0.693...
Point cloud filtering plays a crucial role in ground point extraction in urban environments. It can effectively distinguish ground points from object points, reduce data redundancy, and improve processing efficiency, providing accurate foundational d...
Airborne hyperspectral LiDAR (AHSL) is a technology that integrates the spectral content collected using hyperspectral imaging and the precise 3D descriptions of observed objects obtained using LiDAR (light detection and ranging). AHSL detects the sp...
Precise point positioning ambiguity resolution (PPP-AR) is a key technique for high-precision global navigation satellite system (GNSS) observations, with phase bias products playing a critical role in its implementation. The multi-GNSS experiment an...
Aiming at the problem of nonlinear observation model mismatch and insufficient anti-interference ability of SINS/GNSS integrated navigation system in complex dynamic environment, this paper proposes an adaptive robust filtering algorithm with improve...
This paper proposes a novel point cloud multi-scale completion algorithm guided by image rotation attention mechanisms to address the challenges of severe information loss and suboptimal fusion effects in multi-modal feature extraction and integratio...
The long-term monitoring of nighttime lights is essential for understanding sources of light pollution. Nighttime lights observed in space are affected by atmospheric conditions as they transmit from the Earth surface through clouds and aerosols to t...
With the background of on-orbit repetitive connection and separation of CubeSats, an electromagnetic docking mechanism for repeated docking and separation is proposed. A reusable electromagnetic docking scheme combining lead screw transmission with e...
Remotely Piloted Aircraft (RPA) as sensor-carrying airborne platforms for indirect measurement of plant physical parameters has been discussed in the scientific community. The utilization of RGB sensors with photogrammetric data processing based on S...
Low Earth Orbit (LEO) satellite communication is gradually becoming the main carrier for satellite communication by virtue of its advantages, such as high landing power, narrow beam, large transmission bandwidth, and small time delay. In the military...
The deterioration of stone materials due to atmospheric factors is a growing global concern, affecting the integrity and preservation of numerous UNESCO World Heritage Sites around the world. This study provides an estimate of the long-term impact of...
For the satellite orbit pursuit–evasion game problem, this paper proposes a multi-stage optimization-based solution aimed at improving the confrontation strategies between task satellites and target satellites in complex space environments. The...
The temperature and humidity profiles within the planetary boundary layer (PBL) are crucial for Earth’s climate research. The Atmospheric Sounder Spectrometer by Infrared Spectral Technology (ASSIST) measures downward thermal radiation in the a...
Infrared small target detection plays a crucial role in fields such as remote sensing and surveillance. However, during long-distance imaging, factors such as atmospheric attenuation lead to a low signal-to-clutter ratio for the targets, making their...
This research aims to estimate long-term aerosol radiative effects by combining radiation and Aerosol Optical Depth (AOD) observations in Barcelona, Spain. Aerosol Radiative Forcing and Aerosol Forcing Efficiency (ARF and AFE) were estimated by combi...
Coastal areas have been the target of interdisciplinary research aiming to support studies related to their socio-economic and ecological value and their role in protecting backshore ecosystems and assets from coastal erosion and flooding. Some of th...
The effective segmentation of cloud and cloud shadow is an important issue in remote sensing image processing, which is of great significance for surface feature extraction, climate detection, atmospheric correction, etc. However, the characteristics...
Despite advances in remote sensing object detection, accurately identifying small, weak objects remains challenging. Their limited pixel representation often fails to capture distinctive features, making them susceptible to environmental interference...
Ground-penetrating radar (GPR) has emerged as a promising technology for estimating the soil water content (SWC) in the vadose zone. However, most current studies focus on partial GPR data, such as travel-time or amplitude, to achieve SWC estimation....
Time downscaling is one of the most challenging topics in remote sensing and meteorological data processing. Traditional methods often face the problems of high computing cost and poor generalization ability. The framework interpolation method based...
Zhejiang Province, a pivotal economically developed region within China’s Yangtze River Delta, requires systematic investigation of spatiotemporal vegetation dynamics and their drivers to formulate targeted ecological protection policies and op...
Monitoring volumetric glacier change requires cost-effective and accessible methods to generate multi-temporal digital elevation models (DEMs). We present Planet4Stereo, an open-source photogrammetry pipeline developed to generate DEMs from low-cost...
Arid zone lakes function as indicators of watershed ecology and environment, significantly influencing regional social development. In Ebinur Lake, a fuzzy water–land boundary hinders lake area extraction using remote sensing. Furthermore, unqu...
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