2023 December-2 - 164 articles
The problem of accurate source localization has been an area of focus in high-frequency surface wave radar (HFSWR) applications. However, antenna pattern distortion (APD) decreases the direction-of-arrival (DOA) estimation performance of the multiple...
The use of infrared thermography (IRT) technique combining other remoting sensing techniques such as photogrammetry and unmanned aerial vehicle (UAV) platforms to perform geotechnical studies has been attempted by several previous researchers and enc...
Oil wells play an important role in the extraction of oil and gas, and their future potential extends beyond oil and gas exploitation to include the development of geothermal resources for sustainable power generation. Identifying and detecting oil w...
To take full advantage of rapidly deployable unmanned aerial vehicles (UAVs), it is essential to effectively compose many UAV images into one observation image over a region of interest. In this paper, we propose fast image mosaicking using a triangu...
Images captured by deep space probes exhibit large-scale variations, irregular overlap, and remarkable differences in field of view. These issues present considerable challenges for the registration of multi-view asteroid sensor images. To obtain acc...
Change detection is a crucial task in remote sensing that finds broad application in land resource planning, forest resource monitoring, natural disaster monitoring, and evaluation. In this paper, we propose a change detection model for cross-domain...
In recent years, convolutional neural networks (CNNs) have gained widespread adoption in remote sensing image processing. Deploying CNN-based algorithms on satellite edge devices can alleviate the strain on data downlinks. However, CNN algorithms pre...
Sugarcane is a major crop for sugar and biofuel production. Historically, mapping large sugarcane fields meticulously depended heavily on gathering comprehensive and representative training samples. This process was time-consuming and inefficient. Ad...
Obtaining spatial distribution information on mariculture in a low-cost, fast, and efficient manner is crucial for the sustainable development and regulatory planning of coastal zones and mariculture industries. This study, based on the Segment Anyth...
The advent of deep learning has significantly propelled the utilization of neural networks for Synthetic Aperture Radar (SAR) ship detection in recent years. However, there are two main obstacles in SAR detection. Challenge 1: The multiscale nature o...
Historically, the Texas Gulf Coast has been affected by many tropical storms and hurricanes. The most recent severe impact was caused by Hurricane Harvey, which made landfall in August 2017 on the central Texas coast. We evaluated the impact of Hurri...
Continuously global warming and landscape change have aggravated the damage of flood disasters to ecological safety and sustainable development. If the risk of flood disasters under climate and land-use changes can be predicted and evaluated, it will...
In March 1966, Ms 6.8 and 7.2 earthquakes occurred in Xingtai, North China, resulting in widespread soil liquefaction that caused severe infrastructure damage and economic losses. Using Keyhole satellite imagery combined with aerial images and fieldw...
The cities of the future should not only be smart, but also smart green, for the well-being of their inhabitants, the biodiversity of their ecosystems and for greater resilience to climate change. In a smart green city, the location of urban green sp...
Enhancing the spatial resolution of real-aperture microwave radiometers is an essential research topic. The accuracy of the numerical values of brightness temperatures (BTs) observed using microwave radiometers directly affects the precision of the r...
The watershed hydrologic conditions in the Madre de Dios (MDD) Basin in the Peruvian Amazon have been irreversibly impacted by deforestation and changes in land cover. These changes have also had detrimental effects on the geomorphology, water qualit...
To realize aerial target recognition in a complex environment, we propose a multi-source Takagi–Sugeno (T-S) intuitionistic fuzzy rules method (MTS-IFRM). In the proposed method, to improve the robustness of the training process of the model, t...
Ulva prolifera (U. prolifera), a global eco-environmental issue, has been recurring annually in the Yellow Sea of China since 2007, leading to significant impacts on the coastal ecosystem and the economies of coastal cities. To enhance the frequency...
In soybeans, off-target damage from the use of dicamba and 2,4-D herbicides for broadleaf weed control can significantly impact sensitive vegetation and crops. The early detection and assessment of such damage are critical for plant diagnostic labs a...
We present multi-sensor measurements from satellites, unmanned aerial vehicle, marine radar, thermal profilers, and repeated conductivity–temperature–depth casts made in the Kara Gates strait connecting the Barents and the Kara Seas durin...
The relative content of chlorophyll, assessed through the soil and plant analyzer development (SPAD), serves as a reliable indicator reflecting crop photosynthesis and the nutritional status during crop growth and development. In this study, we emplo...
Soil moisture (SM), as a crucial input variable of land surface processes, plays a pivotal role in the global hydrological cycle. The aim of this paper is to examine the spatiotemporal variability in SM in the Heihe River Basin using all-weather land...
The United Nations (UN) Sustainable Development Goals (SDGs) serve as a blueprint for securing a sustainable, healthy, and just future for people and the environment. Through the implementation of various policies and initiatives for Vision 2030, the...
In recent decades, the application of GIS and RS in archaeological and cultural heritage (ACH) has witnessed a notable surge both in terms of quantity and scope. During the initial implementation period (2016–2021) of the Digital Belt and Road...
For practical maritime SAR image classification tasks with special imaging platforms, scenes to be classified are often different from those in the training sets. The quantity and diversity of the available training data can also be extremely limited...
As one of the major water supply systems for inland rivers, especially in arid and semi-arid regions, snow cover strongly affects hydrological cycles. In this study, remote sensing datasets combined with in-situ observation data from a route survey o...
The emergence of new technologies has dynamized the way in which cultural heritage is documented, preserved, and passed on to new generations; something that determines a paradigm shift in terms of research in this field. Most operations now also hav...
In multi-modal images (MMI), the differences in their imaging mechanisms lead to large signal-to-noise ratio differences, which means that the matching of geometric invariance and the matching accuracy of the matching algorithms often cannot be balan...
Geomagnetic storms are one of the leading causes of ionospheric irregularities, depending on their intensity. The 6–10 September 2017 geomagnetic storm, the most severe geomagnetic event of the year, resulted from an X9 solar flare and a subseq...
Anomaly detection based on Kittler’s Taxonomy (ADS-KT) has emerged as a powerful strategy for identifying and categorizing patterns that exhibit unexpected behaviors, being useful for monitoring environmental disasters and mapping their consequ...
The classification of ship images has become a significant area of research within the remote sensing community due to its potential applications in maritime security, traffic monitoring, and environmental protection. Traditional monitoring methods l...
Unmanned aerial vehicles (UAVs) have emerged as a highly efficient means of monitoring landslide-prone regions, given the growing concern for urban safety and the increasing occurrence of landslides. Designing optimal UAV flight routes is crucial for...
The increase of the CO2 content in the atmosphere caused by anthropogenic emissions from the territories of large cities (~70%) is the critical factor in determining the accuracy of emission estimations. Advanced experiment-based methods of anthropog...
The Global Navigation Satellite System Occultation Sounder II (GNOS-II) payload onboard the Chinese Fengyun-3E (FY-3E) satellite is the world’s first operational spaceborne mission that can utilize reflected signals from multiple navigation sys...
Global Navigation Satellite System (GNSS) vertical displacements are widely used to infer terrestrial water storage (TWS) variations. The traditional Laplacian inversion requires dedicated efforts to determine the optimal parameters, which has an imp...
In this study, repeat-pass synthetic aperture radar interferometry (repeat-pass THz InSAR) is first extended to the terahertz band, and it has tremendous potential in the application of high-resolution three-dimensional (3D) imaging due to its shorte...
In 2017, Bureau of Economic Geology (BEG) researchers at the University of Texas at Austin (UT Austin) conducted an airborne lidar survey campaign, collecting topographic and bathymetric data over Lower Laguna Madre, which is a shallow hypersaline la...
Combining images from multiple Earth Observing (EO) satellites increases the temporal resolution of the data, overcoming the limitations imposed by low revisit time and cloud coverage. However, this requires an intercalibration process to ensure that...
Polarimetric synthetic aperture radar (PolSAR) image classification, a field crucial in remote sensing, faces significant challenges due to the intricate expertise required for accurate annotation, leading to susceptibility to labeling inaccuracies....
The spatiotemporal distribution of ecosystem service values (ESVs) and ecological risk are critical indicators to represent the regional ecological protection level and potential of sustainable development, which largely depend on land-use patterns....
The coal industry is a crucial component of China’s energy sector. However, the persistent exploitation of coal resources has gravely impacted the ecological environment. While the Remote Sensing Ecology Index (RSEI) is predominantly used for a...
The Balearic coastline presents an environmental and biological heterogeneity, which confers great complexity on the marine environment and treasures important biodiversity, both at the level of species and marine communities. The endemic phanerogam...
The accurate detection of collapsed buildings is of great significance for post-disaster rescue and reconstruction. High-resolution optical images are important data sources for identifying collapsed buildings, and the identification accuracy mainly...
The intense current of lightning plasma can emit radiation across various parts of the electromagnetic spectrum. Spectral observation is an effective means to understand the radiation characteristics of lightning channels at different wavelengths. In...
The spaceborne Electric Field Detector (EFD) is one of the payloads of the China Seismo-Electromagnetic Satellite (CSES-01), which can measure electric field data at near-Earth orbit for investigating fundamental scientific topics such as the dynamic...
Although deformations are mostly insignificant, they can be catastrophic when accumulated to certain amounts. Precise point positioning (PPP) can work with one receiver, preventing problems caused by the base station constrain upon employment of curr...
With the increasing global focus on renewable energy, distributed rooftop photovoltaics (PVs) are gradually becoming an important form of energy generation. Effective monitoring of rooftop PV information can obtain their spatial distribution and inst...
Land desertification is a key environmental problem in China, especially in Northwest China, where it seriously affects the sustainable development of natural resources. In this paper, we combine high-resolution satellite remote sensing images and UA...
NOMAD is a suite of spectrometers on the board of the ESA-Roscosmos Trace Gas Orbiter (TGO) spacecraft and is capable of investigating the Martian environment at very high spectral resolution in the ultraviolet–visible and infrared spectral ran...
Monocular depth prediction research is essential for expanding meaning from 2D to 3D. Recent studies have focused on the application of a newly proposed encoder; however, the development within the self-supervised learning framework remains unexplore...
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