Advances in Space Research最新文献

{"title":"Preface: Ionospheric imaging: recent advances and future directions","authors":"Marcio T.A.H. Muella, Fabricio S. Prol","doi":"10.1016/j.asr.2025.08.009","DOIUrl":"10.1016/j.asr.2025.08.009","url":null,"abstract":"","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 7","pages":"Pages 3755-3756"},"PeriodicalIF":2.8,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144933842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imaging ionosphere’s wave like structure using interferometry data","authors":"Bhuvnesh Brawar ,&nbsp;Abhirup Datta ,&nbsp;Sarvesh Mangla","doi":"10.1016/j.asr.2025.07.059","DOIUrl":"10.1016/j.asr.2025.07.059","url":null,"abstract":"<div><div>The ionosphere is an ionised region in the Earth’s upper atmosphere, which significantly impacts radio signal propagation by refracting and reflecting them. As a result, ionospheric disturbances can degrade the performance of navigation, communication, and space-based systems. Understanding the dynamics and processes of the ionosphere is essential, leading to significant advancements in instrumentation and analytical techniques.</div><div>This study presents an ionospheric imaging technique using interferometric data. Radio interferometers, such as the Giant Meter-wave Radio Telescope (GMRT), are highly sensitive to phase fluctuations, enabling the detection of total electron content (TEC) variations with a precision of <span><math><mrow><msup><mrow><mn>10</mn></mrow><mrow><mo>-</mo><mn>3</mn></mrow></msup><mspace></mspace><mi>TECu</mi></mrow></math></span> and TEC gradients with an accuracy of approximately <span><math><mrow><mn>7</mn><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mo>-</mo><mn>4</mn></mrow></msup><mspace></mspace><mi>TECu</mi><mspace></mspace><msup><mrow><mi>km</mi></mrow><mrow><mo>-</mo><mn>1</mn></mrow></msup></mrow></math></span>. We introduce an antenna-based approach for constructing phase screens using measured TEC gradients for each interferometric baseline by employing a surface reconstruction algorithm. To incorporate the necessary integral constant as a boundary condition, we utilized output from the International Reference Ionosphere (IRI-2016) model. The generalized least squares method was applied to ensure an optimal reconstruction of the ionospheric phase screen, enhancing the accuracy of ionospheric imaging.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 7","pages":"Pages 3830-3839"},"PeriodicalIF":2.8,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144933698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correlation of atmospheric CO2 level changes with geophysical and atmospheric indices","authors":"Nhung Le ,&nbsp;Luyen K. Bui ,&nbsp;Dmitri Kondrashov ,&nbsp;T.T. Thuy Pham ,&nbsp;Harald Schuh","doi":"10.1016/j.asr.2025.07.054","DOIUrl":"10.1016/j.asr.2025.07.054","url":null,"abstract":"<div><div>Parts of the Earth’s system interact with each other, causing effects that are attributed to the dynamic and complex features of the Earth’s climate system. Both solar and human activities are warned to have an impact on atmospheric Carbon Dioxide (CO₂) concentration, contributing to global climate change. Thus, determining the relationship between changes in atmospheric CO₂ levels and atmospheric and geophysical indices is crucial for a better understanding of the global carbon cycle and key climate drivers. However, the methods and physical parameters selected among studies are inconsistent, as different studies often use different parameters. Additionally, the relationship between CO₂ and the indices of solar and geomagnetic activity has only been quantified by trends indicating increases or decreases, but not specific correlation coefficients. Therefore, through comprehensive assessments of 194 CO₂ monitoring stations in the Fluxnet database, we examine thirteen atmospheric and geophysical indices, including surface atmospheric loading, four meteorological parameters, seven solar activity indices, and the Dst index of the geomagnetic activity, to determine their linear and nonlinear correlations with changes in atmospheric CO₂ levels. The parameters investigated in this study, e.g., the Dst index, plasma speed, and F10.7, may be valuable for ionospheric modeling and communication and navigation applications. Significantly, the cross-correlation technique is employed to detect time lags, which indicate how quickly changes in CO₂ levels are observed on the data pattern of the investigated indices for a better understanding of the carbon cycle. Our experimental results show that Spearman’s test and squared wavelet spectral coherence are recommended for measuring correlations between CO₂ levels and atmospheric and geophysical indices. Moreover, this study identifies the typical thirteen physical parameters statistically relevant to changes in atmospheric CO₂ levels, which might be considered as potential features for the prediction of atmospheric CO₂ levels. Of those, three parameters, namely temperature, wind speed, and shortwave radiation, could be recommended for warnings of atmospheric CO₂ anomalies. Six parameters, including precipitation, atmospheric surface loading, plasma speed, F10.7, R sunspot number, and sunlight magnitude, would be more suitable for (near) real-time tracking of CO₂ level changes. Our findings could also contribute to ionospheric imaging by identifying key parameters for data assimilation or validating ionospheric models under varying solar and geomagnetic conditions.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 7","pages":"Pages 3946-3962"},"PeriodicalIF":2.8,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144933838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing detection of satellite laser ranging signal in low signal-to-noise ratio conditions","authors":"Julian Rodriguez-Villamizar ,&nbsp;Matthew Wilkinson ,&nbsp;Nicolas Maurice ,&nbsp;José Carlos Rodríguez ,&nbsp;Toshimichi Otsubo","doi":"10.1016/j.asr.2025.07.035","DOIUrl":"10.1016/j.asr.2025.07.035","url":null,"abstract":"<div><div>Laser ranging stations encounter low signal-to-noise returns when acquiring more distant satellite targets at lower elevations and in poorer atmospheric conditions. Signal tracks from successful detections of the retro-reflected light returning from a satellite can be identified in repeated range residuals that will also contain background noise. A close look at different observing scenarios and methods used to extract the satellite returns from background noise, developed over time at lunar and satellite laser ranging stations, reveals similar binning, trend removal and threshold approaches tuned to the individual stations, considering so far only parallelogram shapes. To generalise this common signal identification problem at laser ranging stations, the distribution of data recorded during a satellite pass is described using Poisson statistics, accounting for both the signal and noise elements. A model is then outlined and tested against real observations. We propose a method for the reduction of noise for the first-photon arrival effect typical of single-photon avalanche diodes (SPAD).</div><div>The number of entries that fall inside a 2D bin is compared against a threshold, defined by the likelihood ratio, to decide if the observed mean rate is closer to the one of the noise or of the signal. For the optimization of the bin size and threshold, we use Receiver Operating Characteristic (ROC) curves to choose the values that maximize true signal detection with minimum false positives.</div><div>We consider a new geometrical pattern for the 2D binning of the observation domain. The new pattern consists of hexagons and an improvement of 20 % in signal detection was achieved compared to using equivalent parallelogram bins.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 6","pages":"Pages 3465-3479"},"PeriodicalIF":2.8,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preliminary investigation of planar Sun-Ceres trajectories in variable restricted dynamical models","authors":"Robert A. Bettinger,&nbsp;Elliot A. Potter,&nbsp;Conner S. O’Malley,&nbsp;Annika J. Gilliam,&nbsp;Tyler J. Kapolka","doi":"10.1016/j.asr.2025.07.027","DOIUrl":"10.1016/j.asr.2025.07.027","url":null,"abstract":"<div><div>The dwarf planet Ceres is the largest body in the Asteroid Belt and represents a key destination for planetary science missions seeking to understand the evolution of small bodies. Due to its location on the boundary between the inner and outer planets of the Solar System, Ceres could become a lucrative base camp location for asteroid mining and surveying operations, or a way-station for outer planet missions. This paper, for the first time in literature, presents 93 unique planar periodic and quasi-periodic orbits discovered in the Sun-Ceres system that may be employed for Ceres-focused missions. The Circular Restricted Three-Body Problem (CR3BP) and Circular Restricted N-Body Problem (CRNBP) are used as the primary dynamical models for orbit generation. The CR3BP orbits were discovered using a combination of Poincaré mapping and grid search techniques for 10 different Jacobi constants. For the CRNBP, the system is expanded to include not only the Sun and Ceres, but also Earth, Mars, and Jupiter as perturbing gravitational bodies. Poincaré mapping was also employed for the CRNBP, but with two sets of initial grid conditions corresponding to CR3BP Jacobi constant values and two initial phase angle cases for the included bodies. For all discovered orbits, specific initial position and velocity states are provided, accompanied by recommendations for their potential mission applications. This research aims to advance ongoing astrodynamics research by filling a catalog hole and providing a Sun-Ceres orbit baseline for two different multi-body restricted models.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 6","pages":"Pages 3595-3646"},"PeriodicalIF":2.8,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new triplet-branch framework based on pixel-level subtraction features from bi-temporal remote sensing images for semantic change detection","authors":"Xiaoyong Liu ,&nbsp;Xin He ,&nbsp;Zhanhao Xiao ,&nbsp;Zhiguo Du ,&nbsp;Qiong Hu ,&nbsp;Shaozhong Song ,&nbsp;Yanqiu Li","doi":"10.1016/j.asr.2025.07.023","DOIUrl":"10.1016/j.asr.2025.07.023","url":null,"abstract":"<div><div>Semantic Change Detection (SCD) is a task of extracting changed areas and identifying their semantic category information from remote sensing images (RSIs). Previous studies have shown that a triplet-branch structure, consisting of one change detection branch and two semantic segmentation branches, is an effective solution for SCD. However, these methods rely on carefully designed interaction and fusion modules for features among branches to integrate information, which increases the complexity of utilizing semantic information. Moreover, the interaction of deep features from different branches alters the feature information, which may lead to inaccurate segmentation at the decision layer. In this paper, we propose PSFNet, a novel triplet-branch SCD framework that utilizes pixel-level difference features from bi-temporal images. More specifically, it includes two segmentation branches which focus on the segmentation of changed areas and a change branch which enhances boundary distinction between changed and unchanged areas. By conducting experiments on two public challenging benchmarks, we show that our method achieves the optimal performance over the state-of-the-art methods, with the Fscd of 65.20 % and the mIoU of 73.78 % on the SECOND dataset and with the Fscd of 92.79 % and the mIoU of 92.23 % on the Landsat-SCD dataset.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 6","pages":"Pages 3430-3444"},"PeriodicalIF":2.8,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Addressing landcover bias in spatial downscaling of MODIS land surface temperature using generative adversarial network-based regression model (RGAN)","authors":"Rey Jalbuena ,&nbsp;Jurng-Jae Yee ,&nbsp;Geun Young Yun ,&nbsp;Sarath Raj","doi":"10.1016/j.asr.2025.07.024","DOIUrl":"10.1016/j.asr.2025.07.024","url":null,"abstract":"<div><div>The increasing demand for high-resolution Land Surface Temperature (LST) data has driven significant interest in enhancing LST imagery, which is crucial for numerous ecological and urban climate applications. Nevertheless, the issue of consistently available high-spatiotemporal LST data persists. Several techniques, primarily concentrating on LST downscaling, have been suggested to tackle this challenge; however, problems such as thermal contrast and land cover accuracy bias endure. To tackle this, this research recommends the utilization of Regression-based generative adversarial networks (RGAN) for LST downscaling. RGAN employs two neural networks for adversarial training, allowing the creation of hyperrealistic images from image noise. RGAN has been utilized in other pan- sharpening methodologies and yielded enhanced outcomes compared to previous techniques. The research centers on three Korean cities—Seoul, Busan, and Daegu. These cities were chosen to evaluate RGAN’s adaptability to diverse urban topographies. The proposed model is implemented to downscale MODIS LST utilizing Landsat OLI based indices and subsequently compared its efficiency to other machine learning (ML) techniques. Findings exhibit RGAN’s exceptional performance, notably in achieving a Root Mean Square Error (RMSE) of ∼1 °C (0.98 to 1.32 °C), outperforming traditional techniques like TsHARP, RF, ANN, and CNN. This superiority extends to Mean Absolute Error (MAE) and Mean Bias Error (MBE), where RGAN records the most minimal values, suggestive of its high precision and minimal bias. It is also observed that RGAN consistently performs better across various land cover categories and has higher thermal contrast, indicating its dependability across diverse urban settings. Furthermore, SHapley Additive exPlanations (SHAP)-based interpretation was employed to analyze the influence of input features under different land cover contexts, enhancing the model’s transparency and physical relevance.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 6","pages":"Pages 3445-3464"},"PeriodicalIF":2.8,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling of the ionospheric electron density variations induced by intense polar rain electron precipitation","authors":"Su Zhou ,&nbsp;Lingmin Wang ,&nbsp;Zongxian Wu ,&nbsp;Zhijin Zhou ,&nbsp;R. Selvakumaran ,&nbsp;Sneha A. Gokani","doi":"10.1016/j.asr.2025.07.025","DOIUrl":"10.1016/j.asr.2025.07.025","url":null,"abstract":"<div><div>The ionospheric F-region electron density in the polar cap region is highly dynamic, and is influenced significantly by the ionospheric convection driven by the solar wind. Meanwhile, the E-region electron density is dominated by the photochemical processes, which remain less well explored. This study employs the GLOW model to investigate the ionospheric electron density variations caused by intense keV polar rain electron precipitation. These polar rain electrons lead to a notable increase in the ionospheric electron density, primarily in the altitude range of 100–200 km. The peak enhancement occurs at 120–130 km, where the dayside electron density increases by a factor of 1.42 due to the keV polar rain electrons. On the nightside, the electron density produced by solar irradiance is reduced. Consequently, the polar rain electron precipitation increases the peak electron density by a factor of 5. Theoretical calculations indicate that the density increase is primarily due to the electron impact ionization of N₂, which leads to a significant enhancement in the number density of NO⁺. While the intense keV polar rain electrons are much weaker compared to the electron precipitation inside the auroral oval, this study suggests that the electron density at the altitude range of 100–200 km is notably responsive to the precipitation of keV polar rain electrons in the polar cap region.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 6","pages":"Pages 3681-3691"},"PeriodicalIF":2.8,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing tropical flood susceptibility mapping with multi-head attention mechanism and deep learning models","authors":"Azlan Saleh ,&nbsp;Mou Leong Tan ,&nbsp;Fadzli Mohamed Nazri ,&nbsp;Zaher Mundher Yaseen ,&nbsp;Fei Zhang","doi":"10.1016/j.asr.2025.07.022","DOIUrl":"10.1016/j.asr.2025.07.022","url":null,"abstract":"<div><div>Deep learning (DL) models have demonstrated a significant potential in predicting complex phenomena such as flood susceptibility mapping, particularly with large datasets. However, overfitting remains a challenge, limiting DL models generalizability. This study aims to enhance flood susceptibility mapping by integrating the multi-head attention (MHA) mechanism into DL models, focusing on the Muda River Basin. Six machine learning (ML) models were evaluated: Support Vector Machine (SVM), Bidirectional Gated Recurrent Unit (BGRU), K-Nearest Neighbors (KNN), Bidirectional Long Short-Term Memory (BLSTM), and two advanced models, MHA-BGRU and MHA-BLSTM. Fifteen flood influencing factors were selected, including plan curvature, elevation, stream power index (SPI), slope, topographic position index (TPI), profile curvature, topographic wetness index (TWI), rainfall, convergence index (CI), land use/land cover (LULC), aspect, normalized difference vegetation index (NDVI), topographic ruggedness index (TRI), distance from rivers, and soil type. Pearson’s Correlation Coefficient (PCC) and Information Gain Ratio (IGR) methods were applied for optimal feature selection. Results revealed that MHA-based models outperformed the others, with improvements exceeding 11 % in the area under the curve (AUC), 12 % in accuracy, 16.67 % in F1-score, and 33 % in hit rate. Among these, the MHA-BLSTM model achieved superior performance, confirmed by the Wilcoxon signed-rank test and bootstrap uncertainty analysis. Model performance was further assessed using mean annual and total maximum rainfall during flash floods. The MHA-BLSTM model produced more balanced predictions across susceptibility categories. These findings highlight the effectiveness of the MHA mechanism in enhancing flood susceptibility mapping in tropical regions.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 6","pages":"Pages 3402-3429"},"PeriodicalIF":2.8,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radio frequency transients correlated with electron flux measured on-board the STP-Sat6","authors":"Amitabh Nag,&nbsp;Erin H. Lay,&nbsp;Brian A. Larsen,&nbsp;Megan D. Mark,&nbsp;Philip A. Fernandes,&nbsp;Alex R. Attanasio","doi":"10.1016/j.asr.2025.07.026","DOIUrl":"10.1016/j.asr.2025.07.026","url":null,"abstract":"<div><div>We analyzed transient electromagnetic signatures, referred to as spacecraft environment discharges (SEDs) or on-board discharges (OBDs), and the in-situ particle environment simultaneously measured by the Radio Frequency Sensor (RFS) and the Space and Atmospheric Burst Reporting System Z-plasma spectrometer (SABRS-ZPS), respectively. These sensors are on-board the U.S. Department of Defense Space Test Program Satellite 6 (STP-Sat6) in geostationary orbit. Radio frequency signatures of SEDs on STP-Sat6 have relatively high peak amplitudes; they often caused amplitude-saturation in the so-called high band (120–140 MHz frequency range) of the RFS likely due to the proximity of their source to the RFS’s dipole antennas. We examined the occurrence rate of SEDs reported by the RFS and its temporal relationship to electron flux in the 7.9–12.2 keV range. Peaks in SED count rates were time-correlated with peaks in electron flux. The electron-flux peaks appeared to lead the SED count rate peaks by 24–45 min for the 7.9–12.2 keV energies. This indicates that incidence of electrons at this relatively low-energy range likely resulted in ramping up of the charging of the spacecraft leading to periods of high occurrence rates of discharges in and around the spacecraft.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 6","pages":"Pages 3692-3699"},"PeriodicalIF":2.8,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}