Advances in Space Research最新文献

{"title":"A novel InSAR-based method for retrieving active layer thickness: Emphasizing soil pore ratio and unfrozen water content","authors":"Delong Zhang ,&nbsp;Guanjun Wei ,&nbsp;Xueke Ma ,&nbsp;Yongxin Wang","doi":"10.1016/j.asr.2025.03.032","DOIUrl":"10.1016/j.asr.2025.03.032","url":null,"abstract":"<div><div>Active Layer Thickness (ALT) is a crucial indicator for assessing the status of permafrost. Large-scale monitoring of ALT is of significant importance for the ecological environment and engineering projects in permafrost regions. Interferometric Synthetic Aperture Radar (InSAR) has emerged as a vital tool for retrieving ALT. However, due to the harsh natural conditions in permafrost areas, the understanding of the mechanisms governing ALT formation remains incomplete, leading to inaccuracies in InSAR-based ALT retrieval. In this study, we developed an InSAR retrieval model for ALT that integrates surface deformation and soil water content. This model accounts for changes in the pore ratio of permafrost soil and the presence of unfrozen water during freeze–thaw cycles. Using Sentinel-1 ascending and descending data, we derived vertical displacements from 2018 to 2020. These displacements were incorporated into the model to estimate ALT along the Lanzhou-Urumqi High-Speed Railway (LUHR).The results showed that vertical displacements in the study area ranged from −0.061 m to 0.140 m, while ALT estimates varied from 0 to 4.553 m. The average ALT for the years 2018, 2019, and 2020 were 0.986 m, 0.994 m, and 1.099 m, respectively. Validation against ALT estimates derived from the Stefan model revealed mean absolute errors (MAE) of 0.212 m, 0.582 m, and 0.227 m for 2018, 2019, and 2020, respectively. These results demonstrate the high accuracy of our model. This study provides a new idea of using InSAR technology for large-scale ALT estimation.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 11","pages":"Pages 7835-7846"},"PeriodicalIF":2.8,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936043","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":"Observer-based robust preview control for tracking low Earth orbit targets of a 2.5-meter optical telescope with wind disturbance","authors":"Jueqi Lin ,&nbsp;Weirui Chen ,&nbsp;Zheng Wang ,&nbsp;Xiaojun Zhou ,&nbsp;Yu Han","doi":"10.1016/j.asr.2025.03.030","DOIUrl":"10.1016/j.asr.2025.03.030","url":null,"abstract":"<div><div>Fast and accurate tracking of low Earth orbit (LEO) targets is challenging in the presence of variable environmental wind disturbances and measurement noise. To deal with this challenge, a 2.5-meter optical telescope control system is designed in this paper. Based on the descriptor system augmented with the wind disturbance, a T-N-L observer is employed to estimate the extended system states. With these estimations and the preview trajectory information, a composite robust preview controller (TNL-CRPC) is designed and optimized by <span><math><mrow><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></mrow></math></span> method to improve the tracking performance while compensating for wind disturbances. Two simulation experiments are conducted to evaluate the proposed control scheme against three traditional control methods, i.e., PID, ADRC and TNL-PID. Simulation results demonstrate that the developed control system achieves improved tracking performance and disturbance rejection capability, meeting the telescope’s design requirements.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 11","pages":"Pages 8304-8318"},"PeriodicalIF":2.8,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936539","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":"Slope unit-based comprehensive geohazard susceptibility assessment: SHAP interpretability and local InSAR deformation analysis","authors":"Peng Wang ,&nbsp;Hongwei Deng ,&nbsp;Jielin Li ,&nbsp;Zhen Jiang ,&nbsp;Guanglin Tian ,&nbsp;Yao Liu","doi":"10.1016/j.asr.2025.03.034","DOIUrl":"10.1016/j.asr.2025.03.034","url":null,"abstract":"<div><div>Frequent geological hazards worldwide necessitate robust and comprehensive susceptibility models for effective risk management. This study focuses on four common hazards—landslides, rockfalls, unstable slopes, and debris flows—in the Three Gorges Reservoir Area (TGRA) and introduces a comprehensive geohazard susceptibility modeling approach. The method employs a Soft Voting ensemble learning model integrating Random Forest (RF) and Light Gradient Boosting Machine (LGBM). Slope unit-based susceptibility models were developed to calculate individual geohazard susceptibility indexes (GSIs) for each hazard type, which were then combined using a proposed weighted average method to conduct a comprehensive geohazard susceptibility assessment. The results indicate that the ensemble model outperformed base models across all hazard types, achieving area under the receiver operating characteristic (ROC) curve (AUC) of 0.752, 0.721, 0.813, and 0.841 for landslides, rockfalls, unstable slopes, and debris flows, respectively. The comprehensive geohazard susceptibility map (GSM) revealed that high-susceptibility zones concentrated along the Yangtze River, with recent geohazard events closely matching these areas. Frequency Ratio (FR) analysis showed a rapid increase in FR values with rising susceptibility levels, exceeding 1 in high and very high susceptibility zones. To analyze the deformation characteristics of typical high-GSI slope units in the reservoir area, InSAR time-series deformation analysis was conducted, revealing significant subsidence correlated with seasonal rainfall and reservoir water level fluctuations. Additionally, five key factors influencing geohazard occurrence were identified using SHapley Additive exPlanations (SHAP), offering localized interpretation for individual slope units. The findings overcome the limitations of single-hazard assessments and offer practical solutions for regional planning, infrastructure protection, and disaster mitigation. This research provides a valuable framework for policymakers and practitioners to enhance the resilience and ensure safety in geohazard-prone regions.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 11","pages":"Pages 7863-7888"},"PeriodicalIF":2.8,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936113","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":"Orbital prediction accuracy improvement method based on particle swarm optimization RBF neural network","authors":"Muyu Guo,&nbsp;Taiyang Lu,&nbsp;Shibo Chen,&nbsp;Xiangshuai Song,&nbsp;Dakai Liu,&nbsp;Xiande Wu","doi":"10.1016/j.asr.2025.03.031","DOIUrl":"10.1016/j.asr.2025.03.031","url":null,"abstract":"<div><div>In response to the increasing demand for the improved accuracy in satellite orbit prediction, this study introduces a method to enhance the orbit prediction precision with RBF neural network utilizing particle swarm optimization. The research specifically targets low-Earth orbit satellites for the development and modeling process. The constructed PSO-RBFNN model is trained using the orbital error data from real satellites, enabling the prediction of future satellite error data. Then, the prediction error data is utilized to correct any errors that may arise during the calculation of orbit predictions in the dynamics model. In order to demonstrate the outstanding performance of the model proposed in this paper, we trained the PSO-RBFNN designed in this study and other common neural network models (such as BP, LSTM, and RBF) on data at different time intervals. The results confirm that the PSO-RBFNN has good prediction ability when applied to orbital error data. Furthermore, the study examines the impact of neural network architecture and training data on the performance of the model. Finally, this study evaluates the generalization capability of a model designed on one satellite to other satellites.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 11","pages":"Pages 8105-8121"},"PeriodicalIF":2.8,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936543","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":"River salinity mapping through machine learning and statistical modeling using Landsat 8 OLI imagery","authors":"Mohsen Ansari ,&nbsp;Anders Knudby ,&nbsp;Saeid Homayouni","doi":"10.1016/j.asr.2025.03.037","DOIUrl":"10.1016/j.asr.2025.03.037","url":null,"abstract":"<div><div>This study uses Landsat 8 OLI imagery and 102 <em>in situ</em> salinity data points to investigate salinity mapping in the Karun River, southwestern Iran. A total of 24 features, including salinity indices and Landsat 8 OLI spectral bands, were assessed using the Random Forest Feature Importance Score (RFFIS), Sobol’ sensitivity analysis, and correlation with salinity to identify the most sensitive features for salinity estimation. These included the Red and Green bands, Salinity index 2–6, Normalized Suspended Material Index (NSMI), and Enhanced Green Ratio Index (EGRI). A total of 24 regression models, including statistical, kernel-based, Neural Network (NN)-based, and Decision Tree (DT)-based models, were evaluated using statistical error metrics and global, as well as local, Moran’s I measures of residual spatial autocorrelation. The DT-based models, specifically Gradient Boosted DT (GBDT), outperformed other models, demonstrating low errors, bias, and non-significant residual spatial autocorrelation. Kernel-based models performed better than conventional linear models, while NN models tended to underfit. Residual spatial autocorrelation analysis indicated that models incorporating spatial information reduced residual autocorrelation. Landsat 8 OLI imagery effectively mapped salinity dynamics, revealing increased salinity from Gotvand to Ahvaz city due to agricultural activities and the Gachsaran formation within the reservoir.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 10","pages":"Pages 6981-7002"},"PeriodicalIF":2.8,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906047","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":"LBLSTM observer based performance guaranteed tracking control for flying around a non-cooperative target","authors":"Caisheng Wei ,&nbsp;Pengfei Guo ,&nbsp;Ruiwu Lei ,&nbsp;Yi Wang ,&nbsp;Xiaopeng Xue","doi":"10.1016/j.asr.2025.03.020","DOIUrl":"10.1016/j.asr.2025.03.020","url":null,"abstract":"<div><div>This paper investigates fly-around control problem for a non-cooperative space target subject to uncertain space perturbations, actuator saturation and unknown maneuvers of the target. Firstly, to provide the full state information required by prescribed performance control (PPC) method, a Lyapunov based long short-term memory (LBLSTM) observer is designed to adaptively estimate the relative motion velocity in line of sight (LOS) coordinate system. Then, based on the estimated information from LBLSTM observer, a performance guaranteed controller is developed via utilizing PPC technique. Compared with existing fly-around control methods, the key advantage of the proposed approach lies in its ability to accurately estimate the relative motion velocity without relying on prior knowledge of uncertain dynamics. This capability enables high-quality tracking control even in the presence of measurement errors and unknown maneuvers. Finally, two groups of circular and elliptical fly-around illustrative examples are organized to validate the effectiveness of the proposed control method.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 11","pages":"Pages 8052-8064"},"PeriodicalIF":2.8,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936031","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":"Hybrid Gaussian mixture model and unscented transformation algorithm for uncertainty propagation within the PUZZLE software","authors":"Roberto Detomaso,&nbsp;Andrea Muciaccia,&nbsp;Camilla Colombo","doi":"10.1016/j.asr.2025.03.026","DOIUrl":"10.1016/j.asr.2025.03.026","url":null,"abstract":"<div><div>Nowadays, the constant increase of space debris represents a great concern for all space operators and agencies. With a higher amount of space junk, the collision risk for active missions inevitably grows. For this reason, building up accurate models for space debris is useful to support the reconstruction of past fragmentation events, but also to foster the prediction of possible future breakups. However, the available data about space debris distribution are not always accurate and the models may lead to incorrect previsions.</div><div>The work proposed in this paper has two main objectives: firstly, the development of a hybrid method for the non-linear propagation of the uncertainty associated with the state of orbital fragments, then, the inclusion of such model within the PUZZLE software, a routine developed at Politecnico di Milano (initially under a contract with Italian Space Agency) for the detection and characterisation of a past fragmentation event.</div><div>The first goal is achieved by combining the Gaussian Mixture Model (GMM) and the Unscented Transformation (UT) methods for propagating the uncertainty associated with a non-linear system over time. To accomplish the second goal, a simplified version of the hybrid algorithm is introduced within the PUZZLE software to enrich the data set given as input with additional Two Line Elements (TLEs) for each object, taking into account the specified value of uncertainty. Numerical results and graphical representations will show the capability of the updated software for studying breakup events.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 10","pages":"Pages 7226-7241"},"PeriodicalIF":2.8,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143907543","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":"Event-driven prescribed-time control with flexible performance for 6-DOF spacecraft flying around a non-cooperative target under input constraints","authors":"He Zhang,&nbsp;Yin Zheng,&nbsp;Yan Wang","doi":"10.1016/j.asr.2025.03.025","DOIUrl":"10.1016/j.asr.2025.03.025","url":null,"abstract":"<div><div>This paper presents an event-driven prescribed-time control scheme with flexible performance for non-cooperative spacecraft fly-around missions under input constraints. First, an improved integrated model for relative attitude and position control is introduced, accounting for exogenous disturbances, model uncertainties of the non-cooperative target, actuator faults, and input saturation. In practice, the output of actuators is limited, particularly in the case of actuator failure, where the actual thrust or torque generated may not satisfy the requirements of the nominal performance function. To address this, a novel auxiliary system is proposed, which generates a series of modified signals. By incorporating these auxiliary signals, a flexible prescribed-time performance function is designed, allowing the performance to be adaptively relaxed during actuator saturation, and returning to its nominal level once saturation is resolved. Subsequently, an event-triggered robust adaptive controller is developed based on the performance function. This controller updates the control signal aperiodically, thereby conserving communication resources and reducing energy consumption. It guarantees that the relative attitude and position of the spacecraft strictly evolve within the bounds of the designed performance function and converge to the prescribed performance boundary within a specified time frame. Moreover, all closed-loop system states are ultimately uniformly bounded, and the design ensures the avoidance of Zeno behavior. Finally, the effectiveness of the proposed scheme is demonstrated through comparisons with advanced control schemes.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 11","pages":"Pages 8084-8104"},"PeriodicalIF":2.8,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936033","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":"Exploring the relationship between eruptive and non-eruptive solar flares through the periodic behaviour of magnetic helicity flux","authors":"Viktória Németh ,&nbsp;Szabolcs Soós ,&nbsp;Marianna B. Korsós","doi":"10.1016/j.asr.2025.03.027","DOIUrl":"10.1016/j.asr.2025.03.027","url":null,"abstract":"<div><div>To better understand the underlying processes and prerequisites for solar activity, it is essential to study the evolution of the lower solar atmospheric magnetic field of solar active regions (ARs) associated with large solar eruptions. Specifically, we aim to explore the relationship between derived quantities and the type of flares produced by the ARs, determining whether they are/are not associated with fast coronal mass ejections (CMEs). In this study, we examined the oscillations of the emergence (EM), shearing (SH), and total (T) components of the magnetic helicity flux in 14 <span><math><mrow><mi>δ</mi></mrow></math></span>-type ARs, building upon the work initiated by <span><span>Soós et al. (2022)</span></span>. By utilising the measured periods from their wavelet analysis of the three helicity flux components, we sought to further investigate their findings. Initially, it was observed that the periodic components of EM are typically 7 h longer when the flare occurs without a fast CME. Conversely, when the flare is accompanied by a fast CME, the periods of the SH component are generally 6 h longer than those of the EM component. These results support models that differentiate between what is the most dominant physical process of the eruptive and confined flare cases.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 11","pages":"Pages 8391-8397"},"PeriodicalIF":2.8,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936108","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":"On the response of equatorial and low latitude ionosphere over Indian region to the tropical cyclones","authors":"K. Shimna ,&nbsp;C. Vineeth ,&nbsp;R.K. Choudhary ,&nbsp;T.K. Pant ,&nbsp;M.S.M. Vijayan","doi":"10.1016/j.asr.2025.03.017","DOIUrl":"10.1016/j.asr.2025.03.017","url":null,"abstract":"<div><div>This paper presents, for the first time, the distinct impacts of two tropical cyclones Ockhi (2017) and Burevi (2020) on the equatorial and low-latitude ionosphere using multiple ionospheric parameters, including the Equatorial Electrojet (EEJ)-induced magnetic field, foF2, h′F, and GPS TEC. As the cyclones traversed the Indian equatorial region, the study investigates how modified electrodynamics over the dip equator (Trivandrum: 8.5°N, 77°E, 0.5°N dip latitude) influenced the low-latitude ionosphere (Hyderabad: 17.4°N, 78.4°E, 11.7°N dip latitude). During the passage of Tropical Cyclone Ockhi, a strong Counter-Electrojet (CEJ) with varying strength (–22 to −5 nT) was observed, accompanied by a decrease in foF2, and TEC at the equatorial site. Correspondingly, the low-latitude ionosphere also exhibited a decrease in TEC. In contrast, Tropical Cyclone Burevi, which was weaker than Ockhi, exhibited a weaker CEJ (−13 to −2.6 nT) along with an increase in critical frequency of F2 layer, and TEC at the equatorial site. Similarly, the low-latitude ionosphere showed an increase in TEC during Burevi’s passage. Ockhi, being a more intense cyclonic storm, demonstrated the presence of strong blanketing Es layers over Trivandrum, particularly near the peak of its cyclonic activity. On these days, although the Pre-Reversal Enhancement (PRE) was weaker, the presence of Equatorial Spread-F (ESF) was still observed. The wavelet periodogram of the EEJ-induced magnetic field, h′F and TEC revealed an intensification of gravity waves with ∼1-hour periodicity during the cyclones’ passage. Similarly, wavelet analysis of TEC over Trivandrum indicated the presence of enhanced terdiurnal tides during these events. It is proposed that. gravity waves generated by the cyclones likely caused the observed CEJs and ESF events. The observed variability in ionospheric parameters and TEC is attributed to modifications in E-region electrodynamics and subsequent changes in the plasma fountain. Strong tropical cyclones can disrupt the ionosphere through intense convection and lightning activity. Therefore, identifying the disturbances associated with cyclones is important for the studies pertaining to ionospheric modelling and space weather forecasting.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 11","pages":"Pages 8192-8205"},"PeriodicalIF":2.8,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935951","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}