Advances in Space Research最新文献

{"title":"A new method for shoreline extraction based on the mountain shadow index reveals detailed changes in the coastline of eastern Zhejiang coast, China","authors":"CuiShuo Ye,&nbsp;LiNa Cai,&nbsp;Jie Yin,&nbsp;XiaoYu Yang","doi":"10.1016/j.asr.2025.04.022","DOIUrl":"10.1016/j.asr.2025.04.022","url":null,"abstract":"<div><div>In recent years, coastlines have undergone significant changes due to human activities and environmental changes. Precise extraction of the coastline is especially necessary. However, in complex terrains such as mountainous coastal areas, the spectral similarity between mountain shadows and water bodies can lead to misclassification, reducing the accuracy of coastline extraction. To address this issue, this study proposed a visually-based Mountain Shadow Index and based on which we established a new coastline extraction method suitable for both high and low turbidity waters. This method achieves higher accuracy in areas with mountain shadows and turbid waters compared to the NDWI and MNDWI. Using this method, the study analyzed changes in the coastline of eastern Zhejiang over the past 20 years. The results show a clear seaward advancement of the coastline, with a shift from a jagged to a smoother profile. This transformation is primarily attributed to large-scale land reclamation projects, driven by increasing land-use pressures in the region. Moreover, the newly established method can be applied to other coastal areas worldwide.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 12","pages":"Pages 8627-8641"},"PeriodicalIF":2.8,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131186","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":"The pointer network for reward maximisation in multi-target space mission sequence selection","authors":"Edward Tomanek-Volynets,&nbsp;Matteo Ceriotti","doi":"10.1016/j.asr.2025.04.045","DOIUrl":"10.1016/j.asr.2025.04.045","url":null,"abstract":"<div><div>Multi-target space mission scenarios such as asteroid rendezvous, debris removal or satellite servicing, require targeting several orbits in a single mission, often to be selected among a large set, and therefore choosing optimal sequences of these orbits to be visited. This paper demonstrates a reinforcement-learning-based framework for selecting the sequence of targets to be visited in large-scale multi-target mission optimisation problems. The sequence selection is a NP-hard combinatorial optimisation problem. The proposed method builds upon a neural network architecture for combinatorial optimisation originally developed for Euclidean problems, to produce estimates of the optimal sequence of targets in very short amounts of time. The neural network is trained using a policy-gradient reinforcement-learning approach. Once training is complete, the network can be evaluated in two ways: one of these (greedy decoding) produces solutions on average 15<!--> <!-->% less optimal than Ant Colony Optimisation (ACO); the other (stochastic search) is on average 5<!--> <!-->% less optimal than ACO, using an iterative process that is slower than greedy decoding but still orders of magnitude faster than ACO. The quality of the network’s solutions is shown both averaged over large amounts of problems, and demonstrated more closely on a few specific instances.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 12","pages":"Pages 8687-8706"},"PeriodicalIF":2.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131099","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":"Long term global path planning for stratospheric airships under time-sequential uncertainty wind fields","authors":"JiaWen Xie ,&nbsp;JingGang Miao ,&nbsp;YuXuan Cui ,&nbsp;ZongQi Zhao ,&nbsp;Ying Lu","doi":"10.1016/j.asr.2025.03.029","DOIUrl":"10.1016/j.asr.2025.03.029","url":null,"abstract":"<div><div>Stratospheric airships serve as crucial platforms for near-space applications, and their path planning in complex wind fields is a key challenge limiting future large-scale applications. The wind field exhibits temporal variability and uncertainty, leading to discrepancies between the currently available forecast data and the actual wind field. In this study, we construct determined, undetermined and Time-Sequnential uncertainty wind fields by sequentially updating the global forecast wind field at appropriate frequencies and incorporating uncertainty distributions. Building upon local static field path planning using Markov Decision Processes (MDP), this paper introduces a Sequential Multi-stage Markov Decision Process (DR-MDP) algorithm to find the shortest-time path from the current position to a target area in complex, time-varying wind fields, enabling global long-term path planning.Through simulation experiments, this study analyzes the regional reachability and optimal path selection of aerostats with different propulsion capabilities under three wind field models. Results demonstrate that the proposed method can plan the shortest-time path to a target point in a given two-dimensional wind field environment and provide expected arrival times at each position, providing a feasibility basis for the actual flight planning of the stratospheric airship.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 12","pages":"Pages 8761-8779"},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131104","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":"Adaptive entry guidance with time and full state constraints using analytical drag-vs-energy profile","authors":"Peichen Wang ,&nbsp;Xunliang Yan ,&nbsp;Wenjiang Nan ,&nbsp;Xinguo Li","doi":"10.1016/j.asr.2025.04.017","DOIUrl":"10.1016/j.asr.2025.04.017","url":null,"abstract":"<div><div>Advanced entry vehicles need to satisfy both flight time and full state constraints in the specific global transportation and cooperative rendezvous missions. This paper mainly proposes an adaptive entry guidance algorithm with time and terminal full state constraints. The algorithm is composed of three parts: longitudinal analytical guidance, lateral guidance and three-degree-of-freedom (3DOF) guidance. In the longitudinal analytical guidance, a smooth drag acceleration-vs-energy profile is represented as five piecewise polynomials by using the double-parameter interpolation between upper and lower boundary of entry corridor first. A high-precision analytical prediction algorithm for time and range to-go is derived over a spherical and rotating Earth, and the double-parameter of the profile can be corrected using double-objective iterative method to satisfy terminal height, velocity, flight-path angle, range, and time constraints. Secondly, an online adaptive analytical update strategy for the profile based on the double/single parameter sequential solving mode is proposed to improve the robustness of the algorithm. In the lateral part, a double-stage adaptive lateral guidance algorithm based on heading adjustment and maintaining is put forward, which is enabled to plan and update the bank-reversal sequence according to the terminal position and heading angle constraints. Finally, a real-time 3DOF entry guidance algorithm for the wide range heading adjustment is proposed to achieve the generation of the 3DOF guidance commands online rapidly. Simulations with the CAV-H model show that the presented approach is capable of satisfying all path constraints, terminal time and full state constraints, robust to typical entry dispersions, and adaptive for various entry missions with high real-time performance. The advantage of the guidance strategy is also verified by comparisons.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 12","pages":"Pages 8860-8879"},"PeriodicalIF":2.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144130971","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":"Error compensation method of GNSS/INS integrated navigation system based on PSO-LSTM","authors":"Guiling Zhao,&nbsp;Yuan Wang,&nbsp;Xu Wang","doi":"10.1016/j.asr.2025.04.024","DOIUrl":"10.1016/j.asr.2025.04.024","url":null,"abstract":"<div><div>The integrated navigation system based on the Global Navigation Satellite System and Inertial Navigation System (GNSS/INS), can provide continuous and dependable positioning information for airborne motion. The GNSS signal outages are easily caused by electromagnetic interference environments such as high-rise buildings, and canyons high-voltage towers. A long period of missing GNSS positioning information will lead to a rapid decline in the navigation precision of the GNSS/INS system. In order to solve this problem, the optimum value of Long Short-Term Memory (LSTM) is obtained through Particle Swarm Optimization (PSO). An LSTM network model based on the PSO algorithm (PSO-LSTM) is designed. It is used to assist the integrated navigation of GNSS/INS based on Kalman Filter (KF). When GNSS signals are available, the PSO-LSTM model is trained with carrier dynamic information and navigation information. When GNSS signals are not available, the PSO-LSTM model is used to obtain pseudo-GNSS signals for Kalman Filter measurement updates. In order to verify the validity of the algorithm, unmanned aerial vehicle (UAV) flight tests of GNSS signal outages are performed. The results of the positioning are compared to the conventional LSTM model. When the GNSS signal experiences outages of 30 s, the maximum positioning error of the LSTM model is 4.142 m. The PSO-LSTM model is 2.883 m, which decreases by 30.4 % relative to LSTM. When the GNSS signal experiences outages of 60 s, the maximum positioning error of the LSTM model is 5.992 m. The PSO-LSTM model is 2.898 m, which decreases by 51.2 % relative to LSTM. When the GNSS signal experiences multiple outages, the maximum positioning error of the LSTM model is 11.362 m. The PSO-LSTM model is 6.042 m, which decreases by 46.8 % relative to LSTM.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 12","pages":"Pages 8657-8666"},"PeriodicalIF":2.8,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131097","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 agricultural drought monitoring with the Integrated Agricultural Drought Index (IADI): A multi-source remote sensing approach","authors":"Ujjal Senapati ,&nbsp;Tapan Kumar Das","doi":"10.1016/j.asr.2025.04.021","DOIUrl":"10.1016/j.asr.2025.04.021","url":null,"abstract":"<div><div>Drought has significantly threatened India’s agro-economic sector, resulting in widespread environmental degradation and socio-economic challenges. This study provides remote sensing technology to overcome the limitations of traditional drought monitoring methods. To address this, Integrated Agricultural Drought Index (IADI), a newly proposed index that combines multiple remotely sensed-derived indicators with Analytical Hierarchy Process (AHP) for comprehensive agricultural drought assessment, is used. IADI integrates indicators such as Vegetation Health Index (VHI), Normalized Difference Drought Index (NDDI) and Enhanced Vegetation Index (EVI) to provide a concise assessment suitable for different farming systems. The study was conducted in the upper Dwarkeswar river basin focusing on drought trends from 2000 to 2019. Initially, drought years were identified using the Rainfall Anomaly Index (RAI). Subsequently, spatial drought indices were calculated and integrated into the IADI framework. The results revealed significant spatial variation in drought severity with an annual increase of 21.88 km² in drought-affected areas (R² = 0.98). Validation using Area Under Curve-Receiver Operating Characteristic (AUC-ROC) showed that the IADI achieved an accuracy of 76 %, outperforming individual indices such as VHI (72 %), NDDI (49 %) and EVI (47 %). These results highlight the improved predictive power of IADI, providing useful insights for real-time drought monitoring, resource allocation and strategic planning. This approach provides a sustainable framework for drought management, assisting policymakers and stakeholders in enhancing regional food security and resilience to climate variability.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 12","pages":"Pages 8599-8626"},"PeriodicalIF":2.8,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131185","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":"An innovative hybrid method utilizing fused transformer-based deep features and deep neural networks for detecting forest fires","authors":"Kemal Akyol","doi":"10.1016/j.asr.2025.04.020","DOIUrl":"10.1016/j.asr.2025.04.020","url":null,"abstract":"<div><div>Forest fires, one of the most pernicious and devastating disasters, cause deforestation, wildlife extinction, global warming, and climate change. Early fire detection is critical before it reaches catastrophic dimensions. Artificial intelligence-based systems that detect forest fires accurately and quickly are needed for early intervention. Delayed extinguishing efforts without such systems cause tremendous damage and losses. An effective monitoring system allows for the reduction of fire damage and hence prevents forest loss. This study aims to develop a successful artificial intelligence model to detect fire from forest landscape images. In this context, this work is new as it provides new insights into robust and scientific modeling for forest fire detection by analyzing feature maps based on fused transformer architectures using Deep Neural Networks. The experimental models were validated using accuracy, sensitivity, precision, and area under the receiver operating characteristic curve measures. The validation findings reveal that the proposed hybrid model performs the best while all models yield reasonable results. To summarize, satisfactory accuracy values of 99.58% and 96.79% for both datasets, respectively, strongly support the proposed hybrid model’s fire detection achievement with the 5-fold cross-validation. Furthermore, the high sensitivity and high precision measures imply that the model has few false negatives and false positives. Considering the obtained accuracies, the proposed hybrid model could be used for comprehensive fire detection modeling. To the author’s best knowledge, this study is the first to use transformer architectures and Deep Neural Networks for forest fire detection and is therefore important for the relevant literature. In this context, this study presents a new approach to distinguishing landscape images of forest fires and further developing fire detection strategies by the role of transformer architectures in feature extraction. It is thought that by executing the proposed model in an unmanned aerial vehicle equipped with a real-time system, fire detection will provide decision support to field professionals in reducing damage and managing forest fires.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 12","pages":"Pages 8583-8598"},"PeriodicalIF":2.8,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144130969","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":"Spatial coupling coordination evaluation between land use efficiency and urbanization in the Chang-Zhu-Tan urban agglomeration, China","authors":"Qiong Zheng,&nbsp;Huangteng Zhu,&nbsp;Qing Xia,&nbsp;Zixiao Guo,&nbsp;Lihong Zhu","doi":"10.1016/j.asr.2025.04.023","DOIUrl":"10.1016/j.asr.2025.04.023","url":null,"abstract":"<div><div>Ensuring that land use efficiency and urbanization are in harmony has emerged as a critical concern requiring immediate attention to achieve sustainable urbanization in China. Taking the Chang-Zhu-Tan urban agglomeration (CZTUA) as an example, this study establishes an evaluation index system of land use efficiency and urbanization using multi-source remote sensing data in 2020 and analyzes the coupling coordination degree (CCD) between these factors. Furthermore, the standardization methods and exploratory spatial data analysis method are combined to investigate the spatial correlation of the CCD among land use efficiency and urbanization. The study shows that: (1) In CZTUA, there is a positive correlation between land use efficiency and urbanization and this promotes urbanization. (2) The overall coupling degree in the CZTUA is in the running-in level and most districts are at the elementary or middle rank coordinated levels. (3) The spatial clustering characteristics have the “center-periphery” pattern, with the further away from the core city, the lower the level of coupling coordination becomes. (4) From the perspective of geographical association, the High-High agglomeration, mainly located in Changsha City, showed higher development levels compared to surrounding areas. Development gradually diminished as one moves outward, forming a Low-High agglomeration. Low-Low agglomeration was represented by You, Chaling and Yanling districts. The methodology used in this study is relevant for promoting urbanization and improving land use efficiency in Chinese city clusters.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 12","pages":"Pages 8642-8656"},"PeriodicalIF":2.8,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131187","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":"Multi-satellite based possible precursory signals detection linked to the 2024 Mw 7.5 Noto Peninsula Japan earthquake","authors":"Rasim Shahzad ,&nbsp;Munawar Shah ,&nbsp;Imtiaz Nabi ,&nbsp;Punyawi Jamjareegulgarn","doi":"10.1016/j.asr.2025.04.015","DOIUrl":"10.1016/j.asr.2025.04.015","url":null,"abstract":"<div><div>Satellite-based anomaly detection can provide substantial precursory information linked to impending earthquakes (EQ). The strong EQs are followed by some complex precursory signals both before and after the main shock. For this, different methods and datasets are employed to monitor these disastrous events. In our study, we used the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite to evaluate land surface temperature (LST), the Global Navigation Satellite System (GNSS) to observe total electron content (TEC) variations, Swarm satellites to monitor spatial variations in electron density, and Cosmic satellites were used to measure variations in the vertical profile of electron density to look for the complex precursors of Noto Peninsula Japan EQ of 7.5 Mw (occurred on 1st January 2024). Our objective was to observe both the pre- and post-EQ induced anomalies within 25 days and 10 days of the main shock by integrating the statistical, nonlinear autoregressive network with exogenous inputs (NARX) and continuous wavelet transformation (CWT) methods. We found synchronized and co-located pre-seismic anomalies on December 25 in LST, TEC and electron density. Which was further confirmed using NARX and CWT as well. Additionally, we found some potential post-seismic anomalies. There was an anomalous enhancement in daytime LST, TEC, and electron density on January 2nd with the exception of nighttime LST which showed abrupt increments on the night of the main shock (i.e., January 1st). These findings point towards the strong EQ-induced energy into the atmosphere and ionosphere for more prominent proof of lithosphere-atmosphere–ionosphere coupling (LAIC).</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 12","pages":"Pages 8830-8848"},"PeriodicalIF":2.8,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131036","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":"CMKD-Net: a cross-modal knowledge distillation method for remote sensing image classification","authors":"Huaxiang Song ,&nbsp;Junping Xie ,&nbsp;Yingying Duan ,&nbsp;Xinyi Xie ,&nbsp;Yang Zhou ,&nbsp;Wenhui Wang","doi":"10.1016/j.asr.2025.04.009","DOIUrl":"10.1016/j.asr.2025.04.009","url":null,"abstract":"<div><div>Cross-modal knowledge distillation (KD) offers the potential to synergize the strengths of Vision Transformers (ViTs) and Convolutional Neural Networks (CNNs) in remote sensing image (RSI) classification. However, existing KD techniques in this field are frequently ineffective and time-consuming. We contend that this inefficiency stems from the data sparsity inherent in RSI samples—a challenge long overlooked in previous studies. To address this issue, we propose a novel algorithm designed to alleviate data sparsity and enhance the quality of the training data. Building upon this, we introduce CMKD-Net, a KD framework that facilitates knowledge transfer from a ViT teacher to a CNN student model. Experimental evaluations on three RSI datasets demonstrate that CMKD-Net outperforms 17 state-of-the-art models published since 2022 on classification accuracy and model compactness. Furthermore, our method cuts down training time by at least 83% compared to current KD methods, making cross-modal KD for RSI classification much more effective.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 12","pages":"Pages 8515-8534"},"PeriodicalIF":2.8,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144130940","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}