Advances in Space Research最新文献

{"title":"Satellite-driven machine learning framework for monitoring river sediment discharge: integrating Sentinel-2 spectral data with hydrometric insights","authors":"Milad Ahmadi ,&nbsp;Seyed Hossein Mohajeri ,&nbsp;Changhyun Jun ,&nbsp;Dongkyun Kim ,&nbsp;Soran Ezati ,&nbsp;Sayed M. Bateni ,&nbsp;Shohreh Azizi","doi":"10.1016/j.asr.2025.04.061","DOIUrl":"10.1016/j.asr.2025.04.061","url":null,"abstract":"<div><div>Accurate prediction of river sediment discharge is crucial for effective water resource management and flood mitigation, especially as direct measurements are challenging. This study integrates spectral bands from Sentinel-2 satellite imagery and total suspended matter (TSM) data, processed using the C2RCC processor, with ground-based hydrometric data to enhance machine learning models for sediment discharge prediction. The Karun River, Iran’s most vital and water-rich river, was selected as the study area due to its significant role in regional water supply. In this study, we analyzed several machine learning techniques, including K-nearest neighbors, random forest, gradient boosting, multi-layer perceptron, and extreme gradient boosting. The findings reveal that these models significantly outperformed traditional sediment rating curves, with the Random Forest model achieving an R² value of 0.92 and low error metrics (RMSE = 454 g/s, MAE = 286 g/s, and MBE = −22 g/s). By integrating TSM data, spectral bands, and hydrometric measurements, the study provides frequent sediment discharge updates every five days, reducing the need for in-situ measurements. A new SRC was developed by combining in-situ river discharge data with sediment discharge estimates from the RF model, improving prediction accuracy and reducing errors compared to traditional methods. This approach enhances SRCs and improves sediment transport analysis, providing more reliable tools for water resource planning and hydraulic structure design.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 1","pages":"Pages 236-253"},"PeriodicalIF":2.8,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222873","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 improved Monte Carlo tree search algorithm with dynamic classification for multi-spacecraft multi-target allocation","authors":"Ji Ye ,&nbsp;Yao Zhang ,&nbsp;Yu-Jun Chen","doi":"10.1016/j.asr.2025.04.030","DOIUrl":"10.1016/j.asr.2025.04.030","url":null,"abstract":"<div><div>This paper proposes a solution framework based on the Monte Carlo Tree Search algorithm for the multi-spacecraft multi-target allocation problem in the active debris removal mission. The target allocation problem is modeled as a multi-step optimal decision-making problem by the Markov Decision Process. An improved Monte Carlo Tree Search algorithm is proposed to tackle the allocation problem to obtain the optimal target sequence. In the expansion operation, a dynamic classification mechanism is introduced to retain more valuable actions based on the orbital elements of targets. In the backpropagation and simulation operations, fuel consumption is employed as the value assessment criterion to reconstruct the objective of the algorithm. In the selection operation, the roulette wheel selection is applied to enhance the search efficiency. Numerical simulations are conducted to compare the improved Monte Carlo Tree Search algorithm with other commonly used algorithms. The results demonstrate that the proposed algorithm exhibits superior optimization capabilities (about 13 % fuel reduction in 40 target scenarios) and robustness compared to the commonly used algorithms, along with a more stable fuel-saving performance as the number of targets increases.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 1","pages":"Pages 412-428"},"PeriodicalIF":2.8,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222825","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-instrument study of the response of intense solar flares during the descending period of the 24th solar cycle","authors":"Joysankar Majumdar,&nbsp;Kshama Tiwari,&nbsp;Abhay Kumar Singh","doi":"10.1016/j.asr.2025.04.063","DOIUrl":"10.1016/j.asr.2025.04.063","url":null,"abstract":"<div><div>This study delves into the ionosphere’s response in low and equatorial regions of the two most powerful solar flares in the descending phase of the 24th solar cycle, which was attained on July 23, 2016, and April 02, 2017, using multi-instrument measurements using very low frequency (VLF) waves, global positioning system (GPS) based total electron contents (TEC) over four different IGS stations, electron density profiles derived from COSMIC and SWARM satellite. Due to the sudden increase in ionization of the D layer, VLF signals exhibited an elevation in amplitude during a solar flare at a low-latitude station, Varanasi. A strong correlation exceeding 70% was identified between X-ray flux and VLF amplitude variation. Additionally, a sudden rise in ionospheric TEC from 4 different IGS stations indicated an augmentation up to ∼4.40 TECU. Notably, the M7.16 flare, which occurred at 02:12 UT, induced a greater enhancement in electron density and TEC compared to the X1.09 flare, largely due to its timing. Ground-based measurements further corroborated electron density profiles derived from COSMIC and SWARM satellite data, showcasing significant variations near the F-region, where electron density peaked dramatically. The study highlights how solar flares impact different ionospheric layers based on region, with increased extreme ultraviolet (EUV) flux driving photo-ionization and TEC enhancements in the upper ionosphere (F region), while elevated flux triggers ionization and disturbances in the lower ionosphere (D region).</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 1","pages":"Pages 371-384"},"PeriodicalIF":2.8,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222822","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":"Analysis and simulation of the relationship between Es layer and solar activity","authors":"Yabin Zhang ,&nbsp;Jie Feng ,&nbsp;Jianyuan Wang ,&nbsp;Wen Yi ,&nbsp;Haiying Li ,&nbsp;Jiajing Wu ,&nbsp;Haisheng Zhao ,&nbsp;Huaiyun Peng ,&nbsp;Shuji Sun ,&nbsp;Jian Wu","doi":"10.1016/j.asr.2025.04.064","DOIUrl":"10.1016/j.asr.2025.04.064","url":null,"abstract":"<div><div>Based on the data of ionosondes at four different mid-latitude stations of Manzhouli (49.6°N, 117.5°E), Beijing (40.1°N, 116.2°E), Suzhou (31.3°N, 120.4°E) and Guangzhou (23.2°N, 113.4°E) in China region during maximum (2013–2015) and minimum (2019–2021) solar activity years, the effects of solar activity on the Es layer traces, velocity and lifetime of descending Es layers are analyzed. The results show that the Es layer traces, height distribution and incidence of Es layers are negatively correlated with solar activities, while solar activities have little influence on the descent velocity and lifetime of descending Es layers. The simulation and spectral analysis results show that the descent velocity and lifetime of Es layers are mainly influenced by atmospheric tidal waves.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 1","pages":"Pages 385-395"},"PeriodicalIF":2.8,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222823","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":"Connection of frontal systems with the ITCZ over the Brazilian Northeast","authors":"Davidson Lima de Melo ,&nbsp;Natalia Fedorova ,&nbsp;Vladimir Levit","doi":"10.1016/j.asr.2025.04.051","DOIUrl":"10.1016/j.asr.2025.04.051","url":null,"abstract":"<div><div>There has been a significant increase in the number of Frontal Systems (FS) reaching the Brazilian Northeast in 2022, resulting in severe storms (91 fatalities). The processes underlying this invasion, the conjunction of the front zone with the Inter-Tropical Convergence Zone (ITCZ) between 1000 and 850 <em>hPa</em>, had not yet been thoroughly analyzed. There is evidence suggesting that inter-hemispheric circulations play a significant role in the intense frontal propagation. The primary objective of this study is to determine the configurations of meridional processes of frontal systems and their connection types with the Inter-Tropical Convergence Zone (ITCZ). The following data sources were utilized: satellite images in the infrared channel provided by GIBBS - NOAA; RADAR data (maxcappi) from CEMADEN; ERA5 reanalysis data (0.25° x 0.25°) from ECMWF. A total of 27 events were recorded. The most common system was the frontal end. The developed conceptual model establishes patterns among the synoptic characteristics of the detected cases. Three types of connection were defined: Type 1 (11 cases), Type 2 (9 cases), and Type 3 (7 cases). Type 1 involves cyclogenesis and meridional regeneration of the FS towards the equator; there was interaction between a Upper-Tropospheric Cyclonic Vortex (UTCV) and the Bolivian High (BH). Type 2 is associated with a fracture in the frontal trough, resulting in the formation of a cluster of clouds linked to the ITCZ; at higher levels, inter-hemispheric anticyclonic vorticity was generally observed. Type 3 is characterized by the meridional movement of the frontal band towards the ITCZ trough, drained by an intense ridge; one or more UTCVs are present throughout the process. The number of negative meridional cores required to connect frontal zones with the ITCZ ranged between 4 and 5 in the Southern Hemisphere, a smaller number of cells than in the Northern Hemisphere, where 6 to 7 cells were required.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 1","pages":"Pages 189-201"},"PeriodicalIF":2.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222687","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":"Satellite-based monitoring of soil moisture in catchment basins: a novel approach integrating temperature, albedo, and spectral indices","authors":"Amirhossein Mohseni,&nbsp;Majid Rahimzadegan","doi":"10.1016/j.asr.2025.04.057","DOIUrl":"10.1016/j.asr.2025.04.057","url":null,"abstract":"<div><div>Soil Moisture Content (SMC) is a crucial parameter in the management of water resources. Due to the expansive nature of catchment basins, satellite remote sensing in optical wavelengths is identified as a vital approach for monitoring soil moisture in these basins. The main goal of this study is to develop a methodology based on a physical linear relationship that utilizes surface temperature, albedo, and spectral indices obtained from satellite imagery in both visible and thermal wavelengths to determine SMC. Considering the availability of field SMC data and the acknowledged challenge of achieving increased accuracy in estimating SMC in regions with sparse vegetation, the state of Utah in the United States was selected as the selected study area. A dataset comprising 792 SMC measurements collected by the Soil Climate Analysis Network (SCAN) on April 23, 2021, October 16, 2021, April 23, 2022, and October 16, 2022, was compiled as ground truth data. Additionally, 288 Visible Infrared Imaging Radiometer (VIIRS) and 360 Moderate Resolution Imaging Spectroradiometer (MODIS) images corresponding to the field data period were gathered. Then, a novel experimental relationship was developed to estimate SMC based on Normalized Difference Vegetation Index (NDVI), albedo, land surface temperature, and Bare Soil Index (BSI), in spatial resolutions of 375 and 250 m. Comparing the estimated SMC using this experimental approach and measured SMC to a depth of 5 cm, the Pearson’s correlation coefficient (R) achieved 0.504 for VIIRS data and 0.503 for MODIS data in the optimal scenario. The Nash-Sutcliffe criterion (NSE) for this modeling yielded approximately 0.253 for both sensors, while the Kling-Gupta criterion (KGE) was 0.278 for the MODIS data and 0.270 for VIIRS data. The Root Mean Square Error (RMSE) was also 0.023 and 0.027 for these two datasets (m3/m3). The results suggest that the method proposed in this research, compared to the established triangular method, demonstrates equivalent or superior outcomes, thus affirming the validity of the developed Relationship.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 1","pages":"Pages 221-235"},"PeriodicalIF":2.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222690","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 hybrid-optimized Random Forest interpretable model for debris flow susceptibility by prior model-based negative sampling","authors":"Haijia Wen,&nbsp;Jiayi Li,&nbsp;Mingyong Liao,&nbsp;Mingrui Di,&nbsp;Jiwei Hu,&nbsp;Bo Liu","doi":"10.1016/j.asr.2025.04.055","DOIUrl":"10.1016/j.asr.2025.04.055","url":null,"abstract":"<div><div>Existing methods for negative sample data selection in debris flow susceptibility studies often introduce bias due to inadequate screening of geologically unstable “pseudo non-hazard” areas. To address this gap, this study presents a novel method for predicting debris flow susceptibility based on a hybrid-optimized random forest (Grid-SVM-RF) model combined with the SHAP (Shapley Additive Explanations) interpretability technique. The key innovation lies in a proactive SVM-based screening step: a Support Vector Machine (SVM) is first applied to rigorously identify areas of very low susceptibility within the study region, from which reliable negative sample data are extracted. This approach significantly reduces noise and bias compared to traditional negative sample sampling methods. A random forest (RF) model is then trained using these datasets, with hyperparameters optimized via GridSearchCV to enhance prediction accuracy and generalization ability. Experimental results demonstrate the superiority of the Grid-SVM-RF model, achieving 90.91% accuracy, an F1 score of 0.8966, and an AUC of 0.9582 on the test set. These metrics enable precise susceptibility classification, dividing the study area into five categories: very low, low, medium, high, and very high. SHAP analysis further resolves the model’s “black-box” limitations by quantifying the impact of key drivers (e.g., distance from road, stream power index) on predictions, offering actionable insights for risk management. The model’s effectiveness is validated through the 2023 Banzigou debris flow event in Sichuan Province, where it accurately predicted very high susceptibility in the affected area.</div><div>This study advances debris flow susceptibility modeling by (1) introducing a data screening framework that mitigates selection bias, (2) establishing a hybrid model with both high accuracy and interpretability, and (3) linking SHAP-derived factor contributions (e.g., POI nuclear density, river proximity) to practical disaster management strategies. The results highlight the Grid-SVM-RF model’s potential to improve reliability in susceptibility mapping and support targeted mitigation efforts.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 1","pages":"Pages 202-220"},"PeriodicalIF":2.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222688","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":"Comprehensive landslide hazard assessment using spatial, temporal and size probabilities combined with landslide density analysis in Çanakkale (NW Türkiye)","authors":"Samet Berber ,&nbsp;Sener Ceryan ,&nbsp;Murat Ercanoglu","doi":"10.1016/j.asr.2025.04.048","DOIUrl":"10.1016/j.asr.2025.04.048","url":null,"abstract":"<div><div>To assess the landslide hazard (LH) of the area between Lapseki and Güzelyalı (Çanakkale, NW Türkiye) the LH map and the landslide density hazard map were produced. The LH maps produced in this study were calculated by multiplying the spatial probability, size probability, and temporal probability. The landslide susceptibility (LS) map was produced using the Random Forest method. While producing the LS map, elevation, land use, curvature, lithology, NDVI, distance to streams, slope, TWI, and aspect were used as input parameters. The rainfall triggering landslides was obtained as 220 mm. Using Gumbel distribution, the exceedance probability of the 220 mm rainfall value in 5, 10, 25, and 50 years were calculated as 0.453, 0.701, 0.951, and 0.997, respectively. The probability of occurrence of a landslide that is equal to or greater than a selected area was found using landslide frequency-area distribution. The probability of a landslide in the study area, surpassing an area of 0.1 km², an area of 0,35 km², and an area of 1 km², with corresponding probabilities of 0.701, 0,361, and 0.184, respectively. To solve questions about where and how densely potential landslides will occur at a given time, a landslide density hazard map was produced. The Landslide density hazard map was calculated from the spatial probability, landslide density, and temporal probability. It was seen in this study that the landslide hazard concept should be considered by the decision makers for the future works such as land-use management and urban development strategies.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 1","pages":"Pages 170-188"},"PeriodicalIF":2.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222763","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":"Statistical precursors of solar flares on September 6, 2017, March 23 and May 1, 2024","authors":"A.E. Volvach,&nbsp;L.P. Kogan,&nbsp;L.N. Volvach,&nbsp;I.V. Yakubovskaya","doi":"10.1016/j.asr.2025.04.056","DOIUrl":"10.1016/j.asr.2025.04.056","url":null,"abstract":"<div><div>We present a study of changes in the properties of small-scale fluctuations in the probability density of solar X-ray fluxes by the GOES instrument, with the aim of identifying a set of repeating events that may be precursors to solar flares. The X-ray data obtained before the solar flares that occurred on September 6, 2017, March 23, and May 1, 2024 were considered. Our results reveal that, within a time window ranging from approximately three to five days before a powerful flare, the Sun’s behavior becomes significantly less random. In all cases studied, the onset of strong flares was preceded by the appearance of distinct linear structures exhibiting a high degree of determinism. Based on our analysis, we classify the precursors of these solar events into three groups: the first group appears 130 to 30 h before the flare. The second group emerges around 5 h before the flare. The third group corresponds to the formation of a characteristic “flare parallelogram” pattern, occurring approximately 150 to 100 h before the event. These findings highlight potential early indicators of solar flares, offering valuable insights for space weather forecasting.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 1","pages":"Pages 551-561"},"PeriodicalIF":2.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222860","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 ionospheric VTEC forecasting model over China based on the kernel ridge regression","authors":"Bang-min Han ,&nbsp;Qiao Yu ,&nbsp;Jian Wang ,&nbsp;Leonid F. Chernogor ,&nbsp;Yu Zheng","doi":"10.1016/j.asr.2025.04.049","DOIUrl":"10.1016/j.asr.2025.04.049","url":null,"abstract":"<div><div>Forecasting Vertical Total Electron Content (VTEC) is critical for understanding ionospheric processes and improving wireless communication systems. To enhance the forecast accuracy of the VTEC model, we propose a short-term forecasting model using Kernel Ridge Regression (KRR) to improve VTEC predictions with data from China. This model has the following characteristics: 1) It addresses the nonlinear nature of VTEC and reduces multicollinearity using a kernel function; 2) The ridge regression approach prevents overfitting; 3) It effectively handles the nonlinear relationship between VTEC and input variables. We compared the proposed model with the Decision Tree (DT), Random Forest (RF), Long Short-Term Memory Network (LSTM), and the International Reference Ionosphere (IRI) model. Overall, the KRR model achieved lower Root Mean Squared Error (RMSE) compared to the DT, RF, LSTM, and IRI-2016 models, with reductions of 0.55 TECU, 0.43 TECU, 0.17 TECU, and 6.95 TECU, respectively. In the 2019 datasets, the KRR model showed significant improvements in performance in regions like Sanya (31.3%, 27.78%, 10.11%, 86.02%), Wuhan (33.71%, 26.58%, 15.33%, 83.93%), Beijing (30.4%, 25.64%, 15.53%, 84.12%), and Mohe (37.72%, 29.70%, 11.25%, 76.41%) compared to DT, RF, LSTM, and IRI-2016 models. The proposed KRR model offers a new approach to improving VTEC forecasting accuracy, demonstrating clear advantages over existing models.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"76 1","pages":"Pages 353-370"},"PeriodicalIF":2.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222821","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}