Advances in Space Research最新文献

{"title":"Satellite-based re-examination of global soil moisture variation","authors":"Huihui Feng ,&nbsp;Shu Wang ,&nbsp;Shijie Li ,&nbsp;Wei Wang ,&nbsp;Jingya Li ,&nbsp;Runxi Gu ,&nbsp;Jixian Huang","doi":"10.1016/j.asr.2024.12.030","DOIUrl":"10.1016/j.asr.2024.12.030","url":null,"abstract":"<div><div>It was crucial to capture the variation in global soil moisture for exploring the global eco-hydrological processes. Based on the global soil moisture data from the Climate Change Initiative (CCI) published by the European Space Agency (ESA), this study re-examined the spatial pattern and temporal trend of global soil moisture from 1978 to 2021. Our results showed that the global mean soil moisture was 0.208 cm³·cm⁻³, which showed a weak decreasing trend over the past four decades <strong>(</strong>−1.2 × 10^-4 cm³·cm⁻³ yr⁻¹, <em>R²</em> = 0.23, <em>p</em> = 0.001<strong>)</strong>. Spatially, about 12.99 % of the land showed a significant drying trend, while only 6.74 % of the land showed a wetting trend. However, in the last decade, global soil moisture exhibited a distinct upward trend (7 × 10^-4 cm³·cm⁻³ yr⁻¹, <em>R²</em> = 0.87, <em>p</em> = 0.000). Specifically, during this period, 5.72 % of the land showed a marked drying tendency, while 9.09 % of the land displayed a wetting trend. Soil moisture variation in the arid climate zones showed a negative contribution to the global trend, with the total contribution of −45.72 %. In contrast, soil moisture trends in temperate and cold climate zones mainly exerted positive contributions to the global trend. From a continental perspective, Asia’s positive contribution was the most significant, accounting for 39.96 %, whereas North America showed a significant negative contribution of −37.43 %. Temporally, the negative maximum change in soil moisture occurs in June-August and the positive maximum change occurs in September-November, serving as the predominant d river for the annual trend. Results of this study helped to clarify the variation of global soil moisture, which could support the sustainable water management in the changing climate.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 4","pages":"Pages 3486-3495"},"PeriodicalIF":2.8,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402861","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":"Detecting surface subsidence trends in permafrost areas with undulating terrains using GPS interferometric reflectometry","authors":"Jinsheng Tu ,&nbsp;Xiufeng He ,&nbsp;Xiaolei Wang ,&nbsp;Minfeng Song ,&nbsp;Zhixiang Yang","doi":"10.1016/j.asr.2024.12.033","DOIUrl":"10.1016/j.asr.2024.12.033","url":null,"abstract":"<div><div>Global navigation satellite system interferometric reflectometry (GNSS-IR) technology has been applied to detect surface deformation in permafrost areas. Affected by terrain, previous studies have mainly focused on GNSS sites located in permafrost areas with uniform flat surfaces; however, the number of sites is small, which limits the expansion of regional research. This study provides ideas for the detection of surface subsidence trends in permafrost areas with undulating terrains using global positioning system (GPS) interferometric reflectometry. We selected the GPS site AB33 in Coldfoot, Alaska, and the GPS signal-to-noise ratio (SNR) data during the 2023 snow-free thaw season were processed to obtain continuous surface reflector heights. Outlier detection of reflector heights to extract robust and reliable information and reflector height change trends were analyzed to identify satellite results of detected surface subsidence trends. Thereafter, hierarchical clustering was performed by azimuth and reflector height to group the satellite results into similar clusters and average them. Finally, the correlation between the surface subsidence trends detected at different azimuth ranges after clustering and the subsidence trends simulated by the thawing index was analyzed. The results showed that the detected surface subsidence trends strongly correlated with the simulated trends, with a maximum correlation coefficient (R) of 0.74. This verifies that the ideas presented in this study can effectively detect surface subsidence trends in permafrost areas with undulating terrains.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 4","pages":"Pages 3496-3506"},"PeriodicalIF":2.8,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402862","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 methodology for determining the long-term behavior of earth surface deformations from InSAR results","authors":"Yavuz Gül ,&nbsp;Kemal Özgür Hastaoğlu ,&nbsp;Fatih Poyraz","doi":"10.1016/j.asr.2024.12.035","DOIUrl":"10.1016/j.asr.2024.12.035","url":null,"abstract":"<div><div>The InSAR method is an effective method of presenting the temporal change and behavior characteristics of surface deformations to users and monitoring deformations. In general, it is possible to determine the spatial distribution and magnitude of surface deformations using InSAR analysis results. However, more detailed analyses should be performed to reveal and interpret the long-term behavior of deformations from these results. It is especially important to classify deformation velocities and present the temporal change and behavior characteristics of deformations by analyzing the densities of these classes and their periodic changes. This study developed a new methodology and software to present the temporal change and behavior characteristics of deformations to users. With the new methodology and software developed, values such as time-dependent increasing/decreasing trend of deformations, continuity, velocity value and class, and areal ratio/density can be determined and long-term behavior characteristics of deformations can be revealed. It is possible to make more reliable predictions of future behavior by considering the current increasing or decreasing trend of deformation behavior. The methodology and software developed were used to monitor surface deformations at the dump site of Kangal/Kalburçayırı open-pit coal mine, and the results were discussed. Owing to the method developed, deformation behavior was determined, and the prospective support heel precaution was taken. The new situation and deformation behavior that occurred as a result of this precaution were examined with the same methodology and software, and the success of the support heel was discussed.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 4","pages":"Pages 3521-3540"},"PeriodicalIF":2.8,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403140","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":"Flood risk assessment in Ténès city (Algeria) using land cover based on machine learning methods and Pléiades tri-stereo images","authors":"Zaabar Narimane ,&nbsp;Niculescu Simona ,&nbsp;Mihoubi Mustapha Kamel","doi":"10.1016/j.asr.2024.12.036","DOIUrl":"10.1016/j.asr.2024.12.036","url":null,"abstract":"<div><div>On a global scale, a considerable amount of life, property, and resources are lost because of the increasing frequency and severity of flooding occurrences. This necessitates worldwide development, thorough flood risk assessments and urbanization policies. This work used sophisticated remote sensing data and hydraulic models to create an effective and appropriate methodology for flood risk assessment in a coastal city located in western Algeria. In the first stage, Sentinel-2 optical data was classified using deep learning and machine learning methods for land cover and land use (LULC). The CNN deep model based on LULC was selected for its outstanding overall accuracy. Then, a 1-D HEC-RAS hydraulic model was performed, integrating LULC maps with a higher precision, topography using a digital surface model (DSM) derived from Pléiades tri-stereo data, and another digital elevation model (12 m). Flood hydrographs were also constructed for four scenarios (10, 20, 50, and 100 years) using hydrometric data. The 1D flood model was indeed validated using a flood event data. Flood hazard, LULC and flood risk maps were derived. Results show the high flood hazard areas are concentrated on the left bank of the Oued Allala River and urban cities near the coast. According to the results of the flood hazard simulation of 100 years, built-up areas and roads are the LULC classes most affected by flood hazard, with more than 94.4 % and 69.34 % for DSM tri-stereo and DEM models, respectively. As well, results of flood risk assessment by combining hazard risk and LULC vulnerability show that for the DSM model, 0.48 %, 44.55 %, and 53.11 %, and 54.04 % of flooded areas are in low, medium, and high flood risk, respectively. For the DEM model, 3.14 %, 45 %, and 51.04 % of flooded areas are in low, medium, and high flood risk, respectively. Results confirmed that topographic resolution models and LULC accuracy of CNN models can highly affect hydraulic simulation output results. Based on the obtained results, Ténès City needs necessary planning for flood risk management, particularly in the coastal area. Derived maps can serve as valuable information for regional and national decision-making.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 4","pages":"Pages 3541-3564"},"PeriodicalIF":2.8,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403141","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":"Phase space deep neural network with Saliency-based attention for hyperspectral target detection","authors":"Maryam Imani ,&nbsp;Daniele Cerra","doi":"10.1016/j.asr.2024.12.037","DOIUrl":"10.1016/j.asr.2024.12.037","url":null,"abstract":"<div><div>The accurate separation of targets and background is challenging in hyperspectral target detection algorithms, due to the high variability and complex non-linear scattering interactions in spectra acquired by imaging spectrometers. Moreover, the target regions may be contaminated by the background signal in real images, hindering the separation of a specific target in a scene. To address these challenges, a deep neural network is proposed in this work, consisting of three modules. First, to extract features hidden in the spectral signature of pixels, the hyperspectral image is considered as a dynamic system, and its phase space is reconstructed in the spectral feature space. Subsequently, in order to highlight the targets and suppress the background, a saliency map is produced, which shows candidate regions for the targets of interest. The saliency map is then utilized as an attention map for weighting the hyperspectral input within the network. The proposed multi-branch deep neural network processes each dimension of the reconstructed phase space. The resulting Phase Space Deep Neural Network with Saliency-based Attention (PSDNN-SA) outperforms several state-of-the-art detectors both quantitatively and visually in experiments carried out on different real hyperspectral subsets.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 4","pages":"Pages 3565-3588"},"PeriodicalIF":2.8,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403142","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 analysis of different GNSS receivers performance based on PPP-AR and positioning accuracy during 22 geomagnetic storms in 2023","authors":"Zhuang Chen ,&nbsp;Xiaomin Luo ,&nbsp;Xinmei Liang ,&nbsp;Yujie Li ,&nbsp;Yingzong Lin ,&nbsp;Shaofeng Bian","doi":"10.1016/j.asr.2024.11.067","DOIUrl":"10.1016/j.asr.2024.11.067","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Geomagnetic storms induced ionospheric disturbances can degrade the positioning accuracy and Ambiguity Resolution (PPP-AR) of GPS Precise Point Positioning (PPP), and this negative effect varies among different GNSS receivers. Under current conditions with frequent geomagnetic storms occurrences during the peak of solar cycle 25, selecting GNSS receivers with strong resistance to ionospheric disturbances is meaningful for precise GNSS positioning and ionospheric research. Therefore, it is necessary to conduct a comprehensive comparison and evaluation of the performance for different GNSS receivers under geomagnetic storms. Based on 22 geomagnetic storms in 2023, we investigated the three-dimensional root mean square error (3D RMS) and ambiguity resolved percentage (ARP), which is defined as the ratio of the number of carrier-phase observations with fixed ambiguities to the total number of phase measurements of GPS kinematic PPP, across ten groups of collocated stations around the world. For the groups using different receiver brands, the performance ranking for positioning accuracy and PPP-AR during geomagnetic storms are as follows: TPS &gt; JVAVD &gt; SEPTENTRIO &gt; TRIMBLE. The station with a larger average ARP generally has a smaller average 3D RMS error than the another GNSS station. The average 3D RMS error between collocated stations using different receiver brands is typically greater than 0.010 m and even larger. The largest 3D RMS error difference is observed between collocated stations with SEPTENTRIO and JAVAD receivers, with 3D RMS errors of 0.089 m and 0.019 m, respectively. These identical-brand receivers with different types are as follows: TPS NET-G5 &gt; TPS NET-G3A, TRIMBLE ALLOY &gt; TRIMBLE NETRS, SEPT POLARX5TR &gt; SEPT POLARX5S, and LEICA GR10 &gt; LEICA GR30, respectively. The average differences in 3D RMS and ARP can reach up to 0.021 m and 6.0 %, respectively. We found that the choice of antennas does not significantly affect PPP positioning performance during storms, with differences in average 3D RMS below 0.005 m and ARP differences below 0.2 %.. Higher latitudes have more satellites affected by ionospheric disturbances, while this effect is typically only observed during strong storms (&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;Dst&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;min&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;≤&lt;/mo&gt;&lt;mo&gt;-&lt;/mo&gt;&lt;mn&gt;100&lt;/mn&gt;&lt;mi&gt;n&lt;/mi&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;) in mid-latitudes. Adequate available GPS satellites are crucial for achieving high PPP-AR and positioning accuracy during storms. The variations of disturbed satellites and the average Rate of Total Electron Content Index (ROTI) for collocated stations are generally consistent. However, there are differences in the average of ROTI values for different receivers under geomagnetic storms. The differences in PPP-AR performance and ROTI values among different receivers under geomagnetic storms can be attributed to the variations in satellite tracking algorithms, tracking loo","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 4","pages":"Pages 3630-3650"},"PeriodicalIF":2.8,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403146","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":"Toward the optimal spatial resolution ratio for fusion of UAV and Sentinel-2 satellite imageries using metaheuristic optimization","authors":"Ahmad Toosi ,&nbsp;Farhad Samadzadegan ,&nbsp;Farzaneh Dadrass Javan","doi":"10.1016/j.asr.2025.02.019","DOIUrl":"10.1016/j.asr.2025.02.019","url":null,"abstract":"<div><div>Sentinel-2A/2B twin satellites provide multispectral imagery every 5 days at a medium spatial resolution (10 m for visible and near-infrared bands). In contrast, UAV photogrammetry with low-cost visible-light (RGB) sensors produces ultra-high-resolution orthomosaics but lacks rich spectral information. Fusing these datasets is a solution to enhance the resolution of Sentinel imagery using UAV data. However, fusion is challenging due to large spatial resolution disparities, particularly in Ground Sampling Distance (GSD). By challenging the common practice of sharpening the Sentinel image to match the UAV resolution, we propose a method that fuses the two images at an intermediate resolution level where their information content is comparable. Our approach uses natural target edge analysis and a Genetic-based metaheuristic optimization technique. By minimizing an objective function comprising true GSD or Ground Resolved Distance (GRD) and Mutual Information (MI), we determine the optimal resolution level for fusion. Experimental validation on two UAV and Sentinel datasets, yielded optimal GRD estimates of 2.35 m and 2.03 m, respectively, with Sentinel GRD values of 12.12 m and 12.39 m. The optimal UAV-Sentinel GRD ratios were 0.193 and 0.164. The sharpened Sentinel images showed efficient fusion through subjective and objective quality assessments. Testing the method on 24 UAV-Sentinel datasets from various regions, including America (United States), Europe (Germany, Spain, and Switzerland), and Asia (Iran and Qatar), demonstrated its robustness across different land covers and sensor types. This approach can be applied to any multi-sensor remote sensing image fusion task with significant resolution differences, establishing the meaningful level for fusion.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 7","pages":"Pages 5254-5282"},"PeriodicalIF":2.8,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient area coverage planning using approximation tiling heuristics for mosaic imaging with agile spacecraft","authors":"Paula Betriu ,&nbsp;Manel Soria ,&nbsp;Jordi L. Gutiérrez ,&nbsp;Diego Andía ,&nbsp;Marcel Llopis","doi":"10.1016/j.asr.2024.12.024","DOIUrl":"10.1016/j.asr.2024.12.024","url":null,"abstract":"<div><div>This work focuses on the Area Coverage Planning Problem (ACPP) for optical cameras onboard agile spacecraft in space exploration missions. The objective is to determine the optimal observation path of the camera’s boresight to obtain a mosaic that fully covers a designated Region Of Interest (ROI) on the target’s surface, while considering activity makespan and computational demand. To tackle this problem, four improved heuristics are implemented, each addressing differently the need to create an acquisition plan that dynamically adjusts to the camera’s observation geometry over time. Based on the proposal from a previous study, these heuristics have been further refined to correct spatial distortion and improve computational efficiency. In consequence, the current implementation allows for application to non-convex, irregularly shaped celestial bodies. We have developed a comprehensive program framework with supporting functions and assets to enable the iterative execution of the applied heuristics under diverse observation geometries along the spacecraft’s trajectory, ensuring their robustness and adaptability.</div><div>The ACPP is a component of a broader scheduling problem for agile spacecraft, which aims to maximize the scientific return while adhering to geometric and operational constraints imposed by both the spacecraft and its payload. In this context, deterministic step-stare algorithms are preferred for their efficiency in balancing accuracy and computational resources.</div><div>The algorithms are showcased through the simulation of observations from Galileo during one of its flybies over Europa. Arbitrary and diverse ROIs are considered on the target’s surface, allowing for a comprehensive evaluation of the algorithms in different observation geometries. The outcomes are analyzed over coverage completeness, efficient planning and computational burden. Thus, the resulting mosaics provide insights into the optimal usage of the heuristics in specific circumstances.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 4","pages":"Pages 4013-4034"},"PeriodicalIF":2.8,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402758","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 robust GNSS velocity estimation method combining Doppler and carrier phase observations in complex urban environments","authors":"Yantao Liang ,&nbsp;Xiaohong Zhang ,&nbsp;Ying Liu ,&nbsp;Xianlu Tao ,&nbsp;Wanke Liu ,&nbsp;Hailu Jia ,&nbsp;Hongxia Bai","doi":"10.1016/j.asr.2024.11.071","DOIUrl":"10.1016/j.asr.2024.11.071","url":null,"abstract":"<div><div>Accurate and reliable velocity information is crucial for kinematic positioning, as it not only characterizes the carrier state but also serves as constraint information for positioning. However, due to the influence of low-cost Global Navigation Satellite System (GNSS) chips and complex environments, GNSS signals are prone to attenuation and interruptions. Consequently, frequent gross errors and cycle slips occur in observations, significantly degrading the velocity precision and reliability. To address this challenge, we have proposed a method combining Doppler and Time-Differenced Carrier Phase Velocity Estimation (D-TDCPVE). First, we assess the accuracy of both Doppler and carrier phase observations to determine the appropriate weight ratio for their combination. Second, we analyze the correlation between the two observation types and propose an adaptive parameter estimation strategy for estimating one or two clock bias variations to address their potential differences. Finally, we incorporate a combination of pre- and post-detection quality control measures along with additional cycle slip parameters to mitigate the impact of gross errors and cycle slips in complex environments. Experimental results conducted with three low-cost devices in urban environments demonstrate the superior performance of the D-TDCPVE method over both Doppler velocity estimation (DVE) and time-differenced carrier phase velocity estimation (TDCPVE). It enhances the success rate of velocity estimation by 3.3% to 20.1% compared to TDCPVE and improves velocity estimation accuracy by 16.1% to 60.9% compared to DVE. Moreover, the method does not necessitate the combination of dual-frequency observations, making it particularly valuable for cycle slip detection in scenarios involving mixed single- and dual-frequency observations, which is particularly useful in urban environments.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 4","pages":"Pages 3838-3855"},"PeriodicalIF":2.8,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402865","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":"DAI algorithm: A QGIS plugin for daily aerial image interpolation","authors":"Tobías Romero-Macías ,&nbsp;C. Amurrio-García ,&nbsp;José L. Jiménez-García ,&nbsp;Pablo Blanco-Gómez","doi":"10.1016/j.asr.2024.11.081","DOIUrl":"10.1016/j.asr.2024.11.081","url":null,"abstract":"<div><div>This article describes the Daily Aerial Image (DAI) algorithm, a QGIS plugin implemented in Python for satellite image interpolation. The presence of clouds and the time difference between two satellite images make it difficult to observe the Earth’s surface with remote sensors. To solve this problem, the spatial and temporal combination of two observed clean images may be of particular interest to GIS users and satellite image scientists. The DAI package uses tri-band raster images from two different dates to interpolate the intermediate images on a daily basis.</div></div>","PeriodicalId":50850,"journal":{"name":"Advances in Space Research","volume":"75 4","pages":"Pages 3335-3339"},"PeriodicalIF":2.8,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403037","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}