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Image enhancement is the process of improving the quality of a digital image. Improved image quality is one of the goals of the ongoing effort to improve the information content and interpretability of satellite images. Two sets of remote sensing data were collected for this region: one from the SPOT-4 (2018) satellite and the other from the Enhanced Thematic Mapper Plus (ETM+) Landsat 7 (2020) satellite. This study used two images taken at various spatial resolutions of the same location. Two images are shown here: one with a 30 m spatial resolution and the other with a 5 m resolution with multispectral processing. The results indicate that integrating spatial and spectral resolution using geomatics techniques significantly benefits various applications. Before merging the images, it was root mean square error (RMSE) 11.55 Easting, 5.77 Northing and became 1.52 Easting, 1.45 Northing after merging the images. After implementing the approach, the resulting fusing image exhibits enhanced spatial resolution, and the resulting multispectral image has excellent spatial as well as spectral resolution. Finally, the improved combined image with great spatial and spectral resolution is prepared for analysis and classification. [ABSTRACT FROM AUTHOR]

The ICESat-2 and SWOT satellite earth observation missions have provided highly accurate water surface slope (WSS) observations in global rivers for the first time. While water surface slope is expected to remain constant in time for approximately uniform flow conditions, we observe time varying water surface slope in many river reaches around the globe in the ICESat-2 record. Here, we investigate the causes of time variability of WSSs using simplified river hydraulic models based on the theory of steady, gradually varied flow. We identify bed slope or cross section shape changes, river confluences, flood waves, and backwater effects from lakes, reservoirs, or the ocean as the main non-uniform hydraulic situations in natural rivers that cause time changes of WSSs. We illustrate these phenomena at selected river sites around the world, using ICESat-2 data and river discharge estimates. The analysis shows that WSS observations from space can provide new insights into river hydraulics and can enable the estimation of river discharge from combined observations of water surface elevation and WSSs at sites with complex hydraulic characteristics. [ABSTRACT FROM AUTHOR]

Flight data for deep space satellites launched and operated between 1991 and 2020 is analyzed to generate various reliability metrics. Satellite reliability is first estimated by the Kaplan‐Meier estimator, then parameterized through the Weibull distribution. This general process is applied to a general satellite data set that included all deep space satellites launched between 1991 and 2020, as well as two data subsets. One subset focuses on deployable satellites, while the other introduces a methodology of normalizing satellite lifetimes by satellite design life. Results from the general data set prove deep space satellites suffer from infant mortality while the results from the deployable data subset show deployable deep space satellites are only reliable over short periods of time. Results from the design life normalized data set give promising results, with satellites having a relatively high chance of reaching their design life. Available information regarding specific modes of failure is also leveraged to generate a percent contribution to overall satellite failure for eight distinct failure modes. Satellite failure due to crashing, in‐space propulsion failure, and telemetry system failure are proven to drive both early in life failure and later in life failure, making them the main causes of decreased reliability. [ABSTRACT FROM AUTHOR]

With ongoing advancements in space exploration and communication technology, the realization of an Earth-Moon space information network is gradually becoming a reality. One of the critical factors for efficient communication within this network is the allocation of satellite links. To optimize the communication delay between Earth-Moon satellites, a dedicated Earth-Moon satellite link allocation algorithm has been developed using NSGA-II (non-dominated sorting genetic algorithm II). To determine the most suitable crossover operator for this algorithm, three different operators were evaluated for their impact on communication delay within NSGA-II. We regard the links assignment in each slot as a general graph-matching problem. An initial distribution of satellite links is generated by using a depth-first search algorithm. Subsequently, NSGA-II is applied to optimize the overall satellite link sequence. The simulation scenes include five lunar satellite constellations and 24 MEO (medium earth orbit) satellites from Earth's BeiDou constellation, and the simulation results show that our method can effectively solve the problem of link allocation. Notably, the sequential crossover method outperforms the single-point and two-point crossover methods in reducing communication delays between Earth and Moon satellites. This study provides both theoretical and technical support for the development of future Earth-Moon space information networks, ultimately enhancing the efficiency of space communications. [ABSTRACT FROM AUTHOR]

It has previously been shown that trends in sensible heat from climate models have had a substantial contribution to global precipitation changes. We illustrate that this is the case also in the most recent Coupled Model Intercomparison Project Phase 6 (CMIP6). However, we find that over the period since 1980 reanalyses do not support the reduction in sensible heat from the CMIP6 models and rather estimate a global increase in sensible heat which would contribute to a precipitation reduction. Satellite data over a period of two decades over global ocean generally show an opposite sign of the sensible heat trend to the CMIP6 models, similarly to the reanalyses. [ABSTRACT FROM AUTHOR]

In recent years, the need to protect and conserve biodiversity has become more critical than ever before, as a prerequisite for both sustainable development and the very survival of the human species. This has made it a priority for the scientific community to develop technological solutions that provide data and information for monitoring, directly or indirectly, biodiversity and the drivers of change. A new era of satellite earth observation upgrades the potential of Remote Sensing (RS) to support, at relatively low cost, but with high accuracy the extraction of information over large areas, at regular intervals, and over extended periods of time. Also, the recent development of the Earth Observation Data Cubes (EODC) framework facilitates EO data management and information extraction, enabling the mapping and monitoring of temporal and spatial patterns on the Earth's surface. This submission presents the ELBIOS EODC, specifically developed to support the biodiversity management and conservation over Greece. Based on the Open Data Cube (ODC) framework, it exploits multi-spectral optical Copernicus Sentinel-2 data and provides a series of Satellite Earth Observation (SEO) biodiversity products and spectral indices nationwide. [ABSTRACT FROM AUTHOR]

Introduction: Noncommunicable diseases (NCDs) are the leading cause of morbidity and mortality worldwide, accounting for 74% of deaths annually. Satellite imagery provides previously unattainable data about factors related to NCDs that overcome limitations of traditional, non-satellite-derived environmental data, such as subjectivity and requirements of a smaller geographic area of focus. This systematic literature review determined how satellite imagery has been used to address the top NCDs in the world, including cardiovascular diseases, cancers, chronic respiratory diseases, and diabetes. Methods: A literature search was performed using PubMed (including MEDLINE), CINAHL, Web of Science, Science Direct, Green FILE, and Engineering Village for articles published through June 6, 2023. Quantitative, qualitative, and mixed-methods peer-reviewed studies about satellite imagery in the context of the top NCDs (cancer, cardiovascular disease, chronic respiratory disease, and diabetes) were included. Articles were assessed for quality using the criteria from the Oxford Centre for Evidence-Based Medicine. Results: A total of 43 studies were included, including 5 prospective comparative cohort trials, 22 retrospective cohort studies, and 16 cross-sectional studies. Country economies of the included studies were 72% high-income, 16% upper-middle-income, 9% lower-middle-income, and 0% low-income. One study was global. 93% of the studies found an association between the satellite data and NCD outcome(s). A variety of methods were used to extract satellite data, with the main methods being using publicly available algorithms (79.1%), preprocessing techniques (34.9%), external resource tools (30.2%) and publicly available models (13.9%). All four NCD types examined appeared in at least 20% of the studies. Conclusion: Researchers have demonstrated they can successfully use satellite imagery data to investigate the world's top NCDs. However, given the rapid increase in satellite technology and artificial intelligence, much of satellite imagery used to address NCDs remains largely untapped. In particular, with most existing studies focusing on high-income countries, future research should use satellite data, to overcome limitations of traditional data, from lower-income countries which have a greater burden of morbidity and mortality from NCDs. Furthermore, creating and refining effective methods to extract and process satellite data may facilitate satellite data's use among scientists studying NCDs worldwide. [ABSTRACT FROM AUTHOR]

The Earth exhibits an equatorial flattening specified by the ellipticity and the east longitude (or orientation) of the equatorial major axis, which is uniquely determined by the degree 2 and order 2 gravitational coefficients, C22 and S22. The 31-year SLR (satellite laser ranging) and 22-year GRACE/GRACE-FO (gravity recovery and climate experiment) data are analyzed to study the climate-related secular and 5.7 years to decadal variations in C22 and S22, in turn, the drift and decadal variation in the Earth's equatorial ellipticity and orientation of the principal axis of the least moment of inertia. The effects of the surface floating mass changes (including atmosphere, ocean and surface water redistribution and the melting of the mountain and polar glaciers) and the interior fluid convective (Earth's core flows) were evaluated. Results reveal that the equatorial ellipticity of the Earth is linearly increasing along with a remarkable decadal variation and the Earth's equator is flattening by ~ 0.16 mm/yr. [ABSTRACT FROM AUTHOR]

Objectives: The prediction accuracy of Earth rotation parameters (ERP), as one of the hot spots in geodetic research, has been attracting attention from users such as autonomous satellite navigation and deep space exploration. In order to further satisfy the users' requirements, we combine the new effective angular momentum (EAM) data for the ERP prediction study. Methods: The EAM fitted residual series in the excitation domain is first transferred to the geodetic observation domain, and an empirical adjustment factor is added to construct a new EAM fitted residual series. Then the fitted residual series of ERP and the fitted residual series of the new EAM are subtracted to obtain the difference series. Using the least square extrapolation and autoregressive (LS+AR) models driven by ERP data, prediction experiments are performed for the difference series and the new EAM residual series, respectively, and finally predictions for the target ERP series are jointly introduced. Results: Based on experiments from the beginning of 2012 to the beginning of 2021, it is shown that an overall better result can be obtained for the adjustment factor of 0.7 in both the X-direction and Y-direction at a prediction horizons of 1-365 days, with an average improvement of 31.86% and 21.00% over the traditional method, respectively. The average improvement over the traditional method is 15% when the adjustment factor of length of day is 1. Conclusions: This verifies the existing conclusion that about 70% of the high-frequency changes in the short time scale of polar motion are stimulated by EAM by means of numerical prediction, and provides a reference for ERP prediction research. [ABSTRACT FROM AUTHOR]

The features of the infrared (IR) spectra of various isotopic forms of water (–OH, –OD, H2O, HDO, and D2O) included in the crystal structure of the main rock-forming minerals of lunar basalts—olivines (forsterite)—have been studied. The results of numerical modeling (CUSTEP/Biovia Materials Studio) and experimental studies using the FT-801 IR Fourier spectrometer with a plug-in using the method of disturbed internal reflection (Simex, Novosibirsk) are presented. Numerical calculations have shown that forsterite can contain hydroxyl groups –OH(D) in its crystal lattice under certain conditions. The possibility of retaining various isotopic forms of molecular water on the surface of forsterite has been experimentally verified and the corresponding IR spectra of the mineral with a water film have been obtained. The IR spectra of forsterite containing isotopologues of water obtained theoretically and experimentally are compared with the observations of the Chandrayaan-1 and SOFIA artificial lunar satellites. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the representativeness of Calibration/Validation (Cal/Val) sites for satellite data, develop a framework for establishing new Cal/Val sites, and propose a heterogeneity index to be applied within this framework, specifically focusing on South Korea. The proposed framework assesses the representativeness of existing Cal/Val sites, and, if found inadequate, provides a methodology for optimizing the location and number of additional Cal/Val sites, along with a prioritization strategy for their installation. Furthermore, the framework includes a methodology for evaluating the suitability of utilizing existing ground observation networks as additional Cal/Val sites and for prioritizing their use. The heterogeneity index is derived by synthesizing differences in geographic, climatic, vegetation, and spectral characteristics between the current Cal/Val sites and the broader regions. A higher heterogeneity index indicates significant divergence from existing Cal/Val sites across these factors, highlighting areas with a need for additional Cal/Val sites and a higher expected impact from their establishment. This index serves as a key tool within the framework to determine the optimal locations and number of new Cal/Val sites, as well as to evaluate the efficacy of utilizing existing ground observation networks. The framework was applied to South Korea, where the representativeness of the current eight Cal/Val sites was found to be insufficient. The optimal number of Cal/Val sites was determined to be 33, requiring the addition of 25 new sites in South Korea. The southeastern peninsula and surrounding islands were identified as priority regions for new installations. Additionally, the potential for utilizing the existing ground observation network was examined. Twenty-three Automatic Mountain Meteorology Observation System (AMOS) sites in South Korea were selected and compared with the optimized Cal/Val sites. The inclusion of these 23 AMOS sites was found to significantly improve representativeness, approaching the level of the optimized Cal/Val sites. This strategic deployment is expected to enhance the accuracy and reliability of remote sensing data, contributing to improved environmental monitoring and research in South Korea. [ABSTRACT FROM AUTHOR]

Explosions or collisions of satellites around the Earth generate space debris, whose uncontrolled dynamics might raise serious threats for operational satellites. Mitigation actions can be realized on the basis of our knowledge of the characteristics of the fragments produced during the breakup event and their subsequent propagation. In this context, important information can be obtained by implementing a breakup simulator, which provides, for example, the number of fragments, their area-to-mass ratio or the relative velocity distribution as a function of the characteristic length of the fragments. Motivated by the need to analyze the dynamics of the fragments, we reconstruct a simulator based on the NASA/JSC breakup model EVOLVE 4.0 that we review for self-consistency. This model, created at the beginning of the XXI century, is based on laboratory and on-orbit tests. Given that materials and methods for building satellites are constantly progressing, we leave some key parameters variable and produce results for different choices of the parameters. We will also present an application to the Iridium–Cosmos collision and we discuss the distribution function after a breakup event. The breakup model is strongly related to the propagation of the fragments; in this work, we discuss how to choose the models and the numerical integrators, we propose examples of how fragments can disperse in time, and we study the behavior of multiple simultaneous fragmentations. Finally, we compute some indicators for detecting streams of fragments. Breakup and propagation are performed using our own simulator SIMPRO, built from EVOLVE 4.0; the executable program will be freely available on GitHub. [ABSTRACT FROM AUTHOR]

The gravity-geological method (GGM) is an approach that utilizes marine gravity anomalies (GAs) and shipborne bathymetric data to invert seafloor topography by resolving short-wavelength GAs through the Bouguer Plate approximation. Such an approximation ignores the non-linear effects caused by surrounding seafloor topographical undulations that actually exist in short-wavelength GAs, and thus leaving the space for further modification of GGM. This study thoroughly derives the relationship between seafloor topography and GA, as well as the formula of GGM. Then, we propose a self-adaptive method to improve the accuracy of the inversion significantly: the enhanced GGM (EGGM). The method uses the equivalent mass line method to approximate the non-linear gravitational effects of the surrounding seafloor topography to correct the short-wavelength GAs. By introducing two optimal density contrast parameters, EGGM has been designed to effectively integrate the combined effects of various non-linear factors to a certain extent. The accuracy of the seafloor topography models, produced with a spatial resolution of 1′ × 1′, was evaluated over the study area (132°E–136°E, 36°N–40°N) located in the Sea of Japan. The results indicate that the accuracy of EGGM has a relative improvement of 13.73 per cent compared to that of GGM in the overall study area, while the accuracy of both models is higher than that of the SIO_unadjusted model. The study further investigated the feasibility and stability of EGGM by examining the accuracy of both GGM and EGGM in various water depth ranges and areas with diverse terrain characteristics. [ABSTRACT FROM AUTHOR]

We studied a variant of the vehicle routing problem (VRP) arising in last-mile distribution, called the multi-depot two-echelon vehicle routing problem with delivery options (MDTEVRP-DO). The MDTEVRP-DO involves two decision levels: (i) designing routes for a fleet of vehicles located in multiple depots to transport customer demands to a set of satellites and (ii) routing a fleet of vehicles from the satellites to serve the final customers. Nowadays, a relevant feature of the problem characterizing delivery services is that customers can collect their packages at pickup stations near their homes or workplaces. We designed an effectively simulated annealing (SA) heuristic for the problem. The new algorithm was extensively tested on benchmark instances from the literature, and its results were compared with those of start-of-the-art algorithms. The results show that the proposed SA obtains 30 out of the 36 best solutions for the MDTEVRP-DO benchmark instances. Moreover, its computation performance is superior to state-of-the-art algorithms for the MDTEVRP-DO. [ABSTRACT FROM AUTHOR]

Space debris are a tangible risk for satellites in Earth orbits. Indeed, in the last decades fragmentation events have generated a large number of uncontrolled objects that have made the debris population grow. Modelling the space debris environment is becoming a fundamental task to evaluate the vulnerability of operational satellites, the probability of accidental collisions with uncontrolled objects, and the evolution of the debris population. With this aim, remote and in-situ measurements provide valuable data to tune the space debris population models and improve their reliability. While large satellites can be observed and tracked from ground, the sub-millimeter debris population requires in-situ measurements. In this context, in-orbit impact sensors are a key technology to obtain information about the sub-mm space debris environment. In this framework, a small-scale impact sensor sized to be integrated in a 2U CubeSat is being developed at the University of Padova. The sensor consists of a multitude of thin, conductive stripes arranged on a thin film of non-conductive material. When a debris hits the sensor, one or more stripes are severed, and the impact is detected. Moreover, the sensor design ensures low power consumption, making it feasible for CubeSat space missions. This work presents the latest outcomes obtained from the development of the sensor. Specifically, structural analyses are performed to assess that the sensor can withstand the launch loads, as well as thermal analyses to confirm its endurance capability with in-orbit temperatures. The number of expected impacts during the mission is predicted through orbital propagation, using state-of-the-art debris environment modelling tools. Finally, the paper presents a functional shooting test and vibration tests, executed onto a development model of the sensor, which verify its functionality and validate a Technology Readiness Level (TRL) of 4. • Space-borne sensor for in-situ monitoring of space debris. • Resistive impact sensor based on thin films and flexible PCB technology. • Thermal and structural analyses of CubeSat-sized impact sensor. • Vibrational test and functional test campaigns on a development model. [ABSTRACT FROM AUTHOR]

Floods are among the most devastating natural disasters, posing significant risks to life, property, and infrastructure globally. Earth observation satellites provide data for continuous and extensive flood monitoring, yet limitations exist in the spatial completeness of monitoring using optical images due to cloud cover. Recent studies have developed gap-filling methods for reconstructing cloud-covered areas in water maps. However, these methods are not tailored for and validated in cloudy and rainy flooding scenarios with rapid water extent changes and limited clear-sky observations, leaving room for further improvements. This study investigated and developed a novel reconstruction method for time series flood extent mapping, supporting spatially seamless monitoring of flood extents. The proposed method first identified surface water from time series images using a fine-tuned large foundation model. Then, the cloud-covered areas in the water maps were reconstructed, adhering to the introduced submaximal stability assumption, on the basis of the prior water occurrence data in the Global Surface Water dataset. The reconstructed time series water maps were refined through spatiotemporal Markov random field modeling for the final delineation of flooding areas. The effectiveness of the proposed method was evaluated with Harmonized Landsat and Sentinel-2 datasets under varying cloud cover conditions, enabling seamless flood mapping at 2–3-day frequency and 30 m resolution. Experiments at four global sites confirmed the superiority of the proposed method. It achieved higher reconstruction accuracy with average F1-scores of 0.931 during floods and 0.903 before/after floods, outperforming the typical gap-filling method with average F1-scores of 0.871 and 0.772, respectively. Additionally, the maximum flood extent maps and flood duration maps, which were composed on the basis of the reconstructed water maps, were more accurate than those using the original cloud-contaminated water maps. The benefits of synthetic aperture radar images (e.g., Sentinel-1) for enhancing flood mapping under cloud cover conditions were also discussed. The method proposed in this paper provided an effective way for flood monitoring in cloudy and rainy scenarios, supporting emergency response and disaster management. The code and datasets used in this study have been made available online (https://github.com/dr-lizhiwei/SeamlessFloodMapper). [ABSTRACT FROM AUTHOR]

The transition towards the fifth generation (5G) of communication systems has been fueled by the need for compact, high-speed and wide-bandwidth systems. These advancements necessitate the development of novel and highly efficient antenna designs characterized by the compact size. In this paper, a novel antenna design with a hexagonal-shaped resonating element and two U-shaped open-ended stubs is presented. Millimeter-wave (mmWave) frequency range suffers from attenuation due to atmosphere and path loss because of higher frequencies. To address these issues, the deployment of a high-gain antenna is imperative. This design is created through an evolutionary process to work best in the mmWave frequency range with a high gain. A thin Rogers RT5880 substrate with a thickness of 0. 254 mm, a dielectric constant of 2. 3 and a loss tangent of 0. 000 9 supports the copper-based radiating element. A partial ground plane with a square slot and trimmed corners at the bottom enhances the antenna's bandwidth. The single-element antenna exhibits a wide bandwidth of nearly 6 GHz and a gain of 4. 58 dBi. By employing the proposed antenna array, the antenna gain is significantly enhanced to 14. 90 dBi while maintaining an ultra-compact size of 24 mm × 46 mm at the resonant frequency of 31 GHz. The antenna demonstrates a wider impedance bandwidth of 15. 73% (28 - 34 GHz) and an efficiency of 94%. The proposed design works well for 5G communication and satellite communication, because it has a simple planar structure and focused dual-beam radiation patterns from a simple feeding network. [ABSTRACT FROM AUTHOR]

High altitude platform station (HAPS) is one of the promising solutions to many of the developing and less developed countries. To a great extent, HAPS is relatively cost‐effective and can be easily moved on demand while observing the required quality of service. For tropical countries, rain attenuation is the main factor that affects HAPS performance. This study investigated HAPS performance in Tanzania under heavy rain conditions. Rain rate, rain attenuation, and carrier‐to‐noise ratio were used to quantify the system's performance. In this study, the rain rate exceeds by 0.01% (R0.01)$({{R}_{0.01}})$ of an average, was obtained using the Chebil model. Based on Tanzania Meteorological Agency data, the R0.01${R}_{0.01}$ registered a high amount of rainfall for the five selected regions: Dar es Salaam, Kagera, Tanga, Unguja, and Pemba. By using ITU‐R model, rain attenuation for the downlink was predicted, assuming horizontal polarisation, for 31.0–31.3 GHz. Finally, the HAPS link budget was analysed with a platform altitude of 22 km at frequency of 31.0–31.3 GHz for different elevation angles. Results showed that the performance of the system was promising in the given rainfall scenarios. [ABSTRACT FROM AUTHOR]

Satellite communication, in over half a century have attained remarkable breakthrough in high speed transmission. These innovations, on the other hand, have come in tandem with significant performance improvements in other IT and telecommunications systems. As a result, these significant benefits are not as visible to the broader public as they would be as if this burst of performance had occurred in isolation. In nutshell, space satellite communication using optical technology provide powerful alternative to radio frequency (RF) and make communication reliable and cost effective. Satellite communications systems allow a whole new race of civilian and defence operations in surveillance, telecommunications, object tracking and space exploration. Since independent satellites are restricted by volume, space and strength, small satellites production in bulk clusters may be effective for a range of wildfire monitoring, science missions, mapping in gravity and water management exploration, among others. The development of communications satellites would provide for a more comprehensive understanding of the near-earth environment as well as a more efficient and cost-effective way of reaching space, thanks to the utilisation of multi-satellite systems. As a result, when satellites are designing, IsOWC is an utmost point to be considered. The numerous researches being performed in the satellite communications for introducing multi communications based on different orbits are described in this study. IsOWC systems over radio frequency based communication are preferred due to large bandwidth, high speed, absence of electromagnetic interference (EMI), lower transmission losses and improved security. We also present a detailed listing of challenges in Is-OWC such as Doppler shift, point ahead angle, satellite vibration and tracking, acquisition tracking and pointing (ATP) and background noise sources. [ABSTRACT FROM AUTHOR]

Earth observation satellites (EOS) are satellites equipped with optical sensors that orbit the Earth to take photographs of particular areas at the request of users. With the development of space technology, the number of satellites has increased continuously. Yet still, the number of satellites cannot meet the explosive growth of applications. Thus, scheduling solutions are required to satisfy requests and obtain high observation efficiency. While the literature on multi-satellite scheduling is rich, most solutions are centralized algorithms. However, due to their cost, EOS systems are often co-funded by several agents (e.g., countries, companies, or research institutes). Central solutions require that these agents share their requests for observations with others. To date, there has yet to be a solution for EOS scheduling that protects the private information of the interested parties. In this study, we model the EOS scheduling problem as a distributed constraint optimization problem (DCOP). This modeling enables the generation of timetables for the satellites in a distributed manner without a priori sharing users' private information with some central authority. For solving the resulting DCOP, we use and compare the results of two different local search algorithms—Distributed Stochastic Algorithm and Maximum Gain Message—which are known to produce efficient solutions in a timely manner. The modeling and solving of the resulting DCOP constitute our new solution method, which we term Distributed Satellite Timetable Solver (DSTS). Experimental evaluation reveals that the DSTS method provides solutions of higher quality than a commonly used centralized greedy algorithm and is comparable to an additional centralized algorithm that we propose. [ABSTRACT FROM AUTHOR]

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In recent years, deep learning has significantly reshaped numerous fields and applications, fundamentally altering how we tackle a variety of challenges. Areas such as natural language processing (NLP), computer vision, healthcare, network security, wide-area surveillance, and precision agriculture have leveraged the merits of the deep learning era. Particularly, deep learning has significantly improved the analysis of remote sensing images, with a continuous increase in the number of researchers and contributions to the field. The high impact of deep learning development is complemented by rapid advancements and the availability of data from a variety of sensors, including high-resolution RGB, thermal, LiDAR, and multi-/hyperspectral cameras, as well as emerging sensing platforms such as satellites and aerial vehicles that can be captured by multi-temporal, multi-sensor, and sensing devices with a wider view. This study aims to present an extensive survey that encapsulates widely used deep learning strategies for tackling image classification challenges in remote sensing. It encompasses an exploration of remote sensing imaging platforms, sensor varieties, practical applications, and prospective developments in the field. [ABSTRACT FROM AUTHOR]

The Remote Sensing Ecological Index (RSEI) model is widely used for large-scale, rapid Ecological Environment Quality (EEQ) assessment. However, both the RSEI and its improved models have limitations in explaining the EEQ with only two-dimensional (2D) factors, resulting in inaccurate evaluation results. Incorporating more comprehensive, three-dimensional (3D) ecological information poses challenges for maintaining stability in large-scale monitoring, using traditional weighting methods like the Principal Component Analysis (PCA). This study introduces an Improved Remote Sensing Ecological Index (IRSEI) model that integrates 2D (normalized difference vegetation factor, normalized difference built-up and soil factor, heat factor, wetness, difference factor for air quality) and 3D (comprehensive vegetation factor) ecological factors for enhanced EEQ monitoring. The model employs a combined subjective–objective weighting approach, utilizing principal components and hierarchical analysis under minimum entropy theory. A comparative analysis of IRSEI and RSEI in Miyun, a representative study area, reveals a strong correlation and consistent monitoring trends. By incorporating air quality and 3D ecological factors, IRSEI provides a more accurate and detailed EEQ assessment, better aligning with ground truth observations from Google Earth satellite imagery. [ABSTRACT FROM AUTHOR]

Turbulence within the tropical cyclone boundary layer plays a crucial role in the exchange of heat, moisture, and momentum between the surface and the atmosphere. This study investigates the characteristics of coherent structures, specifically streaks and rolls, using large eddy simulations. Our results highlight significant differences across the three radius cases, with smaller radius exhibiting more intense and organized turbulence and streak/roll structures. Our analyses reveal that thermodynamic conditions significantly impact the timing of initial streak/roll development but do not affect their intensity in the steady state. Wind structures closer to the tropical cyclone center lead to stronger and more rapidly developing streaks/rolls, indicating their critical role in determining the intensity and formation of these features. Sensitivity tests on the Coriolis parameter (f) and radial decay parameter of tangential wind (n) show minimal impact on the development of streaks/rolls, suggesting these factors are less influential compared to wind and thermodynamic conditions. [ABSTRACT FROM AUTHOR]

Super Typhoon Doksuri is a significant meteorological challenge for China this year due to its strong intensity and wide influence range, as well as significant and prolonged hazards. In this work, we studied Doksuri's main characteristics and assessed its forecast accuracy meticulously based on official forecasts, global models and regional models with lead times varying from 1 to 5 days. The results indicate that Typhoon Doksuri underwent rapid intensification and made landfall at 09:55 BJT on July 28 with a powerful intensity of 50 m s-1 confirmed by the real-time operational warnings issued by China Meteorological Administration (CMA). The typhoon also caused significant wind and rainfall impacts, with precipitation at several stations reaching historical extremes, ranking eighth in terms of total rainfall impact during the event. The evaluation of forecast accuracy for Doksuri suggests that Shanghai Multi-model Ensemble Method (SSTC) and Fengwu Model are the most effective for short-term track forecasts. Meanwhile, the forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) and United Kingdom Meteorological Office (UKMO) are optimal for long-term predictions. It is worth noting that objective forecasts systematically underestimate the typhoon maximum intensity. The objective forecast is terribly poor when there is a sudden change in intensity. CMA-National Digital Forecast System (CMA-NDFS) provides a better reference value for typhoon accumulated rainfall forecasts, and regional models perform well in forecasting extreme rainfall. The analyses above assist forecasters in pinpointing challenges within typhoon predictions and gaining a comprehensive insight into the performance of each model. This improves the effective application of model products. [ABSTRACT FROM AUTHOR]

The ESCAP/WMO Typhoon Committee is an intergovernmental regional organization dealing with typhoon (tropical cyclones) related disasters. Millions of people around the Asia-Pacific region remain exposed to a higher frequency and intensity of natural hazards. For more developed countries, tropical cyclone related impacts cause major social and economic disruptions through loss of lives and property. With recognizing the importance of aligning its efforts with UN Early Warnings for All (EW4All) initiative which aims to strengthen early warning systems globally, Typhoon Committee resolved to initiate the monitoring of ongoing or past efforts by TC Members in contributing to the four key pillars of the EW4all initiative aiming to (1) evaluate the Committee's contributions to EW4All; and (2) identify the opportunities for enhancing performance through Member Reports and the WGs' AOP specification. TC had its 18th IWS/4th TRCG forum with a theme of "Early Warnings for All Through Enhancement of Typhoon Standard Operating Procedures (SOP)" and "Towards a Typhoon Resilient Society"; TC Secretary (TCS) initiated a reviewing and monitoring on the ongoing or previous efforts of TC Members, through analyzing the AOPs' implementation of TC WGs, in contributing to the pillars of the EW4All initiative with the objective of enabling an evaluation of the Committee's contributions to EW4All and identify opportunities for further enhancing its performance. This paper intends to discuss the directions on how to further enhance TC activities aligning with and contribution to EW4All in future. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TC) pose a persistent natural hazard to Costa Rica. Exposure to natural hazards, such as mass movements and floods, is compounded by a growing urban population and inadequate land use planning. This study conducted a comprehensive analysis of the economic impacts of TC of Costa Rica from Hurricane Joan in 1988 to Hurricane Eta in 2020, assessing the impact by municipality and economic sector using baseline information of the Ministry of National Planning and Economic Policy. According to the study, road infrastructure (933.8 US million), agriculture (280.5 US million), river rehabilitation (153.96 US million), housing 98.26 (US million), and health (81.74 US million) were among the sectors most severely affected by TC over the past 30 years. The Pacific basin municipalities in Costa Rica were found to be the most vulnerable, primarily due to the indirect impacts of TC. The study's results offer useful information on the economic sectors and municipalities that are most exposed from TC in Costa Rica and provide a replicable methodology for other regions and countries facing similar tropical phenomena. [ABSTRACT FROM AUTHOR]

Using high-frequency onshore wind data from four different heights of a coastal tower, the variations in gust factor with turbulence intensity, height and wind speed were studied under typhoon conditions. The gust factor increases with increasing turbulence intensity and, most often, can be described by a linear relationship with the turbulence intensity. The gust factor decreases with height and is relatively small compared with those presented in the national codes and other studies. A value of 2.5 is acceptable for the peak factor, which is close to the recommended value of the national code in China. The gust factor increases with increasing wind speed and is also affected by the wind direction. The gust factor has a value to that of previously published results when the wind flows roughly perpendicular to the shoreline, and has a smaller value when the wind flows roughly parallel to the shoreline. The phenomenon is caused by the confinement of shoreline on the sea wave development. Sea waves tend to propagate normal to the shoreline because of the refraction effect. As a result, a shorter roughness length exists in the parallel direction to the shoreline. It can be further explained by the weakness in the momentum flux exchange between the air and sea based on the wave form drag theory when the wind flows parallel to the shoreline. [ABSTRACT FROM AUTHOR]

Based on the ERA5 reanalysis data and the surface observations from automatic weather stations, a comparative analysis has been conducted to investigate the differences in heavy rainfall distributions caused by two landfalling tropical cyclones (TCs): LUPIT (2109) and LISA (9610). The two TCs have similar tracks, intensity and landing points, but show different asymmetric features in their rainstorm location relative to their tracks. The results indicate that the TC rainfall differences are mainly caused by different rainstorm formation mechanisms. The wind shear contributes most to the rainstorm of LISA, while land-sea contrast and topographical effect are the main factors of LUPIT rainstorm. Under the influence of strong environmental vertical wind shear and the weak cold air invasion from the west, the circulation center of LISA tilts westward with height, which cooperates with the low-level water vapor convergence and vertical ascending movement on the western side of the TC center to jointly cause the heavy rainstorm to the west of LISA center. In contrast, LUPIT has weak environmental vertical wind shear and no obvious structure tilting with height. Topographic effect plays a crucial role in causing the heavy rainstorm on the north of TC center. The southeasterly jet is blocked by the Taimu Mountain in the northeastern Fujian Province, and the strong ascending motion caused by the terrain-induced convergence appears to the north of LUPIT center. In addition, the moisture convergence is more pronounced in the north and weaker in the south. The intrusion of weak cold air from the east to the coastal areas of central-northern Fujian, and the moisture-convergence distribution, jointly cause the heavy rainstorm to the north of LUPIT. [ABSTRACT FROM AUTHOR]

Traditionally, an empirical speed-up factor was introduced to reflect the effects of nonflat terrain on near-surface wind speeds. In this paper, the resistance effects of nonflat terrain are considered by introducing the terrain drag coefficient in the parametric wind field model for tropical cyclones (TCs) with a theoretical method. Terrain effects on wind fields are investigated in complex areas along the coastal zone in China under TC conditions. The results show that the terrain drag coefficient is the function of the slope angle and is sensitive to the spatial resolution. After including the resistance effect of nonflat terrain, the TC intensities weaken overall during landfall, with a slight enhancement near the coastal zone. The wind speeds outside the radius of the maximum wind speed decrease, while the wind speeds within the radius of the maximum wind speed increase. Both the TC eye and the radius of maximum wind speed shrink, which is more obvious when the TC center is entirely over land. As a result, the location and magnitude of the maximum wind speed are affected by the nonflat terrain. The changed structure of the wind fields demonstrates the necessity of considering the effects of nonflat terrain in simulating the wind fields under TC conditions. [ABSTRACT FROM AUTHOR]

This study highlighted a high wave case by severe tropical cyclone Harold and conducted a simulation with a newly developed wave forecasting system for the South Pacific based on the Japan Meteorological Agency third generation wave model (JMA MRI-III) using the National Center for Environment Prediction Global Forecast System (GFS) winds. Harold was a very intense tropical cyclone (TC) and very high waves up to 10 m affected parts of Vanuatu and Fiji. The model results were reasonable and verified against observations of orbital satellites and a wave buoy at Komave in Fiji. The statistical verifications were carefully analysed. The Root Mean Squared Error (RSME), Scatter Index (SI), Bias and R2 are all showing very impressive results. The new wave forecasting system is the first high resolution operational model at Fiji Meteorological Service (FMS), which covers the whole Fiji area. The system will provide guidance to FMS in preparing marine alerts and warning better and more confidence in providing the marine forecast accurately. [ABSTRACT FROM AUTHOR]

Cargo transport to the space station and the transport of satellites to orbit the Earth are necessary for not only scientific analysis, but also for the telecommunications sector; therefore, the use of rockets with propellant fuel has been growing. Therefore, our manuscript proposes a mathematical model to analyze nonlinear dynamic behavior. Such a model is based on Mathieu's solution. However, we consider that the application of force for rocket propulsion is not ideal. The formulation of the applied force is based on Bessel s equations and has a dependence on parameters (ao and bo) that enable interesting characteristics. such as ao = 0 which makes it possible to turn the non-ideal force into a force ideal, that is, a simple oscillatory force. And as a result. the parametric set was established to diagnose the chaotic and periodic behavior that can be observed in mathematical modeling. Establishing these analyzes allows the application of future work in the development of control projects to reduce vibrations that can cause anomalies in the trajectories for the system's entry into orbit. Another application of nonlinear dynamic analysis is to establish regions for future suppression of the chaotic regime that were observed in our numerical analyses. [ABSTRACT FROM AUTHOR]

In terms of communications and scientific observations, a stratospheric airship can be an effective alternative to the artificial satellites in Earth's orbit. For an airship to float in the low air-density stratosphere, it must be designed with light, flexible, and strong materials. In the present study, we have designed and developed six different coated and laminated structures by using high-performance para-aramid fabric, polyvinylidene chloride (PVDC)-coated biaxially oriented polyethylene terephthalate (BOPET), and polyvinyl fluoride (PVF) films. The developed coated and laminated stratospheric airship structures demonstrate excellent performance even in the harsh environmental conditions such as very low atmospheric pressure (∼0.001 atm), extreme temperatures (80°C in the day and −80°C in the night;), high UV irradiation, and ozone as well as atomic oxygen. In order to analyze the effect of the harsh environmental conditions existing in stratospheric atmosphere on physico-mechanical properties such as tensile strength, tear strength, peel strength, and helium (He) gas barrier of the prepared laminate structures, they were evaluated after exposure in simulated accelerated artificial weathering conditions up to 400 h. The developed multilayered laminated structures exhibited superior He-gas permeability (0.04 L/m2/24 h), high tensile strength (>820 N/cm), and good tear strength (401–477 N/cm) with relatively low areal density (207–262 g /m2). Furthermore, all the laminates also demonstrated very low degradation in mechanical properties, that is, 3%–8% in peel strength, 1%–3% in tear strength, and 1%–2% in tensile strength under artificial weathering conditions up to 400 h. [ABSTRACT FROM AUTHOR]

Objectives: Using satellite video data as a target tracking data source can effectively remedy the problems of fixed angle and a small monitoring range of ground surveillance video, and provide a beneficial supplement for disaster prevention, intelligent transportation, crime tracking and other aspects. However, ground objects in satellite videos are complicated. If the texture, geometry, color and other appearance features of the target are blocked and submerged by other objects, tracking drift or tracking loss will occur in the tracking algorithm. Methods: Based on the fully-convolutional siamese network (SiamFC), this paper proposes an anti-occlusion target tracking algorithm based on satellite video, which can effectively solve the tracking loss problem of moving targets under different cover-up degrees. If the target occlusion degree is low, the forward result obtained by template update network is used as the tracking result of the current frame, and the forward result is set as a new forward template to obtain the changing characteristics of the moving target. If the target is highly obscured, first, the forward result is set as the new backward template, and used to repeatedly track the target in the previous frame. Then, the spatial position prediction module is used to obtain the historical trajectory features of the target and get the trajectory result. Finally, the forward result and the trajectory result are combined to get the tracking result of the current frame based on the bidirectional verification error obtained from the repeated tracking. Results: The proposed algorithm is verified by using typical moving target, aircrafts, ships and vehicles of Jilin-1 satellite video. The results show that the proposed algorithm can provide more accurate tracking results when the target is occluded. The tracking accuracy and success rate reach 76.2% and 78.9%, respectively, and the tracking speed is 33 frame per second. Conclusions: The proposed algorithm can realize the continuous tracking and monitoring of moving targets under occlusion conditions, and can effectively improve the emergency handling ability of intelligent transportation, disaster prevention and relief, wartime monitoring and other aspects in practical application. [ABSTRACT FROM AUTHOR]

The terrestrial ecosystem stores a huge amount of carbon in biomass and acts as a major carbon sink. Gross primary productivity (GPP) measures the carbon assimilation rate in terrestrial ecosystems. Accurate quantification and spatiotemporal analysis of GPP have become the essential indicators of various management, policy developments, and restoration activities in recent decades with the installation of new ground stations, development of robust models, and use of Earth Observation satellite data. The model-estimated and satellite data-derived GPP values greatly differ from ground observations due to model structure and approach, input driving data, coefficients and parameters, and various assumptions. Consequently, considerable ambiguity prevails among datasets and their benchmarking. Moreover, the productivity of ecosystems is regulated by physiological traits coupled with the local environmental conditions. This review provides an overview of the environmental and anthropogenic variables that regulate productivity and pose challenges in GPP estimation and evaluation of the available GPP products. It also evaluates the various available GPP datasets/ products and estimation methods/ models and compares the ecosystem productivity in broad natural and human-modified ecosystems in South Asia. Moreover, this study includes a case study on evaluating five globally available GPP products with variable spatiotemporal resolutions, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), the Vegetation Photosynthesis Model (VPM), the Global Land Surface Satellite (GLASS), Global OCO-2-based SIF product (GOSIF), and the Penman-Monteith-Leuning (PML) in three major land cover type of South Asia (forest, cropland, and grassland) comparing with eddy covariance (EC) flux tower data. Results showed a better performance of GOSIF and GLASS data than other GPP products. The study aims to provide an overview of the prevailing environmental conditions and carbon sequestration in different ecosystems and assist in developing sustainable landscape management strategies to reduce carbon emissions and mitigate climate change impact. Article highlights: • A critical review of the methods employed for GPP estimation and their limitations. • Impact of various management practices, extreme events, and climate change on GPP. • Comparison among available GPP datasets. [ABSTRACT FROM AUTHOR]

Long revisit intervals and cloud susceptibility have restricted the applicability of earth observation satellites in surface water studies. Integrating multiple satellites offers potential for more frequent observations, yet combining different satellite sources, particularly optical and SAR satellites, presents complexities. This research explores the data-fusion potential and limitations of Landsat-8/9 Operational Land Imager (OLI), Sentinel-2 Multispectral Instrument (MSI), and Sentinel-1 Synthetic Aperture (SAR) satellites to enhance surface water monitoring. By focusing on segmented surface water images, we demonstrate that combining optical and SAR data is generally effective and straightforward using a simple statistical thresholding algorithm. Kappa coefficients(κ) ranging from 0.80 to 0.95 indicate very strong harmony for integration across reservoirs, lakes, and river environments. In vegetative environments, integration with S1SAR shows weak harmony, with κ values ranging from 0.27 to 0.45, indicating the need for further studies. Global revisit interval maps reveal significant improvement in median revisit intervals from 15.87 to 22.81 days using L8/9 alone, to 4.51 to 7.77 days after incorporating S2, and further to 3.48 to 4.62 days after adding S1SAR. Even during wet season months, multi-satellite fusion maintained the median revisit intervals to less than a week. Maximizing all available open-source earth observation satellites is integral for advancing studies requiring more frequent surface water observations, such as flood, inundation, and hydrological modeling. [ABSTRACT FROM AUTHOR]

For low-Earth-orbit (LEO) satellites, high-precision clock estimation often depends on high-precision real-time global navigation satellite system (GNSS) products. Thus, service providers often choose to downlink observation data to the ground to achieve high accuracy. To relieve this burden for future LEO mega-constellations, this study investigates the performance of relative clocks and orbits determined between LEO satellites using the phase common-view (PCV) method. The PCV results are compared with results from three other single-satellite-based clock and orbit determination methods. Using real data from the Gravity Recovery and Climate Experiment (GRACE) Follow-On satellites and three different types of real-time GNSS products, the PCV method can deliver a relative clock precision below 0.2 ns and a relative orbital user range error of approximately 5 cm, even when using the broadcast ephemeris, whereas all three other methods encountered sharp degradations in their results when using degraded real-time GNSS products. [ABSTRACT FROM AUTHOR]

A significant challenge for interplanetary small satellites is fully propulsive orbit insertion due to limited total velocity change capabilities. At destinations with significant atmospheres, this challenge can be circumvented via aerocapture, a technique that uses a single atmospheric pass to convert a hyperbolic approach trajectory into a captured elliptical orbit. This paper investigated small satellite aerocapture at Mars with the morphable entry system, a deployable entry vehicle concept that uses shape morphing for trajectory control. A Monte Carlo dispersion analysis was conducted to assess the vehicle's robustness with respect to uncertainties in entry state, atmospheric density, and vehicle aerodynamics. Under the combined effects of these uncertainties, the morphable entry system achieved a 100% aerocapture success rate. Furthermore, the total velocity change required to place the vehicle on the target orbit for 99% of the simulated trajectories was 166.5 m/s, which is within the current capabilities of small satellite propulsion systems. The results suggest that the morphable entry system is a viable option for smallsat aerocapture at Mars. • Morphable entry system (MES) uses shape-morphing for aerocapture trajectory control. • MES achieved 100% aerocapture success rate at Mars. • MES may be a viable option for small satellite aerocapture at Mars. [ABSTRACT FROM AUTHOR]

• Integrated planning for observation and data downlink tasks. • A priority adjustment method for higher revenue rate. • Rapid inference speed for multiple satellites. The autonomous coordination and integrated planning of observation and data downlink missions for the distributed agile Earth observation satellite (AEOS) constellation hold significant importance in practical applications. In order to address this issue, we introduce an abstract universal mission model and present an algorithm rooted in deep reinforcement learning (DRL), termed the Attention-based Distributed Satellite Mission Planning (ADSMP) algorithm, which is designed to generate effective planning solutions. This algorithm employs a neural network that utilizes the attention mechanism, enabling each satellite to independently make decisions with equal intelligence. Furthermore, a mission priority adjustment method is devised to facilitate the coordination of data download and observation scheduling. The ADSMP is trained using the REINFORCE algorithm with Rollout Baseline. By conducting comparative experiments, we demonstrate that the proposed algorithm attains the highest revenue rate in corresponding scenarios, while simultaneously ensuring fast inference speed. [ABSTRACT FROM AUTHOR]

The aerosols play a main role in precipitation formation in the atmosphere. Organic Carbon (OC) is a must-imported aerosol because it is considered a cloud condensation nuclear CCN. This work dealt with the relationship between Organic Carbon (OC) and many variables that affect precipitation formation in South Iraq (Basra and AL-Muthana) including Cloud Top Temb Cloud Top Temperature CTT, Total PrecipitableWater TPW, and Precipitation. The cases selected are 14 – 15 Nov. 2018 and 26 – 29 Jan. 2019 to test the relationship between variables. Data obtained from retrospective analysis for research and applications, version 2 (MERRA-2). Including OC, total Precipitablewater (TPW), and precipitation amount of 3 hours. The times are fixed according to the cases. The cloud top temperature (CTT) was obtained by the infrared satellite images provided by the European Space Agency, using a group of satellites. The result indicates a strong effect of OC on the cloud depth and the TPW when finally increases the precipitation amount. [ABSTRACT FROM AUTHOR]

Low Earth orbit (LEO) communication satellite constellation provides network service to remote areas without terrestrialnetwork coverage. In sparsely populated areas, the deployment of ground stations is also scarce, due to geographic constraints and the lack of terrestrial backhaul. Due to the constant orbiting of the satellite constellation, location management in LEO satellite-assisted vehicular networks faces the challenges of the dual mobility of access points and users. In this paper, we propose a privacy-preserving location management scheme in an LEO satellite network with sparsely deployed ground stations. Specifically, the proposed scheme exploits the RSA-based accumulator and the Non-Interactive Proof-of-Knowledge of Exponent (NI - PoKE ) protocol to verify the linkages between satellites and vehicles. Meanwhile, our scheme combines the homomorphic Symmetric Homomorphic Encryption (SHE ) cryptosystem, the Secure Less than (SLESS ) protocol, and the KdTree structure, to identify the potential set of accessing satellites. Security analysis shows that the proposed scheme achieves privacy preservation and authentication. Performance evaluations show that ours achieve high computation and communication efficiency. [ABSTRACT FROM AUTHOR]

A growing body of literature studies how expert practices constitute issues such as climate change, migration, or public health as international objects of expertise. The article contributes to this research agenda by highlighting the role of digital visual technologies and infrastructures in the constitution and governance of these international objects. It develops the concept of visual objects and uses it to trace and explain the emergence of a new technological initiative conducted by the European Space Agency (ESA) and the EU: the vision of a 'digital twin Earth' (DTE). The idea behind the DTE is to combine various technologies, including satellite Earth observation, advanced computer models, and AI, to build a digital replica of our planet and thereby govern risks emanating from environmental changes and other global challenges. The article provides a first analysis of the international politics of the DTE. It shows how the visual object of the DTE functions as an attractor of heterogeneous actors and practices involved in the European space policy field thereby temporarily stabilizing this complex assemblage. Finally, it traces how the DTE and its machinic ways of seeing enact the Earth not only as an object of knowledge but also as one of experimentation and intervention. [ABSTRACT FROM AUTHOR]

As the world is moving towards the Internet of Things (IoT), more data rate is required with wider coverage and small delay. While the 5G supports the needed increased data rate, it suffers from a decreased coverage per tower. In contrast, the low population areas such as deserts, oceans, forests, and mountains contain most of the world's transportation such as highways, ships, and planes as well as large areas of agricultural lands that are all not supported by 5G. Consequently, LEO satellite constellations have been introduced to cover the earth's surface with a high-speed data rate. Each LEO satellite constellation requires 4000 + satellites and at least one ground base station (BS) for control, tracking, telemetry, and remote sensing functions. However, to support the needed downlink high-speed data rate demand, the LEO satellite constellation must add many BSs to increase the uplink data rate. As a result, the GEO communication satellites face great competitors in their market. This paper introduces the hybrid LEO-GEO satellite communication system to change this competition into cooperation that benefits both systems. In the hybrid LEO-GEO satellite communication system, this paper proposes maximizing the downlink utilization of both LEO and GEO satellites by the traffic-aware Artificial Expectation Detection (AED) technique. In such a technique, the trending multicast data choose the GEO link while the unicast data and control data choose the LEO link to maximize the downlink utilization efficiency. Our results show that using AED is power efficient and delay efficient while increasing the data rate by (100)x to (100k)x or decreasing the needed number of LEO BSs. [ABSTRACT FROM AUTHOR]

Summary: Cellular networks are projected to deal with an immense rise in data traffic, as well as an enormous and diverse device, plus advanced use cases, in the nearest future; hence, future 5G networks are being developed to consist of not only 5G but also different radio access technologies (RATs) integrated. In addition to 5G, the user's device (UD) will be able to connect to the network via LTE, WiMAX, WiFi, Satellite and other technologies. On the other hand, Satellite has been suggested as a preferred network to support 5G use cases. However, achieving load balancing is essential to guarantee an equal amount of traffic distributed between different RATs in a heterogeneous wireless network; this would enable optimal utilisation of the radio resources and lower the likelihood of call blocking/dropping. This study presented an artificial intelligent‐based application in heterogeneous wireless networks and proposed an enhanced particle optimisation (EPSO) algorithm to solve the load balancing problem in 5G‐Satellite networks. The algorithm uses a call admission control strategy to admit users into the network to ensure that users are evenly distributed on the network. The proposed algorithm was compared with the Artificial Bee Colony and Simulated Annealing algorithm using three performance metrics: throughput, call blocking and fairness. Finally, based on the experimental findings, results outcomes were analysed and discussed. [ABSTRACT FROM AUTHOR]

Recent years have seen the rapid deployment of low-cost CubeSats in low-Earth orbit, many of which experience significant latency (several hours) from the time information is gathered to the time it is communicated to the ground. This is primarily due to the limited availability of ground infrastructure that is bulky to deploy and expensive to rent. This article explores the opportunity in leveraging the extensive terrestrial LoRa infrastructure as a solution. However, the limited bandwidth and large amount of Doppler on CubeSats precludes these LoRa links to communicate rich satellite Earth images—instead, the CubeSats can at best send short messages. This article details our experience in designing LoRa-based satellite ground infrastructure that requires software-only modifications to receive packets from LoRa-enabled CubeSats recently launched by our team. We present Vista, a communication system that adapts encoding onboard the CubeSat and decoding configuration on commercial LoRa ground stations to allow images to be communicated. We perform a detailed evaluation of Vista by leveraging wireless channel measurements from a recent CubeSat (2021), and show that Vista can achieve 55.55% lower latency in retrieving data with 12.02 dB improvement in packet retrieval in the presence of terrestrial interference. We then evaluate Vista on a case study on land-use classification over images transmitted over the CubeSat link to further demonstrate a 4.56 dB improvement in image PSNR and 1.38× increase in classification accuracy over baseline approaches. [ABSTRACT FROM AUTHOR]

This paper studies a multiple-deep automated vehicles storage and retrieval system (AVS/RS) rack following a Depth-First storage and a Depth-First relocation strategy. We propose an analytical model based on a novel approach that utilises the Markov chain stochastic steady-state model. To verify the analytical model, a numerical simulation is developed. We also derive an empirical model using first- and second-order polynomial functions that are accurately fitted with regression equations and examined with MAPE and RMSE prediction accuracy measurements from a large-scale simulation study. The empirical model enables a straightforward calculation of the expected number of location movements of shuttle carriers and the attached satellite vehicles from which the AVS/RS throughput performance can be calculated. We present threefold and sixfold deep AVS/RS case study scenarios with an equal number of storage locations and estimate the cycle times. The evaluation of the case study results reveals that the analytical and empirical models achieve less than 2% error in the case of a dual command cycle time prediction compared to the simulation results. This proves that our approach allows an accurate estimation of multiple-depth AVS/RS throughput performance. [ABSTRACT FROM AUTHOR]