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A novel model reduction method for viscously damped structures with statically determinate interfaces, such as spacecraft flexible appendages, is proposed. The paper presents a derivation of the complete complex modal expansion of the interface dynamic stiffness of these structures. Based on the identity relation for all complex modes, which is obtained during the derivation, it is found that the interface acceleration impedance can be expressed as a rational fraction with high accuracy using only low-order complex modes. Using this rational fraction as an approximation model, numerical results of the frequency response can be fitted. The fitted interface acceleration impedance can be applied to real-time control as a reduced model in the form of a transfer function. Furthermore, it can be transformed into the form of system matrices by introducing auxiliary variables, which then participate in the dynamic analysis of the assembly. The reduction process circumvents complex modal analysis and necessitates only the results of frequency responses. Thanks to the powerful ability of conventional finite element software to perform frequency response analysis, this reduction method can be used for large-scale complex models in actual engineering applications. [ABSTRACT FROM AUTHOR]

Understanding beach dynamics, both in time and in space, is paramount to better understand how and when to intervene to improve coastal management strategies. Beach morphodynamics is expressed in a variety of ways. As indicators of beach change, we can measure the shoreline, the beach topography, and the bathymetry; e.g., in situ measurements rarely cover large extents, are often collected on a local scale (beach), and rarely cover a sufficient time span with a sufficient surveying frequency or a simultaneous measurement of the beach and bar system. Regular-revisit satellites, such as the ESA's Sentinel-2 mission, provide the opportunity to regularly monitor both shoreline and sandbar dynamics, and the time span is increasing and likely to continue for the decades to come. Using the satellite-derived shoreline and bar position, here, we show that the shoreline and bar are intrinsically coupled. Using Sentinel-2 satellite imagery, we show that the actual erosion/accretion status of the beach at Saint Louis (Senegal) is strongly influenced by the sandbar dynamics. There is a coupled behavior in their seasonal evolution and trend. Our results show that a very large accretive wave of about 50 m observed on the beach is driven by a local welding of the inner sandbar to the beach. Finally, we conclude that this type of event could be anticipated by an analysis of the sandbar. [ABSTRACT FROM AUTHOR]

This paper presents a study of deep learning approaches to image recovery using spatially-extended sequential observations of near-Earth satellites. Image recovery is often a prerequisite for use of ground-based extended imagery in space domain awareness (SDA) due to aberrations induced by atmospheric turbulence along the path from satellite to sensor. Traditional deconvolution-based image recovery methods are sensitive to factors such as observation sequence length and estimates of the point spread function (PSF), which has motivated recent interest in autoencoders and other learned approaches. However, no previous study has applied general state-of-the-art image restoration models to the space domain data. In this work, we evaluate the effectiveness of recent deep learning methods, specifically Generative Adversarial Networks (GANs) and Vision Transformers, for image restoration of satellites. We analyze the trade-offs between restoration quality, time, and computational complexity of each method. We experimentally demonstrate that deep learning models provide high-quality image restoration with less data than traditional deconvolution methods. We further optimize the most successful state-of-the-art model and demonstrate its efficacy in image restoration at a previously unseen degradation level (SNIIRS = 2.5). Our deep learning models are trained on simulated data from the SILO dataset and require no training on real data, yet they restore the most severely degraded real satellite imagery with state-of-the-art performance of 27.0 dB PSNR and 0.95 SSIM on the SILO dataset, as well as better visual results on the real satellite images. [ABSTRACT FROM AUTHOR]

There is a growing risk to aircraft in flight from collisions with debris produced by the breakup of uncontrolled rocket bodies and satellites during atmospheric reentry. On one hand, the aviation industry has grown to almost 39 million flights per year, with a 63 % increase between 2004 and 2019. On the other hand, the number of successful rocket launches more than doubled between 2015 and 2023, from 87 to 212, respectively. During those 212 launches in 2023, 128 rocket bodies were abandoned in orbit, left to reenter uncontrollably. Such uncontrolled space object reentries are hard to predict, making mitigation measures difficult. In November 2022, a reentering Long March 5B rocket caused the closure of airspace over Europe, delaying 645 flights and having a plausible economic impact of millions of Euros. There are international and domestic laws that might enable the recovery of economic losses resulting from uncontrolled reentries, but such losses should not be allowed to occur in the first place. Instead of leaving the location of a reentry to chance, controlled reentries can be achieved with existing technologies and mission designs, directing reentries away from areas of high aircraft traffic. Moving to a controlled reentry regime would create a cost to space operators – but that cost is currently being externalized to the aviation industry. Multilateral solutions to create a controlled reentry regime should be pursued, as recommended in the 2023 Montreal Recommendations on Aviation Safety and Uncontrolled Space Object Reentries, before there is a tragedy caused by an aircraft collision with debris from a rocket body or satellite. • As the number of rocket launches and commercial aircraft flights increase, the probability of a catastrophic collision between an aircraft and reentering space debris is also growing. • Technologies and mission designs exist to enable all rocket bodies to be returned to Earth in a controlled manner, eliminating the casualty risk. • From a broad economic perspective, space companies are externalizing some of their risks and costs and imposing them on the aviation industry. • States are liable for damage caused by reentering space objects and could be liable for the economic costs caused by precautionary airspace closures. • The 2023 Montreal Recommendations offer actionable steps to reduce the risk of collisions between space debris and aircraft. [ABSTRACT FROM AUTHOR]

Since the 1970s, remote sensing has been used to monitor the environment, address national security concerns, and manage Earth resources within a market framework. However, environmental organizations can also utilize remote sensing data infrastructure to support oppositional narratives, legal processes, and direct action. We present a framework for the socio-technical practice of remote sensing in alliance with those communities and organizations that are struggling for environmental justice on the global commodity frontiers. Positioned at the intersection of critical geography and political ecology, we examine the ways that critical remote sensing has been adopted in five major types of environmental conflict: struggles opposing fossil fuel exploitation, timber extraction, intensive food production, water management practices, and the effects of mining. We present a baseline inventory of remote sensing resources that are useful to the five conflict types and are freely accessible online. A global perspective on the planetary environmental crisis is essential, and we suggest that remote sensing practitioners can, through workshops or online tutorials, help environmental justice organizations towards independent use of remote sensing data. The local communities should then determine whether remote sensing products can contribute to their struggles. [ABSTRACT FROM AUTHOR]

The article reveals the importance of space for national security. The points of interaction between space activities and national security are identified, which reflect the growing importance of outer space for ensuring the security of States and emergency management, the growth of international cooperation in the field of space technologies. The newest possibilities of space to ensure national security (warning and military intelligence systems; communication systems and means of coordination; systems of space monitoring of the environment and resource management; systems of border and maritime surveillance; development of other technologies; development of global cooperation) are revealed. The problems of ensuring the priority of national security in the use of space resources have been formed, with the formation of a global strategy that geopolitical stability and prevention of the militarization of space should become key aspects for ensuring the national security of any State.

Here, the novel technique of extended-range high-energy-resolution fluorescence detection (XR-HERFD) has successfully observed the n = 2 satellite in manganese to a high accuracy. The significance of the satellite signature presented is many hundreds of standard errors and well beyond typical discovery levels of three to six standard errors. This satellite is a sensitive indicator for all manganese-containing materials in condensed matter. The uncertainty in the measurements has been defined, which clearly observes multiple peaks and structure indicative of complex physical quantum-mechanical processes. Theoretical calculations of energy eigenvalues, shake-off probability and Auger rates are also presented, which explain the origin of the satellite from physical n = 2 shake-off processes. The evolution in the intensity of this satellite is measured relative to the full Kα spectrum of manganese to investigate satellite structure, and therefore many-body processes, as a function of incident energy. Results demonstrate that the many-body reduction factor S02 should not be modelled with a constant value as is currently done. This work makes a significant contribution to the challenge of understanding many-body processes and interpreting HERFD or resonant inelastic X-ray scattering spectra in a quantitative manner.

Will proliferated satellites enable a transparent battlefield in a way that might transform continental warfare? Many now think so. We argue, however, that anti-satellite (ASAT) capabilities will limit satellites’ potential contribution, but only if land forces adapt by deploying ground-based jamming and dazzling technologies. In a sustained measure-countermeasure competition, these non-kinetic approaches enjoy advantages that can deny an opponent effective use of space for battlefield surveillance. If ground forces contest the use of space in this way, the future battlefield will be much less transparent than many now expect. [ABSTRACT FROM AUTHOR]

We show that the Landsat and Sentinel-2 satellites can detect NO2 plumes from large point sources at 10 to 60 m pixel resolution in their blue and ultrablue bands. We use the resulting NO2 plume imagery to quantify nitrogen oxides (NOx) emission rates for several power plants in Saudi Arabia and the United States, including a 13-y analysis of 132 Landsat plumes from Riyadh power plant 9 from 2009 through 2021. NO2 in the plumes initially increases with distance from the source, likely reflecting recovery from ozone titration. The fine pixel resolutions of Landsat and Sentinel-2 enable separation of individual point sources and stacks, including in urban background, and the long records enable examination of multidecadal emission trends. Our inferred NOx emission rates are consistent with previous estimates to within a precision of about 30%. Sources down to ~500 kg h-1 can be detected over bright, quasi-homogeneous surfaces. The 2009 to 2021 data for Riyadh power plant 9 show a strong summer peak in emissions, consistent with increased power demand for air conditioning, and a marginal slow decrease following the introduction of Saudi Arabia's Ambient Air Standard 2012. [ABSTRACT FROM AUTHOR]

As the number of small satellites in low-Earth orbit increases, the goal of shortening the deorbit period after the end of operation has been set. Along with this trend, a more effective deorbit system than used to date is required. This paper proposes a deorbit component that combines a method of obtaining plasma drag by interference between on-orbit plasma and an electromagnetic field generated by an electromagnetic coil in a small satellite, and a method of obtaining air drag using deployable membranes. The proposed component uses a deployable membrane structure with electromagnetic coils, and it is possible to mount multiple components on a small satellite. It is possible to obtain greater drag using multiple components. In this paper, the plasma drag is calculated using the two-dimensional Full-Particle-In-Cell method when multiple deorbit components are mounted, and the appropriate coil arrangement is clarified. Furthermore, the deorbit duration is calculated by the total drag of the plasma drag and the air drag, and the performance of the proposed deorbit component is evaluated. [ABSTRACT FROM AUTHOR]

Since the late 1950s, when the first artificial satellite was launched, the number of Resident Space Objects has steadily increased. It is estimated that around one million objects larger than one cm are currently orbiting the Earth, with only thirty thousand larger than ten cm being tracked. To avert a chain reaction of collisions, known as Kessler Syndrome, it is essential to accurately track and predict debris and satellites' orbits. Current approximate physics-based methods have errors in the order of kilometers for seven-day predictions, which is insufficient when considering space debris, typically with less than one meter. This failure is usually due to uncertainty around the state of the space object at the beginning of the trajectory, forecasting errors in environmental conditions such as atmospheric drag, and unknown characteristics such as the mass or geometry of the space object. Operators can enhance Orbit Prediction accuracy by deriving unmeasured objects' characteristics and improving non-conservative forces' effects by leveraging data-driven techniques, such as Machine Learning. In this survey, we provide an overview of the work in applying Machine Learning for Orbit Determination, Orbit Prediction, and atmospheric density modeling. [Display omitted] • Survey the introduction of new statistical techniques for Orbital Estimation. • Overview of deep learning techniques to improve empirical atmospheric density models. • Systematically study trends in Orbital Estimation using ML-based enhancements. • Define potential applications of Machine Learning approaches to Orbit Determination. [ABSTRACT FROM AUTHOR]

This paper delves into the recent advancements in phased-array antenna systems, focusing on their application in low earth orbit (LEO) satellite systems and their implications for high-speed, low-latency communication networks. The escalating demand for high-speed data transfer and responsive communication has spurred the exploration of novel antenna technology solutions. In light of meeting these needs, phased-array antenna systems are now giving the prospect of offering something that conventional antenna systems cannot: the capacity to steer building and pathway beams in numerous and precise means to make the most of signal intersection. Realized by the directing and molding strategies, this capability reduces the signal transmission time, which enhances the low latency process in the network hence increases its responsiveness. In addition, the design of phased-array antennas allows increased data rates as it increases network capacity and allows for multiplication of transmission beams to provide faster data processing. The paper also looks into the interaction of these advancements with the LEO satellites, satellites that orbit close to the Earth and move from point to point quite frequently. The issues that arise when implementing LEO systems such as target mobility and communicating with multiple targets, overcoming interference in crowded orbits can be resolved by adopting phased-array antenna systems for resilient infrastructure. [ABSTRACT FROM AUTHOR]

The arrival of the nuclear age highlighted the inadequacy of U.S. and allied information networks for transmitting vital messages across the globe. Submarine cables could be cut and radio easily jammed. U.S. and allied officials looked to emerging space technologies to compensate for the inadequacies of radio and submarine cables and to reduce their dependence on terrestrial telecommunications hardware. But satellites were also vulnerable and insufficient for meeting all communications requirements. Consequently, creating layered telecommunications networks that stretched from under the sea, across the land, and into space emerged as the optimal strategy for strengthening information security. [ABSTRACT FROM AUTHOR]

A large number of satellites operate in Earth's orbit. These are satellites for Earth observation, navigation, meteorology and climate, communication, and many others. They perform tasks and provide services without which today's world would not function. All these satellites are highly vulnerable since there are different kinds of threats. They are primarily space debris and various natural threats such as near-Earth objects and space weather. In addition, there are also intentional, man-made threats which are divided into kinetic, non-kinetic, electronic and cybernetic. The article discusses the development of knowledge of individual types of threats and suggests/analyses possible ways how to recognize them and how to protect vital satellites from them. [ABSTRACT FROM AUTHOR]

The Laplace resonance is a mean-motion resonance that involves the three inner Galilean moons of Jupiter. However, its true nature is in part unclear; in particular, different views can be found in the literature on whether the Laplace resonance is a pure three-body resonance or a mere superposition of two-body resonances. To settle this question, we conduct a thorough analysis of the many resonances involved, starting from the two-body 2:1 commensurabilities of the couples Io–Europa and Europa–Ganymede, and ending with the three-body 4:2:1 commensurability between the three moons. By artificially varying the parameters of the system and monitoring its fundamental frequencies, we cartography all resonances involved and their interactions. From the analysis of the individual 2:1 commensurabilities, we find that despite the oscillation of the resonant angles they are not genuine resonances, as the trajectory of the system in the phase space is not enclosed by separatrices. On the contrary, as suggested by previous works, we show that the only current true mean-motion resonance is the pure three-body resonance between all three satellites. Moreover, we find that the current values of the moons' orbital elements make the Laplace resonance sufficiently separated from the individual two-body 2:1 resonances, preventing chaotic effects from appearing. [ABSTRACT FROM AUTHOR]

Summary: Autonomy is becoming a prime requirement for satellite mission control operations. Data‐driven methods like Machine Learning models are playing a key role in bringing in autonomy. Health keeping data from satellite telemetry is a key ingredient in these data‐driven methods. In real‐world satellite operations, the health‐keeping telemetry data gradually drifts due to adverse space weather effects and wear and tear of electronic and mechanical components. The key question that arises is how to detect and quantify the data drift which is generally a gradual phenomenon. This paper discusses a novel statistical method for detecting data drift occurring in satellite telemetry. For the purpose of experimental work in this paper, an actual telemetry data set of the BUS CURRENT sensor which is part of the Electrical Power System of a Low Earth Orbit Satellite was considered. Data drift detection test was carried out using this sensor data using the developed novel statistical method and with Kolmogorov Smirnov test which is a probabilistic method. Both results are analysed and compared. Thereafter novel statical method was used to check its efficacy using a synthetic data set with induced drift. [ABSTRACT FROM AUTHOR]

The high-speed videorecording method is used to investigate the effect of an electrostatic field (with the potential Φ = 0, 16, and 18 kV) on the flow geometry in the case of gravity-induced separation of a drop from a capillary tube. The flow videograms are analyzed and the dimensions of the characteristic structural elements, that is, the drops themselves, a bridge, and satellites, are determined. The oscillations of the linear dimensions and the mother liquid volume after drop separation are traced at 0 and 18 kV. Both fundamental frequencies and their harmonics are observable in the spectra. It is found that small (12%) variations in the potential value lead to qualitative variations in the flow pattern and, in particular, to direct separation of the drop from the mother liquid without the formation of a bridge. At a constant liquid discharge in the capillary the dimensions of the separated drops decrease with increase of the voltage. The experiments show the possibility of the fine controlling of drop flows using electrostatic fields. [ABSTRACT FROM AUTHOR]

The amount of space debris is rising rapidly, and the number of satellites launched by humans is also growing. This poses a serious threat to the security of many important space assets including the International Space Station and the China Space Station. Due to the frequent occurrence of hazardous space conjunction (potential collisions) events, we aim to use a constellation composed of a few optical satellites to observe these space dangerous conjunction events, thereby improving the observation accuracy and timeliness of key conjunction events. We consider a variety of factors to establish an optical nanosatellite constellation design model, develop constellation observation efficiency evaluation criteria, construct a constellation configuration evaluation function, and design the performance parameters of space-based optical telescopes. The optimal orbit parameters and constellation configuration are obtained by using the genetic algorithm for optimization calculation. It is determined that a constellation of 6 satellites can track and observe more than 96% of potentially dangerous conjunction objects 24–48 h before a dangerous conjunction occurs. According to the observation data, high-precision orbit information of space objects can be obtained, which can reduce the collision false alarm rate by 99%. As a result, operators are notified to take collision avoidance measures only when the space object is truly in danger. This approach greatly reduces the number of avoidance operations caused by false early warnings, lowers the operating cost of space assets, and ensures the safety of space assets. [ABSTRACT FROM AUTHOR]

The paper deals with a state-of-the-art applied problem related to the detection of landscape's unnatural changes based on satellite images. An approach to constructing a detection system based on neural network processing of local terrain areas is proposed. As part of the approach, a neural network architecture and mechanisms for tuning to a specific area have been developed. It is shown that the use of neural networks and images corresponding to local areas (as initial data) provides easy expansion of the system to various types of terrain. The paper also presents a data filtering algorithm to adjust the balance of recall and overall precision of the system. Experimental studies have confirmed the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

With the number of new satellites increasing dramatically, comprehensive space surveillance is becoming increasingly important. Therefore, high-resolution inverse synthetic aperture radar (ISAR) imaging of satellites can provide an in-situ assessment of the satellites. This paper demonstrates that pseudo-noise signals can also be used for satellite imaging, in addition to classical linear frequency-modulated chirp signals. Pseudo-noise transmission signals offer the advantage of very low cross-correlation values. This, for instance, enables the possibility of a system with multiple channels transmitting instantaneously. Furthermore, it can significantly reduce signal interference with other systems operating in the same frequency spectrum, which is of particular interest for high-bandwidth, high-power systems such as satellite imaging radars. A new routine has been introduced to generate a wideband pseudo-noise signal with a peak-to-average power ratio (PAPR) similar to that of a chirp signal. This is essential for applications where the transmit signal power budget is sharply limited by the high-power amplifier. The paper presents both theoretical descriptions and analysis of the generated pseudo-noise signal as well as the results of an imaging measurement of a real space target using the introduced pseudo-noise signals. [ABSTRACT FROM AUTHOR]

This article discusses the observation of vertical coupling during a major sudden stratospheric warming (SSW) event in 2020/2021. The study focuses on the response of the thermospheric winds and temperature to the SSW using observations from NASA's ICON and GOLD satellites. The results show significant changes in winds and temperature during the SSW, with enhanced northward and westward winds in the thermosphere and a drop in temperature around 150 km. These changes are likely caused by the SSW-induced changes in atmospheric wave propagation and dissipation conditions. The study highlights the manifestation of long-range vertical coupling in the atmosphere during major SSW events. [Extracted from the article]

The response of tropical high clouds to surface warming and their radiative feedbacks are uncertain. For example, it is uncertain whether their coverage will contract or expand in response to surface warming and whether such changes entail a stabilizing radiative feedback (iris feedback) or a neutral feedback. Global satellite observations with passive and active remote sensing capabilities over the last two decades can now be used to address such effects that were previously observationally limited. Using these observations, we show that the vertically averaged coverage exhibits no significant contraction or expansion. However, we find a reduction in coverage at the altitude where high clouds peak and are particularly radiatively‐relevant. This results in a negative longwave (LW) feedback and a positive shortwave (SW) feedback which cancel to yield a near‐zero high‐cloud amount feedback, providing observational evidence against an iris feedback. Next, we find that tropical high clouds have risen but have also warmed, leading to a positive, but small, high‐cloud altitude feedback dominated by the LW feedback. Finally, we find that high clouds have been thinning, leading to a near‐zero high‐cloud optical depth feedback from a cancellation between negative LW and positive SW feedbacks. Overall, high clouds lead the total tropical cloud feedback to be small due to the negative LW‐positive SW feedback cancellations. Plain Language Summary: Tropical high clouds can have both cooling and heating effects: by reflecting sunlight, they cool the planet and by preventing terrestrial radiation from escaping to space, they also heat the planet. Despite their influence on how much heat gets stored in the Earth system, there is a surprisingly poor understanding of how these clouds will respond to global warming. This uncertainty is largely due to the paucity of observational data. Now, however, instruments aboard satellites orbiting Earth have provided unprecedented data on the changes in the vertical structure of clouds as well as their heat impacts. Our work shows that the dominant signal in the satellite cloud record is the rise of high clouds in response to warming, not any net contraction of coverage. The high clouds are also found to be warming and thinning. Overall, these high cloud changes induce less reflection of sunlight and allow more terrestrial radiation to escape to space. However, these radiative effects cancel and altogether cause no significant heating impact in the tropics. Key Points: Tropical high clouds are rising, warming, thinning, and when vertically averaged, are not contractingTropical high clouds show a positive altitude radiative feedback and near‐zero optical depth and amount radiative feedbacks [ABSTRACT FROM AUTHOR]

This paper represents the equilibrium positions and stability of two artificial satellites connected by light, flexible, and elastic long tethers under the combined effect of several classical perturbative forces in an elliptical orbit. The tether may be conducting or non-conducting. In our problem, it is taken as non-conducting in nature. We have treated the problem by taking five perturbative forces on the system simultaneously. Three perturbations exist due to the influences of the earth, namely geomagnetic fields, shadows, and oblateness. The other perturbations are due to the elasticity of the cable and solar light pressure. The effect of air resistance is neglected, considering the satellites as high-altitude satellites. To determine the stability of the satellites, we have used the Lyapunov method. The dynamical behaviors of the satellites are represented by differential equations. Based on analytical analysis of the differential equations of motion, we get the equilibrium positions of the system concerned in elliptical orbit. Lyapunov method gives the equilibrium position as unstable as expected. [ABSTRACT FROM AUTHOR]

The increasing number of vehicles on the road places high demands for autonomous driving in future intelligent transportation systems (ITSs). To realize automated services in ITSs, high-accuracy positioning is increasingly important, while positioning simultaneity for high-mobility vehicles should be guaranteed. Existing positioning systems have many constraints in locating vehicles in urban environments, making it difficult to meet the performance requirements. With the development of 6G, massive numbers of high-frequency base stations (BSs) are expected to be deployed to ensure connectivity and benefit positioning performance. However, high-frequency signals have severe distance attenuations and strong sensitivity to the non-line-of-sight (NLoS) environment that is prevalent in cities. Intelligent reflecting surface (IRS), with its ability to control signal reflections and create beyond-LoS communications, is a promising technology to improve positioning performance in urban vehicular networks. In this article, we discuss the existing positioning systems and explain the potentials of IRS for future BS-enabled positioning systems. We also provide an example to illustrate how to optimize the performance of IRS-aided vehicle positioning systems. Furthermore, we highlight important issues and give future directions. [ABSTRACT FROM AUTHOR]

Accurate and consistent reliability measures are invaluable for the safe and sustainable design and operation of systems in space applications. To achieve those goals, the current practices in the space community range from probabilistic and heuristic approaches, to best-practice and out-of-field guideline-based approaches. Establishing common ground and offering a go-to handbook for the space community was the goal of the reliability.space project. The resulting reliability.space handbook covers a majority of reliability prediction aspects in space applications. In this paper, the status quo and its deficiencies are summarized, followed by an introduction to the reliability.space handbook and its interactive digital version that aim at addressing all raised deficiencies. A case study finally applies the principles of the reliability.space handbook to the reliability prediction of a megaconstellation of CubeSats. [ABSTRACT FROM AUTHOR]

The increasing availability of external data in the realm of big data significantly impacts the operations and performance of businesses. In this study, we focus on Earth Observation (EO) technology, which supplies an extensive range of data related to Earth's chemical, biological, physical, and societal aspects. Our primary goal is to understand how the utilisation of EO data affects companies operating in the downstream sector. These enterprises possess the expertise and capabilities to extract valuable insights and information from EO data. We use a rich and innovative dataset representing 74% of the Italian EO downstream sector. The results show that EO data have heterogeneous impacts across downstream firms. Economic performance and innovation are positively correlated only for a subset of firms, especially the ones in the northern regions. Firms in the centre of Italy exploit the spillover of being close to large space infrastructures, but their performance in economic and innovation terms is mixed. The sub-sample in the South of Italy innovates due to EO but performs poorly economically. We discuss the determinants of such discrepancies and suggest policy and managerial implications for the industry's future development. [ABSTRACT FROM AUTHOR]

LabOSat is an applied research group whose main objective is to increase the technology readiness level of electronic devices and systems for their use in satellite missions. Since 2013 the Group has participated in nine low-Earth orbit missions in collaboration with Satellogic. Its flagship payload, LabOSat-01, is a Source-Measurement-Unit instrument dedicated to the electrical characterization of electronic devices. In this brief communication, results of in-orbit operation of LabOSat-01 are presented. A summary of the Group activities in the period 2013–2022 is also presented. These results represent almost ten years of experience in nine missions hosting different technologies in orbit. [ABSTRACT FROM AUTHOR]

The present paper discusses a number of topics relevant to line broadening in the presence of periodic oscillatory fields. Specifically, we discuss the applicablility of the expression usually employed to compute the autocorrelation function, the dressing, accounting for random phases, neglecting fine structure and numerical issues associated with stiffnes. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is gaining popularity and market share, driven by its ability to connect devices and systems that were previously siloed, enabling new applications and services in a cost-efficient manner. Thus, the IoT fuels societal transformation and enables groundbreaking innovations like autonomous transport, robotic assistance, and remote healthcare solutions. However, when considering the Internet of Remote Things (IoRT), which refers to the expansion of IoT in remote and geographically isolated areas where neither terrestrial nor cellular networks are available, internet connectivity becomes a challenging issue. Non-Terrestrial Networks (NTNs) are increasingly gaining popularity as a solution to provide connectivity in remote areas due to the growing integration of satellites and Unmanned Aerial Vehicles (UAVs) with cellular networks. In this survey, we provide the technological framework for NTNs and Remote IoT, followed by a classification of the most recent scientific research on NTN-based IoRT systems. Therefore, we provide a comprehensive overview of the current state of research in IoRT and identify emerging research areas with high potential. In conclusion, we present and discuss 3GPP's roadmap for NTN standardization, which aims to establish an energy-efficient IoRT environment in the 6G era. [ABSTRACT FROM AUTHOR]

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Wars will not be fought on the grounds in future, but explosions will occur beyond horizons. The subject of advanced strategies of Great Powers, space militarization, and political adventurism of China, USA, and Russia has been extensively inscribed in this research paper. The paper mainly reflects the political stratagem and space arms race of Russia, China, and the USA, which are combating each other for power status in orbits of space. As China and Russia challenge USA dominance in space, the USA seeks to weaponize space to maintain its supremacy and counter these rivals. The evolving international structure and world order are steering warfare into new dimensions, with space militarization posing nontraditional security threats like spying, surveillance, space debris, and satellite destruction. Technology has advanced to the point where states have developed sophisticated spy satellites and anti-satellite weapons capable of targeting other satellites from space or the ground. Despite international legal efforts and multilateral cooperation, major powers continue to expand their space arsenals, creating national security concerns. The study argues that international institutions have failed to curb the space arms race due to their ineffectiveness. Thus, there is a need for a shift in focus to find common ground and resolve this space security conflict. The paper provides a theoretical overview of the role of international institutions and state behavior in the international system. Using qualitative research techniques, the study conducts in-depth exploration through secondary data gathered from various articles, journals, reports, vlogs, videos, and magazines. Descriptive and explanatory research approaches are employed to achieve the research objectives.

We describe a method to estimate coefficients ${{{\bm{h}}}_{\bm{n}}}$ of a power spectral density of the form ${\bm{\Sigma}}{{{\bm{h}}}_{\bm{n}}}/{{{\bm{f}}}^{\bm{n}}}$ (${\bm{f}}\;{\bm{\ }}\text{is}$ the frequency and integer ${\bm{n}} \geq 0$) from corresponding measured time series with periodic gaps. This technique is applied to consistently estimate the amount of $1/{\bm{f}}$ noise present in weather system follow-on microwave microwave imager's (MWI) channels from the time-series data collected with different periodic gaps during prelaunch ground tests. The method assumes that the power spectrum of $1/{\bm{f}}$ noise present in MWI can be represented as a second-order frequency polynomial model of the form ${\bm{\Sigma}}{{{\bm{h}}}_{\bm{n}}}/{{{\bm{f}}}^{\bm{n}}}{\bm{\ }}$ and attempts to retrieve the true spectrum by solving for the ${{{\bm{h}}}_{\bm{n}}}$ coefficients using the power spectrum of the time-series data with periodic gaps. The method also assumes that the periodicity and duration of the data gaps are known and consistent for a given time series. The theoretical basis of the new technique is derived and tested using simulation and the new procedure is then applied to real test data to estimate the coefficients of the frequency polynomial. As a quantitative estimate for the $1/{\bm{f}}$ noise, the radiometer gain fluctuation (${\bm{\Delta}}{\bm{G}}/{\bm{G}}$) at 1 Hz is then solved from the frequency polynomial of the gain fluctuation power spectrum. The 1 Hz $( {{\bm{\Delta}}{\bm{G}}/{\bm{G}}} )$ values were compared between two sets of ground test data for the same MWI channels but with large (92%) and small (4.89%) duty cycles. The similarity of the 1 Hz $( {{\bm{\Delta}}{\bm{G}}/{\bm{G}}} )$ values extracted from these two disparate datasets establishes confidence in the method. The derived noise power spectrum is then used to simulate MWIs radiometric brightness temperature images and predict the level of unwanted striping in the flight data due to $1/{\bm{f}}$ noise content. This method may be applicable to solve for the polynomial coefficients of the power spectrum of any noise process, which can be modeled as a frequency polynomial, given the polynomial form is known a priori.

Microwave remote sensing technology has emerged to provide valuable products to monitor and assess soil moisture content at regional or global scales. However, each soil moisture product exhibits different advantages and shortcomings. Data fusion could help improve accuracy by merging information from different sources. In this research, a traditional triple collocation (TC) based method and a novel long short term memory network (LSTM) are used to merge soil moisture products from the soil moisture active passive mission, Advanced Microwave Scanning Radiometer 2 (AMSR2), and The Advanced SCATterometer for a study area located in western Europe. This research reveals that the LSTM outperforms the traditional TC based method for data fusion. The study identifies that both climate forcing and physiographic attributes significantly influence the spatial and temporal variations observed in the LSTM merging scheme. Consequently, the study highlights the considerable potential of the LSTM method for large-scale integration of remote sensing soil moisture data.

Understanding beach dynamics, both in time and in space, is paramount to better understand how and when to intervene to improve coastal management strategies. Beach morphodynamics is expressed in a variety of ways. As indicators of beach change, we can measure the shoreline, the beach topography, and the bathymetry; e.g., in situ measurements rarely cover large extents, are often collected on a local scale (beach), and rarely cover a sufficient time span with a sufficient surveying frequency or a simultaneous measurement of the beach and bar system. Regular-revisit satellites, such as the ESA’s Sentinel-2 mission, provide the opportunity to regularly monitor both shoreline and sandbar dynamics, and the time span is increasing and likely to continue for the decades to come. Using the satellite-derived shoreline and bar position, here, we show that the shoreline and bar are intrinsically coupled. Using Sentinel-2 satellite imagery, we show that the actual erosion/accretion status of the beach at Saint Louis (Senegal) is strongly influenced by the sandbar dynamics. There is a coupled behavior in their seasonal evolution and trend. Our results show that a very large accretive wave of about 50 m observed on the beach is driven by a local welding of the inner sandbar to the beach. Finally, we conclude that this type of event could be anticipated by an analysis of the sandbar.

National security in space has long focused on the threat posed by potentially offensive capabilities or behavior of nation-states. However, there is a huge shift in the type of dominant actor in space and this may result in instability, caused by ripple effects disrupting the existing governance structure and demonstrating the slipping rank of Russia as a space superpower. As a result, the fundamental nature of space is changing, and with that change comes disruption as to how the domain has been governed to date. If international governance does not evolve along with the domain, then we run the risk of seeing inadvertent escalations or even conflict between countries as a result. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) rely on satellite systems for stable positioning. However, due to limited satellite coverage or communication disruptions, UAVs may lose signals for positioning. In such situations, vision-based techniques can serve as an alternative, ensuring the self-positioning capability of UAVs. However, most of the existing datasets are developed for the geo-localization task of the objects captured by UAVs, rather than UAV self-positioning. Furthermore, the existing UAV datasets apply discrete sampling to synthetic data, such as Google Maps, neglecting the crucial aspects of dense sampling and the uncertainties commonly experienced in practical scenarios. To address these issues, this paper presents a new dataset, DenseUAV, that is the first publicly available dataset tailored for the UAV self-positioning task. DenseUAV adopts dense sampling on UAV images obtained in low-altitude urban areas. In total, over 27K UAV- and satellite-view images of 14 university campuses are collected and annotated. In terms of methodology, we first verify the superiority of Transformers over CNNs for the proposed task. Then we incorporate metric learning into representation learning to enhance the model’s discriminative capacity and to reduce the modality discrepancy. Besides, to facilitate joint learning from both the satellite and UAV views, we introduce a mutually supervised learning approach. Last, we enhance the Recall@K metric and introduce a new measurement, SDM@K, to evaluate both the retrieval and localization performance for the proposed task. As a result, the proposed baseline method achieves a remarkable Recall@1 score of 83.01% and an SDM@1 score of 86.50% on DenseUAV. The dataset and code have been made publicly available on https://github.com/Dmmm1997/DenseUAV. [ABSTRACT FROM AUTHOR]

SARAL/AltiKa, the first microwave altimeter operating at Ka-band frequency, recently completed nine years of operations in orbit. During these years, it has catered to many applications related to operational oceanography, climate sciences, hydrology and cryosphere. More specifically, in oceanography, SARAL has contributed immensely to operational wave and circulation modelling, eddy detection/tracking, ocean current generation and many more. However, since Feb 2019, SARAL has moved from the drifting phase (DP) to the mispointing phase (MP) due to the malfunctioning of the star sensor of the spacecraft. In this study, we analyse the instrument's performance and its waveforms during its ongoing MP. We find out that during the MP, significant wave height (SWH) measurements are anomalously high between 18 and 24 m, and wind speed measurements are between 16 and 19 m/s. In sea surface height anomaly (SSHA), there is a steady rise in negative values during the MP. In the return waveform, ∼15% degradation in Brown-type waveforms in the open ocean region is noticed. These changes significantly impact the SARAL applications. Two important applications of wave forecast and eddy detection are discussed here as examples. Following this, we also recommend using provided quality flags so that the data can be further explored for various ocean applications. [ABSTRACT FROM AUTHOR]

The purpose of the study is to demonstrate the role of artificial intelligence in the ability to accelerate global efforts to protect the environment and conserve natural resources by monitoring air pollution and energy emissions. Monitoring attacks on forest areas, as well as describing the role of the constitutions of the world's countries, including the Jordanian Constitution, by adding constitutional texts addressing environmental protection using artificial intelligence technologies. The importance of this research lies in demonstrating international and constitutional efforts to protect the environment using artificial intelligence technologies by accelerating global and local efforts to protect the environment, conserve natural resources, and use digital tools to monitor air pollution and energy emissions. And monitoring attacks on forest areas, as well as describing the role of countries' constitutions, including the Jordanian Constitution, by adding constitutional texts addressing environmental protection using artificial intelligence technologies. [ABSTRACT FROM AUTHOR]

Precise mapping and continuous monitoring of fine-scale surface albedo are indispensable for assessing and optimizing renewable energy sources. Understanding the variations in surface reflectivity is crucial in capturing the full potential of renewable technologies, as it directly impacts the efficiency of harnessing solar energy for sustainable power generation. Satellite remote sensing stands out as the sole practical approach for estimating surface albedo at both regional and global scales. Although there are different methods to calculate albedo from satellite data, most satellite products result in low spatial resolution for large heterogeneous areas, such as urban and peri-urban areas. This paper evaluates and compares several methodologies to calculate surface albedo from Landsat 8 imagery. As a result, a new methodology for estimating surface albedo for heterogeneous areas has been proposed. The new methodology has been compared with direct and indirect albedo measurements, improving the original methodologies of Baldinelli and Silva with respect to the Arctic-Boreal Vulnerability Experiment (ABOVE) albedo images by reducing the RMSE by 85% and 52%, respectively. [ABSTRACT FROM AUTHOR]