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Thematische Bibliographien / Satellite Intelligence / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Satellite Intelligence“

Autor: Grafiati

Veröffentlicht am 7. Juni 2025

Zuletzt aktualisiert am 2. August 2025

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1

Huseynov, Mugabil, and Elshan Hashimov. "Imaginary Intelligence Via Satellites." Modeling Control and Information Technologies, no. 6 (November 22, 2023): 57–60. http://dx.doi.org/10.31713/mcit.2023.014.

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This article gives basic information about all types of satellites. The types of satellites reveal the functions, purposes and applications. Information is provided on the sections required to use a satellite. The features of reconnaissance satellites are characterized. Analytical factors of satellite imagery, their pros and cons were compared. The role and functions of satellite imagery in current and probable future wars are declared.

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Haloho, Luwis Suryani, and Asep Adang Supriyadi. "Utilization of satellite technology in communication systems, disaster monitoring, border surveillance, and military intelligence: a literature review." Remote Sensing Technology in Defense and Environment 1, no. 1 (2024): 36–44. http://dx.doi.org/10.61511/rstde.v1i1.2024.842.

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Background: The utilization of satellite technology has become a critical aspect in many fields, including communications, disaster monitoring, border surveillance, and military intelligence. The ability of satellites to provide real-time, high-resolution data offers significant benefits in supporting these activities. This study aims to explore the contributions and benefits of satellites in this context through a literature review approach. Methods: This study used the literature review method, which involves collecting, analyzing, and synthesizing relevant scientific studies. The literature

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Kim, Dongwoo, and Taejin Chung. "Design of an Elliptical Orbit for High-Resolution Optical Observation at a Very Low Altitude over the Korean Peninsula." Journal of Astronomy and Space Sciences 40, no. 1 (2023): 35–44. http://dx.doi.org/10.5140/jass.2023.40.1.35.

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Surveillance and reconnaissance intelligence in the space domain will become increasingly important in future battlefield environments. Moreover, to assimilate the military provocations and trends of hostile countries, imagery intelligence of the highest possible resolution is required. There are many methods for improving the resolution of optical satellites when observing the ground, such as designing satellite optical systems with a larger diameter and lowering the operating altitude. In this paper, we propose a method for improving ground observation resolution by using an optical system f

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Chandru, P. A., Arianne Gutierrez, Cynthia Valenzuela, Poorvi Shetty, and Shristy Kumar. "Review on Semi-Autonomous Robots for Satellite Maintenance and Refueling." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 11 (2024): 1–8. http://dx.doi.org/10.55041/ijsrem38888.

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As the number of satellites in Earth's orbit continues to grow, the need for efficient satellite servicing solutions becomes increasingly pressing. Currently, about 9,900 satellites are in orbit, with over 3,300 of these being inactive, posing a threat as space debris. Traditional methods for satellite maintenance and refueling are complex, expensive, and risky. The development of semi-autonomous robots, powered by advancements in artificial intelligence and robotics, presents a more efficient alternative. These robots can perform complex maintenance and refueling tasks with minimal human inte

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Wang, Shuai, Ruoke Wu, Yizhi Jiang, et al. "A Graph Convolutional Network Framework for Area Attention and Tracking Compensation of In-Orbit Satellite." Applied Sciences 15, no. 12 (2025): 6742. https://doi.org/10.3390/app15126742.

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In order to solve the problems of low tracking accuracy of in-orbit satellites by ground stations and slow processing speed of satellite target tracking images, this paper proposes an orbital satellite regional tracking and prediction model based on graph convolutional networks (GCNs). By performing superpixel segmentation on the satellite tracking image information, we constructed an intra-frame superpixel seed graph node network, enabling the conversion of spatial optical image information into artificial-intelligence-based graph feature data. On this basis, we propose and build an in-orbit

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Verma, Dr Charu Vaibhav. "BHOO-MI – BHOONIDHI META INTELLIGENCE." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 06 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem35917.

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Presently satellite data products are supplied to the users in various formats and with required meta data associated to it. In general, this Meta data contains the latitude/longitude information of the area covered. The utilization of satellite imagery in diverse fields necessities efficient methods to add value to the core images. In this research work, we designed a comprehensive methodology to design a system which provides the intelligence to the basic data product by adding various geographic features over that area. Both natural and manmade geographic features were considered in study.

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Zhang, Pengfei. "Research on satellite selection algorithm in ship positioning based on both geometry and geometric dilution of precision contribution." International Journal of Advanced Robotic Systems 16, no. 1 (2019): 172988141983024. http://dx.doi.org/10.1177/1729881419830246.

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With the networking of four Global Navigation Satellite Systems, the combination of multi-constellation applications has become an inevitable trend, and there will be more and more visible satellites that can be participated in ship positioning. However, the computational complexity increases sharply, which greatly improves the load capacity of the receiver’s data processor and reduces the output frequency of the positioning result. To achieve the balance between positioning accuracy and computational complexity, a new fast satellite selection algorithm based on both of geometry and geometric

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Makare, Isha Nitin. "Bhoonidhi: Transforming Satellite Data into Smart Intelligence." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 5229–31. https://doi.org/10.22214/ijraset.2025.71457.

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The rapid development of satellite imaging technology has reshaped a variety of fields, including urban planning and disaster management. Despite the availability of high-resolution imagery, traditional satellite datasets primarily offer basic geographic coordinates, failing to provide meaningful insights into the geographic context. It is difficult for planners, researchers, and decision-makers to extract actionable intelligence from raw imagery due to this gap. The Bhoonidhi MetaIntelligence system was created to add enriched metadata to satellite data. By integrating natural and manmade geo

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Thosar, Rutuja S. "REVIEW ON SATELLITE COMMUNICATION." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem33919.

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Satellite communication, an unprecedented invention, has completely altered global connectivity, serving as a backbone various sectors, such as like telecommunication, broadcasting, navigation, and remote sensing. The abstract will delineate the intriguing history of satellite communications and satellite orbits. Additionally, the abstract provides, when using artificial intelligence, it can potentially offer opportunities for enhanced performances, efficiency, and adaptability. In this review paper, we have discussing the numerous challenges facing satellite communication. The complexities su

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Chen, Hao, Shu Yang, Jun Li, and Ning Jing. "Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation." Mathematical Problems in Engineering 2018 (August 6, 2018): 1–23. http://dx.doi.org/10.1155/2018/2103625.

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With the development of aerospace science and technology, Earth Observation Satellite cluster which consists of heterogeneous satellites with many kinds of payloads appears gradually. Compared with the traditional satellite systems, satellite cluster has some particular characteristics, such as large-scale, heterogeneous satellite platforms, various payloads, and the capacity of performing all the observation tasks. How to select a subset from satellite cluster to perform all observation tasks effectively with low cost is a new challenge arousing in the field of aerospace resource scheduling.

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Kim, Doyi, and Yeji Choi. "Utilization of satellite imagery and artificial intelligence for disaster management: Approaches and case studies." ITU Journal on Future and Evolving Technologies 6, no. 1 (2025): 47–56. https://doi.org/10.52953/qofv8553.

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The advent of advanced satellite observations and the rapid evolution of Artificial Intelligence (AI) technologies have led to a fundamental shift in disaster management. These technologies enhance precise prediction, closer monitoring, and more efficient and effective responses to natural disasters. This study introduces AI-based satellite image analysis solutions throughout the disaster management cycle: prevention, preparedness, response, and recovery. Satellite imagery, captured through various channels, resolutions, and orbits, plays a crucial role throughout the entire disaster managemen

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Secrieru, Nicolae, Viorel Carbune, Tudor Zadorojneac, et al. "ARCHITECTURE OF THE SPACE RADIATION SENSOR SATELLITE MODULE BASED ON ARTIFICIAL INTELLIGENCE." JOURNAL OF ENGINEERING SCIENCE 31, no. 4 (2025): 73–83. https://doi.org/10.52326/jes.utm.2024.31(4).05.

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This paper is dedicated to the study of the cosmic radiation and its effects on electronics, as well as methods to measure it in order to aid the elaboration of the architecture of the satellite module with space radiation sensors for classification and real-time analysis of cosmic radiation-induced fault patterns and state predictions the of electronic systems embedded in satellites. The architecture of the satellite module with an intelligent radiation sensor based on an FPGA device is proposed, which will include as radiation sensing elements arrays of various types of electronic memories (

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Secrieru, Nicolae, Viorel Carbune, Tudor Zadorojneac, et al. "Architecture of the space radiation sensor satellite module based on artificial intelligence." Journal of Engineering Science 31, no. 4 (2024): 73–83. https://doi.org/10.52326/jes.utm.2024.31(4).05.

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This paper is dedicated to the study of the cosmic radiation and its effects on electronics, as well as methods to measure it in order to aid the elaboration of the architecture of the satellite module with space radiation sensors for classification and realtime analysis of cosmic radiation-induced fault patterns and state predictions the of electronic systems embedded in satellites. The architecture of the satellite module with an intelligent radiation sensor based on an FPGA device is proposed, which will include as radiation sensing elements arrays of various types of electronic memories (o

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Bogireddy, Gari Sairekha. "An improved technique for enhancement of satellite image." i-manager’s Journal on Image Processing 11, no. 2 (2024): 10. http://dx.doi.org/10.26634/jip.11.2.20816.

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In the age of artificial intelligence, remote sensing and especially satellite imagery are gaining widespread interest among the computer science community in their efforts to enable machines to recognize their environment through satellite image classification. Imaging satellites provide images of Earth that are collected, analyzed, and processed for both civil and military purposes. Satellite images are an important source of data, captured by artificial satellites orbiting the Earth. These images are susceptible to noise and irregular illumination, which can affect their quality. This paper

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Dawid Jurczyński and Paweł Buchwald. "Mechanisms for Data Acquisition to Train Artificial Intelligence Models for Detecting Increased Susceptibility to Fire Situations by Using Internet of Things Devices and Satellite Systems." SAFETY & FIRE TECHNOLOGY 63, no. 1 (2024): 34–43. http://dx.doi.org/10.12845/sft.63.1.2024.3.

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Aim: Exploration and developing mechanisms of advanced data acquisition necessary for training an artificial intelligence model capable of effectively detecting areas with increased susceptibility to fire situations. The study focuses on utilizing data from satellite missions and ground-based sensors, which provide both high-resolution imagery and precise data on temperature, humidity, and other environmental factors. By analysing these diverse data sources, the research aims to create a comprehensive and efficient model capable of early detection of potential fire hazards, which is crucial fo

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Zhang, Ke, Tong Yang, Yi Duan, Huansheng Liu, and Yang Zhang. "Intelligent detection and recovery on satellite telemetry loss." Journal of Physics: Conference Series 2990, no. 1 (2025): 012011. https://doi.org/10.1088/1742-6596/2990/1/012011.

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Abstract The article takes the high-orbit satellite telemetry system as an example. Firstly, the general system architecture of the satellite telemetry system is summarized. Then, starting from the system design characteristics, the recovery strategy analysis method for satellite in orbit telemetry loss faults is studied. We have established a tree decomposition diagram of telemetry loss fault reason classification and countermeasures, consisting of a three-layer model of fault reason classification, fault root localization, and response and recovery strategy. At the level of fault root locali

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Hafner, Janez. "Satellite image classification with artificial intelligence methods." Geologija 41 (December 30, 1998): 435–75. http://dx.doi.org/10.5474/geologija.1998.021.

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Fourati, Fares, and Mohamed-Slim Alouini. "Artificial intelligence for satellite communication: A review." Intelligent and Converged Networks 2, no. 3 (2021): 213–43. http://dx.doi.org/10.23919/icn.2021.0015.

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Thangavel, Kathiravan, Roberto Sabatini, Alessandro Gardi, et al. "Artificial Intelligence for Trusted Autonomous Satellite Operations." Progress in Aerospace Sciences 144 (January 2024): 100960. http://dx.doi.org/10.1016/j.paerosci.2023.100960.

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Patel, Prof Abhishek, Prof Saurabh Verma, Prof Pankaj Pali, Harsh Tiwari, and Sagar Kanojiya. "Application of Artificial Intelligence (AI) to Enhance Satellite Security." International Journal of Innovative Research in Computer and Communication Engineering 12, no. 04 (2023): 3237–40. http://dx.doi.org/10.15680/ijircce.2023.1104284.

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The security of satellite systems is paramount for maintaining the integrity and reliability of critical infrastructure and national defense. This paper explores the application of artificial intelligence (AI) to enhance satellite security. AI technologies can significantly improve anomaly detection, cyber security, signal jamming mitigation, space situational awareness, predictive maintenance, secure communication, and autonomous satellite operations. By leveraging machine learning algorithms, AI can detect and respond to cyber threats in real-time, differentiate between benign and malicious

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Liu, Jitong. "Overview of Low Earth Orbit Satellite Communication Systems." Applied and Computational Engineering 145, no. 1 (2025): 1–6. https://doi.org/10.54254/2755-2721/2025.21920.

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Low Earth Orbit (LEO) satellite communication systems have emerged as a critical solution to address the growing demand for global, seamless, and low-latency connectivity. Compared with Geosynchronous Earth Orbit (GEO) satellites, LEO satellites enable reduced signal delays and broad coverage. Therefore, they are particularly suitable for remote and underserved regions. This paper provides a comprehensive review of LEO satellite communication systems, focusing on three major aspects: frequency band division, system architecture, and case analysis. The study explores the utilization of various

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Al-Zubaidi, Ehsan Ali, and Riyad Al Khafaji. "Unsupervised Classification of Landsat-8 Satellite Imagery-Based on ISO Clustering." Wasit Journal of Computer and Mathematics Science 3, no. 1 (2024): 40–53. http://dx.doi.org/10.31185/wjcms.212.

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Remote sensing, specifically satellite imagery, is gaining prominence in computer science nowadays, in the era of artificial intelligence, in an attempt to deliver more precise information. The satellite images of Earth are gathered, evaluated, and processed for use in civil and military applications with a military aim. Satellite images do have a wide range of services. The areas of study of agriculture, fishery, oceanography, and meteorology include geology, biodiversity, cartography, land use planning, and armed conflict. Transformation is the goal of the categorization of satellite images.

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Alluhaybi, Abdulaziz, Panos Psimoulis, and Rasa Remenyte-Prescott. "An Evaluation of Optimization Algorithms for the Optimal Selection of GNSS Satellite Subsets." Remote Sensing 16, no. 10 (2024): 1794. http://dx.doi.org/10.3390/rs16101794.

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Continuous advancements in GNSS systems have led, apart from the broadly used GPS, to the development of other satellite systems (Galileo, BeiDou, GLONASS), which have significantly increased the number of available satellites for GNSS positioning applications. However, despite GNSS satellites’ redundancy, a potential poor GNSS satellite signal (i.e., low signal-to-noise ratio) can negatively affect the GNSS’s performance and positioning accuracy. On the other hand, selecting high-quality GNSS satellite signals by retaining a sufficient number of GNSS satellites can enhance the GNSS’s position

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Enyinaya Stefano Okafor, Olatunji Akinrinola, Favour Oluwadamilare Usman, Olukunle Oladipupo Amoo, and Nneka Adaobi Ochuba. "CYBERSECURITY ANALYTICS IN PROTECTING SATELLITE TELECOMMUNICATIONS NETWORKS: A CONCEPTUAL DEVELOPMENT OF CURRENT TRENDS, CHALLENGES, AND STRATEGIC RESPONSES." International Journal of Applied Research in Social Sciences 6, no. 3 (2024): 254–66. http://dx.doi.org/10.51594/ijarss.v6i3.854.

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Cybersecurity is a critical concern in satellite telecommunications networks, given their vulnerability to cyber threats. This abstract presents a conceptual development of current trends, challenges, and strategic responses in using cybersecurity analytics to protect these networks. The paper discusses the increasing reliance on satellite telecommunications, making them attractive targets for cyber attacks. It explores the role of cybersecurity analytics in detecting and mitigating these threats, highlighting the importance of proactive monitoring and threat intelligence. Challenges in cybers

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Iqtiar, Md Siddique. "Digital Satellite Technology: Innovations and Applications in the Modern Era." European Journal of Advances in Engineering and Technology 11, no. 6 (2024): 39–46. https://doi.org/10.5281/zenodo.12748154.

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Digital satellite technology has undergone profound evolution, transitioning from analog to advanced digital systems that revolutionize communication, broadcasting, and remote sensing applications. Innovations in signal processing, modulation techniques, and encoding standards have significantly boosted data transmission rates, signal quality, and reliability in satellite communications. This evolution has facilitated the integration of multimedia services like high-definition television (HDTV), internet access, and mobile broadcasting, expanding the scope and efficiency of satellite-based net

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Alhassan, Ahmad, Okoro Ernest chidi, Mohammed Auwal Adamu, et al. "THE SUCCESS OF SATELLITE GRAVIMETRY IN GEOPHYSICAL INVESTIGATIONS." Geological Behavior 8, no. 1 (2024): 23–26. https://doi.org/10.26480/gbr.01.2024.23.26.

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Terrestrial measurements of gravity data are limited to only accessible areas. Areas that are not easily accessible due to lack of access route, security, cost etc. are found unfavorable for terrestrial measurements. These among others lead to the development of satellites to fill those gaps. Satellites have been used for data acquisition for years and have recorded a great success in numerous ways. This paper presents the principle of operation of such satellites. The successful geophysical researches carried out using satellite acquired gravity data from existing literature were also discuss

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Nicholas, Jaeger. "THE MILITARIZATION OF SPACE: STARLINK AND THE FUTURE OF WARFARE." INTERNATIONAL EDUCATION AND RESEARCH JOURNAL - IERJ 11, no. 1 (2025): 158–60. https://doi.org/10.5281/zenodo.15599799.

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The advent of satellite technology, particularly through private enterprises like Starlink, has transformed modern warfare, redefining military strategies and capabilities. This paper explores Starlink's pivotal role in the Russo-Ukrainian war, analyzing the strategic advantages and ethical challenges of increasing space militarization. It traces the evolution of satellite usage in warfare, from reconnaissance missions in the 1950s to their indispensable contributions in contemporary conflicts. Starlink's decentralized network provided Ukrainian forces with critical communication and intellige

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Iqtiar, Md Siddique. "Emerging Trends in Small Satellite Technology: Challenges and Opportunities." European Journal of Advances in Engineering and Technology 11, no. 2 (2024): 42–48. https://doi.org/10.5281/zenodo.12748476.

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The rapid advancement of small satellite technology has sparked significant interest in recent years, revolutionizing space exploration and Earth observation capabilities. This abstract explores the current trends, challenges, and opportunities in the field of small satellites. Key topics include the miniaturization of components, advances in propulsion and communication systems, and the integration of artificial intelligence for autonomous operations. Challenges such as limited payload capacity and orbital debris management are also discussed. Opportunities lie in leveraging small satellites

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Zhao, Xiaopeng, Shen Wang, Zhenlin An, and Lei Yang. "Crowdsourced Geospatial Intelligence: Constructing 3D Urban Maps with Satellitic Radiance Fields." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 8, no. 3 (2024): 1–24. http://dx.doi.org/10.1145/3678572.

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In urban planning and research, 3D city maps are crucial for activities such as cellular network design, urban development, and climate research. Traditionally, creating these models has involved costly techniques like manual 3D mapping, interpretation of satellite or aerial images, or the use of sophisticated depth-sensing equipment. In this work, we propose a novel approach to develop 3D urban maps by examining the influence of urban structures on satellite signals, using GPS records crowdsourced from hundreds of smartphones during everyday user movements. We introduce the concept of satelli

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Fan, Huilong, Zhan Yang, Shimin Wu, Xi Zhang, Jun Long, and Limin Liu. "An Efficient Satellite Resource Cooperative Scheduling Method on Spatial Information Networks." Mathematics 9, no. 24 (2021): 3293. http://dx.doi.org/10.3390/math9243293.

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To overcome the low timeliness of resource scheduling problems in spatial information networks, we propose a method based on a dynamic reconstruction of resource request queues and the autonomous coordinated scheduling of resources. First, we construct a small satellite network and combine the graph maximum flow theory to solve the link resource planning problem during inter-satellite data transmission. In addition, we design a multi-satellite resource scheduling algorithm with minimal time consumption based on graph theory. The algorithm is based on graph theory to reallocate the resource req

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Melnic, Vladimir. "ATTITUDE CONTROL OF THE NANOSATELLITE USING A HYBRID FUZZY ALGORITHM BY MEANS OF THE REACTION WHEELS." Journal of Engineering Science 30, no. 2 (2023): 104–16. http://dx.doi.org/10.52326/jes.utm.2023.30(2).09.

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Numerous application fields of automation the industrial processes have demonstrated favorable outcomes with modern control algorithms that rely on artificial intelligence. Therefore, some researchers have endeavored to implement these algorithms in the attitude control of satellites by evaluating their performance in simulated scenarios. However, due to the associated cost and risks, there is a scarcity of experimental data available for testing new attitude control algorithms on a real satellite. To address this issue, simulation of satellite positioning based on the dynamic model of the sat

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Sun, Yaohua, and Mugen Peng. "Edge intelligence assisted resource management for satellite communication." China Communications 19, no. 8 (2022): 31–40. http://dx.doi.org/10.23919/jcc.2022.08.003.

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Chib, Sunita, and M. Syamala Devi. "CLASSIFICATION OF COLOR SATELLITE IMAGES USING COMPUTATIONAL INTELLIGENCE." ICTACT Journal on Image and Video Processing 12, no. 1 (2021): 2525–30. http://dx.doi.org/10.21917/ijivp.2021.0358.

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The classification of color satellite images is presented using Multilayer Perceptron Neural Network and Support Vector Machine. Multilayer Perceptron is used for non-linear classification with 10 hidden layers using different number of epochs. A multiclass SVM is chosen for classification using radial basis function (RBF) kernel. Before performing classification, the image enhancement and feature extraction steps are carried out. The image enhancement is done using contrast stretching. The color features are extracted by using Principal Components Analysis (PCA). Classification results are ob

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Ma, Zhong, Yuejiao Wang, Yidai Yang, Zhuping Wang, Lei Tang, and Stephen Ackland. "Reinforcement Learning-Based Satellite Attitude Stabilization Method for Non-Cooperative Target Capturing." Sensors 18, no. 12 (2018): 4331. http://dx.doi.org/10.3390/s18124331.

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When a satellite performs complex tasks such as discarding a payload or capturing a non-cooperative target, it will encounter sudden changes in the attitude and mass parameters, causing unstable flying and rolling of the satellite. In such circumstances, the change of the movement and mass characteristics are unpredictable. Thus, the traditional attitude control methods are unable to stabilize the satellite since they are dependent on the mass parameters of the controlled object. In this paper, we proposed a reinforcement learning method to re-stabilize the attitude of a satellite under such c

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He, Yongming, Lei He, Yuan Wang, Yu Xiao, Yingwu Chen, and Lining Xing. "Autonomous Mission Replanning Method for Imaging Satellites Considering Real-Time Weather Conditions." Journal of Computational and Theoretical Nanoscience 13, no. 10 (2016): 6967–73. http://dx.doi.org/10.1166/jctn.2016.5654.

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During the observations made by imaging satellites, meteorological factors are likely to change frequently. The vagaries of weather conditions and significant effects on the actual observation results mean that there is an urgent need to apply more intelligence to satellite mission planning. Thus, this paper describes an autonomous replanning method for imaging satellites that considers the real-time weather conditions. Considering the characteristics of different input data, this method replans the low-yield task set and fine-tunes others to improve profitability. Moreover, the proposed metho

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Olukunle Kolawole, Soyinka, and Duan Haibin. "Satellite formation keeping via chaotic artificial bee colony." Aircraft Engineering and Aerospace Technology 89, no. 2 (2017): 246–56. http://dx.doi.org/10.1108/aeat-02-2014-0019.

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Purpose Keeping satellite position within close tolerances is key for the utilization of satellite formations for space missions. The presence of perturbation forces makes control inevitable if such mission objective is to be realised. Various approaches have been used to obtain feedback controller parameters for satellites in a formation; this paper aims to approach the problem of estimating the optimal feedback parameter for a leader–follower pair of satellites in a small eccentric orbit using nature-based search algorithms. Design/methodology/approach The chaotic artificial bee colony algor

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B Kamala Deepthi, Boya Sravani, Meedinti Pavithra, Yashaswini C, and Dr. K. Pavan Kumar. "Artificial Intelligence Techniques for Landslides Prediction Using Satellite Imagery." International Journal of Scientific Research in Science, Engineering and Technology 12, no. 3 (2025): 43–48. https://doi.org/10.32628/ijsrset2512311.

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Landslides in hilly areas can be triggered by natural factors like heavy rainfall and earthquakes, or by human activities such as unplanned construction. These events often result in significant loss of life and property. Machine learning (ML) and deep learning (DL) algorithms have been increasingly used for automatic landslide detection from satellite images. While there has been progress in semiautomatic detection, fully automatic systems with high accuracy are still limited. One of the biggest challenges is the lack of appropriate training datasets. This study reviews various ML and DL tech

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Chen, Junfu, Xiaodong Zhao, and Dechang Pi. "A deep auto-encoder satellite anomaly advance warning framework." Aircraft Engineering and Aerospace Technology 93, no. 6 (2021): 1085–96. http://dx.doi.org/10.1108/aeat-09-2019-0185.

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Purpose The purpose of this paper is to ensure the stable operation of satellites in orbit and to assist ground personnel in continuously monitoring the satellite telemetry data and finding anomalies in advance, which can improve the reliability of satellite operation and prevent catastrophic losses. Design/methodology/approach This paper proposes a deep auto-encoder (DAE) satellite anomaly advance warning framework for satellite telemetry data. Firstly, this study performs grey correlation analysis, extracts important feature attributes to construct feature vectors and builds the variational

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de la Cruz, R. M., N. T. Olfindo Jr., M. M. Felicen, N. J. B. Borlongan, J. K. L. Difuntorum, and J. J. S. Marciano Jr. "NEAR-REALTIME FLOOD DETECTION FROM MULTI-TEMPORAL SENTINEL RADAR IMAGES USING ARTIFICIAL INTELLIGENCE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 22, 2020): 1663–70. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-1663-2020.

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Abstract. Flood extent delineation from RADAR images usually entails manual thresholding per scene, which is not feasible when tackling large-scale floods that often covers multiple RADAR scenes. It is also computationally intensive when processed through traditional remote sensing techniques that limit its use during emergency situations. To hasten the production of flood maps from RADAR images during flooding incidents, a deep learning model using Fully connected Convolutional Neural Network (FCNN) has been developed to delineate flooded areas with minimal human intervention. The model was f

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Khan, Christin B., Kimberly T. Goetz, Hannah C. Cubaynes, et al. "A Biologist’s Guide to the Galaxy: Leveraging Artificial Intelligence and Very High-Resolution Satellite Imagery to Monitor Marine Mammals from Space." Journal of Marine Science and Engineering 11, no. 3 (2023): 595. http://dx.doi.org/10.3390/jmse11030595.

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Monitoring marine mammals is of broad interest to governments and individuals around the globe. Very high-resolution (VHR) satellites hold the promise of reaching remote and challenging locations to fill gaps in our knowledge of marine mammal distribution. The time has come to create an operational platform that leverages the increased resolution of satellite imagery, proof-of-concept research, advances in cloud computing, and machine learning to monitor the world’s oceans. The Geospatial Artificial Intelligence for Animals (GAIA) initiative was formed to address this challenge with collaborat

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Jia, Cheng. "The Function of Software in Satellite System and Its Reliability Analysis." Journal of Computing and Electronic Information Management 12, no. 2 (2024): 30–33. http://dx.doi.org/10.54097/uwq2ms7i.

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This paper aims to discuss the function of software in satellite system and the reliability analysis of satellite software. Firstly, the overview of satellite system and the importance of software in it are introduced. Then, the concept of reliability, reliability evaluation method and factors affecting reliability of satellite software are expounded in detail. Then, the strategy to improve the reliability of satellite software is discussed. Finally, the article looks forward to the future development trend of satellite software reliability, including the application of artificial intelligence

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Chen, Zijing, and Yuanyuan Zeng. "A Swarm Intelligence Networking Framework for Small Satellite Systems." Communications and Network 05, no. 03 (2013): 171–75. http://dx.doi.org/10.4236/cn.2013.53b2033.

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董, 坤. "Key Technologies of Threat Intelligence for Satellite Communication Network." Software Engineering and Applications 09, no. 05 (2020): 403–11. http://dx.doi.org/10.12677/sea.2020.95046.

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Golej, Peter, Pavel Kukuliač, Jiří Horák, Lucie Orlíková, and Pavol Partila. "People Detection Using Artificial Intelligence with Panchromatic Satellite Images." Applied Sciences 14, no. 18 (2024): 8555. http://dx.doi.org/10.3390/app14188555.

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The detection of people in urban environments from satellite imagery can be employed in a variety of applications, such as urban planning, business management, crisis management, military operations, and security. A WorldView-3 satellite image of Prague was processed. Several variants of feature-extracting networks, referred to as backbone networks, were tested alongside the Faster R–CNN model. This model combines region proposal networks with object detection, offering a balance between speed and accuracy that is well suited for dense and varied urban environments. Data augmentation was used

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Lindley, Craig A. "Autonomous satellite architecture integrating deliberative reasoning and behavioural intelligence." Telematics and Informatics 10, no. 3 (1993): 231–50. http://dx.doi.org/10.1016/0736-5853(93)90028-3.

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Sloan, Sean, Raiyan R. Talkhani, Tao Huang, Jayden Engert, and William F. Laurance. "Mapping Remote Roads Using Artificial Intelligence and Satellite Imagery." Remote Sensing 16, no. 5 (2024): 839. http://dx.doi.org/10.3390/rs16050839.

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Road building has long been under-mapped globally, arguably more than any other human activity threatening environmental integrity. Millions of kilometers of unmapped roads have challenged environmental governance and conservation in remote frontiers. Prior attempts to map roads at large scales have proven inefficient, incomplete, and unamenable to continuous road monitoring. Recent developments in automated road detection using artificial intelligence have been promising but have neglected the relatively irregular, sparse, rustic roadways characteristic of remote semi-natural areas. In respon

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Khalid, Uman, Usama Inam Paracha, Zeerak Naveed, Trung Q. Duong, Moe Z. Win, and Hyundong Shin. "Quantum Fusion Intelligence for Integrated Satellite-Ground Remote Sensing." IEEE Wireless Communications 32, no. 3 (2025): 46–55. https://doi.org/10.1109/mwc.001.2400425.

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G, Chitra, Ramya Sree D, Amaresh K, Sandeep Reddy C, and Jyoshna M. "Satellite Imagery Analysis For Landslides Prediction Via Artificial Intelligence." International Journal of Computational Learning & Intelligence 4, no. 3 (2025): 484–93. https://doi.org/10.5281/zenodo.15209917.

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Landslides in mountainous and hilly terrains arise due to both natural phenomena and human activities. Natural triggers such as excessive rainfall, seismic shifts, and soil moisture fluctuations play a major role, while human-induced factors like uncontrolled infrastructure development further amplify the risks. These occurrences lead to significant destruction of both human life and property, emphasizing the necessity of early detection to mitigate their impact. In recent years, machine learning methods have gained prominence in automating landslide identification. Various techniques, includi

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Xu, Zhengqian, Peiying Zhang, Chengcheng Li, Hailong Zhu, Guanjun Xu, and Chenhua Sun. "A Collaborative Inference Algorithm in Low-Earth-Orbit Satellite Network for Unmanned Aerial Vehicle." Drones 7, no. 9 (2023): 575. http://dx.doi.org/10.3390/drones7090575.

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In recent years, the low-Earth-orbit (LEO) satellite network has achieved considerable development. Moreover, it is necessary to introduce edge computing into LEO networks, which can provide high-quality services, such as worldwide seamless low-delay computation offloading for unmanned aerial vehicles (UAVs) or user terminals and nearby remote-sensing data processing for UAVs or satellites. However, because the computation resource of the satellite is relatively scarce compared to the ground server, it is hard for a single satellite to complete massive deep neural network (DNN) inference tasks

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Siddique, Iqtiar Md. "Detection and Analysis of Anomalous Behavior in On-Orbit Satellites Using AI Algorithms." Journal of Firewall Software‎ and Networking 2, no. 2 (2024): 6–17. http://dx.doi.org/10.48001/jofsn.2024.226-17.

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The increasing deployment of satellites for essential applications necessitates robust anomaly detection to maintain their operational integrity. Traditional methods, which depend on manual monitoring and predefined thresholds, often prove inadequate in the complex space environment. This paper investigates the application of Artificial Intelligence (AI) algorithms to improve the detection and analysis of anomalous behavior in on-orbit satellites. AI, especially through machine learning (ML) and deep learning (DL), provides advanced capabilities for processing extensive telemetry data and iden

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