Ground Segment Research Articles

Ground Control System for UAS Safe Landing Area Determination (SLAD) in Urban Air Mobility Operations.

The use of the Unmanned Aerial Vehicles (UAV) and Unmanned Aircraft System (UAS) for civil, scientific, and military operations, is constantly increasing, particularly in environments very dangerous or impossible for human actions. Many tasks are currently carried out in metropolitan areas, such as urban traffic monitoring, pollution and land monitoring, security surveillance, delivery of small packages, etc. Estimation of features around the flight path and surveillance of crowded areas, where there is a high number of vehicles and/or obstacles, are of extreme importance for typical UAS missions. Ensuring safety and efficiency during air traffic operations in a metropolitan area is one of the conditions for Urban Air Mobility (UAM) operations. This paper focuses on the development of a ground control system capable of monitoring crowded areas or impervious sites, identifying the UAV position and a safety area for vertical landing or take-off maneuvers (VTOL), ensuring a high level of accuracy and robustness, even without using GNSS-derived navigation information, and with on-board terrain hazard detection and avoidance (DAA) capabilities, in particular during operations conducted in BVLOS (Beyond Visual Line Of Sight). The system is composed by a mechanically rotating real-time LiDAR (Light Detection and Ranging) sensor, linked to a Raspberry Pi 3 as SBC (Session Board Controller), and interfaced to a GCS (Ground Control Station) by wireless connection for data management and 3-D information transfer.

Copernicus Sentinel–1 POD reprocessing campaign

Copernicus Sentinel–1 is a C-Band Synthetic Aperture Radar (SAR) satellite mission within the European Copernicus Programme. The two satellites Sentinel-1A and -1B were launched in April 2014 and 2016, respectively. The Copernicus POD (Precise Orbit Determination) Service is responsible for the determination of orbital and auxiliary products required by the Payload Data Ground Segment (PDGS). Precise orbits are determined based on the dual-frequency GPS (Global Positioning System) data delivered by dedicated geodetic-grade GPS receivers on-board the satellites. Several updates in the operational orbit determination were done during the years including an update of the GPS antenna reference point coordinates. The switch to GPS carrier phase ambiguity-fixing was a major improvement. A reprocessing of the entire mission span of both satellites became necessary to provide a consistent orbit time series for the mission based on state-of-the-art models and processing settings. Due to the lack of independent observation techniques, the Sentinel-1 orbit quality has been assessed by analysing processing metrics, orbit overlaps and orbit comparisons. For this purpose, members of the Copernicus POD Quality Working Group (QWG) provided reprocessed Sentinel-1 orbit time series based on their software packages and their orbit determination settings. A weighted average of all five delivered solutions - a combined orbit - serves as reference for the comparisons. The quality and reliability of this reference orbit depends among others on the number of available orbit solutions and whether a manoeuvre has been performed during the processed day or not. The mean orbit consistency between all orbit solutions is below 1 cm in 3D RMS for the entire mission time interval for both satellites. Only few days show inferior quality due to data gaps or orbit manoeuvres. Following this sophisticated validation process, the reprocessed Sentinel-1 orbits from the Copernicus POD Service have been made available to the user community.

PPTM: A Privacy-Preserving Trust Management Scheme for Emergency Message Dissemination in Space–Air–Ground-Integrated Vehicular Networks

Vehicular networks have tremendous potential to improve the road safety and traffic efficiency, and the adoption of the space–air–ground-integrated network (SAGIN) architecture in vehicular networks can greatly improve the performance of vehicular networks by leveraging the respective advantages of the space, air, and ground segments on coverage, flexibility, reliability, and availability, which results in space–air–ground-integrated vehicular networks (SAGIVNs). Trust management is an important tool for constructing trustworthy SAGIVNs, and privacy preservation is also a primary concern in SAGIVNs. They have conflicting requirements and a satisfactory balance between them is urgently required. In this article, we propose a novel privacy-preserving trust management (PPTM) scheme for the emergency message dissemination in SAGIVNs. The proposed scheme can realize precise trust management and strong conditional privacy preservation simultaneously with low communication overhead, and can provide strong applicability, strong robustness, and multiple other attractive features. Furthermore, the exhaustive theoretical analysis and simulation evaluation are detailed. The results reveal that the proposed scheme is significantly superior to the existing schemes in several aspects.

Ground glass opacity detection and segmentation using CT images: an image statistics framework

Lung cancer is one of the most profound causes of cancer-related deaths in the world. Early detection is known to significantly improve the chances of survival. Several detection and diagnostic methods are used for this purpose. CT is one of the most widely used non-invasive medical imaging modalities in this domain. The biggest challenge faced by radiologists in this case is detection and diagnosis of cancerous lung nodules. The growth of ground glass opacity (GGO) lesions is an indication of malignancy. However, GGO is difficult to capture for physicians as it manifests in the form of tiny, faint shadows. This research paper proposes an approach for aiding GGO identification in CT lung images for improved lung cancer prognosis. In the proposed approach, morphological reconstruction is used for segmentation. Once the region of interest (ROI) is extracted, statistical analysis using mean, standard deviation, variance, entropy, skewness, kurtosis, minimum grey scale value, maximum grey scale value and range is performed. The same statistical measures are determined for normal lung and distribution plot is drawn for comparison. It is observed that maximum grey-scale value demonstrates minimum overlap of approximately 7.4%. To reduce this, a joint feature by summing values of feature mean, skewness, and maximum grey-scale value was used. This approach reduced the overlap to approximately 1.32%. Lastly, ANN was used for classification of GGO and non-GGO lung tissue with an achieved accuracy of 99.5%.

Modular zonal fluid sampling and pressure testing technology for production well

To accurately obtain development dynamic data such as zonal pressure and fluid parameters of each oil layer in the late development stage of a high water-cut old oilfield, a modular zonal sampling and testing technology with the characteristics of modularization, full electronic control and rapidity was proposed and developed. Lab testing and on-site testing was carried out. The modular zonal sampling and testing system is composed of 10 functional modules, namely ground control system, downhole power supply module, drainage pump, electronically controlled anchor, electronically controlled packer, electronically controlled sampler, magnetic positioning sub, terminal sub, adapter cable, and quick connector. Indoor tests have confirmed that the performance parameters of each module meet the design requirements. The downhole function modules of the system can withstand pressures up to 35 MPa and temperatures up to 85 °C. The rubber cylinder of the electronically controlled packer can withstand a pressure difference of more than 10 MPa. The electronically controlled anchor has an anchoring force of greater than 6.9 t, and can be forcibly detached in the event of an accident. The discharge pump has a displacement of 0.8 m3/d and a head of 500 m. The electronically controlled sampler can meet the requirement of taking 500 mL of sample in each of the 3 chambers. Field tests in Jilin Oilfield show that the system can realize rapid isolation and self-check of isolation of a certain production interval downhole, as well as layer-by layer pressure build-up test. The drainage pump can be used to discharge the mixed liquid between the upper and lower packers and near the wellbore to obtain real fluid samples of the tested formation interval. The data obtained give us better understanding on the pay zones in old oilfields, and provide important basis for development plan adjustment, reservoir stimulation, and EOR measures.

Fragmentation of street space usage in Chinatown Village Semarang, Indonesia

As a trade center, Semarang Chinatown contributes to developing the economic activities of the city. The expansion of the economic network creates various opportunities through informal activities. This is reflected in the inclusiveness of the local community, using roads as venues of economic activities, especially on Gang Baru Street in Semarang Chinatown. The street connects the neighborhood, accommodates informal activities, and serves as a traditional market. Furthermore, it has been privatized by trading activities from the shophouses and street vendors. The claim trend has commodified the formal use of the street as access infrastructure. Consequently, the differences in formal and informal activities cause the use of road space to be fragmented. Therefore, this study examines the fragmented use of Gang Baru street caused by the segmented informal activity interests. The qualitative method is used for a thorough bottom-up observation of the street’s activities. Various activities are classified based on the street user segmentation by organizational practices and spontaneous community behavior. This categorization is also based on the users’ participatory or antagonistic response to the street’s formal use. The result shows activity diversity portrays a dialectic interest representing the fragmented use of Gang Baru Street.

A resource friendly authentication scheme for space–air–ground–sea integrated Maritime Communication Network

Recently, the demand for a faster , low-latency, and full-coverage Maritime Communication Network (MCN) has gained attention as marine operations have increased substantially. Using modern information network technologies and integrating space, air, ground, and sea network segments, MCN may be able to offer worldwide coverage and diverse Quality-of-Service (QoS) provisioning. These network segments are expected to provide not only traditional communication services, but also processing, caching, sensing, and control capabilities when linked via Sixth Generation (6G) mobile networks. However, this development in infrastructure growth is subjected to new security and privacy concerns due to open links, moving nodes, and diverse collaborative algorithms. In this paper, we propose an improved and resource friendly authentication scheme for the space–air–ground–sea integrated maritime communication network using Elliptic Curve Cryptography (ECC). To validate the security hardness of the proposed scheme, formal security assessment method such as Random Oracle Model (ROM) is used. Finally, comparisons with relevant authentication schemes are provided in terms of computation and communication costs. The findings support the viability of the proposed scheme.

Impact of Meteorological Uncertainties in the Methane Retrieval Ground Segment of the MERLIN Lidar Mission

MERLIN (MEthane Remote sensing LIdar missioN) is a Franco-German space mission designed to provide weighted columns of atmospheric methane through an inversion of the lidar signal using a priori information on the atmospheric state. Uncertainties about the meteorological parameters of the observed scene used in the ground segment contribute to the error budget on the retrieved methane column. With the LIDSIM (LIDar SIMulator) data simulator and the PROLID (PROcessor LIDar) inversion processor developed for MERLIN, we perform an impact experiment using ECMWF (European Centre for Medium Weather Range Forecast) ensemble forecast data. In addition, we estimate the standard deviation of the error in the methane column due to the meteorological uncertainties to be about 0.6 ppb. In addition, we innovate by discussing the impact of interpolations both in time and space, focusing on vertical extrapolations under the topography by using state-of-the-art methods to determine from the scatter between these methods the range in which the actual profile should be. We conclude that, in areas where the topography variations exceed 10 m over 10 km, an additional random error of 0.1 ppb is due to our lack of knowledge of the adjustment of atmospheric profiles to terrain. Finally, we point out that further work needs to be performed on temporal interpolation. Indeed, the 3 h time interpolation of atmospheric tides can create regional biases of up to 2 ppm (which is a major problem for models trying to identify methane sinks and sources).

A segment-based filtering method for mobile laser scanning point cloud

ABSTRACT In most Mobile Laser Scanning (MLS) applications, filtering is a necessary step. In this paper, a segmentation-based filtering method is proposed for MLS point cloud, where a segment rather than an individual point is the basic processing unit. In particular, the MLS point clouds in some blocks are clustered into segments by a surface growing algorithm, and then the object segments are detected and removed. A segment-based filtering method is employed to detect the ground segments. The experiment in this paper uses two MLS point cloud datasets to evaluate the proposed method. Experiments indicate that, compared with the classic progressive TIN (Triangulated Irregular Network) densification algorithm, the proposed method is capable of reducing the omission error, the commission error and total error by 3.62%, 7.87% and 5.54% on average, respectively.

Managing sustainable development in recreational and protected areas. The Dovre case, Norway

With an emphasis on integrating national parks into wider regional and local tourism development processes during the latter two decades, protected areas have gradually become more closely connected to their economic and social environments. This presupposes a dynamic approach that involves participatory planning. However, the preservation of nature and wildlife in protected areas remains a source of conflict among different stakeholders. The aim of this study is to explore how key stakeholders, with their different interests at stake, identify dilemmas, challenges, and opportunities in a national park, and to suggest how the various opinions can be integrated in an adaptive management framework for sustainable development. The main results from qualitative interviews with key stakeholders reveal three components of the adaptive management framework: 1) “Combining a bottom-up/top-down strategy in protected areas”, 2) “Channeling different user segments in protected areas”, and 3) “The dynamics between protected and surrounding areas”. The first component provides opportunities to look at sustainability issues from different perspectives, build alliances on shared values, and improve dialogue and collaboration. The second component may help national park management to maintain conservation values, for example, by using trails and guided tours. The third component may generate more attractive user experiences, guiding tourism suppliers to design and offer more attractive outdoor recreation activities and create attractive environments for economic development.

A New Earth Observation Service Based on Sentinel-1 and Sentinel-2 Time Series for the Monitoring of Redevelopment Sites in Wallonia, Belgium

Urban planning is a challenge, especially when it comes to limiting land take. In former industrial regions such as Wallonia, the presence of a large number of brownfields, here called “redevelopment sites”, opens up new opportunities for sustainable urban planning through their revalorization. The Walloon authorities are currently managing an inventory of more than 2200 sites, which requires a significant amount of time and resources to update. In this context, the Sentinel satellites and the Terrascope platform, the Sentinel Collaborative Ground Segment for Belgium, enabled us to deploy SARSAR, an Earth observation service used for the automated monitoring of redevelopment sites that generates regular and automatic change reports that are directly usable by the Walloon authorities. In this paper, we present the methodological aspects and implementation details of the service, which combines two well-known and robust methods: the Pruned Exact Linear Time method for change point detection and threshold-based classification, which assigns the detected changes to three different classes (vegetation, building and soil). The overall accuracy of the system is in the range of 70–90%, depending on the different methods and classes considered. Some remarks on the advantages and possible drawbacks of this approach are also provided.

The effect of social media on travel planning process by Chinese tourists: the way forward to tourism futures

Purpose This paper investigates the usage and trust of Chinese social media in the travel planning process (pre-trip, during-trip and post-trip) of Chinese tourists.Design/methodology/approach Through a combination of structured online survey (n = 406) and follow-up interviews, the research identifies the diversification of the demand-and-supply patterns of social media users in China, as well as the allocation of functions of social media as tools before, during and after travel.Findings Social media users are diverse in terms of their adoption of social media, use behaviour and scope; the levels of trust and influence; and their ultimate travel decisions and actions. Correlations between the level of trust, influence of social media and the intended changes in travel decisions are observed. Destination marketers and tourism industries should observe and adapt to the needs of social media users and potential tourist markets by understanding more about user segmentation between platforms or apps and conducting marketing campaigns on social media platforms to attract a higher number of visitors.Research limitations/implications This paper demonstrated the case of social media usage in mainland China, which has been regarded as one of the fastest growing and influential tourist-generating markets and social media expansions in the world. This study further addressed the knowledge gap by correlating social media usage and travel planning process of Chinese tourists. The research findings suggested diversification of the demand-and-supply pattern of social media users in China, as well as the use of social media as tools before, during and after travel. Users were diversified in terms of their adoption of social media, use behaviour, scope, the levels of trust, influence and the ultimate travel decisions.Practical implications Destination marketing organizations should note that some overseas social media platforms that are not accessible in China like TripAdvisor, Yelp, Facebook and Instagram are still valued by some Chinese tourists, especially during-trip period in journeys to Western countries. Some tactics for specific user segments should be carefully observed. When promoting specific tourism products to Chinese tourists, it is necessary to understand the user segmentation between platforms or apps.Originality/value Social media is a powerful tool for tourism development and sustainability in creating smart tourists and destinations worldwide. In China, the use of social media has stimulated the development of both information and communication technology and tourism.

A Comparison of K-Means and Agglomerative Clustering for Users Segmentation based on Question Answerer Reputation in Brainly Platform

Brainly is a question and answer (QA) site that students can use as a media for questions and answers. Students can also use Brainly to find and share educational information that helps students solve their homework problems. In Brainly, users can answer questions according to their interests. However, it could be that the interest is not necessarily following the competencies possessed. It causes many answers to the questions given not to have a high rating because the answers given are of low quality to be prioritized as the main answer. This study aims to apply the K-Means and Agglomerative Clustering methods to segment users based on the reputation of the answerers by conducting clustering based on track records in answering questions on mathematics subjects. This study used the number of the brightest scores and the number of answers that did not get a rating as the basic features for clustering. The comparison between the two methods used is based on the Silhouette Score, representing the quality of the clustering results, calculated by applying the Silhouette Coefficient method. This study result indicates that the K-Means method gives better results than the Agglomerative Clustering. The Silhouette Score generated by the K-Means method is higher at 0.9081 than the Agglomerative Clustering method, which is 0.8990, which produces two clusters or two segments.

BDS-3 Integrity Risk Modeling and Probability Evaluation

Focusing on the global integrity monitoring performance of the BDS-3, the integrity failure model and effect analysis (IFMEA) of the system space segment and the ground control segment were carried out, and the system integrity risk tree model was established according to the IFMEA results. To evaluate the system’s integrity risk probability more reasonably, this paper establishes an abnormal event prediction model with a Bayesian method, based on actual operation data, under a situation in which the BDS-3 just opened service. With statistical analysis results of system anomalies since 27 December 2018—which is the date the BDS-3 began providing basic service—according to the anomaly prediction model, the system’s integrity risk probability under the 95% confidence limit was calculated to be approximately 0.9e-7/h, meeting the design index requirements of 1e-7/h. The analysis results also show that the main risk factors affecting the integrity of BDS-3 are ‘pseudorange measurement anomaly’ and ‘miss-detection of satellite autonomous integrity monitoring’. The results are important references with practical engineering significance for improving the integrity performance of BDS-3.

Learning From the Past to Improve the Future

Contact tracing apps were considered among the first tools to control the spread of COVID-19 and ease lockdown measures. While these apps can be very effective at stopping transmission and saving lives, the level of adoption remains significantly below the expected critical mass. The public debate as well as academic research about contact tracing apps emphasizes general concerns about privacy (and the associated risks) but often disregards the value-added services, as well as benefits, that can result from a larger user base. To address this gap, the study analyzes goal-congruent features as drivers for user adoption. It uses market research techniques – specifically, conjoint analysis – to study individual and group preferences and gain insights into the prescriptive design. While the results confirm the privacy-preserving design of most European contact tracing apps, they emphasize the role of value-added services in addressing heterogeneous user segments to drive user adoption. The findings thereby are of relevance for designing effective contact tracing apps, but also inform the user-oriented design of apps for health and crisis management that rely on sharing sensitive information.

THE DESIS L2A PROCESSOR AND VALIDATION OF L2A PRODUCTS USING AERONET AND RADCALNET DATA

Abstract. The hyperspectral instrument ”DLR Earth Sensing Imaging Spectrometer” (DESIS) is a VNIR sensor on-board of the International Space Station (ISS) and operational since October 2019. DESIS acquires images of Earth on user request with a swath of about 30 km width and 235 bands with a Full Width at Half Maximum (FWHM) of 3.5 nm in the spectral range between 400 to 1000 nm.In this article we will present the basis of the atmospheric correction by PACO software, implemented inside the DESIS Ground Segment as L2A processor. The resulting L2A products will be validated against independent in-situ measurements.The aerosol optical thickness and water vapor will be compared with the Aerosol Robotic Network (AERONET) measurements and the surface reflectance will be validated with the Radiometric Calibration Network (RadCalNet) data.

FENGYUN-4A Advanced Geosynchronous Radiation Imager Layered Precipitable Water Vapor Products’ Comprehensive Evaluation Based on Quality Control System

A physical retrieval algorithm has been developed for deriving the layered precipitable water vapor (LPWs) product from infrared radiances of the Advanced Geosynchronous Radiation Imager (AGRI) onboard FengYun-4A (FY-4A), the first of the new generation of Chinese geostationary weather satellites (FengYun-4, or FY-4 Series). The FY-4A AGRI LPWs are evaluated with different types of reference datasets based on Quality Control System (QCS), including those from Himawari-8 AHI (Advanced Himawari Imager), MODIS (Moderate Resolution Imaging Spectroradiometer), Radiosonde, ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis v5), NCEP (National Centers for Environmental Prediction) reanalysis and CMA (China Meteorological Administration) forecast product from global medium range numerical weather prediction (NWP) system. QCS is one of the important components of FY-4A ground segment, which mainly focuses on the satellite products’ evaluation and validation. It is found that the AGRI LPW product has a good agreement with different evaluating sources and the quality is favorable and stable. With the capability of frequent (5-min interval) observations over the East Asia and Western Pacific regions, the AGRI LPW products can be used to investigate the atmospheric temporal and spatial variations in the pre-landfall environment for typhoons. The QCS is a useful tool to monitor, evaluate, and validate the AGRI LPW products.

THE STUDY OF KINEMATIC GNSS SURVEYING FOR BIM GEOREFERENCING

Abstract. Building Information Modeling is a tool for creating, presenting and managing building data. The use of BIM has the advantage of obtaining greater detail and fidelity in design, construction and operation, increases efficiency, and serves as a digital transformation of the construction industry. As BIM continues to evolve and integrate, needs accurate spatial georeferencing is needed as a way to correctly display a model without changing the underlying data. The great common tool for referencing is GNSS. Having in mind tight surveying conditions for urban territories. It is preferable to use kinematic surveying mode. This study is an analysis of field measurements aimed at investigating the problem of GNSS accuracy under various adverse operating conditions. Every year, new updated receiver models and software versions appear on the geodetic market, so it is necessary to study their effectiveness and given accuracy. This paper shows information about a kinematic survey performed in a canopy, multipath and in an open area to evaluate the performance of the user segment of various manufactures.

Topology Design for GNSSs Under Polling Mechanism Considering Both Inter-Satellite Links and Ground-Satellite Links

Inter-satellite links (ISLs) are adopted in global navigation satellite systems (GNSSs) for high-precision orbit determination and space-based end-to-end telemetry telecommand control and communications. Due to limited onboard ISL terminals, the polling time division duplex (PTDD) mechanism is usually proposed for space link layer networking. By extending the polling mechanism to ground-satellite links (GSLs), a unified management system of the space segment and the ground segment can be realized. However, under the polling system how to jointly design the topology of ISLs and GSLs that are both time-slotted to improve data interaction has not been studied. In this paper, we formulate the topology design problem as an integer linear programming problem, aiming at minimizing the average delay of data delivery from satellites to ground stations while satisfying the ranging requirement for orbit determination. To tackle the computational complexity problem, we first present a novel modeling method of delay to reduce the number of decision variables. Furthermore, we propose a more efficient heuristic based on maximum weight matching algorithms. Simulation results demonstrate the feasibility of the proposed methods for practical operation in GNSSs with time-slotted GSLs. Comparing the two methods, the heuristic can achieve similar performance with respect to average delay but with significantly less complexity.

Slicing-Based Software-Defined Mobile Edge Computing in the Air

Network slicing is a promising approach supporting various Internet of Everything applications with diverse and differential requirements. To implement flexible and efficient network slices, unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) is deployed to leverage aerial and ground segments, which provides multi-dimensional resources involving various hardware devices and facilities (e.g., UAVs, edge servers, and network devices). Such a complex and hierarchical structure requires an efficient framework to orchestrate and control network slices while considering specific and unique characteristics of the UAVs deployed in the system. In this work, we propose a new systematic architecture named slicing-based software-defined MEC in the air, where virtual resource blocks provided by UAVs and edge devices are ubiquitously integrated into network slices to offer customized UAV-enabled MEC services by software-defined technologies. Then we identify three slicing patterns implemented by organized embeddings of UAVs, which are full slicing, partial slicing, and separated slicing patterns. Based on the proposed slicing-based software-defined scheme, two potential application scenarios and some open issues are discussed. In particular, we develop a Lyapunov optimization-based offloading algorithm for the efficient selection of resource slices. Finally, some simulation results are presented to depict the effectiveness of the proposed scheme.