Many scientists have the common need of visualizing data in a collaborative and interactive manner. In a modern environment, these data are often stored across a widely distributed network and the researchers themselves are just as often separated by large geographical distances. Traditional visualization and collaboration approaches require the local installation of software specific to each end user as well as the downloading of data to each local machine. The proposed innovation would provide researchers with an environment that allows them to visualize remote data using the standard and familiar web browser as the application platform. No proprietary software need be installed and no data has to be downloaded to local machines. Furthermore, multiple researchers can interactively explore data via visualization in a joint session where changes by one researcher are seamlessly seen by the others. The architecture is based on technologies underlying state of the art web applications such as Google Maps. Employing a modular design using web services as means to connect the modules, the environment is easy to modify and improve as new data access, rendering, and client-side display technologies mature and become available.

Dataset

This dataset was created by Abdallah Nasser

Released under Apache 2.0

Contents

Flight data monitoring (FDM) systems offer a comprehensive suite of product features to enhance aviation safety and operational efficiency: Flight Data Recording and Storage: Captures and stores critical flight parameters, including aircraft performance, environmental data, and pilot inputs. Data Analysis and Visualization: Analyzes recorded data to identify trends, anomalies, and potential safety concerns, presenting insights through intuitive visualizations. Trend Analysis and Reporting: Generates custom reports to monitor performance metrics over time, allowing airlines to identify areas for improvement and optimize operations. Predictive Maintenance and Alerting: Utilizes advanced algorithms to predict potential equipment failures, enabling proactive maintenance and minimizing operational disruptions. Event Reconstruction and Investigation: Provides a detailed record of flight events in case of incidents or accidents, aiding in investigations and improving safety protocols. Recent developments include: In April 2020, Airbus, as one of the prominent market parts, known to have as many as 7,645 aircraft on the backlog. This is available with more than 80% of these prevailing orders for one of the market products - A320 Family aircraft. A350XWBs alongside A220s account for approximately 14% of the order backlog. The planned aircraft deliveries of new aircraft programs like Boeing 777X, COMAC C919, and MC-21, as part of the upcoming years, are anticipated to propel the demand for the prevalent commercial aircraft flight data monitoring systems.. Key drivers for this market are: Increased focus on aviation safety. Technological advancements in data analysis.. Potential restraints include: Data security and privacy concerns. High cost of FDM systems.. Notable trends are: Predictive analytics for proactive maintenance. Integration with other aviation systems..

This paper describes a method and system for integrating machine learning with planning and data visualization for the management of mobile sensors for Earth science investigations. Data mining identifies discrepancies between previous observations and predictions made by Earth science models. Locations of these discrepancies become interesting targets for future observations. Such targets become goals used by a flight planner to generate the observation activities. The cycle of observation, data analysis and planning is repeated continuously throughout a multi-week Earth science investigation.

With the increase in quantity and complexity of launches at the Wallops Flight Facility (WFF) there is an ever-growing need for a more capable real-time visualization system for the WFF Range Control Center (RCC). This system should have the ability to depict the vehicle using actual CAD vehicle models, display vehicle attitude and stage separation events, and utilize robust network protocol suitable for real-time safety applications. This project will use existing WFF hardware systems and leverage past experiences and lessons learned to produce a Visualization in Real-Time Experiment (VIRTEx) application that will use a cutting edge message protocol for lab demonstration and use during real-time operations.

The objective of this project will be to migrate some of the outputs from the WFF Mission Planning Lab (MPL) into a real-time visualization system. The MPL is responsible for generating pre-flight RF margin link analysis, mission simulation & visualization, and other products for WFF missions. This real-time visualization system would depict in 3D graphics the position and orientation of the launch vehicle(s) or suborbital carrier (UAV, sounding rocket), VIRTEx would be expanded to use a more flexible publish/subscribe architecture, and the system will leverage recently developed advanced telemetry and data handling systems within the Range network.

Another main objective will be updating VIRTEx to support a sounding rocket mission which is scheduled to launch from NASA Wallops Flight Facility (WFF) in the summer of 2014.

This project will also be used to demonstrate the successful attitude data conversion from a WFF telemetry system. Updates are being finished on this telemetry system that convert various NASA Sounding Rocket attitude control systems (ACS) data formats. Multiple ACS systems output different data formats, so libraries and algorithms were added to the telemetry system to convert this data into a standard yaw, pitch, and roll dataset for Range Safety. VIRTEx will be able to easily show this data and will be able to compare it to the pre-flight attitude predictions.

Petscale computing is leading to significant breakthroughs in a number of fields and is revolutionizing the way science is conducted. Data is not knowledge, however, and the challenge has been how to analyze and gain insight from the massive quantities of data that are generated. In order to address the peta-scale visualization challenges, we propose to develop a scientific visualization software that would enable real-time visualization capability of extremely large data sets. We plan to accomplish this by extending the ParaView visualization architecture to extreme scales. ParaView is an open source software installed on all HPC sites including NASA's Pleiades and has a large user base in diverse areas of science and engineering. Our proposed solution will significantly enhance the scientific return from NASA HPC investments by providing the next generation of open source data analysis and visualization tools for very large datasets. To test our solution on real world data with complex pipeline, we have partnered with SciberQuest, who have recently performed the largest kinetic simulations of magnetosphere using 25 K cores on Pleiades and 100 K cores on Kraken. Given that IO is the main bottleneck for scientific visualization at large scales, we propose to work closely with Pleiades's systems team and provide efficient prepackaged general purpose I/O component for ParaView for structured and unstructured data across a spectrum of scales and access patterns with focus on Lustre file system used by Pleiades.

The Global Commercial Aircraft Cockpit Display System Market is experiencing robust growth, driven by the increasing demand for advanced and technologically superior aircraft. The rising adoption of sophisticated avionics, including integrated modular avionics (IMA) and enhanced flight visualization systems, is a major factor fueling market expansion. Airlines are continuously seeking to improve operational efficiency, enhance safety, and reduce pilot workload, all of which contribute to the increased demand for advanced cockpit display systems. Furthermore, the ongoing replacement of aging aircraft fleets with newer, technologically advanced models is significantly impacting the market’s trajectory. Stringent regulatory requirements regarding safety and operational standards also push the adoption of these systems. The market is segmented by display type (LCD, LED, others) and application (narrow-body aircraft, wide-body aircraft, regional jets). While precise market sizing data is unavailable, a logical estimation based on industry trends suggests a substantial market value, projected to see significant growth in the coming years. Leading players like Diehl Aerosystems, Esterline, Honeywell, L-3 Communications, and Thales are fiercely competing through technological advancements and strategic partnerships to capture a greater market share. The market's growth is anticipated to be consistent across various regions, with North America and Europe currently holding significant shares due to established aerospace manufacturing hubs and a high concentration of airline operators. However, the Asia-Pacific region is expected to witness the fastest growth rate due to the booming aviation industry in countries like China and India. Market restraints include the high initial investment costs associated with implementing these sophisticated systems and the need for continuous software updates and maintenance. Nevertheless, the long-term benefits in terms of operational safety, efficiency, and fuel savings are expected to outweigh these challenges, ensuring sustained market growth over the forecast period of 2025-2033. Technological advancements like augmented reality and artificial intelligence integration within cockpit display systems will further shape market dynamics in the coming years.

Existing scientific visualization tools have specific limitations for large scale scientific data sets. Of these four limitations can be seen as paramount: (i) memory management, (ii) remote visualization, (iii) interactivity, and (iv) specificity. In Phase I, we proposed and successfully developed a prototype of a collection of computer tools and libraries called SciViz that overcome these limitations and enable researchers to visualize large scale data sets (greater than 200 gigabytes) on HPC resources remotely from their workstations at interactive rates. A key element of our technology is the stack oriented rather than a framework driven approach which allows it to interoperate with common existing scientific visualization software thereby eliminating the need for the user to switch and learn new software. The result is a versatile 3D visualization capability that will significantly decrease the time to knowledge discovery from large, complex data sets.

Typical visualization activity can be organized into a simple stack of steps that leads to the visualization result. These steps can broadly be classified into data retrieval, data analysis, visual representation, and rendering. Our approach will be to continue with the technique selected in Phase I of utilizing existing visualization tools at each point in the visualization stack and to develop specific tools that address the core limitations identified and seamlessly integrate them into the visualization stack. Specifically, we intend to complete technical objectives in four areas that will complete the development of visualization tools for interactive visualization of very large data sets in each layer of the visualization stack. These four areas are: Feature Objectives, C++ Conversion and Optimization, Testing Objectives, and Domain Specifics and Integration. The technology will be developed and tested at NASA and the San Diego Supercomputer Center.

On behalf of Australia, and in support of the Malaysian accident investigation, the Australian Transport Safety Bureau (ATSB) led search operations for missing Malaysian Airlines flight MH370 in the Southern Indian Ocean. Geoscience Australia provided advice, expertise and support to the ATSB to facilitate marine surveys, which were undertaken to provide a detailed map of the sea floor topography and to aid navigation during the underwater search.

This dataset comprises Side Scan Sonar (SSS), Synthetic Aperture Sonar (SAS) and multibeam sonar backscatter data at 5 m resolution. Data was collected during Phase 2 marine surveys conducted by the Governments of Australia, Malaysia and the People’s Republic of China between September 2014 to January 2017. The data was acquired by Echo Surveyor 7 (Kongsberg AUV Hugin 1000), Edgetech 2400 Deep Tow and SLH PS-60 Synthetic Aperture Sonar Deep Tow deployed from the following vessels: Fugro Supporter, Fugro Equator, Fugro Discovery, Havila Harmony, Dong Hai Jiu 101 and Go Phoenix.

All material and data from this access point is subject to copyright. Please note the creative commons copyright notice and relating to the re-use of this material. Geoscience Australia's preference is that you attribute the datasets (and any material sourced from it) using the following wording: Source: Governments of Australia, Malaysia and the People's Republic of China, 2018. MH370 Phase 2 data. For additional assistance, please contact marine@ga.gov.au. We honour the memory of those who have lost their lives and acknowledge the enormous loss felt by their loved ones.

This dataset provides attributed geospatial and tabular information for identifying and querying flight lines of interest for the Airborne Visible InfraRed Imaging Spectrometer-Classic (AVIRIS-C) and Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) Facility Instrument collections. It includes attributed shapefile and GeoJSON files containing polygon representation of individual flights lines for all years and separate KMZ files for each year. These files allow users to visualize and query flight line locations using Geographic Information System (GIS) software. Tables of AVIRIS-C and AVIRIS-NG flight lines with attributed information include dates, bounding coordinates, site names, investigators involved, flight attributes, associated campaigns, and corresponding file names for associated L1B (radiance) and L2 (reflectance) files in the AVIRIS-C and AVIRIS-NG Facility Instrument Collections. Tabular information is also provided in comma-separated values (CSV) format.

This dataset provides resources for identifying flight lines of interest for the MODIS/ASTER Airborne Simulator (MASTER) instrument based on spatial and temporal criteria. MASTER first flew in 1998 and has ongoing deployments as a Facility Instrument in the NASA Airborne Science Program (ASP). MASTER is a joint project involving the Airborne Sensor Facility (ASF) at the Ames Research Center, the Jet Propulsion Laboratory (JPL), and the Earth Resources Observation and Science Center (EROS). The primary goal of these airborne campaigns is to demonstrate important science and applications research that is uniquely enabled by the full suite of MASTER thermal infrared bands as well as the contiguous spectroscopic measurements of the AVIRIS (also flown in similar campaigns), or combinations of measurements from both instruments. This dataset includes a table of flight lines with dates, bounding coordinates, site names, investigators involved, flight attributes, and associated campaigns for the MASTER Facility Instrument Collection. A shapefile containing flights for all years, a GeoJSON version of the shapefile, and separate KMZ files for each year allow users to visualize flight line locations using GIS software.

description: The Information Fusion & Visualization Lab supports the engineering research and development of algorithms, software and systems needed in the areas of information fusion and imagery exploitation driven by Navy aviation needs. In addition, this lab develops software tools and processes and verifies information fusion, sensor fusion, expert systems and imagery exploitation capabilities, from initial concept exploration through prototyped algorithms.The Information Fusion & Visualization Labalso performs aircraft radiometric and photometric measurements inside and outside of aircraft and is prepared to support multiple tasks of low to medium complexity.; abstract: The Information Fusion & Visualization Lab supports the engineering research and development of algorithms, software and systems needed in the areas of information fusion and imagery exploitation driven by Navy aviation needs. In addition, this lab develops software tools and processes and verifies information fusion, sensor fusion, expert systems and imagery exploitation capabilities, from initial concept exploration through prototyped algorithms.The Information Fusion & Visualization Labalso performs aircraft radiometric and photometric measurements inside and outside of aircraft and is prepared to support multiple tasks of low to medium complexity.

Ground resolution 15 cm. Purchase made for the project to monitor illegal building in the Portofino Park - Coverage: Portofino Park - Origin: Digital aerophotogrammetric image, orthorectified and georeferenced

Today's mission designers rely on state of the art tools with modern GUI elements and real-time 3D interactive graphics to visualize their trajectories and orbit control strategies. One such tool, NASA GSFC's General Mission Analysis Tool (GMAT), offers advanced mission design and optimization capabilities with a flexible GUI. However, its current 3D graphics are lacking in both the quantity and quality of graphical components as well as the maturity of its visualization architecture. Fortunately, GMAT's underlying flexible and Open Source software architecture was designed to facilitate modular improvements. We propose to provide GMAT with world-class visualization capabilities and a graphics architecture that can adapt to future visualization technologies by replacing the existing basic graphics code with the OpenFrames visualization software. OpenFrames is an Open Source API that allows simulations to incorporate high-performance interactive 3D visualizations without requiring significant architecture changes. In this research, we develop comprehensive requirements for GMAT's visualization needs, create a plan to integrate OpenFrames into GMAT, demonstrate a prototype of OpenFrames in GMAT, and compare the performance of OpenFrames to the existing basic visualizations in GMAT. This research will not only bring GMAT visualizations up to par with other mission design tools, such as AGI's STK/Astrogator and NASA JSC's Copernicus, but will also allow GMAT to support cutting-edge technologies such as interactive visual trajectory design and virtual reality environments such as the GSFC CAVE. In turn, this will increase GMAT's user base and increase its utility for future NASA missions, such as Decadal Survey and Discovery class missions that require high-fidelity simulations paired with truly interactive 3D visualizations.

The X-Plane Communications Toolbox (XPC) is an open source research tool used to interact with the commercial flight simulator software X-Plane. XPC allows users to control aircraft and receive state information from aircraft simulated in X-Plane using functions written in C or MATLAB in real time over the network. This research tool has been used to visualize flight paths, test control algorithms, simulate an active airspace, or generate out-the-window visuals for in-house flight simulation software.

Please note: for a correct view and use of this dataset it is advisable to consult it at original page on the Grosseto Portal. At the same address there are also, for the enabled datasets, additional access formats, the preview of the visualization via API call, the consultation of the fields in DCAT-AP IT format, the possibility to express an evaluation and comment on the dataset itself. All resource formats available for this dataset can be downloaded as ZIP packages: inside the package sarà available the resource in the chosen format, complete with all the information on the metadata and the license associated with it. Interometric data - descending flight

Commercial aircraft avionics market size and share projected to reach USD 81.3 Billion by 2035, with a CAGR of 6.6% during the forecast period. Rising aircraft deliveries directly fuel the market growth due to the increasing the demand for new and upgraded avionics systems.

The aerodynamic force on flying insects result from the vortical flow structures that vary both spatially and temporally throughout flight. Due to these complexities and the inherent difficulties in studying flying insects in a natural setting, a complete picture of the vortical flow has been difficult to obtain experimentally. In this paper, Schlieren, a widely used technique for highspeed flow visualization, was adapted to capture the vortex structures around freely flying hawkmoth (Manduca). Flow features such as leading-edge vortex, trailing-edge vortex as well as the full vortex system in the wake was visualized directly. Quantification of the flow from the Schlieren images was then obtained by applying a physics-based optical flow method, extending the potential applications of the method to further studies of flying insects.

The axis of the strips corresponds to that of the sections of the CTR at a scale of 1:10000. The georeferenced digital version has been available since 2002 - Coverage: Entire Regional Territory - Origin: Made by orthoprojection of the b/w frames of the flight at 1:40000 scale

In this study, a combined test facility was developed using a combination of an arc-jet tunnel and a shock tunnel for aerothermodynamic testing. The performance validation of individual parts was performed, and results were obtained from the combined test. A small-scale Huels-type arc-jet tunnel was used to preheat the test model by aerodynamic heating before conducting the experiments in the shock tunnel to duplicate the hot surfaces of flight objects encountered during hypersonic flight. The high-enthalpy flow in the arc-jet tunnel provided a heat flux of 1.99±0.03 MW/m2 for a flat-faced model of 10 mm diameters, and the flow condition of the shock tunnel used in this study simulated a Mach 5 flight at a pressure altitude of about 24 km. The two combined experiments employing different shape and material models were carried out to examine the effect of aerothermodynamic phenomena. In the first experiment, the effect of ablation-induced shape change on the fluid-structure was investigated using a cone model manufactured of AL6061 material. The effect of surface roughness on the fluid-structure was examined in the second experiment, which used a hemisphere model constructed of STS303 material. Although substantial findings could not be validated due to the limits of qualitative evaluations utilizing visualization methods, however preheating-related changes in surface roughness were found. As a follow-up study, a force measuring experiment based on the test procedures is being carried out at this facility utilizing a preheated model with an accelerometer. The performance and experimental results obtained using this integrated setup are discussed in detail, highlighting the potential of this combined hypersonic test facility.