GIS and Flight Training

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Flight simulators have been present for some time for pilot training. However, they have generally not been incorporated as analytical GIS tools for the training of pilots and air traffic  control or navigation. One common tool is ArcGIS for aviation, which can be used for navigation purposes and is setup to meet FAA guidelines.[1]

Real time flight data application and radar tracking using 4D modeling

Recent technical developments have created 4D environments where real-time data and updates are integrated into a 3D environment and simulation platform that anticipates movement and conditions that aircraft operate within. This can give advanced warning of possible incidents far before they even occur using real time flight data.[2]

4D training for pilots

In fact, for pilot trainees, 4D technologies, including a tool called NextGen, have proven to be useful for improving pilot response and flight learning, demonstrating the utility of creating software that integrates spatial data, real-time information on given environments, and time updates.[3] Flight simulators have, for some time, incorporated GIS as a way to include terrain and conditions where a pilot can utilize both an immersive but analytical environment for training. For instance, providing data that helps with runway approaches or navigation under give weather conditions is improved by having an analytical environment such as in GIS.

A waypoint decision aid with visualized weather shows alternative routes to student pilots. Image: Shepherd & Gossett, 2012.

A waypoint decision aid with visualized weather shows alternative routes to student pilots. Image: Shepherd & Gossett, 2012.

Flight simulators and use of artificial intelligence for pilotless aircraft

More recently, flight simulators have now taken the extra step where artificial intelligence along with GIS capabilities of mapping and spatial analysis have allowed not just pilot-based but also pilotless aircraft, or drones, to be more effective and intelligent in reacting to their conditions. This, in fact, may represent one avenue of further growth for pilotless flying, where GIS is increasingly used as a data management tool along with artificial intelligence that anticipates needed maneuvers based on real-time data coming in from sensors and radar for pilotless aircraft.[4] What is clear is that the future of aviation technology looks to continue to utilize GIS in ways that allow better training and smarter aircraft.

[1] For information on ArcGIS for airports, see: http://www.esri.com/software/arcgis/extensions/aviation/airports

[2] For more on this real time flight data application and radar tracking using 4D modeling, see:  J. J. Liu, L. Y. Tian, Q. X. Wu, M. He, “Civil Aircraft Radar Track Simulation Algorithm Based on 4D Trajectory“, Advanced Materials Research, Vol. 905, pp. 514-518, 2014.

[3] For more information on 4D training for pilots, see:  Munoz, B. T. (2011). Four-dimensional modeling and simulation for use in interactive airspace. S.l.: Proquest, Umi Dissertatio.

[4] For more information on flight simulators and use of artificial intelligence for pilotless aircraft, see:  Pickles, J. (2004). A history of spaces: cartographic reason, mapping, and the geo-coded world. London ; New York: Routledge, pg. 156.



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