Airport digital Mock-up
View/Open
Cita com:
hdl:2117/377040
Document typeMaster thesis
Date2022-10-27
Rights accessOpen Access
Except where otherwise noted, content on this work
is licensed under a Creative Commons license
:
Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
The accessibility of the Aeronautical Information is available in format such as AIXM, these formats are most suitable for trained eyes and intended for the purpose of Aerodrome monitoring, Landing & Takeoff procedures and Navigation systems on full fledge devices designed and built for AIXM only. Let's say if we want to develop an Aerodrome game where we can land an aeroplane in an airport whose characteristics are close to the real ones on a cross platform friendly format, it is not possible with the current available formats. In this thesis we take advantage of ENAIRE Spain's Air Navigation and Aeronautical Information service provider, availing Aeronautical Information Publication service https://aip.enaire.es/AIP/#LEPA/LESJ, where they provide data regarding to Aerodromes in Spain in the form of PDF and CSVs. The pdfs are sually used by pilots and co pilots as a reference to identify hotspots, taxiways status and obstacles inside the aerodrome, CSV files serve as a data to feed GIS platforms such as QGIS and mostly used by researchers and other people who are involved in aeronautical domain to identify the obstacles in and around the Aerodromes. We used Python libraries such as Pandas, Camelot to extract and convert data from PDF which are in the form of tables. The extracted information which contains Geo Locations and other critical information such as area, altitude and Runways important properties such as Clear way, Strip dimensions & geographic reference point is combined with the Obstacles data such as Geo Location and other characteristics such as altitude, Lighting, Marking and other available information of obstacles such as Trees, vegetation, Signal Towers into a geojson format. The Generated output geojson files are viewed on a 2-Dimensional map on http://geojson.io/#map=2/20.0/0.0, which has two split panes where we can view the geojson information and its geolocation against each other
Files | Description | Size | Format | View |
---|---|---|---|---|
memoria.pdf | 48,05Mb | View/Open |