Airports contribute to the economy by facilitating the rapid transportation of the public and freight. Generally, windshield surveys are conducted annually to inspect the regional airports and maintain good operational performance. However, they are highly dependent on the experience of the inspector and other factors. The advancements in unmanned aerial vehicle (UAV) technology have propelled its application for mapping and assessing the conditions of runways, taxiways, apron areas, and helipads of a regional airport in Texas. For this, an optical camera sensor was mounted on the UAV to execute preplanned flight plans to map the paved surfaces of the airport in a single day. The ability to geotag images using high accuracy post-processed kinematic Global Navigation Satellite System (GNSS) was very helpful in obtaining high-quality data for making quantitative assessments. Three-dimensional models of the airport assets were developed from the aerial images to identify the condition of those assets. Airport asset conditions were quantitatively assessed to identify the pavement condition index. Many lessons were learned starting from the coordination of the inspections to the data collection stage. The research study presented in this paper is expected to guide the airport managers on the application of UAVs for airport asset management.


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    Titel :

    Lessons Learned in Airport Asset Inspection Using Unmanned Aerial Vehicle (UAV) Based Close-Range Photogrammetry


    Beteiligte:

    Kongress:

    International Conference on Transportation and Development 2022 ; 2022 ; Seattle, Washington



    Erscheinungsdatum :

    2022-08-31




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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