TY - GEN
T1 - Use of Photogrammetry and Laser Scanning Technologies in Runway Inspections
AU - Sanaei, Parisa
AU - Salman, Baris
N1 - Publisher Copyright:
© 2024 ASCE.
PY - 2024
Y1 - 2024
N2 - Runways are among the most important assets for many airports due to their high life-cycle costs and functional importance. Runway inspections are mainly conducted through manual inspections requiring visual identification of distresses. These practices may suffer from potential inaccuracies and biases due to the time- and resource-consuming nature of these inspection procedures. Manual data collection procedures also hinder the potential for adopting more sophisticated approaches to asset management featuring artificial intelligence and digital twin technologies. In this paper, the potential of photogrammetry and laser scanning - two emerging methods to construct 3D models - in improving runway inspection procedures is examined. Results obtained from online surveys of airport authorities and industry leaders and semi-structured interviews are presented. A road map is presented to assist airport authorities with adopting photogrammetry and laser scanning technologies to improve their condition assessment procedures. While these technologies have found applications in other domains, their adoption in the aviation sector has been somewhat limited. It is anticipated that this paper and other publications in this area will foster further research and practical applications in the 3D modeling of airport infrastructure, resulting in considerable improvements to airport asset management practices.
AB - Runways are among the most important assets for many airports due to their high life-cycle costs and functional importance. Runway inspections are mainly conducted through manual inspections requiring visual identification of distresses. These practices may suffer from potential inaccuracies and biases due to the time- and resource-consuming nature of these inspection procedures. Manual data collection procedures also hinder the potential for adopting more sophisticated approaches to asset management featuring artificial intelligence and digital twin technologies. In this paper, the potential of photogrammetry and laser scanning - two emerging methods to construct 3D models - in improving runway inspection procedures is examined. Results obtained from online surveys of airport authorities and industry leaders and semi-structured interviews are presented. A road map is presented to assist airport authorities with adopting photogrammetry and laser scanning technologies to improve their condition assessment procedures. While these technologies have found applications in other domains, their adoption in the aviation sector has been somewhat limited. It is anticipated that this paper and other publications in this area will foster further research and practical applications in the 3D modeling of airport infrastructure, resulting in considerable improvements to airport asset management practices.
UR - http://www.scopus.com/inward/record.url?scp=85188746987&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85188746987&partnerID=8YFLogxK
U2 - 10.1061/9780784485262.040
DO - 10.1061/9780784485262.040
M3 - Conference contribution
AN - SCOPUS:85188746987
T3 - Construction Research Congress 2024, CRC 2024
SP - 386
EP - 396
BT - Advanced Technologies, Automation, and Computer Applications in Construction
A2 - Shane, Jennifer S.
A2 - Madson, Katherine M.
A2 - Mo, Yunjeong
A2 - Poleacovschi, Cristina
A2 - Sturgill, Roy E.
PB - American Society of Civil Engineers (ASCE)
T2 - Construction Research Congress 2024, CRC 2024
Y2 - 20 March 2024 through 23 March 2024
ER -