Data-Driven Analysis of Aircraft Touchdown Patterns on Airport Runways using Satellite Image Processing Techniques

Abstract

This paper presents an image processing-based method for analyzing satellite scans taken from 24 airports and runways different in size and location to detect and understand variations in landing behaviors by extracting aircraft wheels rubber spots deposited in runway touchdown zones. The analysis establishes a clear correlation between the observed rubber material distributions and the locally or globally governing operational constraints, showing for instance the effect of the ongoing pandemic or noise abatement procedures on the change of landing behaviors in some European airports. Statistical generalizations are also suggested and combined with an explanatory Monte Carlo model under Gaussian Processes considerations. In addition, the identified change in landing manners is correlated with runway landing operations efficiency in the short and long terms. The paper also provides examples of the proposed method applications that may be of potential value for both aircraft and airport operators.