Estimating Aircraft Take-Off Roll Time Using ADS-B Data

This paper explores the potential of refining the Landing and Take-off (LTO) cycle originally defined by the International Civil Aviation Organization (ICAO) through the use of Automatic Dependent Surveillance-Broadcast (ADS-B) data. In this paper, a methodology is developed to automatically analyze ADS-B data within the ASTERIX data format in order to estimate the duration of the take-off roll of individual airport movements, hence improving the time duration parameter of the take-off phase of the LTO cycle. By employing ADS-B data complemented by crowd-sourced aircraft databases, the paper also offers insights into the variations of take-off roll time among various aircraft types. The results show that using ADS-B data provides a good picture of actual operating conditions at the airport, thus enabling more accurate calculations of emissions within the LTO cycle and contributing to an improved understanding of the extent of environmental impacts of aviation activities at airports. This research contributes to the advancement of LTO cycle analysis, emphasizing the necessity of using real data in order to enhance its accuracy.