Feature Extraction from Trajectory Data for the Identification of Holding and Point Merge Patterns

Jean Phelipe de Oliveira Lima
Tábada Cesar Domingues Silva
Álef Gonçalves Quintanilha
André Elias Melo
Pollyanne Evangelista da Silva

Airspace Control Institute

Download PDF DOI: 10.29327/9786527220244.1239745 Also published on Even3

Event: XXII SITRAER – Brasília, DF, Brasil, October 22–24, 2025
Volume: Anais do XXII Simpósio de Transporte Aéreo – SITRAER 2025 · ISBN 978-65-272-2024-4 · DOI 10.29327/9786527220244
Publisher: Even3 Publicações
Editors: Fabiana Serra de Arruda, Camila Lucena, Giovanna Miceli Ronzani Borille, Evandro José da Silva

Abstract

One of the most critical phases of a flight is the approach phase, conducted within the Terminal Maneuvering Area (TMA). In this phase, multiple aircraft converge toward the same airport (or nearby airports) within a constrained airspace, resulting in high traffic density and workload for controllers. This work aims to show that it is possible to detect relevant flight patterns in terminal airspace, focusing on holdings and point merge procedures. The results can be used to indicate that there is an imbalance in the terminal area and that there are flow management inefficiencies, for example. They can also support post-operations by providing a performance analysis of the TMA, thereby generating valuable data for improved flow management. The proposed algorithm processes trajectory data with the aim of identifying critical points, those possibly associated with holding patterns and point merge procedures, through a multi-step analysis that includes the representation of distance to the aerodrome, signal smoothing, detection of stationary intervals, and analysis of the zeros of the gradient function. The results include the application of the methodology to real flight trajectory data for arrivals at SBGR, where it is possible to observe that key trajectory points were successfully identified by the proposed algorithm.

Keywords: Feature Extraction; Holding Pattern; Point Merge System; Pattern Recognition; Air Traffic Management

How to cite

ABNT

LIMA, Jean Phelipe de Oliveira; SILVA, Tábada Cesar Domingues; QUINTANILHA, Álef Gonçalves; MELO, André Elias; SILVA, Pollyanne Evangelista da. Feature Extraction from Trajectory Data for the Identification of Holding and Point Merge Patterns. In: SIMPÓSIO DE TRANSPORTE AÉREO, 22., 2025, Brasília. Anais [...]. Recife: Even3, 2026. ISBN 978-65-272-2024-4. DOI: 10.29327/9786527220244.1239745. Disponível em: https://sitraer-sbta.org/anais-2025-1239745.html.

APA

Lima, J. P. O., Silva, T. C. D., Quintanilha, Á. G., Melo, A. E., & Silva, P. E. (2025). Feature Extraction from Trajectory Data for the Identification of Holding and Point Merge Patterns. In F. S. Arruda, C. Lucena, G. M. R. Borille, & E. J. Silva (Eds.), Anais do XXII Simpósio de Transporte Aéreo – SITRAER 2025. Even3. https://doi.org/10.29327/9786527220244.1239745

BibTeX

@inproceedings{lima2025feature,
  author = {Lima, Jean Phelipe de Oliveira and Silva, Tábada Cesar Domingues and Quintanilha, Álef Gonçalves and Melo, André Elias and Silva, Pollyanne Evangelista da},
  title = {{Feature Extraction from Trajectory Data for the Identification of Holding and Point Merge Patterns}},
  booktitle = {Anais do XXII Simpósio de Transporte Aéreo – SITRAER 2025},
  editor = {Arruda, Fabiana Serra de and Lucena, Camila and Borille, Giovanna Miceli Ronzani and Silva, Evandro José da},
  year = {2025},
  address = {Brasília, DF, Brasil},
  publisher = {Even3 Publicações},
  isbn = {978-65-272-2024-4},
  doi = {10.29327/9786527220244.1239745},
  url = {https://sitraer-sbta.org/anais-2025-1239745.html}
}