Event Detection and Spatio-temporal Analysis of Low-Altitude Unstable Approach

Low-altitude unstable approach (UA) is one of the crucial risks that threaten flight safety. In this study, we proposed a technical program for detecting low-altitude UA events. The detection logic was to optimize the step-wise regression model with iterative surveys with more than 20 experienced pi...

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Bibliographic Details
Published inApplied sciences Vol. 10; no. 14; p. 4934
Main Authors Sun, Huabo, Xie, Jiayi, Jiao, Yang, Huang, Rongshun, Lu, Binbin
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.07.2020
Subjects
Aircraft accidents & safety
Airports
Civil aviation
Correlation analysis
Correlation coefficient
Correlation coefficients
Data analysis
detection method
Elevation
evaluation model
Event history analysis
Fault diagnosis
Geospatial data
Ground stations
Landing of aircraft
Low altitude
Methods
Questionnaires
Spatial analysis
Spatial data
Spatial distribution
spatio-temporal analysis
Studies
unstable approach
Variables
Weather
Wind
China
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Summary:Low-altitude unstable approach (UA) is one of the crucial risks that threaten flight safety. In this study, we proposed a technical program for detecting low-altitude UA events. The detection logic was to optimize the step-wise regression model with iterative surveys with more than 20 experienced pilots. Accordingly, the frequencies of UA events occurring around each airport in January 2018 were calculated for all the airports within mainland China. Finally, the spatial distribution characteristics of UA events were analyzed via exploratory spatial data analysis. In addition, Pearson’s correlation coefficient and the geographically weighted correlation coefficient were used to explore the correlations between UA frequency and the altitude elevation, wind level, and bad weather. The experimental results revealed that the proposed method can accurately detect the occurrence of low-altitude UA and quantitatively characterize risks. It was found that UA exhibits obvious differences in spatial distribution. Moreover, significantly strong correlations were found between UA and altitude elevation, wind level, and bad weather, and correlation differences were also reflected in different regions in China.
ISSN:2076-3417
2076-3417
DOI:10.3390/app10144934