Abstract
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.
Highlights
A stable approach is a flying stage during which the pilot establishes and maintains a constant angle glidepath towards a predetermined point on the landing runway [1]
The trigger frequency was calculated as the ratio of the number of unstable approach (UA) events divided by the total amount of air traffic of each airport, and it was modeled as a spatial analysis unit in this paper
The spatio-temporal statistics of all the UA events triggered by Chinese civil aircraft in January 2018 were analyzed
Summary
A stable approach is a flying stage during which the pilot establishes and maintains a constant angle glidepath towards a predetermined point on the landing runway [1]. An unstable approach (UA) can happen when the pilot fails to plan, prepare and conduct a stable approach. The approach process only accounts for about 4% of the entire flight process, unsafe incidents occurring during this process account for up to 49.1% of total flight accidents [3]. UA was a causal factor in 66% of. 76 approach-and-landing accidents or serious incidents all over the world in 1984 through 1997 [4]. It is of great practical significance to explore and analyze the spatio-temporal distribution of UA events and their influencing factors
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