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...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-07-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/10/14/4934 |
| _version_ | 1797562070506405888 |
|---|---|
| author | Huabo Sun Jiayi Xie Yang Jiao Rongshun Huang Binbin Lu |
| author_facet | Huabo Sun Jiayi Xie Yang Jiao Rongshun Huang Binbin Lu |
| author_sort | Huabo Sun |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T18:23:23Z |
| format | Article |
| id | doaj.art-0c81c12493d54b5caaa3b835f8acbf55 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T18:23:23Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-0c81c12493d54b5caaa3b835f8acbf552023-11-20T07:09:29ZengMDPI AGApplied Sciences2076-34172020-07-011014493410.3390/app10144934Event Detection and Spatio-temporal Analysis of Low-Altitude Unstable ApproachHuabo Sun0Jiayi Xie1Yang Jiao2Rongshun Huang3Binbin Lu4Engineering and Technical Research Center of Civil Aviation Safety Analysis and Prevention, China Academy of Civil Aviation Science and Technology, Beijing 100028, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, ChinaEngineering and Technical Research Center of Civil Aviation Safety Analysis and Prevention, China Academy of Civil Aviation Science and Technology, Beijing 100028, ChinaEngineering and Technical Research Center of Civil Aviation Safety Analysis and Prevention, China Academy of Civil Aviation Science and Technology, Beijing 100028, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, ChinaLow-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.https://www.mdpi.com/2076-3417/10/14/4934unstable approachdetection methodevaluation modelspatio-temporal analysis |
| spellingShingle | Huabo Sun Jiayi Xie Yang Jiao Rongshun Huang Binbin Lu Event Detection and Spatio-temporal Analysis of Low-Altitude Unstable Approach Applied Sciences unstable approach detection method evaluation model spatio-temporal analysis |
| title | Event Detection and Spatio-temporal Analysis of Low-Altitude Unstable Approach |
| title_full | Event Detection and Spatio-temporal Analysis of Low-Altitude Unstable Approach |
| title_fullStr | Event Detection and Spatio-temporal Analysis of Low-Altitude Unstable Approach |
| title_full_unstemmed | Event Detection and Spatio-temporal Analysis of Low-Altitude Unstable Approach |
| title_short | Event Detection and Spatio-temporal Analysis of Low-Altitude Unstable Approach |
| title_sort | event detection and spatio temporal analysis of low altitude unstable approach |
| topic | unstable approach detection method evaluation model spatio-temporal analysis |
| url | https://www.mdpi.com/2076-3417/10/14/4934 |
| work_keys_str_mv | AT huabosun eventdetectionandspatiotemporalanalysisoflowaltitudeunstableapproach AT jiayixie eventdetectionandspatiotemporalanalysisoflowaltitudeunstableapproach AT yangjiao eventdetectionandspatiotemporalanalysisoflowaltitudeunstableapproach AT rongshunhuang eventdetectionandspatiotemporalanalysisoflowaltitudeunstableapproach AT binbinlu eventdetectionandspatiotemporalanalysisoflowaltitudeunstableapproach |