Analysis of Influence Factors for Unstable Approach in Fine⁃Grained Scale

XIE Jiayi; SUN Huabo; WANG Chun; LU Binbin

doi:10.13203/j.whugis20190120

Volume 46 Issue 8

Aug. 2021

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Geomatics and Information Science of Wuhan University > 2021 > 46(8): 1201-1208. > DOI: 10.13203/j.whugis20190120

XIE Jiayi, SUN Huabo, WANG Chun, LU Binbin. Analysis of Influence Factors for Unstable Approach in Fine⁃Grained Scale[J]. Geomatics and Information Science of Wuhan University, 2021, 46(8): 1201-1208. DOI: 10.13203/j.whugis20190120

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Analysis of Influence Factors for Unstable Approach in Fine⁃Grained Scale

1.
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
2.
Institute of Aviation Safety, China Academy of Civil Aviation Science and Technology, Beijing 100028, China

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The National Natural Science Foundation of China U1833201

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Author Bio:
XIE Jiayi, master, specializes in spatial statistics and geographically weighted models.JiayiXie@whu.edu.cn
Corresponding author:
LU Binbin, PhD, associate professor. E-mail: binbinlu@whu.edu.cn
Received Date: November 19, 2019
Published Date: August 04, 2021

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Abstract

Abstract

Objectives Unstable approach is one of the most important risks that threatens the flight safety during the descending phase, and is affected by factors such as meteorological and topographical that have strong spatial heterogeneity.
Methods In this article, we use the big data of quick access recorder (QAR) that collected by China Academy of Civil Aviation Science and Technology (CAST) to detect the unstable approach happening in Airbus and Boeing aircrafts in January 2018, and utilize exploratory spatial data analysis methods to explore the spatial patterns and relative influencing factors. In addition, Pearson correlation coefficient and geographically weighted correlation coefficient are used to investigate the pair-wise relationships between unstable approach and factors.
Results Experimental results show that unstable approaches of different aircraft types are distinctive in spatial distributions, and unstable approach of same aircraft type spatially varies in different regions in China. Besides, the correlation description in the fine-grained scale is better than in the global scale.
Conclusions This study provides an important research basis and guidance for the future quantitative cause analysis, which is significant for avoiding such risks.
- unstable approach,
- flight safety,
- spatial heterogeneity,
- space-time cube,
- geographically weighted summary statistics

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