Yan Zhou
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Yan Zhou has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Pei Zhu
College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2 shared publications - Quan Shao
College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2 shared publications - Mengxue Shao
National Key Laboratory of Helicopter Aeromechanics, Nanjing University of Aeronautics and Astronautics , Nanjing 210016, China
1 shared publication - Yan Ma
College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
1 shared publication
Latest Publications
- Open Access
- 11 November 2020
- Published by MDPI AG in Sustainability
- Vol. 12 (22) , 9357
Spatiotemporal Analysis of Environmental Factors on the Birdstrike Risk in High Plateau Airport with Multi-Scale Research
The aircrafts’ engine performance deteriorates sharply during the take-off and landing at high plateau airport. This situation increases the take-off or landing distance, aggravating the hidden danger of birdstrikes at high plateau airport. This paper first used GIS to classify and rasterize the bird data and calculated the monthly Birdstrike Risk Index (BRI) within 6, 13, and 25 km radii of Lhasa Airport, based on the bird observation data of Tibet and the birdstrike data of Lhasa Airport from 2015 to 2019. The spatiotemporal relationships between the BRI and the environmental factors around Lhasa Airport were compared by the Geographically or Temporally Weighted Regression (GWR or TWR) model and Geographically and Temporally Weighted Regression (GTWR) model. The results showed that the temporal nonstationary effect of environmental factors was more significant than that of spatial nonstationary at Lhasa Airport. Besides, the composition of land types had positive impacts on birdstrike risk within the 6 km radius, and this scope was broader than that of the plain airport. Within the 13 km and 25 km ranges, the water distribution and the altitude during dry season also positively impacted birdstrike risk. Moreover, the key factor to birdstrike risk was the water distribution in December.
- 11 November 2020
- Published by MDPI AG in Sustainability
- Vol. 12 (22) , 9357
Open AccessSpatiotemporal Analysis of Environmental Factors on the Birdstrike Risk in High Plateau Airport with Multi-Scale Research
The aircrafts’ engine performance deteriorates sharply during the take-off and landing at high plateau airport. This situation increases the take-off or landing distance, aggravating the hidden danger of birdstrikes at high plateau airport. This paper first used GIS to classify and rasterize the bird data and calculated the monthly Birdstrike Risk Index (BRI) within 6, 13, and 25 km radii of Lhasa Airport, based on the bird observation data of Tibet and the birdstrike data of Lhasa Airport from 2015 to 2019. The spatiotemporal relationships between the BRI and the environmental factors around Lhasa Airport were compared by the Geographically or Temporally Weighted Regression (GWR or TWR) model and Geographically and Temporally Weighted Regression (GTWR) model. The results showed that the temporal nonstationary effect of environmental factors was more significant than that of spatial nonstationary at Lhasa Airport. Besides, the composition of land types had positive impacts on birdstrike risk within the 6 km radius, and this scope was broader than that of the plain airport. Within the 13 km and 25 km ranges, the water distribution and the altitude during dry season also positively impacted birdstrike risk. Moreover, the key factor to birdstrike risk was the water distribution in December.
- Open Access
- 4 September 2020
- Published by MDPI AG in Sustainability
- Vol. 12 (18) , 7235
Key Factors Assessment on Bird Strike Density Distribution in Airport Habitats: Spatial Heterogeneity and Geographically Weighted Regression Model
Although the factors influencing bird strikes have been studied extensively, few works focused on the spatial variations in bird strikes affected by factors due to the difference in the geographical environment around the airport. In this paper, the bird strike density distribution of different seasons affected by factors in a rectangular region of 800 square kilometers centered on the Xi’an Airport runway was investigated based on collected bird strike data. The ordinary least square (OLS) model was used to analyze the global effects of different factors, and the Geographically Weighted Regression (GWR) model was used to analyze the spatial variations in the factors of bird strike density. The results showed that key factors on the kernel density of bird strikes showed evident spatial heterogeneity and the seasonal difference in the different habitats. Based on the results of the study, airport managers are provided with some specific defense measures to reduce the number of bird strikes from the two aspects of expelling birds on the airfield area and reducing the attractiveness of habitats outside the airport to birds, so that achieve the sustainable and safe development of civil aviation and the ecological environment.
- 4 September 2020
- Published by MDPI AG in Sustainability
- Vol. 12 (18) , 7235
Open AccessKey Factors Assessment on Bird Strike Density Distribution in Airport Habitats: Spatial Heterogeneity and Geographically Weighted Regression Model
Although the factors influencing bird strikes have been studied extensively, few works focused on the spatial variations in bird strikes affected by factors due to the difference in the geographical environment around the airport. In this paper, the bird strike density distribution of different seasons affected by factors in a rectangular region of 800 square kilometers centered on the Xi’an Airport runway was investigated based on collected bird strike data. The ordinary least square (OLS) model was used to analyze the global effects of different factors, and the Geographically Weighted Regression (GWR) model was used to analyze the spatial variations in the factors of bird strike density. The results showed that key factors on the kernel density of bird strikes showed evident spatial heterogeneity and the seasonal difference in the different habitats. Based on the results of the study, airport managers are provided with some specific defense measures to reduce the number of bird strikes from the two aspects of expelling birds on the airfield area and reducing the attractiveness of habitats outside the airport to birds, so that achieve the sustainable and safe development of civil aviation and the ecological environment.