Airports In China Research Articles

Differential effect of aircraft noise on the spectral-temporal acoustic characteristics of frog species

Human activities worldwide are increasingly releasing low-frequency noise into the environment. Anthropogenic noise imposes a novel stress for wild animals and has become an increasing global concern. Many animals have been found to mitigate noise disturbance by modifying their acoustic parameters, yet the calling behaviours of species that breed near airports have not been explored in detail, especially for amphibians. Here, we measured the environmental noise of a swamp close to the runway at Haikou Meilan Airport in China. We also recorded the calls of four anuran species that reproduce in this swamp, and we measured the sound pressure levels of each focal species. These frogs vary in their call amplitude and possess disparate spectral and temporal traits. We show that two frog species characterized by lower frequency calls increase their call frequency when an airplane takes off. Moreover, three anuran species characterized by higher call rates significantly reduce their call rates (or call efforts) in response to airplane flyby. These results suggest that animals’ behavioural adaptation to human-made noise may be species specific. Because call frequency and call effort have close relationships with reproductive success, we deduce that such noise-induced behaviour adjustments may influence the fitness of taxa that depend on communication by sound. • Low-frequency frogs increase their call frequency when an aircraft takes off. • Frogs that have more temporal overlap with noise decrease their call activity. • Anuran behavioral responses to human-made noise are species specific. • Aircraft noise may affect the reproductive success of frog species.

Extracting built-up land area of airports in China using Sentinel-2 imagery through deep learning

In China, airports have a profound impact on people’s lives, and understanding their dimensions has great significance for research and development. However, few existing airport databases contain such details, which can be reflected indirectly by the built-up land in the airport. In this study, a deep learning-based method was used for extraction of built-up land of airports in China using Sentinel-2 imagery and for further estimating their area. Here, a benchmark generation method is introduced by fusing two reference maps and cropping images into patches. Following this, a series of experiments were conducted to evaluate the network architectures and select the positive impact bands in Sentinel-2 imagery. A well-trained model was used to extract the built-up land for China airports, and the relationship between China airports’ built-up land and the carrying capacity of air transportation was further analysed. Results show that ResUNet-a outperformed U-Net, ResUNet, and SegNet, and the B2, B4, B6, B11, and B12 bands of Sentinel-2 had a positive impact on built-up land extraction. A well-trained model with an overall accuracy of 0.9423 and an F1 score of 0.9041 and 434 China airports’ built-up land was extracted. The four most developed airports are located in Beijing, Shanghai, and Guangzhou, which matches China’s political and economic development. The area of built-up land influenced the passenger throughput and aircraft movements. The total area influenced the cargo throughput, and we found a certain correlation among the built-up land, carrying capacity, and nighttime light.

Aircraft Trajectory Clustering in Terminal Airspace Based on Deep Autoencoder and Gaussian Mixture Model

The aircraft trajectory clustering analysis in the terminal airspace is conducive to determining the representative route structure of the arrival and departure trajectory and extracting their typical patterns, which is important for air traffic management such as airspace structure optimization, trajectory planning, and trajectory prediction. However, the current clustering methods perform poorly due to the large flight traffic, high density, and complex airspace structure in the terminal airspace. In recent years, the continuous development of Deep Learning has demonstrated its powerful ability to extract internal potential features of large dataset. Therefore, this paper mainly tries a deep trajectory clustering method based on deep autoencoder (DAE). To this end, this paper proposes a trajectory clustering method based on deep autoencoder (DAE) and Gaussian mixture model (GMM) to mine the prevailing traffic flow patterns in the terminal airspace. The DAE is trained to extract feature representations from historical high-dimensional trajectory data. Subsequently, the output of DAE is input into GMM for clustering. This paper takes the terminal airspace of Guangzhou Baiyun International Airport in China as a case to verify the proposed method. Through the direct visualization and dimensionality reduction visualization of the clustering results, it is found that the traffic flow patterns identified by the clustering method in this paper are intuitive and separable.

Short review of concepts and practices in green airports in China

Becoming a green airport is an inevitable trend of future airport construction. In recent years much effort has been put towards developing green airports in China. This paper reviewed the evolution of the concepts of green airports, analyzed the domestic green airport projects according to the publicity material, to provide some useful suggestions for the future development of green airports in China.

National level assessment of using existing airport infrastructures for photovoltaic deployment

The airport is one of the most fundamental infrastructures in our society, its terminal buildings and parking lots are ideal locations for photovoltaic (PV) installation. The future trend of the electrification of the aviation and automobile industries will increase the electricity demand at airports calls for the integration of PV systems with airport infrastructure. Understanding the benefits of airport PV systems is crucial for the stakeholders including investors, project developers and policymakers to promote PV sector development. Thus, evaluation of the PV potential and relevant economic performance of airports is essential. Combined with the geographic information system (GIS), the PV potential of the civil airports in China is investigated. The results show that potential PV capacity of China’s 239 civil airports reaches up to 2.50 GW. The annual electricity demand of the aviation industry in 8 provinces can be self-satisfied via airport PV generation. Detailed economic analysis shows that all airport PV systems are profitable through appropriate investment and operation strategies.

A data-driven flight schedule optimization model considering the uncertainty of operational displacement

The slot allocation mechanism aims to match flight demand and airport resources from a strategic perspective. However, current research mainly focused on airlines' interests, ignoring the influencing factors that lead to primary delays, which makes the temporal and spatial distribution of flight schedules unreasonable. This paper proposes a data-driven approach to reduce operational delays at a strategic level by considering operational efficiency and airline interests. The displacement probability distribution between the actual execution time and the scheduled time is first mined from the historical operation data. We then develop a model with the ultimate objective of improving the punctuality rate and reducing the actual operational delays by minimizing the total operational displacement. In addition to considering the basic operational restrictions of airports, the model also introduces the corridor capacity of the terminal airspace surrounding an airport, reducing the delay caused by the corridor flow control to a certain extent. The proposed model is applied to Hangzhou Xiaoshan International Airport in China. The experimental results suggest that the optimized flight schedule can significantly reduce flight delay, conforms to airport operational restrictions, and maintains flight connectivity.

Traffic congestion mechanism in mega-airport surface

In this paper, guided by macroscopic cell transmission models, a cell transmission model of aircraft traffic flow on runways, taxiways and aprons was established to deduce and analyze the evolution rules of an airport surface traffic. The model was simulated by adopting data from a large domestic airport in China. The relationship between three parameters of traffic flow on taxiways was evaluated, and the airport surface traffic flow characteristics were analyzed. Moreover, this paper macroscopically analyzed the characteristics of spatial–temporal distribution of airport surface recurrent and non-recurrent traffic congestion. Simulation results showed that arrival rates and pushback rates had significant influence on the formation and dissipation of recurrent traffic congestion in different phases of the surface aircraft traffic flow. When the arrival rate was 0.3 aircraft/minute and the pushback rate was 0.23 aircraft/minute, the speed of aircraft on taxiways was high, the density and flow were large, and the aircraft had a high degree of obstacle-free taxiing. At this time, the airport ran smoothly and the surface network operation efficiency was high. Compared with the arrival rate, the outward expansion trend of each parameter was more obvious when the pushback rate changed. Parallel taxiways are less robust than apron taxiways and connect taxiways.

Characterizing Flight Delay Profiles with a Tensor Factorization Framework

In air traffic and airport management, experience gained from past operations is crucial in designing appropriate strategies when facing a new scenario. Therefore, this paper uses massive spatiotemporal flight data to identify similar traffic and delay patterns, which become critical for gaining a better understanding of the aviation system and relevant decision-making. However, as the datasets imply complex dependence and higher-order interactions between space and time, retrieving significant features and patterns can be very challenging. In this paper, we propose a probabilistic framework for high-dimensional historical flight data. We apply a latent class model and demonstrate the effectiveness of this framework using air traffic data from 224 airports in China during 2014–2017. We find that profiles of each dimension can be clearly divided into various patterns representing different regular operations. To prove the effectiveness of these patterns, we then create an estimation model that provides preliminary judgment on the airport delay level. The outcomes of this study can help airport operators and air traffic managers better understand air traffic and delay patterns according to the experience gained from historical scenarios.

Reclaimed-Airport Surface-Deformation Monitoring by Improved Permanent-Scatterer Interferometric Synthetic-Aperture Radar: A Case Study of Shenzhen Bao'an International Airport, China

Reclaimed airports usually have fragile geological structures and are susceptible to the uneven ground settlements caused by filling-material consolidation, underground construction, and dynamic loading from takeoff and landing of aircrafts. Therefore, deformation monitoring is of great significance to the safe operation of reclaimed airports. This study adopts an improved permanent-scatterer interferometric synthetic-aperture radar strategy to map the spatiotemporal deformation of Shenzhen Bao'an International Airport in China using ascending and descending Envisat/ASAR data acquired from 2007 to 2010 and Sentinel-1 data from 2015 to 2019. The results show that uneven settlements of the airport concentrate in the new reclaimed land. Then we explore the settlement characteristics of each functional area. Furthermore, we separate out the dynamic-load settlement of runway No. 2 and confirm the settlements caused by dynamic load. This study provides new ideas for studying deformation in similar fields, and technical references for the future construction of Shenzhen Airport.

Research on evaluation of airport service quality based on improved AHP and Topsis methods

The aim of this paper is to propose a multi-criteria decision-making approach, combining the ‘analytic hierarchy process’ (AHP) and ‘technique for order preference by similarity to ideal solution’ (Topsis) for the quantitative assessment of airport service quality so as to increase the objectivity and reliability of the results. The criteria hierarchy with quantitative indicators is established to make up for the deficiencies of previous evaluation criteria. Some of these indicators are improvements to the qualitative indicators that are commonly mentioned, and some have been only rarely taken into account in previous research studies or evaluation activities, but are also very important. An empirical study for evaluating the service quality of four major international airports in China is presented to illustrate the superiority and rationality of the criteria system and method. This comprehensive method not only helps to obtain the overall ratings of the airports, as well as the specific weaknesses and advantages in particular service items, but also improves the efficiency and increases the credibility and objectivity of the results. Finally, some interesting conclusions are obtained and some targeted measures are offered to the four airports for improvement of the service level.

How does China keep COVID-19 outside its boarder? First-hand experience of medical staff at an international airport in China.

How does China keep COVID-19 outside its boarder? First-hand experience of medical staff at an international airport in China.

A Tabu Search-Based Algorithm for Airport Gate Assignment: A Case Study in Kunming, China

An airport gate is the core resource of an airport operation, which is an important place for passengers to get on and off the aircraft and for maintaining aircraft. It is the prerequisite for other related dispatch. Effective and reasonable allocation of gates can reduce airport operating costs and increase passenger satisfaction. Therefore, an airport gate assignment problem (AGAP) needs to be urgently solved in the actual operation of the airport. In this paper, considering the actual operation of the airport, we formulate an integer programming model for AGAP by considering multiple constraints. The model aims to maximize the number of passengers on flights parked at the gate. A tabu search-based algorithm is designed to solve the problem. In the process of algorithm design, an effective initial solution is obtained. A unique neighborhood structure and search strategy for tabu search are designed. The algorithm can adapt to the dynamic scheduling of airports. Finally, tests are performed using actual airport data selected from Kunming Changshui International Airport in China. The experimental results indicate that the proposed method can enhance the local search ability and global search ability and get satisfactory results in a limited time. These results provide an effective support for the actual gate assignment in airport operations.

Calibrating a Local Civil Airport Runway Residual Life Prediction Model Using Random Effects and Joint Estimation

Existing runway residual life prediction models need to be modified using the historical data of evaluated airports during evaluation and management for civil airports in China. If the data measured in the field and the historical data used for model calibration do not represent the actual historical performance of the evaluated airport, the predicted performance of the revised model might be poor. This study used measured pavement performance data for local civil airports in Henan Province from 2007 to 2017. The joint-estimation method was used to establish a functional residual life prediction model for local civil airport pavement with another dataset. A functional residual life prediction model for airport pavement was proposed in consideration of the influence of aircraft traffic and the thickness of the pavement surface layer. Taking into account the differences between samples in the two datasets, nonlinear regression with random-effect analysis and joint estimation were used to explain unobserved heterogeneity at the sample level and heteroscedasticity in the dataset. Based on the results of the established residual life prediction model, the marginal effect of the model parameters and the prediction performance of the entire model were analyzed with the measured data from the local airport pavement. Finally, the engineering applicability of the calibrated prediction model for pavement residual life was further evaluated.

Planning of arrival and departure routes in terminal maneuvering area based on high dimensionality reduction environment modeling method

The efficient design of arrival and departure routes in the terminal maneuvering area plays a key role in increasing airport capacity and reducing traffic congestion. In our study, we establish an arrival and departure route planning model in the terminal maneuvering area, taking into account the airspace environmental constraints and aircraft operational constraints. Then the three-dimensional environment modeling method with a high degree of dimensionality reduction is introduced to improve the efficiency of route planning, and routes are planned sequentially using the A* algorithm in a dimensionally reduced environment. Numerical simulation tests, performed on the terminal maneuvering area of Chengdu Shuangliu Airport in China, show the effectiveness of the proposed method. Each route is given two planning schemes considering the maximum and minimum takeoff or descent slope, and a total of seven routes is generated.

Measuring Operational Performance of Major Chinese Airports Based on SBM-DEA

This study analyzes the sustainable feasibility of major airports in China in terms of airport operational efficiency (AOE). As AOE should be measured by economic performance as well as qualitative service management such as delay rate abatement, our study uses a multi-input/output slack-based data envelopment analysis model. We find that the 37 major airports in China have very low AOE levels, with an average of 48.2% during the study period of 2016–2019, implying great potential to enhance their efficiency. Even though the AOE trend is increasing upwards, it is still very much behind in terms of global standards. Moreover, this upward trend may come from external factors in the commercially driven eastern region airports and politically supported western region airports, and the AOE gap with airports in the central region is becoming larger. This implies that most airports in China are not yet self-sustaining. There are two ways for these airports to enhance AOE: more investment in infrastructure, such as airport facilities, and management upgrades from peer-learning efforts. We examined the feasibility of these two optimal paths and found that there is no need for decreasing returns to scale, implying that most of the airports can improve their AOE through additional investment, except for the eight airports with constant returns to scale, such as Beijing and Guangzhou. Moreover, each of the individual airports should learn from the top benchmarking airports on the production frontier. This study emphasizes the role of qualitative service performance and concludes that customized, self-sustaining innovation is required for all of the 37 major airports in China.

Real-time Screening of Specimen Pools for Coronavirus Disease 2019 (COVID-19) Infection at Sanya Airport, Hainan Island, China.

A 10:1 pooled test strategy on-site at an airport of China was pursued, resulting in increased test throughput, limited use of reagents, and increased testing efficiency without loss of sensitivity. This testing approach has the potential to reduce the need for contact tracing when the results are delivered first time.

Fuzzy Comprehensive Evaluation of the Apron Control Transfer Management Evaluation System

The apron operation management evaluation is one of the measures to test the effect of apron control transfer management. Due to the relatively short implementation time of apron control transfer management in China, there is no comprehensive and unified evaluation system to evaluate the effects of domestic airports. Therefore, this study uses text mining to extract the high-frequency words or phrases from 300 pieces of literature of Web of Science Core Collection and 13 official documents of Civil Aviation Administration of China, and 140 effective high-frequency words or phrases are obtained after screening. Then, high-frequency words or phrases with similar meanings are classified. Apron control transfer management evaluation system which contains four main criteria elements and 25 subcriteria indices is sorted and established. Finally, the method of combining the analytic hierarchy process and fuzzy comprehensive evaluation is used to evaluate the current status of apron operation management of A airport in China. The fuzzy comprehensive evaluation result is good, and the weight results of the main criteria elements show that the human elements are the most concerned by managers.

Airports and air pollutions: Empirical evidence from China

Civil aviation is a crucial transportation mode, which plays a crucial role in air pollution. This study investigates the effect of aircraft frequency on the PM2.5 level. This study evaluates whether flight frequency has a significant positive effect on air pollution based on the monthly data of aircraft movements from 59 major airports in China from January 2014 to December 2017 by employing the two-way fixed effects model. The effect occurs mainly through two channels, namely, the aircraft and the emissions while commuting to the airports. The former is significantly positive, whereas the latter is significantly negative. This study utilizes the spatial econometric methods to consider the spatial correlation. Results show that after considering the spatial correlation, the aircraft frequency also has a substantial effect on the PM2.5 level. These results indicate that decision-makers should provide attention to air pollution driven by aircraft and emissions while commuting to the airport. This study also calls for the concern of the spatial correlation in the reduction of air pollution. Moreover, the study provides a distinctive contribution to the relative field by identifying the influence of each channel and considering the spatial correlation.

Border Quarantine Measures and Achievement of COVID-19 Control in Taiwan

Since December 21, 2019, on-board inspection had been implemented on direct flights from Wuhan, China, marking the beginning of boarder quarantine challenges in respond to COVID-19 pandemic. In line with the development of the international epidemic, the Central Epidemic Command Center gradually expanded entry restrictions and post-entry quarantine requirements. Since March 19, 2020, all foreign nationals had been prohibited from entering Taiwan. Passengers eligible for entry were required to undergo home quarantine for 14 days. Upon arrival, passengers were required to declare their symptoms and travel history, and to receive fever screening and health assessment. Throat swab specimens were collected from those who presented symptoms at the airport or in the hospital, and then these passengers stayed in a centralized quarantine facility to wait for testing results. In addition, aiming at reducing risks originated from crowds and frequent movement, only aircrafts from five airports in China were allowed to enter Taiwan. Also, all connecting flights were suspended, and cruises and cross-strait passenger liners were banned from calling at ports of Taiwan. For front-line officers at ports of entry, health monitoring and protection guidelines were developed to protect their safety. In order to ensure safety and security of air and sea transport, the competent authorities in charge of transportation have established an epidemic prevention and management mechanism for air and sea transport respectively. Over 184,000 home quarantine notices had been issued by border quarantine authorities. More than 80% of the inbound travelers completed the declaration via Entry Quarantine System, greatly improving timeliness and accuracy of information required for further epidemic prevention and control in community. With on-board quarantine and health surveillance system for entry, not only the first confirmed case in Taiwan, but also more than one-third of imported cases were detected through border quarantine, sparing more capacity for domestic response and preparedness for medical resources and medical systems and therefore alleviating pressure on epidemic prevention and control in the community. Despite continuous and serious epidemic and significant challenges ahead, Taiwan keeps on implementing various quarantine measures in accordance with the principle of ＂strict risk control at border ＂ to comprehensively protect border security.

Innovations at Beijing Daxing International: the world’s biggest airport terminal

Beijing Daxing International, which officially opened in September 2019 after 5 years of construction, is the largest airport in China and has the world’s biggest airport terminal. It is also the first to feature double-deck arrival and departure lounges and an underground high-speed rail service. Engineering highlights include a world-class seismic base isolation system, a long-span irregular curved node truss structure, a glazed roof with 12 800 panes, eight hyperboloid C-shaped columns as the main load-bearing elements and multiple energy-saving systems.