Beijing Capital Research Articles

Real Time Building Evacuation Modeling with an Improved Cellular Automata Method and Corresponding IoT System Implementation

Facility emergence evacuation is often a complicated process under extreme conditions. Most of the buildings today use pre-installed signages to guide the emergence evacuation. However, these guidances are sometimes insufficient or misleading, particularly for evacuating from high-rise buildings or complex buildings, such as schools, hospitals, and stadiums. Following a planned route may lead the crowd to move towards dangers, such as smoke and fire. The future emergency guidance system should be more intelligent and be able to guide people to evacuate with a higher survival possibility. This study proposes a real-time building evacuation model with an improved cellular automata (CA) method. This algorithm combines cellular automata with the potential energy field (PEF) model in fluid dynamic theory (FDT) to choose safe paths for the crowd and reduce the possibility of stampedes. Custom-designed wireless sensors, artificial intelligence (A.I.) enhanced surveillance cameras, intelligent emergency signage systems, and edge computing servers are used to sample fire and crowd data, operate the intelligent evacuation algorithm, and guide the crowd with the signage system in real-time conditions. In addition, we performed the algorithm simulation on a two-dimensional plane generated based on the building structure of the Beijing Capital Airport Hospital. The evacuation drill simulations show that the average escape time is significantly shortened with optimal real-time guidance. In one case, a 72% reduction in evacuation time is achieved compared with evacuation using pre-installed signages. The results also demonstrated that the proposed model and system’s evacuation time reduction performance is particularly good in crowded buildings, such as schools or stadiums.

A Multicomponent Temporal Coherence Model for 3-D Phase Unwrapping in Time-Series InSAR of Seasonal Deformation Areas

3-D phase unwrapping (PU) methods based on the 2-D linear temporal coherencemodel have been widely used in time-series interferometric synthetic aperture radar (TS-InSAR) for measuring topography and monitoring subtle deformation. However, the linear temporal coherencemodel can not characterize the coherence of highly coherent pixels accurately in seasonal deformation areas, where nonlinear deformation is deterministic and nonnegligible. Especially, for urban areas with groundwater or thermal dilation seasonal changes or permafrost regions, the nonlinear deformation is usually associated with periodic temperature changes. In this work, a general multi-component temporal coherence model, which considers multiple components including the seasonal deformation, is proposed for 3-D PU of seasonal deformation areas. Moreover, the uncertainty evaluation criterion, based on Cramér–Rao bound (CRB), is derived for TS-InSAR. The experimental results, obtained by applying the multi-component temporal coherence model to a data set acquired from January 2012 to February 2016 over the Beijing Capital International Airport area, confirm the effectiveness of the proposed method. High phase consistency, accurate corrected digital elevation model (DEM) and deformation information monitoring with high-density and high-coverage PS pixels are achieved. Under the same iterations and TS-InSAR procedure, the enhanced performance by the proposed model is illustrated by comparing with that of linear model in terms of phase consistency of 3-D phase unwrapping, PSCs selection at each step, and final results evaluation. In summary, the number of phase-consistency edges after 3-D PU is increased by about 15%, the number of final PS pixels selected with the same coherence threshold constraint is increased by about 10%, and more PS pixels provide a low uncertainty in residual topography, mean deformation velocity and seasonal amplitude estimation.

Formation mechanism of pumping-induced earth fissures associated with a pre-existing normal fault, Beijing, China

The Shunyi (SY) earth fissures originated due to groundwater pumping and have caused severe damage to the Beijing Capital International Airport (BCIA) and other infrastructure in Beijing, China. They are distributed along the pre-existing NE-SW trending normal Shunyi-Liangxiang (SL) fault zone, with 1–30 cm vertical offsets. Previous studies of this long-term ground displacement have concluded that a subsidence bowl has formed on the footwall (northwestern side) of the SL fault in the BCIA. However, based on our observations, the relative subsidence occurred exclusively on the southeastern side, behaving like the activation of the SL fault. This complex deformation pattern has led to the formation mechanism of the SY earth fissures remaining unclear. In this study, two groups of numerical simulations based on the geological and hydrogeological settings of the SY earth fissures were performed. In Scenario I, the pumping load was on the footwall, whereas in Scenario II, the pumping load was on the hanging wall. Our results show that there are always two areas in the faulted model that have undergone pumping-induced subsidence. The first subsidence area indicates that the actual regional subsidence bowl occurred extensively around the pumping well. This subsidence was blocked by the pre-existing normal fault zone. The second subsidence area is localized and occurred abruptly in the hanging wall adjacent to the fault zone regardless of the effect of the position of the pumping load. This localized differential subsidence, representing the secondary surface faulting, was accompanied by earth fissure formation due to concentration of the surface shear strain. These simulation results agree with the actual land deformation across the SY earth fissures. Furthermore, our results suggest that both the formation location and deformation pattern of the SY earth fissures were dependent upon the characteristics of the pre-existing SL fault zone. This is mainly attributed to the fact that the fault zone has a lower resistance than the surrounding materials. Our findings reveal the formation mechanism of the SY earth fissures and provide a new understanding of pumping-induced earth fissures in other faulted areas.

A novel hybrid method for flight departure delay prediction using Random Forest Regression and Maximal Information Coefficient

Flight departure delay prediction is one of the most critical components of intelligent aviation systems. The accurate prediction of flight departure delays can provide passengers with reliable travel schedules and enhance the service performance of airports and airlines. This article proposes a hybrid method of Random Forest Regression and Maximal Information Coefficient (RFR-MIC) for flight departure delay prediction. Random Forest Regression and Maximal Information Coefficient are inherently fused in terms of Information Consistency. Furthermore, this article focuses on utilizing flight information on multiple air routes for flight departure delay prediction. To validate the proposed flight departure delay prediction model, a numerical study is conducted using flight data collected from Beijing Capital International Airport (PEK). The proposed RFR-MIC model exhibits good performance compared with linear regression (LR), k-nearest neighbors (k-NN), artificial neural network (ANN), and standard Random Forest Regression (RFR). The results also show that flight information on multiple air routes can certainly improve the accuracy of flight departure delay prediction.

Services and surveillance during the pandemic lockdown: Residents’ committees in Wuhan and Beijing

The COVID-19 pandemic caused a lockdown of Wuhan, and strict control was imposed in many major Chinese cities, including the national capital of Beijing. Residents’ committee workers at the grass-roots level have played a critical role in the enforcement of the government’s pandemic prevention and control measures, through their day-to-day service and surveillance as local community managers. This article examines their work in Wuhan and Beijing neighbourhoods during the most critical periods of the outbreak, from late January to June 2020, and the challenges the workers faced as executors of the government’s community-based prevention policy. The two cities have developed different community strategies because of very different epidemiological situations and city functions.

Make Cloud Out of Air: The Allocation of Infrastructure Management Responsibilities and Regional Economic Development

Transportation infrastructure promotes regional economic development. Previous research mainly focuses on the construction of infrastructure, and the maintenance and operation of infrastructure to a large extent is ignored. However, infrastructure is a kind of capital that delivers the flow of service for the whole economy. To fully exploit transportation infrastructure to raise economic development, it is important to utilize the local information and improve the operational efficiency of infrastructure.In 2003, due to the substantial fiscal burden, Civil Aviation Administration of China decided to transfer the ownership and management responsibilities of almost all existing airports, except the Beijing Capital Airport and the airports in Tibet, to the provincial governments. This reform effectively reduced the distance to monitor the agent, and was expected to improve the operational efficiency of airports. This paper studies the causal impact of this reform on regional economic development. We employ a triple difference estimation to evaluate the impact of this reform on city-level total factor productivities（TFP）. In particular, we consider the variation in three dimensions: time, whether a city has an airport, and the reliance on air-travel, defined by the ratio of firms in air-travel-related industries to total number of firms in a city. It is shown that after the reform, the cities with airports significantly increased the TFP by 9.4%. Moreover, the cities with airports and higher reliance on air-travel-related industries enjoyed an additional 3.1% increase in TFP. A variety of robustness checks and placebo tests confirm the causal impact. Heterogeneity analysis shows that the benefits of airport localization reform mainly leave to the Eastern and Central Area. Further analysis suggests that the localization reform raises the complementary transportation infrastructure investment, and boosts the export.This research indicates that the management of transportation infrastructure should consider the incentives and information of different agents, and empower the local government to match the rights with responsibilities and interests. This would substantially improve the efficiency of infrastructure, and fully integrate the infrastructure into the regional economy.

Assessment of the economic cascading effect on future climate change in China: Evidence from agricultural direct damage

The agricultural sector is extremely vulnerable to climate change and also plays a very important role in the operation of the entire economic system, leading many studies to evaluate the possible agricultural direct economic damage (ADED) of climate change. However, this damage may have an amplification impact through the intricate industrial linkages that exist among sectors, and this impact may be even greater than the original damage. Therefore, to elucidate the economic cascading effect (ECE) in China caused by ADED and industrial linkage, this paper used the ARIO model to evaluate the total ECE and analyse the differences in the 19 sectors by taking the ADED under future annual mean temperature (AMT) increases of 1–5 °C as the input condition and adjusting the exogenous parameters to enhance the adaptability of the model; the goal was to assess the economic impact of climate change in China. The results show that (i) there is a significant amplifying impact of ECE due to industrial linkage under the influence of warming, ECE will be 4.24–5.25 times that of ADED, and the total economic impact (ADED + ECE) will exceed the GDP of the Chinese capital of Beijing in 2012 when the AMT increases by 1.5 °C, while it will exceed one tenth of China’s GDP when it increases by 4 °C. (ii) Manufacturing will be the sector most affected by the industrial linkage under ADED, which accounts for 26.58% of total ECE, followed by agriculture (10.39%) and construction (8.5%). (iii) The decrease in cultivated land area will have a significant impact on the economy; when it is reduced to the minimum demand (1.41% less than 2012), ADED increases by 1.65 times and ECE increases by 2.35 times. This paper aims to provide a new perspective from which to evaluate the economic impact of climate change by studying ECEs behind sectoral interactions.

Optimal scheduling of airport ferry vehicles based on capacity network

For daily airport operations, the insufficient number and the improper scheduling of ground support vehicles are the main causes of flight delays. In this paper, a novel network model is proposed to complement the optimal scheduling of ferry vehicles for the flight ground support service. In the process of model construction, we first innovatively construct a ferry vehicle capacity network by having the introduced virtual flights and the ferry vehicle depot as nodes, in which the directed edges indicate that the two nodes associated may be consecutively served by the same ferry vehicle. Based on the capacity network, a mixed integer programming model is constructed to minimize the number of ferry vehicles needed. In addition, this paper shows that the mixed integer programming is equivalent to a linear programming when the service start time of each flight is fixed, which makes the solving process more efficient, and the linear programming model can be applied to solve the minimum node-disjoint path cover of directed acyclic graphs. The efficiency and accuracy of the method are validated by the actual flight data obtained from Beijing Capital International Airport. This study will provide a methodological reference for the optimal scheduling of airport ferry vehicles.

Experiencing Graduated Intimacies during Lockdown (Fengcheng)

In this article, I examine the ways in which the recent, nationwide ‘lockdown’ (fengcheng) in China, caused by the unprecedented COVID-19 pandemic, has abruptly reshaped daily intimacy practices of urban residents. Highlighting the lockdown in a southeast coastal city in the broader context of China’s post-socialist transformations, I propose that class distinctions have profoundly reconfigured local citizens’ daily experiences, producing a system of what might be termed ‘graduated intimacies’. To further contextualize these urban citizens’ experiences of intimacy under the current transnational geo-biopolitics associated with the pandemic, I provide a reflexive and comparative ethnographic look at the national capital of Beijing. In so doing, I offer a glimpse into the lives of several sets of Chinese citizens at an unexpected historical moment induced by a grave public health crisis extending well beyond China’s national borders.

Diagnosing Subsidence Geohazard at Beijing Capital International Airport, from High-Resolution SAR Interferometry

Beijing Capital International Airport (BCIA) has suffered from uneven land subsidence since 1935, which affects the smoothness of airport runways and seriously threatens the safety of aircrafts. In this paper, a spaceborne interferometric synthetic aperture radar (InSAR) with high-resolution Cosmo-SkyMed SAR data was utilized at BCIA for the first time to diagnose the subsidence hazard. The results show that subsidence is progressing at BCIA at a maximum rate of 50 mm/year, which is mainly distributed in the northwest side of the airport. It was found that the Shunyi-Liangxiang fault directly traverses Runway2 and Runway3 and causes uneven subsidence, controlling the spatial subsidence pattern to some degree. Four driving factors of subsidence were investigated, namely: the over-exploitation of groundwater, active faults, compressible soil thickness, and aquifer types. For the future sustainable development of BCIA, the influence of Beijing new airport and Beijing Daxing International Airport (BDIA), was analyzed and predicted. It is necessary to take relevant measures to control the uneven subsidence during the initial operation of BDIA and conduct long-term monitoring to ensure the regular safe operation of BCIA. This case demonstrates a remote sensing method of diagnosing the subsidence hazard with high accuracy and non-contact, providing a reliable alternative for the geohazard diagnosis of key infrastructures in the future.

Characteristics and main causes of earth fissures in northeastern Beijing Plain, China

Earth fissures (EF) form in the northeastern Beijing Plain, causing horizontal and vertical displacements of the ground surface and damaging hundreds of buildings and roads. In addition, since 2009, an unprecedented number of cracks with vertical offsets have occurred in the Beijing Capital International Airport (BCIA), which is the busiest airport in China, causing serious financial losses and increasing the risk of air travel. The EF were divided into three groups, including EF1, EF2, and EF3, based on their distribution and deformation patterns. In general, the EF1 and EF2 fissures formed along segments of the NE-SW trending regional normal faults and have large vertical offsets but small widths. The deformation patterns, trenches and geophysical prospecting profiles, demonstrate that the EF1 and EF2 fissures propagated from the preexisting faults. In contrast, the EF3 fissures formed in a disorganized pattern above the paleochannels of the Chaobai River with short lengths and negligible vertical offsets. The monitoring data for the EF1 fissures indicates that the formation and deformation of the EF in the northeastern Beijing Plain were induced by groundwater pumping. The formation processes of the EF1, EF2, and EF3 fissures are classified into two categories: (1) on the existence of preexisting normal faults and (2) on the existence of paleochannels. Two hypothetical conceptual models are presented to illustrate the formation processes.

Identifying competitive position for ten Asian aviation hubs

The Asia-Pacific region has become one of the biggest aviation markets in the world, and increasing numbers of airports in this region are keen to develop into aviation hubs. In order to understand the competitive position of the major Asian airports, this research has selected ten primary airports in the Asia-Pacific, and has identified the markets in which they have an advantage by looking into their connectivity levels in terms of both quantity and quality. Specifically, we have examined indicators that include the Quantity of Viable Connections (QVC), Quality of Viable Connections (QCI), the Hub Connectivity Performance Index (HCPI) and the Hub Efficiency Index (HEI) of the selected airports. The results reveal that China's Beijing Capital Airport (PEK) and Shanghai Pudong Airport (PVG) have higher QVC values than the others. They should therefore continue to develop the North America-China routes. Tokyo Narita Airport (NRT) is found to have the largest HEI for markets as a whole, and should continue to develop the North America-Asia Pacific, North America-Southeast Asia and North America-China routes. Taiwan's Taoyuan Airport (TPE) has the highest HEI for the North America-Southeast Asia market, and should therefore increase the frequency of flights in this market in order to attract more transfer passengers. Since Malaysia's Kuala Lumpur Airport (KUL) has the highest HEI and Singapore's Changi Airport (SIN) the highest QVC for the Asia Pacific-Europe market, both airports should continue to concentrate on this market. The analysis presented in this paper could help airport authorities identify their market positions and strengthen their comparative advantages based on the results.

Detection of Complex Terrain-Induced Wind Shear by Doppler Lidar at Beijing Capital International Airport

In November 2018, the lidar-based wind shear synchronous experiment was performed at Beijing Capital International Airport (BCIA). In this experiment, aiming at the measurement of the terrain-induced wind shear and the wind field around the runway, the glide path scanning mode, and the RHI strategy were conducted alternately. Radial velocity retrieved from the glide path scanning can obviously present the wakes caused by complex terrain (e.g., hills, tall trees, residential and terminal buildings). The Pulse Coherent Doppler Lidar (PCDL) warned the terrain-induced wind shear, which was verified by the pilot report. The wind field structure around the runway under the wake effect and the building shielding effect is also analyzed.

Relationships between experiential cultural distance, experiential relationship quality and experiential future intentions: the case of Mainland Chinese tourists

ABSTRACT This paper aims at exploring the structural relationships between the dimensions of experiential cultural distance (experiential individualism/collectivism, experiential uncertainty avoidance, experiential power distance, experiential masculinity/femininity), the dimensions of experiential relationship quality (experiential trust and experiential satisfaction) and future experiential intentions. A convenience sample of 683 Mainland Chinese tourists who had taken an international trip for leisure purposes in the past 12 months in Shanghai Pudong International Airport, Shanghai Hongqiao International Airport, Beijing Capital International Airport, Guangzhou Baiyun International Airport and Shenzhen Bao’an International Airport was surveyed. Results will assist destination management in developing and implementing market-orientated service strategies to decrease perceptions of experiential uncertainty avoidance, experiential power distance and experiential masculinity and increase perceptions of experiential individualism, experiential trust and experiential satisfaction in order to promote future experiential intentions.

Airport asphalt pavement health monitoring system for mechanical model updating and distress evaluation under realistic random aircraft loads

The performance of airport asphalt pavement gradually deteriorates under aircraft load repetitions. In this study, a framework of airport asphalt pavement health monitoring system was developed to evaluate pavement performance under realistic random aircraft loads. The taxiway of the Beijing Capital International Airport was used as an example, and sensor layout was designed to obtain pavement mechanical responses and identify random aircraft loads. Multi-layered system theory was selected as the mechanical model to simulate airport asphalt pavement structure considering its computational efficiency. Mechanical model updating and distress evaluation based on airport asphalt pavement health monitoring system were discussed. First, in accordance with the theoretical relationship between mechanical responses and moduli derived from the mechanical model, the moduli of the pavement structure layers were back-calculated using measured mechanical responses. The Kalman filtering method was developed to identify modulus parameters that can be used to update the mechanical model. Second, full-field pavement mechanical responses under each load were reconstructed from the mechanical responses of a single point acquired by the sensors based on the updated mechanical model with knowledge of random aircraft loads and modulus parameters. Finally, real-time deterministic pavement distress calculation (cumulative damage from fatigue cracking and rutting) at any point were realized based on transfer functions between mechanical responses and performance. The strategy and process for short-term non-deterministic distress prediction were developed, and non-deterministic pavement distress at any point after multiple random aircraft loads can then be obtained. This study is beneficial for the understanding of airport pavement behavior and decision-making regarding pavement maintenance.

Land Subsidence and Ground Fissures in Beijing Capital International Airport (BCIA): Evidence from Quasi-PS InSAR Analysis

Land subsidence is a global environmental geological hazard caused by natural or human activities. The high spatial resolution and continuous time coverage of interferometric synthetic aperture radar (InSAR) time series analysis techniques provide data and a basis for the development of methods for the investigation and evolution mechanism study of regional land subsidence. Beijing, the capital city of China, has suffered from land subsidence for decades since it was first recorded in the 1950s. It was reported that uneven ground subsidence and fractures have seriously affected the normal operation of the Beijing Capital International Airport (BCIA) in recent years before the overhaul of the middle runway in April 2017. In this study, InSAR time series analysis was successfully used to detect the uneven local subsidence and ground fissure activity that has been gradually increasing in BCIA since 2010. A multi-temporal InSAR (MT-InSAR) technique was performed on 63 TerraSAR-X/TanDem-X (TSX/TDX) images acquired between 2010 and 2017, then deformation rate maps and time series for the airport area were generated. Comparisons of deformation rate and displacement time series from InSAR and ground-leveling were carried out in order to evaluate the accuracy of the InSAR-derived measurements. After an integrated analysis of the distribution characteristics of land subsidence, previous research results, and geological data was carried out, we found and located an active ground fissure. Then main cause of the ground fissures was preliminarily discussed. Finally, it can be conducted that InSAR technology can be used to identify and monitor geological processes, such as land subsidence and ground fissure activities, and can provide a scientific approach to better explore and study the cause and formation mechanism of regional subsidence and ground fissures.

Research on Impact of Airport Service Quality on Passenger Satisfaction: A Comparison of Incheon Airport and Beijing Capital Airport

Research on Impact of Airport Service Quality on Passenger Satisfaction: A Comparison of Incheon Airport and Beijing Capital Airport

Possessing the King of Flowers, and other things at the Qing court

Rendered in paintings and sung in lyric poetry, birds and flowers asserted the mandate of the emperor and defined an imperial aesthetic in eighteenth-century China. Whether it was a peacock from the west or a peony flower from the south, each represented an object–subject relationship that attracted the covetous gaze of the Qing dynasty (1644–1911) court. This study focuses on images of the peony, historically regarded as the “King of Flowers,” to probe the tremendous marshaling of labor and resources that put them to work as possessions. Through words and images, imperial artists used peonies to map critical nodes of the Qing Empire and form a visuality of conquered subjects: from the cultural heartland of Han Chinese scholars to European missionaries in the capital of Beijing, and finally to Buddhist devotees in Tibet. Meanwhile, the peonies that began their journey as ephemeral objects of southern Chinese gardens ultimately faded from memory along with their messages of loyal and dissent. Thus, although court artists used peonies to construct a totalizing image of the Qing as a global power, the biographies of these objects instead challenge the relationship between the Qing court and the things it possessed.

A two-stage taxi scheduling strategy at airports with multiple independent runways

Long taxiing times at large airports lead to fuel wastage and dissatisfied passengers. This paper investigates the 4D taxi scheduling problem in airports to minimize the taxiing time. We propose an iterative two-stage scheduling strategy. In the first stage, all aircrafts in a current schedule period are assigned initial 4D routes. In the second stage, landing aircrafts that are unavailable to fulfil their initially assigned routes are rescheduled using a shortest path algorithm based approach. In this paper, the simplified model used in most existing literature, that depicts a runway as having a single entrance and a single exit or even sets only one point to represent both of them has been discarded. Instead, we model the fact that a runway has multiple entrance and exit points and use an emerging concept—Runway Exit Availability (REA)—to measure the probability of clearing a runway from a specific exit during a specific time interval so that the taxiing scheduling model can be much higher approximation to the practical operation. An integer programming (IP) model factoring REA is proposed for assigning 4D taxiing routes in the first stage. The IP model covers most practical constraints faced in airport taxiing procedures, such as the rear-end/head-on conflict constraint, runway-crossing constraint, take-off/landing separation constraint, and taxi-out constraint. Besides, flight holding patterns at intersections are much more realistically modelled. Furthermore, to accelerate the solving process of the IP model, we have refined the formulation using several tricks. Simulation results by proposed scheduling approach for operations at the Beijing Capital International Airport (PEK) for an entire day demonstrate a surprising taxiing time saving against the empirical data and simulation results based on a strategy similar to what being used now days while showing an acceptable running time of our approach, which supports that our approach may help in real operation in the future.

Online monitoring of local taxi travel momentum and congestion effects using projections of taxi GPS-based vector fields

Ubiquitous taxi trajectory data has made it possible to apply it to different types of travel analysis. Of interest is the need to allow someone to monitor travel momentum and associated congestion in any location in space in real time. However, despite an abundant literature in taxi data visualization and its applicability to travel analysis, no easy method exists. To measure taxi travel momentum at a location, current methods require filtering taxi trajectories that stop at a location at a particular time range, which is computationally expensive. We propose an alternative, computationally cheaper way based on pre-processing vector fields from the trajectories. Algorithms are formalized for generating vector kernel density to estimate a travel-model-free vector field-based representation of travel momentum in an urban space. The algorithms are shared online as an open source GIS 3D extension called VectorKD. Using 17 million daily taxi GPS points within Beijing over a four-day period, we demonstrate how to generate in real time a series of projections from a continuously updated vector field of taxi travel momentum to query a point of interest anywhere in a city, such as the CBD or the airport. This method allows a policy-maker to automatically identify temporal net influxes of travel demand to a location. The proposed methodology is shown to be over twenty times faster than a conventional selection query of trajectories. We also demonstrate, using taxi data entering the Beijing Capital International Airport and the CBD, how we can quantify in nearly real time the occurrence and magnitude of inbound or outbound queueing and congestion periods due to taxis cruising or waiting for passengers, all without having to fit any mathematical queueing model to the data.