Istanbul Airport Research Articles

The operational dynamics of end-around taxiways: Insights from Istanbul Airport

The rapid rise in global air traffic poses significant challenges for airports, particularly in maintaining operational safety and efficiency. One of the main issues is the risk of runway crossings during ground movements, which can lead to runway incursions. This is particularly problematic in airports with parallel runway operations, where managing multiple runways and ground movements is more complex. End-Around Taxiways (EATs) have been introduced as a strategic solution to mitigate these risks. However, their implementation also introduces new operational challenges and complexities. This study evaluates the impact of EATs on Istanbul Airport (LTFM), one of Europe’s busiest airports. Using Automatic Dependent Surveillance-Broadcast (ADS-B) data, the research examines the use of EATs in taxi times, acceleration counts and durations, stop-and-go counts, level-off times, hot spots, gate and stand usages by developing new catchment algorithms. The findings show that EATs present operational challenges such as increased taxi times, number of acceleration movements, and level off times. The study emphasizes the need to consider local airport configurations when implementing EATs and suggests new constraints to optimize their usage.

An analysis of trust governance mechanism in airline-airport relationship with resource dependence theory and transaction cost theory perspectives

Developments have transformed airport operations into more commercially focused centers in the airport sector. This situation has raised the question of how to execute interdependent airport-airline relationships. In interdependent relationships, trust-based governance is the least costly governance structure and is crucial for fostering cooperation in long-term relationships. Trust-based governance is a management approach where relationships and decisions are guided by mutual trust, transparency, and collaboration between parties. When considering the nature of the relationship, it is observed that environmental uncertainty and asset specificity are high. Transaction cost theory suggests that trust governance mechanisms can be the least costly governance structure under high uncertainty and asset specificity. Similarly, resource dependency theory indicates that in situations with high environmental uncertainty, dependencies can be managed through trust governance mechanisms. Therefore, this study analyzes the trust governance mechanism in airport-airline relationships. Drawing from the perspectives of resource dependency theory and transaction cost theory, this research analyzes the trust governance mechanism in airport-airline relationships using case studies of Turkish Airlines and Istanbul Airport relationship is governed by contract-based trust, while the Pegasus Airlines and Istanbul Sabiha Gokcen Airport relationship is based on goodwill-based trust. It can be argued that the history of the airport-airline relationship and the belief in the continuity of the relationship have a positive impact on trust.

Performance Evaluation of Machine Learning Algorithms in Estimating Taxi Times at Istanbul Airport

Performance Evaluation of Machine Learning Algorithms in Estimating Taxi Times at Istanbul Airport

Runway assignment optimisation model for Istanbul Airport considering multiple parallel runway operations

Abstract The aviation industry has rapidly developed in recent years. Due to the increased number of flight operations, managing air traffic has become essential. The air traffic management system aims to reduce the air traffic control workload and use existing resources more efficiently. This study proposed a new mixed integer linear programming model to minimise the total fuel consumption during taxi operations for the runway assignment problem, comparing the actual Istanbul Airport runway assignment data. The average taxi times are calculated using the 30,000-flight operations data for each arrival and departure taxi route. Also, 47 different aircraft types are obtained using the data for the fuel consumption calculation. The International Civil. Aviation Organisation (IACO) aircraft engine emissions databank provides the fuel consumption values for each aircraft according to engine type. This approach allows our model to calculate more realistic fuel consumption for taxi operations, as each aircraft engine type has a different fuel consumption value. The proposed model is implemented at Istanbul Airport, the busiest airport in Turkey, where multiple parallel runway operations are applied. The results showed that the proposed model reduced total fuel consumption for taxi operations between 6.6% and 14.4% compared to the actual Istanbul Airport runway assignment data.

How IGA Istanbul Airport leverages IoT and automation for improved efficiency, safety and passenger experience

iGA Istanbul Airport is the first and only airport established with a wireless Internet of Things (IoT). IoT systems offer an effective solution for receiving data from many points with advantages such as fast implementation, low installation costs and long lifetime. In addition to standard products, special wireless IoT sensors designed for specific needs are also used in iGA Istanbul Airport. This infrastructure provides data for the execution, improvement and development of airport processes. The big data and analysis application created with the data collected from IoT devices and system integrations manages efficiency and predictive maintenance activities. With the effective use of IoT systems, iGA Istanbul Airport has achieved significant gains in increasing customer satisfaction, managing predictive maintenance from a more proactive perspective, reducing environmental impacts and increasing operational efficiency. This paper discusses the use of the IoT infrastructure at iGA Istanbul Airport and the benefits it provides.

Forecasting surface movements based on PSI time series using machine learning algorithms

ABSTRACT Surface movements pose a critical issue requiring prompt detection and monitoring to ensure safety. To address this concern, the detection and continuous monitoring of surface deformations have gained importance. While numerous point-based surveying methods exist, multi-temporal interferometric synthetic aperture radar (InSAR) analysis has emerged as a powerful technique capable of detecting deformations across large areas with freely available SAR images and software. However, the significance of surface movement forecasting must be addressed, as it plays a significant role in preventing accidents and implementing precautionary measures. In light of this, a comprehensive study was conducted at the new Istanbul Airport in Türkiye, employing the Persistent Scatterer InSAR (PSI) method with a collection of 211 Sentinel-1 SAR images. The results obtained were investigated, and six test case regions were determined for the forecasting analysis in terms of time series movement type (subsidence, uplift, and stable) and structure type (runway and building) using various machine learning (ML) algorithms. To accomplish this, regression-based and sequential-based ML algorithms were employed and compared, showing the potential of cutting-edge techniques. The Stacked LSTM algorithm was the most effective in generating accurate forecasts. Furthermore, by incorporating exogenous variables into the forecasting analysis, the study improved the accuracy of the results. To gain deeper insights into the impact of these exogenous variables, feature importance analysis was conducted using the permutation feature importance method. The results obtained were examined, considering both the structure type and the characteristics of the time series data.

İstanbul Havalimanı Teknik Personelinin Motivasyonunun Örgütsel Bağlılık Üzerine Etkisine Yönelik Bir Araştırma

Airport operators are called service operators. The most important factors which affect the quality of the services are the motivation of the employees and their commitment to organizations. Therefore, contemporary management approaches should investigate the factors that affect the motivation and organizational commitment of employees and find out the results.
 This study investigates the variables which influence the relationship between the motivation and organizational commitment of the technical electricity staff who work at Istanbul Airport. The method that was used in the research is the relational screening method which is one of the quantitative research methods. This screening method as “Motivation Scale” and “Organizational Commitment Scale” had been applied for the technical staff of the Istanbul Airport between October 1, 2019 and November 10, 2019. It is found out that there are significant differences based on gender, marital status, age, education level, working time in the corporate and position in terms of the motivation and commitment of the employees.

SOCIOECONOMIC EFFECTS OF NEWLY BUILT AIRPORTS IN TURKEY: A SWOT ANALYSIS FROM THE INDUCTIVE PERSPECTIVE

Airports make significant contributions to the country's economy through the economic and social contributions they provide to the region in which they are located. In this context, many new airport infrastructure investments have been made in Turkey in recent years, such as the large-scale Istanbul Airport, Ordu-Giresun Airport, which was built on an embankment over the sea, and Çukurova Regional Airport. This study aims to evaluate the socioeconomic effects they have created by making a SWOT analysis of the airports that have been built and are under construction in Turkey in recent years, from an inductive perspective. In line with the findings obtained for all airports built in Turkey in recent years, the effects of new airports were discussed, and suggestions were made on how the policies for airport construction, which is one of the most important aviation infrastructure investments, should continue in the future.

ANALYSIS OF TEMPORAL AND SPATIAL CHANGES IN ISTANBUL NORTHERN FORESTS WITH SATELLITE IMAGES AND LANDSCAPE METRICS

Abstract. There is an urbanization process on a global scale with population growth and technological developments. Especially in metropolitan cities, mega projects located on the city periphery lead to environmental pressure on natural areas and forests. Istanbul Northern Forests, the transition region of the Black Sea and Mediterranean flora, host various ecosystems due to its pseudomaki structure. However, the effects of big projects recently realized such as Istanbul Airport, Northern Marmara Motorway, and Yavuz Sultan Selim Bridge on the Istanbul Northern Forests can be noticed even with the naked eye. This study investigates land use/cover changes in Istanbul Northern Forests which are under intense urbanization pressure using LANDSAT and SENTINEL-2 satellite images in a time series of thirty-nine years (1984–2023). As a result of the analysis, it is seen that the class of impervious surfaces increased in Istanbul Northern Forests between 1984–2023, while the class of barren land, natural areas and agricultural areas decreased. Landscape metrics such as Total Class Area, Percentage of Landscape, and Interspersion Juxtaposition index were used to better understand the change in the study area between 2017 and 2023.

Investigation of the Effects of Important Factors in Suburban Rail Route Determination with MCDM

Thorough evaluation of suburban rail route alternatives is essential for determining the appropriate route. Suburban lines provide transportation services to suburban areas; that is, they provide transportation services to distant points of the city where demand is high. In this study, five alternative suburban rail routes in the commuter rail standard, starting from the Fatih Sultan Mehmet Bridge’s European exit and ending at Istanbul Airport, were determined as a sample corridor in the province of Istanbul. High-standard suburban rail routes and their infrastructure construction costs were determined, and route options were delineated according to their construction costs. Multi-criteria decision-making (MCDM) methods were examined, including the application of the decision matrix method (DMM) and analytical hierarchy process (AHP) to rank the routes in terms of the factors examined in the study. These routes were ranked according to the construction costs and according to the DMM and AHP methods, and the results were compared. In the decision matrix application, geomorphological-geological, geotechnical, infrastructural, and environmental factors were considered in the evaluation and determination process. A solution was developed in which all aspects were weighted to indicate their relevance, and these factors contributed to the determination of the results. The AHP method was also applied, in which five criteria were included in the evaluation: geology (including geomorphology and soil properties), engineering structures, construction costs, population values addressed by the routes, and railroad length. In addition, the distances to the active faults were examined according to the Turkey Earthquake Hazard Map specified in the Turkish Building Earthquake Code (TBDY) 2018. Depending on the factors studied, the ordering of the routes was the same for all three methods.

Use of Machine Learning Techniques in Soil Classification

In the design of reliable structures, the soil classification process is the first step, which involves costly and time-consuming work including laboratory tests. Machine learning (ML), which has wide use in many scientific fields, can be utilized for facilitating soil classification. This study aims to provide a concrete example of the use of ML for soil classification. The dataset of the study comprises 805 soil samples based on the soil drillings of the new Gayrettepe–Istanbul Airport metro line construction. The dataset has both missing data and class imbalance. In the data preprocessing stage, first, data imputation techniques were applied to deal with the missing data. Two different imputation techniques were tested, and finally, the data were imputed with the KNN imputer. Later, a balance was achieved with the synthetic minority oversampling technique (SMOTE). After the preprocessing, a series of ML algorithms were tested with 10-fold cross-validation. Unlike the studies conducted in previous research, new gradient-boosting methods such as XGBoost, LightGBM, and CatBoost were tested, high classification accuracy rates of up to +90% were observed, and a significant improvement in the accuracy of prediction (when compared with previous research) was achieved.

İstanbul Havalimanı’nın Çoklu Paralel Pist Konfigürasyonlarının Zaman ve Yakıt Tüketimi Açısından İncelenmesi

Gelişen hava trafiği talebiyle birlikte havalimanlarına ihtiyaç her geçen gün atmaktadır. Bu ihtiyacı karşılamak için çoğu zaman mevcut havalimanlarının nasıl daha etkin kullanılabileceği incelenirken, kapasitesinin üzerinde talep olan şehirlerde ise yeni pistler veya havalimanları inşa edilmektedir. Son dönemlerde yeni inşa edilen havalimanlarında ise çoklu paralel pist sistemleri kullanılarak ileride oluşacak yoğun talebi de karşılayacak şekilde tasarlanmaktadır. Çoklu paralel pist sistemlerinde pist konfigürasyonlarının kapasite üzerinde büyük bir etkisi olduğuna dair birçok çalışma bulunmaktadır. Bu çalışmalarda havalimanı işletmecisi açısından bakılarak havalimanı kaynaklarının etkin kullanımı hedeflenmektedir. Bu çalışmada ise havayolu şirketlerinin bakış açısıyla 2018 yılında kullanıma açılan, Airports Council International (ACI) verilerine göre 2021 yılının en işlek havalimanları sıralamasında ilk sırada yer alan İstanbul Havalimanı’nın pist konfigürasyonları havayolu işletmecisinin bakış açısıyla zaman ve yakıt açısından değerlendirilmektedir. Çalışmada İstanbul Havalimanı’na iniş yapan trafiklere ait iniş pisti, uçak tipi ve taksi süreleri bilgileri değerlendirilerek pist konfigürasyonları incelenmiştir. Çalışmanın sonucunda minimum taksi süresi ve yakıt tüketimi sağlayan pist konfigürasyonları belirlenmiştir.

International Smuggling of Illicit Drugs by Body Concealment at a Tertiary Hospital in Istanbul.

Smuggling of illicit substances by internal concealment has recently become a preferred method of international drug trade. The drug carriers are known as body packers. This study aimed to assess the demographic features and outcomes of body packers admitted to a referral center in Istanbul. Data were retrospectively evaluated from January 2017 to December 2019 from suspected body packers who were referred to the emergency department of a tertiary-care university by Istanbul Airport narcotics police due to suspected concealment of illicit drugs. Eighty-one cases were identified and included in this study. Of these, 71 subjects were confirmed to be body packers by radiological methods. The 15 women and 56 men had a mean age of 35 years. The most common nationality of the body packers was Nigerian, followed by Turkish and South African. Cocaine was the most commonly smuggled packet, followed by hashish, and heroin. All body packers were conservatively managed using laxatives or watchful waiting. No cases required surgical retrieval of packets. Abdominal radiography and computed tomography are useful tools for the evaluation of suspected body packers. The use of improved packaging material by smugglers and complications due to surgery and endoscopy make the conservative approach preferred.

Air traffic management in parallel-point merge systems under wind uncertainties

The point merge system (PMS) was developed by EUROCONTROL in 2006 to enable controllers to implement systematic sequences and replace the traditional vector technique in Terminal Maneuver Area (TMA) even during peak hours. A conventional PMS includes two arc-shaped route segments referred to as sequencing legs and a single merge point to merge arrivals. When necessary, arrivals can be delayed along these legs using path stretching before they are directed to the merge point. After merging, aircraft join the final approach. The parallel-point merge system (P-PMS), however, has a more complex route structure which consists of two oppositely located PMS and a set of common points located between the merge points and final paths of runways. This system increases the capacity of the airspace and provides the advantages of the single PMS. However, especially in simulation studies where P-PMS has been tested, the emphasis on wind sensitivity came to the fore as one of the main issues affecting the use of the system. The use of P-PMS was stated as feasible but more difficult due to the loss of symmetry, especially when the wind is perpendicular to the sequencing legs. Controllers may need help in providing safe and efficient sequences in this type of structure. In this study, a multi-objective two-stage stochastic programming model is developed for P-PMS to obtain robust aircraft sequences, schedules, and runway assignments considering the uncertainties of both wind direction and speed. The model was implemented on the existing layout of Istanbul Airport having a P-PMS serving five parallel runways using the real traffic and wind data. A scenario-based approach was adopted to represent the uncertainties of the model. Also, to meet the demands of the various stakeholders in the air traffic system, the minimization of total fuel consumption, total flight time, and total delays were considered as single and multi-objectives. As a result, it was found that the stochastic approach provides better solutions in terms of objective values and emission outputs compared to deterministic and FCFS approaches under wind uncertainties. The differences between these solutions are quantified through numerical experiments.

Investigation of the Effects of Ukraine - Russia Tension on Turkish Airspace and Istanbul Airport

It is known that the airline industry, which is known to be more dynamic and complex among all sectors in the world, has been affected by many changes and events. Especially the political tensions between the states and the fact that the airline industry creates a large amount of capital make this situation even more complex and unpredictable. In this study, the reflections of the political tension between Ukraine and Russia in Turkey, which has intense commercial relations with both countries, were examined in the context of the airline industry. As a result of the analyzes carried out, it was seen that the tension between Ukraine and Russia is in a positive correlation with the traffic in Turkish airspace and Istanbul Airport, and it was concluded that Istanbul airport effectively increased the aircraft traffic with the airspace occupation. The study is expected to be the basis for future comprehensive studies.

POSITIONING AND RE- POSITIONING: AN ANALYSIS ON THE POSITIONING STRATEGY OF ISTANBUL AIRPORT, RELOCATED AFTER THE COVID 19 PANDEMIC

Aralık 2019’da Çin’in Wuhan kentinde ortaya çıkan COVID 19 pandemisi birçok sektörde olduğu gibi havacılık sektöründe de büyük değişimlerine yaşanmasına neden olmuştur. Söz konusu zaman dilimine kadar “Dünyanın “sıfırdan yapılan en büyük havalimanı” ile “yeni havacılık merkezi” şeklinde yapılan konumlandırma çalışmaları COVID 19 pandemisi ile beraber strateji değiştirmiştir. Kriz nedeniyle yeniden yapılanan konumlandırma stratejisi, İstanbul Havalimanı için hazırlanan reklam filmleri ve basında çıkan haberlerle de öne çıkmaktadır. İstanbul Havalimanı özellikle COVID 19 döneminde kendisini, “COVID 19 için en güvenilir havaalanı” şeklinde yeniden konumlandırma stratejisini uygulamaktadır. Havaalanının mevcut büyüklüğü önceki konumlandırma stratejisinde kullanıldığı gibi “Dünyanın en büyük havalimanı” konumlandırması yerini “sosyal mesafenin sağlanması için yeterince büyük, bu yüzden güvenilir” şeklinde bir yeniden konumlandırma stratejisine gidildiği gözlemlenmiştir.
 Bu çalışmada, öncelikli olarak konumlandırma, yeniden konumlandırma kavramları incelenmiş sonrasında COVID 19 pandemisi ile ilgili global etkiler üzerinde durulmuştur. Çalışmanın ilerleyen aşamalarında, İstanbul Havalimanı konumlandırması ve COVID19 ile yeniden yapılandırılan İstanbul Havalimanı konumlandırması üzerinde durulmuştur. Yeniden konumlandırma stratejisinin etkisini ölçmek amacıyla, İstanbul Havaalanı’nın bu stratejisinin basına yansımaları araştırma kapsamında incelenmiştir. Oluşturulan stratejinin basında yansımalarını ölçümlemek için 02.02.2020 ile 02.07.2021 tarihleri arasında 1,5 yıllık süreçteki COVID 19 ve İstanbul Havalimanı anahtar kelimeleri kullanılarak ulusal dergi ve gazeteler taranmıştır. Buna göre yapılan taramada, 203 haber araştırmaya dahil edilmiştir. Araştırma sonucu, İstanbul Havalimanı’nın COVID 19 global sağlık krizine yönelik başarılı bir yeniden konumlandırma stratejisi oluşturduğunu ve uyguladığını göstermektedir.

Examining The Effect of Airline Passengers Acceptance and Perceptions Toward Technology on Re-purch ase Behavior

Purpose -The purpose of this study is to develop a genuine research model that examines the impact of smart technologies that domestic passengers interact with in their travel planning process on their re-purchase behavior. Design/methodology/approach–This research is a descriptive study and the relationalscreening method was used. Data collection was carried out with a total of 770 participants from Istanbul Airport Domestic Terminal. The collected data was tested using the structural equationmodelling method. It has been determined that the model provides the necessary validity and reliability. Findings -The findings obtained by the research model depict that Performance Expectation, Facilitating Conditions, Social Impact, habits, Consumer Confidence, Perceived Risk, and Consumer Technological Innovation structures have a significant impact on the formation of repurchase intention.Three variables, Price Value, Hedonic Motivation and Effort Expectation could not show a significant effect on the formation of repurchase intention. In the light of the research findings, the rate of explaining therepurchase intention of the supported hypotheses is 65%. This rate turns into repurchase behavior at a rate of 87%. Research results strongly prove the impact of domestic passengers' acceptance and perception of technology on their re-purchase behavior. Discussion –Inthe scope of the carriedresearch, the effect of repurchase intention on repurchase behavior was examined and the findings were discussed.

Assessing spatio-temporal dynamics of large airport’s surface stability

Istanbul Airport will be one of the biggest airports in the world when the construction in old open-pit mining areas which turned into wetlands is completed. To investigate the structural health monitoring of the Istanbul Airport, firstly the temporal evaluation of land use/land cover (LULC) in the region was generated for determining reclaimed lands using Random Forest classifier with Landsat images between 1984 and 2020. The outcomes were then examined with results of multi-temporal Interferometric Synthetic Aperture Radar (InSAR) methods, namely Small Baseline Subset (SBAS) for general displacement overview and Persistent Scatterer Interferometry (PSI) for detailed analysis of the settlement rate in the airport and runways which were applied to Sentinel-1 images. Both of the methods showed similar results for the same regionsand it is determined that there are movements up to 10 mm in Runway A and Runway B and more than 20 mm subsidence in Runway C.

COVID-19 KAPSAMINDA ALINAN TEDBİRLERİN UÇAK GECİKMELERİNE ETKİSİ: İSTANBUL HAVALİMANI ÖRNEĞİ

Baggage handling involves a significant part of airline passenger transport. Disruptions in baggage delivery or flow directly affects the travel time. The receipt of cabin baggage in aircraft warehouses has been a measure that may disrupt this process within the scope of the circular issued with the Covid-19 pandemic. Within the scope of the circular regarding Covid-19 pandemic, oblige to put cabin baggage in aircraft warehouses has been a measure which may disrupt this process. In this study, Istanbul Airport international baggage operations were simulated with the Arena Trial program. The circular period and before were compared in the developed scenarios. It has been observed that there has been an increase in the time of arrival of the luggage to the aircraft as a result of during the Airport Pandemic Precautions and Certification Circular period.

Probabilistic analysis of blast–obstacle interaction in a crowded internal environment

Recent terror events such as the Manchester Arena bombing and Brussels and Istanbul airport attacks featured improvised explosive devices detonated in crowded internal spaces. A blast wave that propagates in the presence of obstacles will have fundamentally different properties to those of an unimpeded blast wave. Physical processes such as reflection, diffraction, and superposition of multiple wave fronts result in highly complex and situational-dependent loading characteristics which cannot be predicted using simple tools such as those for predicting free-field blast parameters. The influence of blast–obstacle interaction within an internal environment has not yet been studied. This article uses computational fluid dynamics within a probabilistic framework to quantify the influence of obstacle density and positioning on blast loading characteristics. Two mechanisms which alter the properties of a blast wave are studied: ‘channelling’ and ‘shielding’. It is shown that channelling effects are highly localised and result in increased loading near the explosive, the effect of which increases with obstacle density. Shielding is shown to be a cumulative effect which increases with distance from the explosive, and with increasing obstacle density. Whole-domain cumulative density functions are used to derive quantitative descriptors of the loading characteristics and how they vary relative to simple benchmark cases, with a view to providing clear guidance on the development of future predictive tools.