The impact of COVID-19 on the worldwide air transportation network

Air travel has been one of the hardest hit industries of COVID-19, with many flight cancellations and airport closures as a consequence. By analysing structural characteristics of the Official Aviation Guide flight data, we show that this resulted in an increased average distance between airports, and in an increased number of long-range routes. Based on our study of network robustness, we uncover that this disruption is consistent with the impact of a mixture of targeted and random global attack on the worldwide air transportation network. By considering the individual functional evolution of airports, we identify anomalous airports with high centrality but low degree, which further enables us to reveal the underlying transitions among airport-specific representations in terms of both geographical and geopolitical factors. During the evolution of the air transportation network, we also observe how the network attempted to cope by shifting centralities between different airports around the world. Since these shifts are not aligned with optimal strategies for minimizing delays and disconnects, we conclude that they are consistent with politics trumping science from the viewpoint of epidemic containment and transport.

Analisis Hukum Terhadap Penumpang Pesawat Atas Keterlambatan Keberangkatan Penerbangan Domestik di Bandara Internasional Kualanamu Deli Serdang

This paper riset aims to examine and analyze the legal rule regarding airlines for passenger aircraft in Indonesia is Law No. 8 of 1999 concerning Consumer Protection, Law no. 1 of 2009 concerning Aviation and Regulation of the Minister of Transportation No. 89 of 2015 concerning Handling Delays in Scheduled Commercial Air Transport Business Entities in Indonesia and Regulation of the Minister of Transportation Number 92 of 2011 amending the Regulation of the Minister of Transportation No. 77 of 2011 concerning the Responsibility of Air Transport Carriers. The factors causing the delay in departure at Kualanamu Deli Serdang International Airport are one of the factors of weather, and technical problems on aircraft but which are more often caused by weather, especially Kuala Lumpur is the hub airport (collecting airport) of several small airports where the weather can change at any time -Time and it is a thing that often happens in Kuala Lumpur. The responsibility of domestic airlines to aircraft passengers who experience delays in departure at Kualanamu Deli Serdang International Airport is to provide compensation and compensation in the form of soft drinks, snacks and heavy meals as well as compensation, depending on the type of delay according to the category, namely: Category 1, 30 to 60 minutes delay, Category 2, 61 to 120 minutes delay, Category 3, 121 to 180 minutes delay, Category 4, 181 to 240 minutes delay, Category 5, more than 240 minutes delay, Category 6, namely flight cancellations, then the airline is obliged to divert to the next flight or refund all ticket costs.

The Impact of COVID-19 on Air Transportation Network in the United States, Europe, and China

The air transportation industry has undergone unprecedented changes throughout the COVID-19 pandemic, as measured in terms of flight cancellations, aircraft retirements, airline bailouts, and disconnection of worldwide communities. In this study, we performed a cross-comparison of the impact COVID-19 had on three aviation centers of the world—the United States, Europe, and China. Methodologically, we analyzed the air transportation system as complex networks and by using time series analysis. We discovered that the peak of COVID-19 impact was around April/May 2020, followed by a strong recovery mostly in domestic subsystems. We found a homogeneous impact on the United States, a strong heterogeneous impact on Europe, and a rather short-term impact on China. Domestic flight connectivity recovered much faster than international flight connectivity, particularly for the Chinese air transportation system. Our study provided a comprehensive, data-driven analysis of the COVID-19 impact on air transportation for these three major regions, augmented by references to the rich scientific literature on this subject. We hope that our work opens up pathways to a better understanding and a higher degree of preparedness for future pandemics.

The Impact of Covid-19 on Flight Departure Delay Time and Cancellations at Philadelphia International Airport

The emergence of Covid-19 has deeply disturbed the aviation industry in many aspects. This study examines the effect of Covid-19 on departure delay time and flight cancellation at Philadelphia International Airport (PHL). By analyzing data of nearly 200,000 flights departed from PHL between January 2019 and February 2021, the research found that Covid-19 noticeably reduced flight departure delay time, and flight cancellations sharply rose then quickly dropped. Furthermore, flight departure delay time is highly correlated with the number of flights: the lower the number of flights, the lower the delay time. The ultimate cause is the lack of passengers, as the number of passengers dictates the number of flights an airline can successfully operate.

TANGGUNG JAWAB PELAKU USAHA TERHADAP KONSUMEN (PENUMPANG) PESAWAT UDARA

The development in the transportation sector, both goods, and services, especially transportation/ transportation using aircraft, is very rapid, it can be seen from the large number of business actors engaged in the aviation business. However, this is not balanced with good service to consumers, airlines have recently made unilateral flight cancellations or cancellations of flights for various reasons. This causes losses for passengers as consumers. This study aims to determine how the responsibility of business actors towards consumers/ passengers who suffer losses due to flight cancellations and legal remedies that can be taken by consumers. This study uses a form of normative legal research, which is research-based on written regulations and legislation and various literature related to the issues to be discussed in this study. An airline as a business actor can be held accountable if it makes a mistake. There are several types of responsibility in law, including responsibility in the sense of responsibility or also called moral responsibility, and responsibility in the sense of liability or also called juridical responsibility. The form of airline responsibility to passengers is included in the form of responsibility based on the element of error (liability based on fault) which is based on the principle of absolute responsibility (strict liability). The onrechtmatige daad doctrine is the basis for the formation of the principle of absolute responsibility as stated in article 1365 of the Civil Code which focuses on fault elements.

Forecasting the number of incoming tourists using Arima model: case study from Armenia

This paper summarizes the arguments and counterarguments within the scientific discussion on the issue of forecasting tourism demand and touristic flows. During COVID-19 tourism sphere suffered a lot in the whole world. Many countries try to do forecasts and make recovery plans for tourism. Tourism has been a growing sphere in Armenia in recent years. However, the number of incoming tourists decreased by 80 percent because of the pandemic. The main purpose of the research is to forecast tourism demand in the Republic of Armenia. Systematization of scientific sources and approaches for solving the problem identified many methods and models for doing forecasts. The variables used to depend on the method selected. For gaining the research goal, the study was carried out in the following logical sequence: 1) discussion on some literature sources; 2) analysis of the current situation of tourism in Armenia; 3) interpretation of forecast results; 4) providing some recommendations. The methodological tool of the research was mainly the ARIMA method. The data rest on the publications of the Statistical Committee of the Republic of Armenia. Time series for the number of incoming tourists include from 2001-Q1 till 2019-Q4 data. 2020 was not included in the model, as there was a sharp decline. Besides, in the second quarter of 2020, there were no tourists at all because of restrictions and flight cancellations. The obtained data show that if there were no pandemic, the number of incoming tourists would increase on average by 12.81% in 2021, 13.42% – in 2022, and 13.66% – in 2023. The results are realistic. The tourism sphere is expected to grow in 2021. This paper suggested some steps for recovering and restoring tourism, particularly by using aggressive marketing strategies, word-of-mouth, influencer marketing, etc. The research results could be useful for state organs of the sphere to forecast their strategic policies. The applied approach and suggestions may be helpful in many countries which try to restart tourism after the pandemic.

Prediction of Air Flight Cancellation during COVID-19 using Deep Learning Methods

Air traffic is vulnerable to external factors, such as oil crises, natural disasters, economic recessions and disease outbreaks due to COVID-19. This reason seems to have a more severe and more rapid impact on air traffic numbers as sudden increases in flight cancellations, aircraft groundings and travel bans. Various Airways loose revenues and it is difficult for them to sustain for a long period. This problem as been facing the entire world. The reductions in passenger numbers are significant. It is due to flights being cancelled or planes flying empty between airports. It is in turn massively reducing revenues for airlines and forced many airlines to lay off employees or declare bankruptcy. Airways also have to attempt refunding cancelled trips in order to diminish their losses. The airliner manufacturers and airport operators have also laid off employees. According to some commentators, this crisis is the worst ever encountered in the history of the aviation industry. Aircraft cancellation prediction is accomplished by utilising deep learning framework. In this framework, two dissimilar recurrent neural networks are assembled as a single entity while inferring the prediction results. Long-short term memory (LSTM) and Gated Recurrent Unit (GRU) are employed to design the proposed predictive model. This predictive model is compared against traditional neural network based Multi-layer perceptron model. Experimental results indicated an accuracy of 98.7% by the proposed model.

A volcanic-hazard demonstration exercise to assess and mitigate the impacts of volcanic ash clouds on civil and military aviation

Volcanic eruptions comprise an important airborne hazard for aviation. Although significant events are rare, e.g. compared to the threat of thunderstorms, they have a very high impact. The current state of tools and abilities to mitigate aviation hazards associated with an assumed volcanic cloud was tested within an international demonstration exercise. Experts in the field assembled at the Schwarzenberg barracks in Salzburg, Austria, in order to simulate the sequence of procedures for the volcanic case scenario of an artificial eruption of the Etna volcano in Italy. The scope of the exercise ranged from the detection (based on artificial observations) of the assumed event to the issuance of early warnings. Volcanic-emission-concentration charts were generated applying modern ensemble techniques. The exercise products provided an important basis for decision-making for aviation traffic management during a volcanic-eruption crisis. By integrating the available wealth of data, observations and modelling results directly into widely used flight-planning software, it was demonstrated that route optimization measures could be implemented effectively. With timely and rather precise warnings available, the new tools and processes tested during the exercise demonstrated vividly that a vast majority of flights could be conducted despite a volcanic plume being widely dispersed within a high-traffic airspace over Europe. The resulting number of flight cancellations was minimal.

Impact-Based Decision Support Services and the Socioeconomic Impacts of Winter Storms

As part of its strategic plan for Building a Weather-Ready Nation, the U.S. National Weather Service (NWS) has increased their efforts to provide decision support services connecting forecasts and warnings to decision-making for core partners responsible for public safety. In 2011, the NWS formalized their approach to provide impact-based decision support services (IDSS) to help core partners better understand and utilize NWS forecasts and warnings in the face of upcoming extreme events. IDSS encourages weather forecasters to better consider societal impacts from weather events. This shift in emphasis toward impacts ensures NWS information and services are more relevant to decision-makers, which will allow those decision-makers to use NWS information and services to take proactive mitigating actions to protect life and property. This study posits that formal IDSS provides core partners with better information and supports decisions that reduce socioeconomic impacts during extreme winter storms. We compare two storms in the New York City area with similar characteristics but differing in their implementation of IDSS: the December 2010 storm occurred before the implementation of formal IDSS, whereas the January 2016 storm occurred after the implementation of formal IDSS. The comparison of the storm events indicates that IDSS and mitigating actions reduce flight cancellations, improve recovery time in the ground transportation sector, and reduce the duration and number of customers affected by power outages. We recommend that future studies of the value of IDSS consider using case studies for a range of weather events as well as other methodological approaches to assessing benefits.

Weather Analysis of Flight Delay at Husein Sastranegara Airport

Flight is an activity that is very vulnerable to weather conditions. The accuracy of weather information strongly supports flight activities. The effects of bad weather on flights include flight delays and flight cancellations. Based on data on flight delays from the Directorate General of Air Transportation of the Ministry of Transportation from January to March 2019 at Husein Sastranegara Airport, it is known that 20-30% of flight delays are caused by weather constraints. To estimate flight delays based on weather forecasts, weather data analysis is carried out to determine the type of weather that is endangering flights and causing flight delays. The analysis was carried out using the K-NN and Random Forest algorithms