Air Traffic Visualisers

Proposal

Project Presentation

Project Application

Research Paper

Poster

Project Introduction

The airplane industry is a very volatile industry. Various events can occur that would lead to the whole airline industry to go into a downward spiral. Clear examples of this events are the September 11 Terrorist Attacks and the 2009 Financial Crisis. However, how much of airline industry is affected due to commercial airplane crashes, and how badly does it affect the number of passengers travelling within the United States.

In this project, our team intend to make use of data visualisation techniques to help correlate between airplane crashes and the fall in number of passengers travelling within the United States. We intend to answer various questions such as, the impact of an airplane crash that occurred in US compared to an airplane crash that occurred outside of the US and other questions such as what should companies do when such an incident happened.

Project Motivation

It is difficult to predict the effect of ‘black swan’ events and how they would affect the airline industry. In the airline industry, crashes are becoming less frequent due to increase in airline safety standards and improving technology. As such, airline crashes tend to be black swan events that are almost unpredictable.

Consequently, we’d like to find out when such event happens, how much do they affect the airline industry, if at all? This would be helpful for airlines to make better decisions in terms of resource allocations when such events happen.

Deliverables and Target Audience

We aim to deliver a highly interactive web application that allows someone to easily navigate between a large amount of time-series data and geographical data.

Our intended audience is:

1. Airline carriers since they would get some insight as to how to better price their tickets and allocate resources
2. Airport operators to better allocate resources after a crash
3. Casual passengers since they would get an idea of the general public’s response and get a better estimate of the outcome of a crash

Objectives

In this project, we will be focusing on the following:

• Identify the trend between plane crashes and the number of passengers travelling within the US over the past 15 years
• Find out if international flights or domestic flight crashes has a greater effect on the confidence of flights
• Other unlikely relationships between airplane crashes and domestic flights taken in US

Dataset

For this visualisation we need a few datasets.

1. Airline Codes - List of airlines IATA and ICAO codes. Retrieved using Import IO viahttp://www.flugzeuginfo.net/table_airlinecodes_airline_en.php.
2. Airport Locations - List of Longitude and Latitude points of all the airports. (We just need United States) Retrieved from Open Flights.org via http://openflights.org/data.html.
3. Domestic US flights Data - List of number of passengers travelling within US. Retrieved from US Department of Transportation via https://www.transportation.gov/policy/aviation-policy/domestic-airline-consumer-airfare-report.
4. Airline Crashes - List of airplane crashes happening throughout the world. Retrieved via http://www.planecrashinfo.com/database.htm.

Below are the list of Table Header name, description and an example for each table.

1. Airline Codes

Name	Description	Example
Airline Company Name	The name of the airline company	Singapore Airlines
IATA Airline Code	2 letter codes given by IATA to uniquely identify an airline company	SQ
ICAO Airline Designators	3 Letter Codes given by ICAO to uniquely identify an airline comapny	SIA

2. Airport Locations

Name	Description	Example
Name	The name of the airport	John F Kennedy International Airport
latitude_deg	The Latitude of the Airport in decimal degrees, usually to six significant digits. Negative is South, positive is North.	40.63980103
longitude_deg	The Longitude of the Airport in decimal degrees, usually to six significant digits. Negative is West, positive is East.	-73.77890015
municipality	The state where the airport resides in.	New York
iata_code	The 3 letter unique identifier for an airport.	JFK

Domestic US flights Data

Name	Description	Example
Year	Year of the data	2014
Quarter	Quarter of the data	2
City1	Descriptive Label for place of departure	Los Angeles, CA (Metropolitan Area)
City2	Descriptive Label for place of arrival	San Francisco, CA (Metropolitan Area)
Passengers	Market Passenger Per Day	21,378

Airline Crashes

Name	Description	Example
Date	The date which the incident occured	2/3/2005
plane_type	The type of plane flying	Boeing 747-131
country	The country where the incident occured	China
airline	The airline which resulted the accident occured	Southwest Air
fat	The number of Fatalities from the crash	4
phase	Which phase the airplane was. (approach, initial_climb, etc.)	en_route
meta	The main category of the cause of the crash (weather, human_error, criminal)	Weather
cause	The cause of the crash	bad weather

Exploration of Visualisation Methods

Chord Diagram
Chord Diagrams are a graphical method of displaying inter-relationships between data in a matrix. In this graphical method, the data is arranged in a circle where it will show the relationships between the various points. We believe that using a chord diagram would be effective as we would be able to visualise the number of passengers travelling between the various states. We would be using D3.js's Chord diagram, since it is both easy to implement and is interactive at the same time.

Brick Map Brick Maps are maps that use bricks to give visualise the absolute amount of people in a geospatial space. We chose to use brick map, because it would give an overview of the number of passengers travelling from each state, and also because it is challenging, as stated from the prof. In order to build this, we would have to build our own libraries, since there is no brick map in any library.

Cross Filter Cross filter is a library that is flexible and allows for people to select a range of dates easily. Since we have to visualise time-based data over 15 years. we intend to make it as flexible and easy to use for all users.

Proposal of StoryBoard

Technical Challenges

Project Timeline

Technologies and Tools

Our team has decided to focus on these few tools and libraries in order to showcase our product.

• Brackets (IDE)
• Github (for version control and Github Pages)
• Microsoft Excel (Data Cleaning)
• Adobe Photoshop (Prototyping storyboard and Wiki Illustrations)
• D3.js (one of the library used to visualise the data)

References