Tools

The following open-source software are freely available for all. These are precious tools for any ATM researcher.

BlueSky, an open air traffic simulator

BlueSky is an open air traffic simulator provided for anybody who wants to visualize, analyze or simulate air traffic. It is commonly used to perform research on Air Traffic Management and Air Traffic Flows.

https://github.com/TUDelft-CNS-ATM/bluesky
GNU General Public License v3.0

OpenAP, Open Aircraft Performance Model and Toolkit

This repository contains all OpenAP databases and a Python implementation which facilitates data access and performance computation. It includes the following key modules:

openap.prop: a module for accessing aircraft and engine properties
openap.thrust: a module for computing aircraft thrust
openap.drag: a module for computing aircraft drag
openap.fuel: a module for computing fuel consumption
openap.kinematic: a utility library to access WRAP data
openap.traj: a module contains a set of tools related with trajectory generation

https://github.com/junzis/openap
GNU General Public License v3.0

pyModeS, a decoder for ADS-B and Mode-S downlink messages

pyModeS is a Python library designed to decode Mode-S (including ADS-B) messages. It can be imported to your python project to decode Mode S messages, or used as a standalone tool to view and save live traffic data.

https://github.com/junzis/pyModeS
http://pymodes.readthedocs.io
GNU General Public License v3.0

pyopensky, the Python interface for OpenSky Impala database with integrated pyModeS decoder

This Python library connects the pyModeS decoder and OpenSky Impala data interface. It aims at making the Enhance Mode-S information from OpenSky network more accessible for researchers. It can be used for:

Query and download ADS-B state vectors and raw Mode S messages from OpenSky Impala database.
Decode OpenSky Comm-B information automatically using pyModeS.

https://github.com/junzis/pyopensky
GNU General Public License v3.0

traffic, a toolbox for processing and analysing air traffic data

The traffic library helps working with common sources of air traffic data.

Its main purpose is to offer basic cumbersome data analysis methods commonly applied to trajectories and ATC sectors. When a specific function is not provided, the access to the underlying structure is direct, through an attribute pointing to a pandas dataframe.

The library also offers facilities to parse and/or access traffic data from open sources of ADS-B traffic like the OpenSky Network or Eurocontrol DDR files. It is designed to be easily extendable to other sources of data.

Static visualisation (images) exports are accessible via Matplotlib/Cartopy. More dynamic visualisation frameworks are easily accessible in Jupyter environments with ipyleaflet and altair; or through exports to other formats, including CesiumJS or Google Earth.

Xavier Olive,
“traffic, a toolbox for processing and analysing air traffic data”,
Journal of Open Source Software, 2019

https://github.com/xoolive/traffic
https://traffic-viz.github.io/
MIT License

openSkies, an R package for aviation data retrieval, analysis and visualization

openSkies aims to provide the data structures and functionalities required to analyze and visualize aviation data in R.

The package provides a system of classes with associated methods representing the most common entities related to aviation data, such as aircrafts, airports, flights or routes.

It also includes a client interface to the OpenSky live API, and a decoder of ADSB messages.

Finally, functions to process and plot aircraft and flight data are also provided.

A full, detailed list of the available features can be found in the manual and the vignette of the package.

https://CRAN.R-project.org/package=openSkies https://github.com/Rafael-Ayala/openSkies CC BY-NC 4.0 License

Mercury, an open source mobility simulator

Mercury is an open source mobility simulator designed by and for researchers. Mercury tracks aircraft across their trajectories, time at the airport, applying internal complex airline rules and optimisation processes. It also tracks passengers along their entire journey, gate-to-gate including connections and possible hurdles (cancelled flights etc). The simulator measures every aspect of the system, from passenger real delay to flight emissions and other processes.

https://github.com/UoW-ATM/Mercury Sample data: https://zenodo.org/records/11384379 GPL-3.0 license

CLIMaCCF Library

The Python Library CLIMaCCF provides an open-source, easy-to-use, and flexible software tool that efficiently calculates spatially and temporally resolved climate impact of aviation emissions by using algorithmic climate change functions (aCCFs). The individual aCCFs of water vapour, NOx-induced ozone and methane, and contrail-cirrus and also merged aCCFs that combine the individual aCCFs can be calculated.

https://github.com/dlr-pa/climaccf LGPL-3.0 license

OpenAirClim

https://zenodo.org/doi/10.5281/zenodo.13682728 OpenAirClim is a model for simplified evaluation of the approximate chemistry-climate impact of air traffic emissions. The model represents the major responses of the atmosphere to emissions in terms of composition and climate change. Instead of applying time-consuming climate-chemistry models, a response model is developed and applied which reproduces the response of a climate-chemistry model without actually calculating ab initio all the physical and chemical effects. The responses are non-linear relations between localized emissions and Radiative Forcing and further climate indicators.

https://github.com/dlr-pa/oac Apache-2.0 license