A Systematic Attempt to Measure Air Traffic Levels and Trails

A Systematic Attempt to

Measure Air Traffic Levels


Count Persistent Jet Trails/Chemtrails

Using a Raspberry Pi-Based ComputerNetwork

PDF Version Here


Andrew Johnson (ad.johnson@ntlworld….)

Version 1.0 – April 2014


This research used a collection of software and hardware to receive and decode ADS-B messages from aircraft as well as photograph the sky at 1-minute intervals. The software ran on several Raspberry Pi computers stationed at up to 6 different locations in the UK. The objective was to count the number of aircraft detected at a given location and compare these counts, both on an hourly and a daily basis, when the skies were clear enough to have seen persistent jet trails or “chemtrails”. Time-stamped time-lapse videos were generated for images taken between sunrise and sunset each day. These were inspected to count the number of trails observed in each 30-min period of daylight. Trail counts and aircraft counts were collated into a Microsoft Access Database. SQL Queries were then developed to allow comparison of aircraft counts during periods when trails were observed and clear periods when no trails were observed.


I am grateful to the following people for their help with this project:

Richard D Hall, Daniel Elliot, Sally Kennedy, Anthony Beckett, Chris Johnson, Steven Littley, Paul Anderson, Al Ward, Elizabeth Johnson, Nick Craddock


And last but not least… The Raspberry Pi and Linux / Open Source / Developer Community!


Borrowash, UK 2009-10-09 07-56-29

Table of Contents


1.1Persistent Jet Trail/Chemtrail Phenomenon

Since the mid-late 1990’s, people around the world have observed what have become known, correctly or incorrectly, as “Chemtrails”. Mainstream science and commentary mostly considers these trails to be a normal result of everyday air traffic movements – i.e. they are purely and simply condensation trails formed as a result of burning kerosene. Others maintain they are part of a secret, clandestine “spraying programme” which is suggested to be either for

  • Geoengineering in the form of some kind of “Solar Radiation Management” (SRM)1

  • Introducing toxins into the atmosphere to affect/control human health

  • Introducing toxins into the atmosphere to affect/control agriculture

This author has previously compiled 2 reports about these trails and their possible nature. The reports were posted on www.checktheevidence… in 20072 and 20103 respectively.

1.2Trail Days and “Non-Trail Days”

One of the main unanswered questions is why we observe days when no trails appear – not even ones that persist enough to actually see them – and then on other days, we can observe many, many trails for such a length of time that they can even seem to spread out and form a “haze blanket”4. There seems to be no satisfactory explanation for these different scenarios, beyond either “hand waving” or making claims which are not supported by the evidence. For example, if it is caused by the state of the jet stream, and its influence on the stratosphere, there has been no clear explanation as to exactly what sort of circumstances/conditions would cause trails to persist for many minutes and, specifically, how jet stream changes would cause these conditions to change.

1.3Grids and Circles of Trails

In the photographs below, mainly from around the United Kingdom, a number of circles and grids of trails can be seen. There seems to be no good, clear explanation for this and, to my knowledge, military exercises have not been proven to be the cause of any of these “displays”. In one instance, from the 16th of Jan 2012, it is alleged that a “NATO plane” created these circles of trails5, though if this was true, the full purpose of the exercise that created them is not clear. An article in the Louth Leader6 claims “the aircraft was a NATO Sentry E3, a surveillance plane, which was on a sortie completing a standard UK orbit.” (As of writing this report, the photo shown below has disappeared from the site, though the story remains).

10 June 2005 – Borrowash, UK

21 Jan 2007, Humberside, UK

03 Aug 2007 – Borrowash, UK

15 Apr 2008 – Pyrenees, France/Spain

21 Feb 2009 – Borrowash, UK

16 Mar 2010 – Blaneau Ffestiniog, Wales, UK

Nov 2010 – Edinburgh, UK

29 Nov 2012 – Hendon, UK

16 Jan 2012 – Kidderminster, UK

16 Jan 2012 – Louth, UK

15 Mar 2013 – Grimsby, UK

04 Aug 2013 – Ashtead, UK

18 Aug 2013 – Ashtead, UK

10 Jan 2014 – Lancashire, UK

1.4Questions, Petitions and Investigations

There has been little, if any, formal investigation into the phenomena shown in section 1.3, though a number of people have tried to raise questions formally using an FOIA7 and through lobbying politicians – such as through the Skyguards group8, which organized a meeting in the European Parliament in Brussels in April 20139. In 2007, Rosalind Peterson gave an address to a UN Climate Change meeting in New York10.

Many hundreds or even thousands of “YouTubers” have uploaded videos of various kinds – some are particularly strange and show planes trailing together – with examples in Germany11 and in the USA12. A number of independent, good quality documentary films have been made by people such as Patrick Pasin13, Clifford Carnicom14, and Michael Murphy15. There are others of varying quality.

Despite all these strange instances of significant trailing, no official answers are forthcoming – only flat denials. It is therefore left to those people who have observed these troubling anomalies, to do their own investigation. This report is the result of one set of investigations.

1.4.1“Overcast” Documentary by Matthias Hancke et al to “Sample a Trail”

This documentary has been in the works for almost 1 year and may be released later in 2014. Matthias Hancke intends to scientifically sample and test material from a persistent trail/chemtrail. Matthias has already done some sampling, but has had problems with the sampling process and has needed funds to complete scientific/chemical analysis. Further updates can be found on the Facebook page16 and crowd-funding page.17

1.5Standard “Explanations” for the Phenomenon

A number of websites, including contrailscience.com/ and Wikipedia claim that all trails that are ever seen are contrails. While these sites do contain some valuable scientific information, you will not find a full explanation for the phenomena shown in the photographs in section 1.3 – to be valid, these explanations would need to include flight numbers and identification of planes on the dates shown. Instead, this evidence is hand-waved away and assumed to be covered with a tagline such as THE SCIENCE AND PSEUDOSCIENCE OF CONTRAILS AND CHEMTRAILS.” Metabunk.org also has some interesting observations and analysis, though is somewhat selective about what it shows and analyses, as is the case with contrailscience.com.

1.5.1Barium in Rainwater?

One claim that has been made several times is that there is a toxic level of barium in some rainwater – this claim has not really been proven to the point where it can be linked to “chemtrails”. An example case is that of Bill Nichols of Arkansas, USA18 – which was reported on KLSA news in 2007. There is a good analysis on contrailscience.com regarding this case19. Similar claims about aluminium levels have been made by Francis Mangels of California, USA20 – but it is not well known that some soils can contain aluminium salts in clays and so on. However, the fact remains that barium titanate has been proposed by the likes of Dr David Keith as a compound to be used in possible Solar Radiation Management projects21.

1.6The Reasons for Persistent Jet Trails/Chemtrails Appearing

Many reasons are suggested for Chemtrails. Clifford Carnicom has proposed the following possible reasons

  • To help create environmental or climate changes,

  • To introduce biological materials to affect humans or agriculture

  • For “military purposes”

  • To change the electromagnetic properties of the atmosphere

  • To cause geophysical or global effects

  • To enable operation of exotic propulsion systems

At this point, it is clear the phenomenon is real – but it is not really clear if the trails are being created through the use of fuel additives or whether there are aircraft in operation that have a separate spraying system installed. Some people claim to have photographed additional nozzles on aircraft, but in some cases, these have been shown to be for other purposes such as science research projects (there are some examples on the “metabunk” forum22 such as a study of a story entitled "Exclusive: Leaked Photos of Chemtrail Dispersal System"23.)

1.6.1Are Trails Appearing as a Result of External Manipulation of our Atmosphere?

One possible explanation that I have proposed in the past is that at least some of the trails are appearing because the atmosphere is being manipulated by some unknown technology – perhaps similar or the same as what was almost certainly used around the time of 9/11/01 to steer Hurricane Erin24.

Perhaps it is based on some of Wilhelm Reich’s Orgone technology25.

1.7Lack of Genuine Whistleblowers

Unfortunately, no genuine, knowledgeable whistleblowers seem to have come forward with detailed information that can be supported by comprehensive documents, photographs or videos. Though there has been internet chatter about people like A.C. Griffiths26and Kristen Meghan27, they do not seem to have brought forth any verifiable, solid information28. Though they may have made reference to documents such as “Owning the Weather by 2025”29 and other documents that have been produced by the military, they don’t seem to have explained many – or even any – of the observations we have made.

1.8Chemtrails/Jet Trails in Advertising and TV Visuals

There does seem to be an unusual prevalence of jet trails in advertising and in places where you might not expect them to be shown – I have collected some examples on this page30. One especially curious example was seen in a 2005 Virgin Trains commercial31.

In 2013, the BBC Wimbledon Introductory Visuals32 showed a trail in almost every shot where the sky was seen. Was it just innocent re-use of a stock image?

2.Air Traffic Investigation

This report represents the preliminary results of ongoing attempts to measure levels of air traffic over several locations during times of clear skies and during times when persistent trails or “chemtrails” appear.

It is not meant to be an explanation for chemtrails – and, indeed, it is not meant to “debunk” anything or anybody. This does not appear to prove there is a conspiracy to spray aerosol compounds in the sky – even though that it is possible that this is actually what is happening. It was simply an attempt to try and match or collect air traffic counts and log aircraft movements and then correlate this data with the appearance of trails. In this regard, at least, it has served a useful purpose.

2.1ADS-B – What is it?

The whole project/system relies on the fact that many aircraft are now transmitting ADS-B (Automatic Dependent Surveillance – Broadcast) messages when in flight. These messages contain the following information

  • A code number identifying the aircraft (sometimes called “ICAO”)

  • Flight Number

  • Altitude

  • Position (Latitude/Longitude)

  • Speed

  • Heading

(This page has a good explanation: planefinder.net/abou….) The tracker simply receives and decodes these messages – then software can be used to process the messages in any way desired. For example, you can count the number of aircraft which are detected in a given period, within a certain range and above a certain altitude or between certain altitudes.

Not all aircraft broadcast all the information above. It seems only about an average of 40% of aircraft detected broadcast their position.

2.2Detecting Aircraft Flying Over Your Location

2.2.1Early Equipment

This project essentially started in perhaps 2006, when I found out that it was possible to detect aircraft flying over a particular location (e.g. your own house!). At that time, I became aware of a piece of equipment called the SBS-1 – which would decode ABS-B messages that it could receive from aircraft. It was then an obvious question to see if it could be used, in some way, to identify and/or track aircraft that appeared to be leaving persistent trails or “Chemtrails”. However, the cost of the equipment (£500) was an initial deterrent to taking this idea further, at that time.


Airnav Radarbox

2.2.2More Recent Developments

In the last few years, websites such as www.FlightRadar24.co…Flight Aware and Planefinder.net have offered tracking and aircraft identification features, though they can in some cases be slow to update and somewhat cumbersome to use. Similarly, there are Android and iPhone Apps which interface to these online services and allow you, for example, to identify flights by holding up your phone in the direction of a plane in the sky. Of course, not everyone has an iPhone or Android phone…

As far as I am aware, the Website and Phone App solutions don’t have logging features of any great sophistication, so are not much use other than for “realtime viewing and tracking”.

2.2.3Airnav Radarbox

In 2010, I decided to invest in an AirNav Radar Box as I was still very curious as to what could be determined from using one to track aircraft. An important feature was that of “logging” any aircraft it detected – this meant that the unit could be left unattended and data could be examined retrospectively. However, there was still no easy way to get a visual record of trailing, other than deciding to go out with a camera and photograph the sky during periods of trailing. This was not very practical, as time could not be devoted exclusively to a “tracking project.”

2.2.4Airnav Software

The software that was shipped with the Radarbox provided a “virtual Air Traffic Controller’s (ATC) display” – all quite natty, but its logging features were limited. For example, it could keep a list of all the aircraft detected – and it could even playback a recording of logged data, but it was not able to produce charts or, for example, count the number of aircraft detected during a specified period, such as 30 minutes.

2.2.5Creating Charts of the Paths of Aircraft Detected

One of the original goals was to try and create charts which would show the path travelled by aircraft – this might allow the appearance of trails to be matched with the “charted path” of an aircraft – to see how close the visual trail matched the logged/charted path.

Airnav Radarbox Logfile

It was not initially clear how to do this, as the logfile simply consisted of lines of text, with the following columns:

  • “PTA” (Text)

  • Date and Time

  • Aircraft ID (ICAO)

  • Callsign

  • Altitude

  • Groundspeed

  • Track

  • Vertical Rate

  • Airspeed

  • Latitude

  • Longitude

It was therefore possible, in theory, to determine the path of an aircraft by plotting the indicated/logged latitude and longitude figures, although this was made more complicated by the fact that the log file was simply a list of logged messages from all aircraft in range of the receiver – the list was not “sorted by aircraft”.

Some Visual Basic for Applications (VBA) routines were developed in Microsoft Excel to process these Radarbox files and

  1. Generate charts of the paths of aircraft and

  2. Generate counts of aircraft detected in certain time periods.

A short section of VBA code used to generate charts and counts.

Aircraft Chart Generated by VBA Code from Airnav Logfile.

Counts were stored in spreadsheet worksheets for days when logging was running.

The data obtained from these logfiles was satisfactory, but time consuming to process and match up with observations.

2.3Wireless Webcams – Photographing the Sky

Time-stamped Webcam Image

FOSCAM Wireless Webcam

Another step was to try and photograph the sky at regular intervals automatically. This was achieved using a pair of FOSCAM wireless WebCams. These could be appropriately positioned on a window sill (indoors – weather proof units were more expensive and more difficult to cable up for power requirements).

2.4Control Program for Webcams and Airnav Logging

A small program was developed which would then switch on the aircraft logging in the Airnav Box Software and also, between dawn and dusk, capture sky images from the 2 webcams and insert a time stamp in each image. All the data was saved on a Netbook computer, which had to be left running 24 hours per day. Unfortunately, this netbook was used for other purposes, for a few days at a time, which meant the logging could not be run for more than a few days at a time.

This programme was not 100% reliable, as the Airnav data logging could not always be successfully switched on. This meant it was not really possible to build a consistent set of data which could be used to count aircraft over an extended period of several weeks or months.

3.Raspberry Pi Air Traffic Monitoring System

3.1Raspberry Pi

The Raspberry Pi is a small, credit card sized fairly powerful computer which runs a version of an Operating System called Debian Linux. It was released in 2012 – See www.raspberrypi.org/… for more information. I had obtained one not long after the release and set it up as a low-powered file server.

It is a credit to the way that Open-Source software systems work that allows developers now to plug together software and hardware components and build both hobbyist and professional projects – to a high level of sophistication – in a relatively short period of time. With appropriate programming knowledge, customisation of software is straightforward and practical. Coupled with the vast and easily searchable resources on the internet, solutions to common problems can quickly be found, enabling system reliability to be improved much more easily and more quickly. Significant computing power in a small, cheap and energy-efficient package also means that more and more advanced projects can be envisioned and developed at a modest cost of only a few hundred pounds.

In June 2013, I wondered if it was possible to connect the Raspberry Pi to the Airnav Radar Box – essentially to replace the Netbook and allow the Pi to take the data from the Airnav box and save it, so that I did not have to tie up a Netbook for this purpose.

After finding a forum discussion about this, I also found another and potentially better way of doing a similar sort of thing and “Pitracker” started to become a workable idea.

3.1.1Dump1090 – ADS-B Message Reception and Decoding on Raspberry Pi

I discovered forum posts and web pages which showed how it was possible to connect a USB dongle to the Raspberry Pi and, having compiled some software, the Pi was able to do most – if not all – of what the Airnav Radar box would do – for a fraction of the cost. A page by Dave Taylor provided a solid basis for some further Raspberry Pi development.

By getting the right type of USB Dongle – a Digital Terrestrial Broadcast Receiver Dongle (DVB-T) with the correct chipset (R820T/RTL2832U), I could track aircraft in realtime using a Raspberry Pi. Hence, all that was now needed was additional software to do the logging and counting. This was made much easier because the program which decoded the ADS-B messages also presented data from them through a web page interface. This program was written in C. In other words, all the hard work of decoding ADS-B messages was already done – I just needed to add some code to count the detected number of aircraft and generate charts.

3.1.2Counting Aircraft

It was relatively straightforward to adapt the Dump1090 program code to make it count detected aircraft in a set period. It was also possible to get it to count aircraft in various categories – such as those above 25000 feet, where trails are formed. All these counts were saved into a “daily data file”. Additionally a log of all aircraft detected was generated and saved. The main software development was done using a Ubuntu Linux installation with the help of the Codeblocks IDE. (The TV Dongle and Dump1090 code could also be used within a Linux installation.) The C code was simply copied onto the Raspberry Pi and compiled so that it would run on the Raspberry Pi directly.

3.1.3Photographing the Sky

In May 2013, a custom camera board was released for the Raspberry Pi and this could be operated by software that ran on the Raspberry Pi. It was now therefore possible to have the Pi log and track the aircraft – and photograph the sky – unattended, and using less than 8 watts of power. Additionally, raspberry Pi camera images were of considerably better quality than the Web Cams, as the Pi Camera has a 5 megapixel sensor.

3.1.4Automatic Capture of Weather Data

Using the World Weather Online website – www.worldweatheronli… – it was possible to obtain weather data at regular intervals, to be saved with the air traffic counts. Although ground-level weather data is not especially useful in relation to conditions which may affect the formation of trails at 25,000 feet and above.

3.1.5Configuration Data

In order to generate meaningful data, it was necessary to add a “configuration feature”. Most importantly, the latitude and longitude that the Raspberry Pi was located at needed to be set up – this would then allow measurements to be made based on this location.

3.1.6Webserver/Webpage to Display Realtime Plane Positions

The Dump1090 software also contained features which allowed the software to generate a Webpage which would show the positions of detected aircraft on a Google Map in real-time, along with any available data about each aircraft detected. However, this Webpage view defaulted to show a location near London, so this part of the software was also modified to display a map based on the configured location. Additionally, the webpage was modified to include additional features, such as aircraft counts and local weather data.

Realtime-Webpage/Google Map view Generated By Raspberry Pi Tracker

3.2Acknowledgements to Volunteers

I am grateful to those 5 volunteers who agreed to host trackers and help me set them up. Without their help, this project would not have been able to gather nearly as much data.

3.2.1Multiple Trackers – Remote Configuration and Upload of Captured Data

In order to get a better sample of data, it was decided early on that several “Pitrackers” should be put into operation, so several volunteers, from around the UK were asked to host them at their homes. This meant that a method had to be developed for transferring the data captured by these trackers to a central location (my own Raspberry Pi file server!) Hence, existing scripts were modified and a server was configured to accept and store the uploaded time-lapse video and aircraft data. Additionally, working with volunteers, the trackers were, when possible, set up to be remotely configurable, which meant that if certain problems developed in their operation, or software needed to be modified/updated, this was possible (and was necessary on more than one occasion). This was made possible by configuring the volunteer’s home router.

3.3System Components and Overall Operation

This diagram illustrates the components and general operation of the tracker system.

3.3.1System Operation

The system uses an unmodified Raspberry Pi with an SD Memory card (like those used in Digital Cameras and similar devices). The memory card holds both the Raspberry Pi Linux Operating system (“Raspbian OS”) and it is used to store the data acquired from the aircraft, as well as photos taken by the Raspberry Pi Camera.

Trackers were placed, when possible, on an upstairs window sill, which had a clear view of the sky. Once configured with a postcode, latitude, longitude and station name, they were left running 24 hours per day, 7 days per week. The tracker software included features to calculate local sunrise/sunset times and would only capture images and create plane charts during local day time.

Linux “scripts” and commands were created to compress (“zip”) each day’s data files and upload them to the server between midnight and 6am. Similarly, time-lapse videos were generated and uploaded to the server every night.

Single tracker in operation.

3.3.2Plane Charting

By using Linux Open Source Graphics Libraries (libplot and libglib), it was possible to plot aircraft paths on charts – as the data was captured by the Rasperry Pi. Charting parameters could be set so that planes within a certain range were drawn on the charts (which were created every 30 minutes by default). Only planes above a certain altitude were logged on the chart.

Aircraft “Traffic Chart” generated by Raspberry Pi Software (100 foot base altitude)

These charts were saved in PNG format (a useful feature of the graphics libraries).

3.3.3Aircraft Data Saved in CSV Format

Aircraft Data was saved on the Raspberry Pi’s SD Card – in a standard Comma Separated Value (CSV) format, which could be easily read and processed by other software.

Aircraft Count Data

Flight Data for Each Aircraft

3.3.4Time-lapse Videos

After realizing that the sky needed to be photographed approximately once every minute, it was realized that several hundred photos per day would be generated and these would need to be reviewed to check for trails. Clicking through hundreds of photos per day would have been a slow process, so it was soon determined that the Raspberry Pi was capable of automatically generating time-lapse video files (in MP4 format) by using another package called libav-tools.

Time-lapse Video Files Stored on Server

3.3.5Aircraft Data Database – Stored with Tracker Software

In experimenting with the AirNav Radarbox Software, it was discovered that it held an aircraft database which contained records for about 155000 aircraft. Each record held information about

  • The type of aircraft

  • Country of “Residence”

  • Airline / Owner

This Database was stored in a single file, which was copied onto the Raspberry Pi’s SD card. This allowed data about most of the detected aircraft to be written to a log file. Before the trackers were put into operation, this database was updated using additional data held in a text file from a free Windows package called PlanePlotter.

3.4Tracker Database Development

In order to generate some statistics from all the data files collected, a method was needed to collate all the data. Originally, some tests were made just using collections of daily spreadsheets that had been generated by the trackers. However, this method was too cumbersome and it was much more difficult to, for example, average out sets of figures over weeks or months. Hence, after data had been successfully collected for several months, a Microsoft Access Database was developed and data from the CSV files was manually imported into this database.

To read the rest, please download the PDF Version Here

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