Andrew Johnson - Report on Pi Tracker Air Traffic/Chemtrail Monitoring Project Apr/May 2014

Here are the details of Andrew Johnson's extensive report based on data gathered from his Pi Tracker Air Traffic/Chemtrail Monitoring Project:

A Systematic Attempt to Measure Air Traffic Levels and Count Persistent Jet Trails/Chemtrails Using a Raspberry Pi-Based Computer Network

"After about 9-10 months of running 1 or more "trackers", I have compiled this report to explain what was done and what the results, so far, were. Please forward to anyone who is interested in the "Chemtrail" Phenomenon. All constructive criticism will be gratefully received and reviewed (including spelling/wording corrections)! I encourage you to repost this message and the links below on forums and on Facebook. I have pasted my "Abstract" and Conclusions below - and the rest can be read in the report (over 50 pages, but quite a few pictures and tables).
Web Version: http://tinyurl.com/airtraffrep1
PDF Version: http://tinyurl.com/airtraffrep1pdf
I will be following this up with a YouTube video version of this report, where I will edit it the time-lapse videos that I refer to. If you want to look at those, they are posted on this page: http://www.checktheevidence.com/video/index.php?dir=PiTrackerTL/
Thanks for reading!
Andrew Johnson (UK)"

Abstract
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.

Conclusions
Detected Air Traffic Levels and Trailing
From all the data gathered so far, it seems there is no large difference in “ADS-B detectable” aircraft on days of high trailing than there are on days of no trailing. The data here does not establish a clear link between levels of aircraft and levels of trailing. Looking at some figures in isolation, it could be argued that there is a lower amount of aircraft on days of trailing. This result, therefore would tend to disprove a general statement that trailing is seen because of increased levels of air traffic – if that is the case, then it is air traffic which is not detectable in the same way as “regular” air traffic.

Perhaps a better detector is needed, although this is unlikely – as a range of 20 miles should be sufficient to “detect planes and see trails” with this sort of equipment. For example, if one examines the charts, most of them have an unbroken line of travel for the planes, which means enough of the messages were picked up, while the plane was in range, to plot the path of the plane.

Identification of Flights Leaving Trails and Formation of Grids
It was sometimes quite difficult to identify which flights left trails – perhaps because only a maximum of about 50% of the flights could have their latitude and longitude decoded. Without this information, it was impossible to know if the flight was precisely overhead, or whether it was 100 miles away. The “percentage located” figure showed no appreciable variation between days of trailing and no trailing.

The study from 25 Nov 2013 of the WA6 tracker shows that it is was not possible, using ADS-B data, to identify all of the flights which made the grids. Though, looking at some of the charts, the potential for grids to form can be seen, these were not seen “in the right place” and not enough flights were detected to prove, from this data, that civilian air traffic is responsible for forming these grids. So they remain a mystery.

A study of data from the DE72 tracker seemed also to show that flights that were travelling in a NorthóSouth Direction were rarely seen on charts – and if they were, it was over the far west of Derby – about 20 miles from where the tracker was sighted. Further attempts at identifying “trailing flights” could be undertaken, even with the existing data.

Days of Trails or No Trails?
No obvious reason could be observed why trails were seen on some days and not others. Again, taking the 25 Nov 2013 time-lapse video, it can easily be seen that there are persistent and non-persistent trails appearing in the same periods of time and the same part of the sky. So this remains unexplained.

Weather Anomalies
The tracker with the best view did seem to observe some kind of weather anomalies on some days – why would cloud formations remain in the same place above the ground, whilst “other weather” drifts past? Why would this happen the clouds both at lower and higher altitudes? What is the cause of linear weather fronts?