The story behind the F-14-map “Where have all the Tomcats gone”

Have you ever wondered what happened to the 712 F-14 Tomcats that were built between 1970 and 1992?

Several of them were lost in crashes or scrapped due to structural failures during service. Most of the aircraft were scrapped after the retirement of the Tomcat in 2006 because of the fear that parts could end up in Iran to keep their F-14 fleet airworthy.

But some 140 survived and are still out there. In Iran there are still 12 to 50 (depending on the sources) airworthy Tomcats.

Click Here and check out the project of a map with all the remaining Tomcats, the crash sites and the historic sites.

But what kind of geek does it take to set up a map with more than 400 markers that represent the life of a 50-year-old plane, a plane that he hasn’t ever seen in real life? Let’s start from the beginning…

The human dimension (for the human-geeks)

(For the technical dimension see below (for the geek-geeks))

A little boy, fascinated by aviation and living in Luxembourg (Europe) … (Luxembourg??? … heard about it, but where is that??? Here!)… , buys on a holiday in South France a little “matchbox” plane with sweep wings … cool stuff in the early 1980s.

During the period of deepest cold war in the early 1980s, this boy plays with his little (as he later found out) Tomcat, fighting the “evil”.

Later he was given an Aviation-history-book with 500 pages that becomes his favourite book. He is lying on the floor, looking in it with big eyes to the technical details and pictures (no, reading wasn’t his thing).

He sees a picture of a US Navy plane landing on a carrier and he recognizes the sweep wings of the toy plane. He compares it with the images in the book and discovers… “Oh…so it is an F-14?!”!

“The Final Countdown” … “looks like an F-14!” … “Top Gun” … “wow… that’s an F-14 too!” … Pictures on the wall, building some models… Growing up, studying, working, marrying, childing … and the passion fades and the time passes.

In 2016 “Hachette Collections” (a weekly magazine where you get parts to build a Tomcat-model) comes with a 1:32 F-14 Tomcat with moving parts …!!! HOW COOL IS THAT!!!

After 2 years of collecting, building and reading (the magazines filled 5 binders, and he reads EVERYTHING, because suddenly, reading became his thing), the 1:32 Tomcat was finished and the passion had grown again!

But since he has not seen a Tomcat in real life yet, he wonders: where is the nearest one?

He is working for the local administration and maps and geodata are his business, so he puts some markers on “Google Earth”.

He starts reading, searching more and putting the data together… YES.. indeed … the simple idea of a map with the location of the remaining Tomcats, escalated a bit …

So today the map shows all the places where you can find Tomcats, where they were built, where they crashed, and where they made history. Every spot is accompanied with data, pictures, documents, statements and stories of all kinds.

But why all this work (“meaningless” for some)?

The answer is passion! Trying to find out something, needing to know everything, sharing it with others…and …to be with YOU … and other geeks …talking about our beloved TOMCAT!

You can even join the Facebook group dedicated to the map and getting in touch with other Tomcat-geeks.

There are still many unknown crash sites, parts or even entire aircraft that are undiscovered and we need your help, experiences and memories …before they fade!

Keep the memory of the F-14 Tomcat alive!

… and no … that “little boy” still hasn’t seen any Tomcat in reality yet.

The technical dimension (for the geek-geeks)

A little “How to” to collect data, combine them with locations and share them.

The “F-14 on display “

The name is a bit confusing because some are in restricted areas and aren’t displayed to the public.

The base of this dataset was the list from the “F-14 Tomcat Association”-homepage. Unfortunately, it hasn’t been kept up to date for a long time because of staff problems.

I combined it with the data from Aerial Visuals and Warbird Registry.

At the beginning I used “Google Earth” for pointing them on the map and kept the lists in Excel.

Quite quickly I wanted to combine the coordinates and the different alphanumeric data in one dataset.

I imported all the Excel-data to Access and linked them together via the BUNO as key. As output I had one big table with all the information fields.

Then I imported all the locations into a shapefile with QGIS and linked the Access file too. By linking the shapefile and the Access file in QGIS, I could display the data. And so, the map was born!

To complete the information of the different fighters, I added the data from Home of the M.A.T.S., The Grumman F-14 Tomcat Reference Work website, although this data has not been updated for a long time too. Adding it was particularly difficult because I had to copy the data page by page to Excel and then transform it to have the BUNO on every line. But this work was very useful because it turned out important for the later “crash sites”-part.

This model is available from AirModels – CLICK HERE TO GET YOURS

After that, I imported the spots as KML to “Google Earth Pro desktop” and I checked one by one on the aerial pictures. “Google Earth” is faster than Google maps and you may also compare with older aerial pictures. This is easy with the outside standing Tomcats. The ones that are inside, I had to compare with the pictures and maps from the museum sites, internet pictures etc … and I tried to move them to the exact position inside the building.

At some point I couldn’t get any further because there were many contradictions. As mentioned before, I live in Luxembourg and my research had shown that the nearest Tomcat is about 5000km/3000miles away. So, I couldn’t check by myself. I needed the help of the Tomcat community to check on site. In addition, other people would probably be interested in the dataset as there was no current public list of all Tomcats.

So, I had to find a way to share the map. After some searching, I discovered that “Google MyMaps” was perfect for this task. I could export my data from QGIS into KML and import it directly to MyMaps.

During the early phase I had to make a lot of modifications and so I kept the data in QGIS and imported the entire dataset to MyMaps on every update. But after some time, I decided to edit the data directly in MyMaps. So today the main database is in MyMaps and I only do regularly backups to KML-files which can easily be imported to Googleearth, Qgis etc..

The “F-14 related Sites“

This section is a collection of POIs that I added gradually.

The „F-14 Crash Sites and Mishaps“

During my researches I discovered a lot of pictures and films of crashes and mishaps and I wanted to add them in some way. Especially Aviation Safety Network inspired me to go further.

I imported the data like before and combined it with the prementioned “Home of the MATS”-list. After some very tricky “filter and sorting” by date and BUNO I could again generate one list with one presumed crash per line. A lot of guessing and comparing…!

After the list was completed, I checked line per line (some 200) and searched for location indications in the text. Sometimes there were exact locations, like the Yuma-Crash site with coordinates from “Home of the MATS”, but most were like “in the Atlantic”. So I copied this location indications into the “Crash Place”-Field and made an “Place-Status”-Field, in which I evaluated this location in following categories:

“OK” : for “Known”, an exact location, like coordinates

“A” : for “Area”, a small area, like “near El Centro”

“LA” : for “large Area”, a large area, like “into the Atlantic”

“?” : for “unknown”, without any indications

After that I had to place all the spots one by one on the map.

Here it became REALY TRICKY !!! only for NERDY-GEEK-GEEKS

How to put something on a map without any location indication?

So, what are relevant information in the dataset?

The identification of the Tomcat : The BUNO

The Crash-date

The Crash-location

The precision of the location indication

The data with “known location” would be displayed:

on the presumed right spot

with a marker in the colour, corresponding to the “Place-Status”

with a Label with the BUNO and the crash date ex: “1XXXXX / YYYY MM DD”

The data “without location”:

To find something in such a dataset, you would search for a BUNO or the “Crash date”. So, they should be displayed in a logical way to find them. I tried to put them in a Cartesian coordinate system with the “Crash Date” on the “X-axis” and the BUNO on the “Y-axis”

with a “?” marker because the location is unknown

with a Label with The BUNO and the crash date ex: “15XXXX / YYYY MM DD”

Sometimes the BUNO wasn’t known. But because I couldn’t leave the field empty I used “157000” for unknown BUNO’s.

This print is available in multiple sizes from AircraftProfilePrints.com – CLICK HERE TO GET YOURS. F-14A Tomcat VF-1 Wolfpack, NE103 / 162603 / Operation Desert Storm, 1991

But I did not want to put the spots one by one, but “automatically”?

So, I made a calculated transformation in Excel.

To understand the transformation, you need to know that I used a local coordinate system. It is a simple XY-System with 1 millimetre as unit and its centre somewhere in north of France. The values that I added in the formulas were selected by “try and fail”. It went quite quickly and I got the result I wanted. So please do not ask me for scientific explanations for the chosen values, there are none!

I searched on Google maps for an area with a lot of space where I wouldn’t place “regular” spots.

The Antarctic sea was be perfect for this.

To make the calculation as easy as possible, I chose, after analysing the data (see below), the following range:

X: 10959000 to 25569000

Y : 15700000 to 16500000

Here is the reasoning:

X-axis: Crash Date First Crash : 03.12.1970 Last possible crash : 04.11.2006 So, the range would be : 01.01.1970 to 31.12.2010 Converting the date to text in Excel: 25569 to 40179



(01/01/1900 = Day #1; 02/01/1900 = Day #2; 03/01/1900 = Day #3…

So, … 01.01.1970 = Day #25569 and 31.12.2010 = Day #40179 …)

To enlarge the display area, I multiplied it by 1000 To “move” the area to an empty space over the sea, I subtracted 14610000 Here is the formula I used to transform the Date (in column A) to the X-Coordinate : =((TEXT(A2;0))*1000)-14610000 So, the X coordinates would be 10959000 to 25569000



Y-axis : BUNO First BUNO : 157980 Last BUNO: 164604 So, the range would be 157000 to 16500 To enlarge the display area, I multiplied it by 100 So, the Y-coordinates would be 15700000 to 16500000



All I had to do then was to apply this formulas on every line of my “crash-site-table”, import it in QGIS as csv-file and then export it into a KML-file in QGIS, which may be directly imported to MyMaps.

After that I attributed symbols and colours to the different “Place-Status”’s and then placed manually one-by-one on the map using the text from the “Crash Place”.

After that, only the “unknown Crash places” remained in the “Cartesian coordinate system” .

To make searching easier I added a grid with labels, which I created the same way as the crash sites.

Photo credit: Marc Wolff and Google MyMaps