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Macrometeorites, by Roxana Torre

An inside look at the Visualizing Meteorites Challenge winner

June 27, 2013

[This a guest post by Roxana Torre*, explaining the process behind the creation of the ‘Macrometeorites‘ visualization, winner of the’s Visualizing Meteorites Challenge .]


Meteorites can be considered as a part of outer space here on Earth and that is what makes them so intriguing even when many of them could easily be confused with normal stones.

“Macrometeorites” is a visualization of the largest meteorites that collided with Earth and it’s based on a data set from “The Meteorolitical Society”. The project has been the winning entry of’s “Visualizing Meteorites” Challenge (June 2013).

I’m always interested in the way data can define its own geography and on how different datasets containing geo-coordinates can relate to each other. I don’ t necessarily feel the need to see the terrain as a container for data in the way a “GIS” (geographical information system) does.

When starting a new project I “play” with the data to see which singularities can be found, Is there something which can be discovered by displaying the data in different ways? Can the data relate to something else?

The Meteorilitical Society’s data set contains geo-coordinates of the landing point of around 40000 meteorites. Having these data, one of the questions you could want to find an answer to is: are meteorites more likely to fall in a certain area on the earth?. After displaying the points geographically the world map became visible and it was easy to see that it was not possible to find an answer to this question, however other interesting facts could be seen.

Macrometeorites, interactive infographic by Roxana Torre
(picture 1: all meteorites included in the dataset | Roxana Torre)

The geography defined by the landing points looks pretty much like the map of highly populated areas in the world. This is quite normal of course but it also means that there might probably be much more meteorites landings which have not been found or documented.

The fact that no meteorites seem to have been found in the Amazon rainforest is easy to understand. However, looking at the map you will see that there are a number of areas with a large density of meteorites which are not highly populated such as Australia, Antarctica, the Sahara and great plains of the US . What’s happening here? A visit to Wikipedia  gives the answer to this question. These are areas where, because of the terrain characteristics, meteorites are relatively easy to find and where a more or less organized search has taken place.

The dataset also includes the year in which the meteorites fell or were found. Taking this into account you could ask yourself if there is a period in history were the most meteorites fell.

Macrometeorites, interactive infographic by Roxana Torre
(picture 2: amount of meteorites “finds and falls” through the years | Roxana Torre)

If we look at the found meteorites through the years, you can see that there has been a gradual increment with a highest point around 2000. Taking a closer look at the names of the meteorites in this period and making a quick search it’s easy to find out that this is the result of systematic meteorite search. That means this increment doesn’t directly mean an increment in meteorite falls in that period.

Classifying meteorites

One of the items in the data set is the classification according to the kind of meteorites, however there are more than 350 different classes! Looking at different sources, I found out that there were three big categories: stony meteorites, iron meteorites and iron-stony meteorites. These categories seemed to me easier to understand for non experts. Although these three classes were not in the database, it was not difficult to find out which meteorites belong to each of them. I did this by following the ‪Meteorite Classification after Weissberg McCoy Krot‬.

Other interesting classification are the groups “Finds and Falls”: which of the meteorites were found and which of them have been spotted when falling. This is a very important classification because on one hand spotting a meteorite falling down has a lot of impact and on the other hand only for this group it is certain the year in which the collided the Earth. For these reasons special attention has been given in differentiating these two groups both in the map and in the timeline.

Curious fact is that there are a few meteorites which come from the Moon and Mars, you could ask yourself how they came to the earth? (I leave the answer to your own curiosity…)

Of course the most intriguing part of this are the greatest meteorites, obviously a meteorite with a mass of more of 10 metric tons doesn’t go unnoticed!! I’ve linked the most famous meteorites to wikipedia’s explanation, although I must say I would have liked to make some further research on this if I’d had more time!

Some details

One of the difficulties of the dataset is that there were too many points to display, so it was important to choose an interesting subset of points. After studying different possibilities I decided that visualizing the heaviest ones was a nice solution because it resulted in an interesting subset without having to discard meteorites in the past or a specific sort (which could have been another alternative).

For the visualization the d3.js library has been used. For the filtering of points I used crossfilter.js, a great library which has simplified my work enormously!

With this visualization I tried to give a broad insight on meteorite landings for all people interested on the subject. You could say that the result is quite “classic” (there’s a map, a timeline and there are possibilities to explore the data through different filters) but the hardest work was trying to find a good balance between what should be shown and what is less relevant for the user.

Macrometeorites, interactive infographic by Roxana Torre
(image: Macrometeorites, by Roxana Torre)


 *Roxana Torre is a media designer (MA) graduated at the Piet Zwart Institute in Rotterdam and has a background in land-surveying. Since 2000 she runs her own studio in Delft, The Netherlands. She combines analytic  design and programming skills to transform large datasets into interactive data visualizations. Vist her website for more of her work:

Written by Tiago Veloso

Tiago Veloso is the founder and editor of Visualoop and Visualoop Brasil . He is Portuguese, currently based in Bonito, Brazil.