Using orthographic projections to map organism distributions

For a current project I'm currently working I show organism distributions using data from GBIF, and I display that data on a map that uses the equirectangular projection. I've recently started to create a series of base maps using the GBIF colour scheme, which is simple but effective:

• #666698 for the sea
• #003333 for the land
• #006600 for borders
• yellow for localities

The distribution map is created by overlaying points on a bitmap background using SVG (see SVG specimen maps from SPARQL results for details). SVG is ideally suited to this because you can take the points, plot them in the x,y plane (where x is longitude and y is latitude) then use SVG transformations to move them to the proper place on the map.

For the base maps themselves I've also started to use SVG, partly because it's possible to edit them with a text editor (for example if you want to change the colours). I then use Inkscape to export the SVG to a PNG to use on the web site.



One thing that has bothered me about the equirectangular projection is that, although it is familiar and easy to work with, it gives a distorted view of the world:

This is particularly evident for organisms that have a circumpolar distribution. For example, Kerguelen's petrel Aphrodroma has a distribution that looks like this using the equirectangular projection:



This long, thin distribution looks rather different if we display it on a polar projection:


Likewise, classic Gondwanic distributions such as that of Gripopterygidae become clearer on a polar projection.



Computing the polar coordinates for a set of localities is straightforward (see for example this page) and using SVG to lay out the points also helps, because it's trivial to rotate them so that they match the orientation of the map. Ultimately it would be nice to have an embedded, rotatable 3D globe (like the Google Earth plugin, or a Javascript+SVG approach like this). But for now I think it's nice to have the option of using different projections available to help display distributions more faithfully.

The bitmap maps and their SVG sources are available on github.

Planet management, GBIF, and the future of biodiversity informatics

Next week I'm in Copenhagen for GBIC, the Global Biodiversity Informatics Conference. The goal of the conference is to:

...convene expertise in the fields of biodiversity informatics, genomics, earth observation, natural history collections, biodiversity research and policy needed to set such collaboration in motion.

The collaboration referred to is the agreement to mobilise data and informatics capability to met the Aichi Biodiversity Targets.

I confess I have mixed feelings about the upcoming meeting. There will be something like 100 people attending the conference, with backgrounds ranging from pure science to intergovernmental policy. It promises to be interesting, but whether a clear vision of the future of biodiversity informatics will emerge is another matter.

GBIC is part of the process of "planet management", a phrase that's been around for a while, but I only came across in the Bowker's essay "Biodiversity Datadiversity"¹:

Bowker, G. C. (2000). Biodiversity Datadiversity. Social Studies of Science, 30(5), 643–683. doi:10.1177/030631200030005001

Bowker's essay is well worth a read, not least for the choice quotes such as:

Each particular discipline associated with biodiversity has its own incompletely articulated series of objects. These objects each enfold an organizational history and subtend a particular temporality or spatiality. They frequently are incompletely articulated with other objects, temporalities and spatialities — often legacy versions, when drawing on non-proximate disciplines. If one wants to produce a consistent, long-term database of biodiversity-relevant information the world over, all this sounds like an unholy mess. At the very least it suggests that global panopticons are not the way to go in biodiversity data. (p. 675, emphasis added)

and

I have not, in general, questioned the mania to name which is rife in the circles whose work I have described. There is no absolutely compelling connection between the observation that many of the world’s species are dying and the attempt to catalogue the world before they do. If your house is on fire, you do not necessarily stop to inventory the contents before diving out the window. However, as Jack Goody (1977) and others have observed, list-keeping is at the heart of our body politic. It is also, by extension, at the heart of our scientific strategies. Right or wrong, it is what we do. (p. 676, emphasis added)

Given that I'm a fan of the notion of a "global panopticon", and spend a lot of time fussing with lists of names, I find Bowker's views refreshing. Meantime, roll on GBIC2012.

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1. Bowker cites Elichirigoity as a source of the term "planet management":

Fernando Elichirigoity (1999), Planet Management: Limits to Growth,
Computer Simulations, and the Emergence of Global Spaces (Evanston, IL: Northwestern
University Press). ISBN 0810115875 (Google Books oP3wVnKpGDkC).

From the limited Google preview, and the review by Edwards, this looks like an interesting book:

Edwards, P. (2000). Book Review:Planet Management: Limits to Growth, Computer Simulation, and the Emergence of Global Spaces Fernando Elichirigoity. Isis, 91(4), 828. doi:10.1086/385020 (PDF here)

Where is the "crowd" in crowdsourcing? Mapping EOL Flickr photos

In any discussion of data gathering or data cleaning the term "crowdsourcing" inevitably comes up. A example where this approach has been successful is the Encyclopedia of Life's Flickr pool, where Flickr users upload images that are harvested by EOL.

Given that many Flickr photos are taken with cameras that have built-in GPS (such as the iPhone, the most common camera on Flickr) we could potentially use the Flickr photos not only as a source of images of living things, but to supplement existing distributional data. For example, Flickr has enough data to fairly accurately construct outlines of countries, cities, and neighbourhoods, see The Shape of Alpha, so what about organismal distribution?

This question is part of a Masters project by Jonathan McLatchie here at Glasgow, comparing distributions of taxa in GBIF with those based on Flickr photos. As part of that project the question arose "where are the Flickr photos being taken?" If most of the photos are being taken in the developed world, then there are at least two problems. The first is the obvious bias against organisms that live elsewhere (i.e., typically many photos won't be taken in those regions where you'd actually like to get more data). Secondly, the presence of zoos, wildlife parks, and botanical gardens means you are likely to get images of organisms well outside their natural range.

Jonathan suggested a "heatmap" of the Flickr photos would help, so to create this I wrote a script to grab metadata for the photos from the Encyclopedia of Life's Flickr pool, extract latitude and longitude, and draw the resulting locations on a map. I aggregated the points into 1°×1° squares, and generated a GBIF-style map of the photos:



Lots of photos from North America, Europe, and Australasia, as one might expect. Coverage of the rest of the globe is somewhat patchy. I guess the key question to ask is extent the "crowd" (Flickr users in this case) is essentially replicating the sampling biases already in projects like GBIF that are aggregating data from museum collections (most of which are in the developed world).

The PHP code to fetch the photo data and create the map is available in github. You'll need a Flickr API key to run the script. The github repository has an SVG version of the map (with a bitmap background). A bitmap copy of the map is available on FigShare http://dx.doi.org/10.6084/m9.figshare.92668.