A group of UCLA geographers published a paper yesterday in the MIT International Review entitled “Finding Osama bin Laden: An Application of Biogeographic Theories and Satellite Imagery”. The UCLA team used purely open source data, including “Landsat ETM+, Shuttle Radar Topography Mission, Defense Meteorological Satellite, QuickBird”. Then used a variety of commons geographic analysis techniques, “distance-decay theory, island biogeography theory, and life history characteristics” to predict high probability locations for Osama Bin Laden. The story has already been picked up by 90 media outlets and has been popping up on the front page of several major news outlets.

It would never make it out of the labyrinth of classification schemas in the US government, but it would be fascinating to see what a crowdsourced search for Bin Laden would turn up if better data was made available from the intel/defense community. Since the government data will never be released we thought we could at least help make the open source data easily accesible. So, we took the available data in the MIT article plus relevant data on Afghanistan and pushed it into GeoCommons. We’ve embedded a map with our own take below.

Maker.maker_host=’http://maker.demo.geocommons.com’;Maker.finder_host=’http://finder.demo.geocommons.com’;Maker.core_host=’http://core.demo.geocommons.com’;
Maker.load_map(“maker_map_28″, “28″);

To view this map in GeoCommons Maker! click here.

In addition to the UCLA data we’ve added gridded population data for the area. A big part of the UCLA thesis was Osama would be, “in a larger town rather than a smaller and more isolated town where extinction rate would be higher”. So, the gridded data gives a rough view of population densities in the remote Tora Bora region.

Source data for the maps is here:

Structure Locations of Possible Hiding Spots of Osama Bin Laden, Parachinar, Pakistan, 2009
Tora Bora 10 KM Buffer Rings
Gridded Population Data, Afghanistan and Pakistan border near Tora Bora

Would be great to see what other folks can do with the data to promote other perspectives. Also a nice opportunity to show the power of opening data up for better analysis, QA and alternative perspectives. Kudos to the UCLA team – great to see geographers in the news for doing what they do best.

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2 Responses to Finding Bin Laden with Open Source Data: Share the Data and Continue the Hunt

  1. marco puppin says:

    Hi there, hi Sean,

    the map is very interesting, the potentiality of geocommons, well they are great.
    I just meet geocommons and they really are such a powerful tool to show some bad-politicians behaviors. Here in Italy we have such a collection of data that it would be a sin to don’t use it..
    eheh..we fight them in something they don’t even can imagine…
    cartography!

    First, about Osama, i am not much in line with this score. I mean, looking the morphology of that place..he would be in such open space, in a versant like that.
    Mountains are a better way to get hide.
    That was a good idea to overlay the density %. Actually, i’ve always imaged Osama somewhere with no many people all around.
    Anyway, i also think he moves frequently. it’s good we try to come nearer, that’s sure..

    Now, i got a problem with my first geocommon map. It shows the % of EU Parliamentarians resigned, the data are just update by the EU Parliament.
    Here it is http://maker.geocommons.com/maps/3017
    Italy rocks!!!!! Bad times my friend, we are living bad times..
    So, i’d like to have the size of the points that increase as increase the value. The style of my layers doesn’t give me possibility, they are different from ones i saw in some web pages.
    Where am i wrong?

    Thanks in advance for any reply.
    OpenCiao!

    marco

  2. Sean Gorman says:

    Hi Marco,

    Many thanks for checking out GeoCommons. I took a look at the data and the map and it appears the columns with % resigned came in as a text field. Try changing the field to numeric and get rid of the text characters including “%”. so if it say “50%” change it to just “50″. Then just change the attribute name to percent resigned. Hope that helps.

    On Bin Laden’s location the estimates came from the UCLA team, so I can’t speak for them. They do lay out the theory as to why he would be in populated places and no remote places in their paper here:

    http://web.mit.edu/mitir/2009/online/finding-bin-laden.pdf

    best,
    sean