About the Author:  Sean Gorman founded FortiusOne in 2005 to bring location based analytics to the mass market. Sean brings over 10 years of experience at the forefront of the geospatial revolution as a researcher, practitioner, and entrepreneur at FortiusOne. Through both academic and entreprenurial efforts he has been working to make geographic data more accessible to the public since 1997 culminating in the creation of GeoCommons – a crowd-sourced repository of statistical data and social feeds that can be easily mapped, remixed and reused by non-technical users. Sean has been featured in media such as, Wired, Der Spiegel, ABC, Washington Post, Business 2.0, MSNBC, CBS and CNN. He also holds a PhD. From George Mason University in Public Policy where he was the Provost’s High Potential Scholar and was the recipient of the Fischer Prize. He has published dozens of articles on geographic data sharing and analysis, and authored the book Networks, Complexity and Security: The Role of Public Policy in Critical Infrastructure Protection. Read more from this author

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.

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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