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SciPy 2013

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The Production of a Multi-Resolution Global Index for Geographic Information Systems Authors: MacManus, Kytt, Columbia University CIESIN Track: GIS - Geospatial Data Analysis In order to efficiently access geographic information at the pixel level, at a global scale, it is useful to develop an indexing system with nested location information. Considering a 1 sq. km image resolution, the number of global pixels covering land exceeds 200 million. This talk will summarize the steps taken to produce a global multi-resolution raster indexing system using the Geospatial Data Abstraction Library (GDAL) 1.9, and NumPy. The implications of presenting this data to a user community reliant on Microsoft Office technologies will also be discussed.

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