Wednesday 26th June, 2013
5:45pm to 6:00pm
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.
Geographic Information Specialist at CIESIN; Adjunct Lecturer at Columbia University SIPA bio from LinkedIn
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