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Please use this identifier to cite or link to this item: http://hdl.handle.net/11299/126871

Title: Efficient Algorithms for Geographic Watershed Analysis
Authors: Barnes, Richard
Lehman, Clarence
Mulla, David
Galzki, Jacob
Wan, Haibo
Nelson, Joel
Keywords: supercomputing
geographic analysis
Issue Date: 3-Jul-2012
Abstract: This project is to analyze where wetlands and other vegetated buffers can be placed on the landscape to intercept drain waters and help purify them before they reach the natural watershed. The computational problem comes because new LIDAR images have expanded the resolution of geographic digital elevation models (DEMs) up to a thousandfold or more. This in turn has taxed the ability of existing algorithms to process the expanded datasets. Here we explain the project and present new efficient algorithms for parallel and scalar processing that reduce run-times from days on ordinary computers to minutes or second using the new algorithms in a parallel supercomputing environment.
Description: poster presented at the MSI 2012 Research Exhibition
URI: http://purl.umn.edu/126871
Appears in Collections:MSI Research Exhibition 2012

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