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dc.contributor.authorArge, Lars
dc.contributor.authorChase, Jeffry S.
dc.contributor.authorHaplin, Patrick
dc.contributor.authorToma, Laura
dc.contributor.authorVitter, Jeffrey Scott
dc.contributor.authorUrban, Dean
dc.contributor.authorWickremesinghe, Rajiv
dc.date.accessioned2011-03-21T17:44:08Z
dc.date.available2011-03-21T17:44:08Z
dc.date.issued2003
dc.identifier.citationL. Arge, J. S. Chase, L. Toma, J. S. Vitter, R. Wickremesinghe, P. Halpin, and D. Urban, “Efficient Flow Computation on Massive Grid Terrain Datasets,” Geoinformatica, 7(4), December 2003, 283–313. An extended abstract appears in “Flow Computation on Massive Grids,” Proceedings of the 9th ACM International Symposium on Advances in Geographic Information Systems (ACM-GIS ’01) Atlanta, GA, November 2001, 82–87. http://dx.doi.org/10.1023/A:1025526421410
dc.identifier.urihttp://hdl.handle.net/1808/7202
dc.descriptionThe original publication is available at www.springerlink.com
dc.description.abstractAs detailed terrain data becomes available, GIS terrain applications target larger geographic areas at ner resolutions. Processing the massive data involved in such applications presents signi cant challenges to GIS systems and demands algorithms that are optimized both for data movement and computation. In this paper we develop e cient algorithms for flow routing on massive terrains, extending our previous work on flow accumulation. We have implemented these algorithms in the Terraflow system, which is the rst comprehensive terrain flow software system designed and optimized for massive data. We compare the performance of Terraflow with that of state of the art commercial and open-source GIS systems. On large terrains, Terraflow outperforms existing systems by a factor of 2 to 1000, and is capable of solving problems no system was previously able to solve.
dc.language.isoen_US
dc.publisherSpringer Verlag
dc.titleEfficient Flow Computation on Massive Grid Terrain Datasets
dc.typeArticle
kusw.kuauthorVitter, Jeffrey Scott
kusw.oastatusfullparticipation
dc.identifier.doi10.1023/A:1025526421410
kusw.oaversionScholarly/refereed, author accepted manuscript
kusw.oapolicyThis item meets KU Open Access policy criteria.
dc.rights.accessrightsopenAccess


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