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dc.contributor.advisorLi, Xingong
dc.contributor.authorGrady, Charles Joseph
dc.date.accessioned2018-01-30T03:17:25Z
dc.date.available2018-01-30T03:17:25Z
dc.date.issued2017-05-31
dc.date.submitted2017
dc.identifier.otherhttp://dissertations.umi.com/ku:15301
dc.identifier.urihttp://hdl.handle.net/1808/25811
dc.description.abstractBased on a conservative projection by the IPCC (IPCC 2007), inundation caused by sea level rise will likely disrupt the physical, economic, and social systems in coastal regions around the world. This research proposed an innovative method to calculate the minimum sea level rise required to inundate a cell in a Digital Elevation Model (DEM). The method, which accounts for water connectivity when determining inundation height for each cell, performs better than the simple “bathtub” approach, especially with sea level rises below 1 m. Several implementation data structures are proposed and compared. The combination of a binary heap and hash table data structure gives the most efficient implementation. The implementation is further parallelized using a master / worker paradigm. The parallel approach significantly outperforms serial implementations with respect to running time and memory footprint. Performance can be further improved with additional processing cores and using the supercomputing resources in the XSEDE (Towns, et al., 2014) program.
dc.format.extent72 pages
dc.language.isoen
dc.publisherUniversity of Kansas
dc.rightsCopyright held by the author.
dc.subjectGeographic information science and geodesy
dc.subjectcost distance
dc.subjectDijkstra's algorithm
dc.subjectinundation height
dc.subjectparallelization
dc.titleDelineating Sea-Level Rise Inundation: An Exploration of Data Structures and Performance Optimization
dc.typeThesis
dc.contributor.cmtememberMiller, James
dc.contributor.cmtememberLei, Ting
dc.thesis.degreeDisciplineGeography
dc.thesis.degreeLevelM.S.
dc.identifier.orcid
dc.rights.accessrightsopenAccess


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