Visualization of flooding using adaptive spatial resolution

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dc.contributor.authorHadimlioglu, I. Alihan
dc.contributor.authorKing, Scott A.
dc.creator.orcidhttps://orcid.org/0000-0003-1588-1245en_US
dc.creator.orcidhttps://orcid.org/0000-0002-4022-0388en_US
dc.creator.orcidhttps://orcid.org/0000-0003-1588-1245
dc.creator.orcidhttps://orcid.org/0000-0002-4022-0388
dc.creator.orcidhttps://orcid.org/0000-0003-1588-1245
dc.creator.orcidhttps://orcid.org/0000-0002-4022-0388https://orcid.org/0000-0003-1588-1245
dc.creator.orcidhttps://orcid.org/0000-0002-4022-0388
dc.date.accessioned2021-10-27T21:49:48Z
dc.date.available2021-10-27T21:49:48Z
dc.date.issued2019-05-04
dc.description.abstractFlood simulations are vital to gain insight into possible dangers and damages for effective emergency planning. With flexible and natural ways of visualizing water flow, more precise evaluation of the study area is achieved. In this study, we describe a method for flood visualization using both regular and adaptive grids for position-based fluids method to visualize the depth of water in the study area. The mapping engine utilizes adaptive cell sizes to represent the study area and utilizes Jenks natural breaks method to classify the data. Predefined single-hue and multi-hue color sets are used to generate a heat map of the study area. It is shown that the dynamic representation benefits the mapping engine through enhanced precision when the study area has non-disperse clusters. Moreover, it is shown that, through decreasing precision, and utilizing an adaptive grid approach, the simulation runs more efficiently when particle interaction is computationally expensive.en_US
dc.description.abstractFlood simulations are vital to gain insight into possible dangers and damages for effective emergency planning. With flexible and natural ways of visualizing water flow, more precise evaluation of the study area is achieved. In this study, we describe a method for flood visualization using both regular and adaptive grids for position-based fluids method to visualize the depth of water in the study area. The mapping engine utilizes adaptive cell sizes to represent the study area and utilizes Jenks natural breaks method to classify the data. Predefined single-hue and multi-hue color sets are used to generate a heat map of the study area. It is shown that the dynamic representation benefits the mapping engine through enhanced precision when the study area has non-disperse clusters. Moreover, it is shown that, through decreasing precision, and utilizing an adaptive grid approach, the simulation runs more efficiently when particle interaction is computationally expensive.
dc.identifier.citationHadimlioglu, I.A. and King, S.A., 2019. Visualization of flooding using adaptive spatial resolution. ISPRS International Journal of Geo-Information, 8(5), p.204.en_US
dc.identifier.citationHadimlioglu, I.A. and King, S.A., 2019. Visualization of flooding using adaptive spatial resolution. ISPRS International Journal of Geo-Information, 8(5), p.204.
dc.identifier.doihttps://doi.org/10.3390/ijgi8050204
dc.identifier.urihttps://hdl.handle.net/1969.6/89881
dc.language.isoen_USen_US
dc.language.isoen_US
dc.publisherMDPIen_US
dc.publisherMDPI
dc.rightsAttribution 4.0 International*
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectflooden_US
dc.subjectsimulationen_US
dc.subjectadaptiveen_US
dc.subjectmappingen_US
dc.subjectquadtreeen_US
dc.subjectgrid-baseden_US
dc.subjectflood
dc.subjectsimulation
dc.subjectadaptive
dc.subjectmapping
dc.subjectquadtree
dc.subjectgrid-based
dc.titleVisualization of flooding using adaptive spatial resolutionen_US
dc.titleVisualization of flooding using adaptive spatial resolution
dc.typeArticleen_US
dc.typeArticle

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