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dc.contributor.advisorWan, Tao Ruan
dc.contributor.advisorPalmer, Ian J.
dc.contributor.authorWang, Chen*
dc.date.accessioned2009-08-24T11:15:12Z
dc.date.available2009-08-24T11:15:12Z
dc.date.issued2009-08-24T11:15:12Z
dc.identifier.urihttp://hdl.handle.net/10454/3350
dc.description.abstract3D environment reconstruction has received great interest in recent years in areas such as city planning, virtual tourism and flood hazard warning. With the rapid development of computer technologies, it has become possible and necessary to develop new methodologies and techniques for real time simulation for virtual environments applications. This thesis proposes a novel dynamic simulation scheme for flood hazard warning. The work consists of three main parts: digital terrain modelling; 3D environmental reconstruction and system development; flood simulation models. The digital terrain model is constructed using real world measurement data of GIS, in terms of digital elevation data and satellite image data. An NTSP algorithm is proposed for very large data assessing, terrain modelling and visualisation. A pyramidal data arrangement structure is used for dealing with the requirements of terrain details with different resolutions. The 3D environmental reconstruction system is made up of environmental image segmentation for object identification, a new shape match method and an intelligent reconstruction system. The active contours-based multi-resolution vector-valued framework and the multi-seed region growing method are both used for extracting necessary objects from images. The shape match method is used with a template in the spatial domain for a 3D detailed small scale urban environment reconstruction. The intelligent reconstruction system is designed to recreate the whole model based on specific features of objects for large scale environment reconstruction. This study then proposes a new flood simulation scheme which is an important application of the 3D environmental reconstruction system. Two new flooding models have been developed. The first one is flood spreading model which is useful for large scale flood simulation. It consists of flooding image spatial segmentation, a water level calculation process, a standard gradient descent method for energy minimization, a flood region search and a merge process. The finite volume hydrodynamic model is built from shallow water equations which is useful for urban area flood simulation. The proposed 3D urban environment reconstruction system was tested on our simulation platform. The experiment results indicate that this method is capable of dealing with complicated and high resolution region reconstruction which is useful for many applications. When testing the 3D flood simulation system, the simulation results are very close to the real flood situation, and this method has faster speed and greater accuracy of simulating the inundation area in comparison to the conventional flood simulation modelsen
dc.language.isoenen
dc.rights<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.en
dc.subjectLarge-scaleen
dc.subjectDigital Terrain Modelen
dc.subjectActive Contour Based Image Segmentationen
dc.subjectIntelligent Shape Match Methoden
dc.subject3D Environmental reconstructionen
dc.subjectFlood Spreading ModelFlood Spreading Modelen
dc.subjectFinite Volume Hydrodynamic Modelen
dc.subject3D flood simulationen
dc.titleLarge-scale 3D environmental modelling and visualisation for flood hazard warning.en
dc.type.qualificationleveldoctoralen
dc.publisher.institutionUniversity of Bradfordeng
dc.publisher.departmentDepartment of Creative Technology. School of Computing, Informatics and Media.en
dc.typeThesiseng
dc.type.qualificationnamePhDen
dc.date.awarded2009
refterms.dateFOA2018-07-18T14:10:57Z


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