3D Simplification Methods and Large Scale Terrain Tiling
dc.contributor.author
dc.date.accessioned
2020-01-30T11:46:57Z
dc.date.available
2020-01-30T11:46:57Z
dc.date.issued
2020-01-30
dc.identifier.uri
dc.description.abstract
This paper tackles the problem of generating world-scale multi-resolution triangulated irregular networks optimized for web-based visualization. Starting with a large-scale high-resolution regularly gridded terrain, we create a pyramid of triangulated irregular networks representing distinct levels of detail, where each level of detail is composed of small tiles of a fixed size. The main contribution of this paper is to redefine three different state-of-the-art 3D simplification methods to efficiently work at the tile level, thus rendering the process highly parallelizable. These modifications focus on the restriction of maintaining the vertices on the border edges of a tile that is coincident with its neighbors, at the same level of detail. We define these restrictions on the three different types of simplification algorithms (greedy insertion, edge-collapse simplification, and point set simplification); each of which imposes different assumptions on the input data. We implement at least one representative method of each type and compare both qualitatively and quantitatively on a large-scale dataset covering the European area at a resolution of 1/16 of an arc minute in the context of the European Marine Observations Data network (EMODnet) Bathymetry project. The results show that, although the simplification method designed for elevation data attains the best results in terms of mean error with respect to the original terrain, the other, more generic state-of-the-art 3D simplification techniques create a comparable error while providing different complexities for the triangle meshes
dc.description.sponsorship
This work was funded by the Executive Agency for Small and Medium-sized Enterprises (EASME),
European Maritime and Fisheries Fund (EMFF), European Union, under the project EASME/EMFF/2016/005 High resolution seabed mapping. R. Garcia was partly funded by the Spanish Government under project CTM2017-83075-R
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
MDPI (Multidisciplinary Digital Publishing Institute)
dc.relation
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/CTM2017-83075-R/ES/ROBOT SUBMARINO INTELIGENTE PARA LA EXPLORACION OMNIDIRECCIONAL E INMERSIVA DEL BENTOS/
dc.relation.isformatof
Reproducció digital del document publicat a: https://doi.org/10.3390/rs12030437
dc.relation.ispartof
Remote Sensing, 2020, vol 12, núm.3, p. 437
dc.relation.ispartofseries
Articles publicats (D-ATC)
dc.rights
Attribution 4.0 International
dc.rights.uri
dc.title
3D Simplification Methods and Large Scale Terrain Tiling
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
030951
dc.contributor.funder
dc.type.peerreviewed
peer-reviewed
dc.relation.FundingProgramme
dc.relation.ProjectAcronym
dc.identifier.eissn
2072-4292