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dc.contributor.authorKermarrec, Gaël
dc.contributor.authorSkytt, Vibeke
dc.contributor.authorDokken, Tor
dc.date.accessioned2023-01-20T16:53:32Z
dc.date.available2023-01-20T16:53:32Z
dc.date.issued2023
dc.identifierONIX_20230120_9783031169540_14
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/60790
dc.description.abstractThis open access book provides insights into the novel Locally Refined B-spline (LR B-spline) surface format, which is suited for representing terrain and seabed data in a compact way. It provides an alternative to the well know raster and triangulated surface representations. An LR B-spline surface has an overall smooth behavior and allows the modeling of local details with only a limited growth in data volume. In regions where many data points belong to the same smooth area, LR B-splines allow a very lean representation of the shape by locally adapting the resolution of the spline space to the size and local shape variations of the region. The iterative method can be modified to improve the accuracy in particular domains of a point cloud. The use of statistical information criterion can help determining the optimal threshold, the number of iterations to perform as well as some parameters of the underlying mathematical functions (degree of the splines, parameter representation). The resulting surfaces are well suited for analysis and computing secondary information such as contour curves and minimum and maximum points. Also deformation analysis are potential applications of fitting point clouds with LR B-splines.
dc.languageEnglish
dc.relation.ispartofseriesSpringerBriefs in Earth System Sciences
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UB Information technology: general topicsen_US
dc.subject.classificationthema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geographyen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PB Mathematics::PBK Calculus and mathematical analysis::PBKS Numerical analysisen_US
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UF Business applications::UFM Mathematical and statistical softwareen_US
dc.subject.otherSurface Modeling
dc.subject.otherOptimum Point Cloud Approximation
dc.subject.otherAkaike Information Criterion
dc.subject.otherLR B-Splines
dc.subject.otherContour Curves Determination
dc.subject.otherDeformation Analysis
dc.subject.otherBathymetry data
dc.titleOptimal Surface Fitting of Point Clouds Using Local Refinement
dc.title.alternativeApplication to GIS Data
dc.typebook
oapen.identifier.doi10.1007/978-3-031-16954-0
oapen.relation.isPublishedBy6c6992af-b843-4f46-859c-f6e9998e40d5
oapen.relation.isFundedBye53ce2e9-6435-444c-9239-a3c6446d50d6
oapen.relation.isFundedBy872eab38-05f9-4293-b5be-c226b96780ba
oapen.relation.isFundedByDeutsche Forschungsgemeinschaft (DFG)
oapen.relation.isbn9783031169540
oapen.collectionDFG Open Access Publication Funding
oapen.imprintSpringer International Publishing
oapen.pages111
oapen.place.publicationCham
oapen.grant.number[...]
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