Surface approximation of coastal regions

LR B-Spline for detection of deformation pattern

verfasst von

Gael Kermarrec, Vibeke Skytt, Tor Dokken

Abstract

Geospatial data acquisition of terrains produces huge, noisy and scattered point clouds. An efficient use of the acquired data requires structured and compact data representations. Working directly in a point cloud is often not appealing. To face this challenge, approximation with tensor product B-spline surfaces is attractive. It reduces the point cloud description to relatively few coefficients compared to the volume of the original point cloud. However, this representation lacks the ability to adapt the resolution of the shape to local variations in the point cloud. The result is frequently that noise is approximated and that surfaces have unwanted oscillations. Locally Refined (LR) B-spline surfaces were introduced to face this challenge and provide a tool for approximating Geographic Information System point clouds. In our LR B-spline based approximation algorithm, iterative least-squares approximation is combined with a Multilevel B-spline Approximation to reduce memory consumption. We apply the approach to data sets from coastal regions in Norway and the Netherlands, and compare the obtained approximation with a raster method. We further highlight the potential of LR B-spline volumes for spatio-temporal visualisation of deformation patterns.

Organisationseinheit(en)

Geodätisches Institut

Externe Organisation(en)

SINTEF Industry

Typ

Konferenzaufsatz in Fachzeitschrift

Journal

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Band

5

Seiten

119-126

Anzahl der Seiten

8

ISSN

2194-9042

Publikationsdatum

17.05.2022

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Instrumentierung, Umweltwissenschaften (sonstige), Erdkunde und Planetologie (sonstige)

Elektronische Version(en)

https://doi.org/10.5194/isprs-annals-V-2-2022-119-2022 (Zugang: Offen)