Using a space filling curve approach for the management of dynamic point clouds

Journal Article (2016)
Author(s)

S Psomadaki

Peter van Van Oosterom (TU Delft - OLD Department of GIS Technology)

TPM Tijssen (TU Delft - OLD Department of GIS Technology)

F. Baart (Deltares)

Research Group
OLD Department of GIS Technology
Copyright
© 2016 S Psomadaki, P.J.M. van Oosterom, T.P.M. Tijssen, F. Baart
DOI related publication
https://doi.org/10.5194/isprs-annals-IV-2-W1-107-2016
More Info
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Publication Year
2016
Language
English
Copyright
© 2016 S Psomadaki, P.J.M. van Oosterom, T.P.M. Tijssen, F. Baart
Research Group
OLD Department of GIS Technology
Volume number
IV-2/W1
Pages (from-to)
107-118
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Abstract

Point cloud usage has increased over the years. The development of low-cost sensors makes it now possible to acquire frequent point cloud measurements on a short time period (day, hour, second). Based on the requirements coming from the coastal monitoring domain, we have developed, implemented and benchmarked a spatio-temporal point cloud data management solution. For this reason, we make use of the flat model approach (one point per row) in an Index Organised Table within a RDBMS and an improved spatio-temporal organisation using a Space Filling Curve approach. Two variants coming from two extremes of the space - time continuum are also taken into account, along with two treatments of the z dimension: as attribute or as part of the space filling curve. Through executing a benchmark we elaborate on the performance -loading and querying time-, and storage required by those different approaches. Finally,
we validate the correctness and suitability of our method, through an out-of-the-box way of managing dynamic point clouds.