4 Citations (SciVal)

Abstract

In this paper, we investigate the performance of six data structures for managing voxelised full-waveform airborne LiDAR data during 3D polygonal model creation. While full-waveform LiDAR data has been available for over a decade, extraction of peak points is the most widely used approach of interpreting them. The increased information stored within the waveform data makes interpretation and handling difficult. It is, therefore, important to research which data structures are more appropriate for storing and interpreting the data. In this paper, we investigate the performance of six data structures while voxelising and interpreting full-waveform LiDAR data for 3D polygonal model creation. The data structures are tested in terms of time efficiency and memory consumption during run-time and are the following: (1) 1D-Array that guarantees coherent memory allocation, (2) Voxel Hashing, which uses a hash table for storing the intensity values (3) Octree (4) Integral Volumes that allows finding the sum of any cuboid area in constant time, (5) Octree Max/Min, which is an upgraded octree and (6) Integral Octree, which is proposed here and it is an attempt to combine the benefits of octrees and Integral Volumes. In this paper, it is shown that Integral Volumes is the more time efficient data structure but it requires the most memory allocation. Furthermore, 1D-Array and Integral Volumes require the allocation of coherent space in memory including the empty voxels, while Voxel Hashing and the octree related data structures do not require to allocate memory for empty voxels. These data structures, therefore, and as shown in the test conducted, allocate less memory. To sum up, there is a need to investigate how the LiDAR data are stored in memory. Each tested data structure has different benefits and downsides; therefore, each application should be examined individually.

Original languageEnglish
Article number559
Pages (from-to)1-19
Number of pages19
JournalRemote Sensing
Volume13
Issue number4
DOIs
Publication statusPublished - 4 Feb 2021

Bibliographical note

Funding Information:
This research was funded by the Centre for Digital Entertainment (CDE) with Grant reference number ?EP/L016540/1? and Plymouth Marine Laboratory. The APC was funded by the UKRI Block Grant fund of University of Bath, UK. Data from the NERC ARF are provided courtesy of NERC via the Centre for Environmental Data Analysis (CEDA) and were processed by NEODAAS. The data were provided by the NERC Airborne Research and Facility (ARF).

Funding Information:
Funding: This research was funded by the Centre for Digital Entertainment (CDE) with Grant reference number “EP/L016540/1” and Plymouth Marine Laboratory. The APC was funded by the UKRI Block Grant fund of University of Bath, UK. Data from the NERC ARF are provided courtesy of NERC via the Centre for Environmental Data Analysis (CEDA) and were processed by NEODAAS.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Keywords

  • Data structures
  • Efficiency
  • Execution time
  • Iso-surface
  • LiDAR
  • Memory management
  • Visualisations
  • Volumetric data
  • Voxelisation

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

Fingerprint

Dive into the research topics of 'A comparative study about data structures used for efficient management of voxelised full-waveform airborne lidar data during 3d polygonal model creation'. Together they form a unique fingerprint.

Cite this