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Article

A Comparative Study about Data Structures Used for Efficient Management of Voxelised Full-Waveform Airborne LiDAR Data during 3D Polygonal Model Creation

1
Centre for Digital Entertainment, Department of Computer Science, University of Bath, Bath BA2 7AY, UK
2
Remote Sensing Group, Plymouth Marine Laboratory, Plymouth PL1 3DH, UK
3
ERATOSTHENES Centre of Excellence, Department of Civil Engineering and Geomatics, Cyprus University of Technology, Lemesos 3036, Cyprus
*
Author to whom correspondence should be addressed.
Current address: ERATOSTHENES Centre of Excellence, Department of Civil Engineering and Geomatics, Cyprus University of Technology, Lemesos 3036, Cyprus.
Current address: EUMETSAT, Germany.
Academic Editor: Linh Truong-Hong
Remote Sens. 2021, 13(4), 559; https://doi.org/10.3390/rs13040559
Received: 31 December 2020 / Revised: 29 January 2021 / Accepted: 1 February 2021 / Published: 4 February 2021
(This article belongs to the Special Issue Lidar Remote Sensing in 3D Object Modelling)
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. View Full-Text
Keywords: LiDAR; voxelisation; iso-surface; visualisations; data structures; efficiency; memory management; execution time; volumetric data LiDAR; voxelisation; iso-surface; visualisations; data structures; efficiency; memory management; execution time; volumetric data
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MDPI and ACS Style

Miltiadou, M.; Campbell, N.D.F.; Cosker, D.; Grant, M.G. A Comparative Study about Data Structures Used for Efficient Management of Voxelised Full-Waveform Airborne LiDAR Data during 3D Polygonal Model Creation. Remote Sens. 2021, 13, 559. https://doi.org/10.3390/rs13040559

AMA Style

Miltiadou M, Campbell NDF, Cosker D, Grant MG. A Comparative Study about Data Structures Used for Efficient Management of Voxelised Full-Waveform Airborne LiDAR Data during 3D Polygonal Model Creation. Remote Sensing. 2021; 13(4):559. https://doi.org/10.3390/rs13040559

Chicago/Turabian Style

Miltiadou, Milto, Neill D.F. Campbell, Darren Cosker, and Michael G. Grant. 2021. "A Comparative Study about Data Structures Used for Efficient Management of Voxelised Full-Waveform Airborne LiDAR Data during 3D Polygonal Model Creation" Remote Sensing 13, no. 4: 559. https://doi.org/10.3390/rs13040559

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