Sorted pulse data (SPD) library. Part II: a processing framework for LiDAR data from pulsed laser systems in terrestrial environments

Bunting, Peter, Armston, John, Clewley, Daniel and Lucas, Richard M. (2013) Sorted pulse data (SPD) library. Part II: a processing framework for LiDAR data from pulsed laser systems in terrestrial environments. Computers & Geosciences, 56 207-215. doi:10.1016/j.cageo.2013.01.010


Author Bunting, Peter
Armston, John
Clewley, Daniel
Lucas, Richard M.
Title Sorted pulse data (SPD) library. Part II: a processing framework for LiDAR data from pulsed laser systems in terrestrial environments
Formatted title
Sorted pulse data (SPD) library—Part II: a processing frame work for LiDAR data from pulsed laser systems in terrestrial environments
Journal name Computers & Geosciences   Check publisher's open access policy
ISSN 0098-3004
1873-7803
Publication date 2013-07-01
Sub-type Article (original research)
DOI 10.1016/j.cageo.2013.01.010
Open Access Status DOI
Volume 56
Start page 207
End page 215
Total pages 9
Place of publication United Kingdom
Publisher Pergamon
Language eng
Subject 1710 Information Systems
1903 Computers in Earth Sciences
Abstract The management and spatial-temporal integration of LiDAR data from different sensors and platforms has been impeded by lack of generic open source tools and standards. This paper presents a new open source software system, the sorted pulse data software library (SPDLib), that provides a processing framework based on an implementation of a new file format for the storage of discrete-return and waveform LiDAR data from terrestrial, airborne and space borne platforms. A python binding and a visualisation tool (SPD Points Viewer), which build on top of the SPDLib and SPD file format have also been provided. The software and source code have recently been made freely available and can be accessed online through an open source code repository. Future developments will focus on the development of advanced waveform processing functionality and optimising IO performance. The software and documentation can be obtained from http://www.spdlib.org.
Formatted abstract
The management and spatial-temporal integration of LiDAR data from different sensors and platforms has been impeded by lack of generic open source tools and standards. This paper presents a new open source software system, the sorted pulse data software library (SPDLib), that provides a processing framework based on an implementation of a new file format for the storage of discrete-return and waveform LiDAR data from terrestrial, airborne and space borne platforms. A python binding and a visualisation tool (SPD Points Viewer), which build on top of the SPDLib and SPD file format have also been provided. The software and source code have recently been made freely available and can be accessed online through an open source code repository. Future developments will focus on the development of advanced waveform processing functionality and optimising IO performance. The software and documentation can be obtained from http://www.spdlib.org.

Highlights ► A new open source systems for the processing of LiDAR data. ► Specific support for the storage of waveform and discrete return data. ► Builds on an innovated new file format (SPD). ► Written in C++ but provides interfaces to higher level languages (e.g., python). ► Provides a high quality visualisation tool.
Keyword LiDAR
Software
Pulse
Waveform
Sorted
SPD
Discrete-return LiDAR
Coniferous forest
Airborne LiDAR
Identification
Decomposition
Scanner
Density
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
Official 2014 Collection
 
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Citation counts: TR Web of Science Citation Count  Cited 12 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 16 times in Scopus Article | Citations
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Created: Sun, 21 Jul 2013, 10:05:38 EST by System User on behalf of School of Geography, Planning & Env Management