Processing Intensive Full-Waveform Aerial Laser Scanning Matlab Jobs through Condor

Fanar Mansour Abed

doi:doi:10.11648/j.iotcc.20130101.12

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Processing Intensive Full-Waveform Aerial Laser Scanning Matlab Jobs through Condor

Fanar Mansour Abed

Published in Internet of Things and Cloud Computing (Volume 1, Issue 1)

Received: 23 June 2013 Published: 10 August 2013

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Abstract

Full-waveform aerial laser scanning is a laser system that records the entire backscattered signal of the laser pulse and stores it in the system recorder for post-processing. Capturing the complete waveform of the backscatter signal enables distinguishing between neighborhood echoes of a range smaller than the pulse length. Full-waveform has shown potential to better describe land cover features through the additional physical information it can provide alongside the standard geometric information. To fully utilize full-waveform for enhanced object recognition and feature extraction, it is essential to develop an automatic and effective routine to manage and process full-waveform datasets in a manner which requires less human effort and reduces time needed to process large laser datasets efficiently. This research tackled this problem through introducing a novel processing strategy for full-waveform data based on a developed pulse detection methodto run through Matlab environment. The solution adopted a grid computing Condor-based approach, which showed significant potential to reduce the time and effort needed to process large datasets such as full-waveform aerial laser scanning to more than 300% in specific conditions.

Published in	Internet of Things and Cloud Computing (Volume 1, Issue 1)
DOI	10.11648/j.iotcc.20130101.12
Page(s)	5-14
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2013. Published by Science Publishing Group

Keywords

Laser Scanning, Lidar, Full-Waveform, Signal Analysis, Grid Computing, Condor

References

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Fanar Mansour Abed. (2013). Processing Intensive Full-Waveform Aerial Laser Scanning Matlab Jobs through Condor. Internet of Things and Cloud Computing, 1(1), 5-14. https://doi.org/10.11648/j.iotcc.20130101.12

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Fanar Mansour Abed. Processing Intensive Full-Waveform Aerial Laser Scanning Matlab Jobs through Condor. Internet Things Cloud Comput. 2013, 1(1), 5-14. doi: 10.11648/j.iotcc.20130101.12

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Fanar Mansour Abed. Processing Intensive Full-Waveform Aerial Laser Scanning Matlab Jobs through Condor. Internet Things Cloud Comput. 2013;1(1):5-14. doi: 10.11648/j.iotcc.20130101.12

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@article{10.11648/j.iotcc.20130101.12,
  author = {Fanar Mansour Abed},
  title = {Processing Intensive Full-Waveform Aerial Laser Scanning Matlab Jobs through Condor},
  journal = {Internet of Things and Cloud Computing},
  volume = {1},
  number = {1},
  pages = {5-14},
  doi = {10.11648/j.iotcc.20130101.12},
  url = {https://doi.org/10.11648/j.iotcc.20130101.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.iotcc.20130101.12},
  abstract = {Full-waveform aerial laser scanning is a laser system that records the entire backscattered signal of the laser pulse and stores it in the system recorder for post-processing. Capturing the complete waveform of the backscatter signal enables distinguishing between neighborhood echoes of a range smaller than the pulse length. Full-waveform has shown potential to better describe land cover features through the additional physical information it can provide alongside the standard geometric information. To fully utilize full-waveform for enhanced object recognition and feature extraction, it is essential to develop an automatic and effective routine to manage and process full-waveform datasets in a manner which requires less human effort and reduces time needed to process large laser datasets efficiently. This research tackled this problem through introducing a novel processing strategy for full-waveform data based on a developed pulse detection methodto run through Matlab environment. The solution adopted a grid computing Condor-based approach, which showed significant potential to reduce the time and effort needed to process large datasets such as full-waveform aerial laser scanning to more than 300% in specific conditions.},
 year = {2013}
}

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TY  - JOUR
T1  - Processing Intensive Full-Waveform Aerial Laser Scanning Matlab Jobs through Condor
AU  - Fanar Mansour Abed
Y1  - 2013/08/10
PY  - 2013
N1  - https://doi.org/10.11648/j.iotcc.20130101.12
DO  - 10.11648/j.iotcc.20130101.12
T2  - Internet of Things and Cloud Computing
JF  - Internet of Things and Cloud Computing
JO  - Internet of Things and Cloud Computing
SP  - 5
EP  - 14
PB  - Science Publishing Group
SN  - 2376-7731
UR  - https://doi.org/10.11648/j.iotcc.20130101.12
AB  - Full-waveform aerial laser scanning is a laser system that records the entire backscattered signal of the laser pulse and stores it in the system recorder for post-processing. Capturing the complete waveform of the backscatter signal enables distinguishing between neighborhood echoes of a range smaller than the pulse length. Full-waveform has shown potential to better describe land cover features through the additional physical information it can provide alongside the standard geometric information. To fully utilize full-waveform for enhanced object recognition and feature extraction, it is essential to develop an automatic and effective routine to manage and process full-waveform datasets in a manner which requires less human effort and reduces time needed to process large laser datasets efficiently. This research tackled this problem through introducing a novel processing strategy for full-waveform data based on a developed pulse detection methodto run through Matlab environment. The solution adopted a grid computing Condor-based approach, which showed significant potential to reduce the time and effort needed to process large datasets such as full-waveform aerial laser scanning to more than 300% in specific conditions.
VL  - 1
IS  - 1
ER  -

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Author Information

Fanar Mansour Abed

Surveying Engineering Department, College of Engineering, University of Baghdad, Baghdad, Iraq

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Fanar Mansour Abed. (2013). Processing Intensive Full-Waveform Aerial Laser Scanning Matlab Jobs through Condor. Internet of Things and Cloud Computing, 1(1), 5-14. https://doi.org/10.11648/j.iotcc.20130101.12

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Fanar Mansour Abed. Processing Intensive Full-Waveform Aerial Laser Scanning Matlab Jobs through Condor. Internet Things Cloud Comput. 2013, 1(1), 5-14. doi: 10.11648/j.iotcc.20130101.12

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AMA Style

Fanar Mansour Abed. Processing Intensive Full-Waveform Aerial Laser Scanning Matlab Jobs through Condor. Internet Things Cloud Comput. 2013;1(1):5-14. doi: 10.11648/j.iotcc.20130101.12

Copy | Download

@article{10.11648/j.iotcc.20130101.12,
  author = {Fanar Mansour Abed},
  title = {Processing Intensive Full-Waveform Aerial Laser Scanning Matlab Jobs through Condor},
  journal = {Internet of Things and Cloud Computing},
  volume = {1},
  number = {1},
  pages = {5-14},
  doi = {10.11648/j.iotcc.20130101.12},
  url = {https://doi.org/10.11648/j.iotcc.20130101.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.iotcc.20130101.12},
  abstract = {Full-waveform aerial laser scanning is a laser system that records the entire backscattered signal of the laser pulse and stores it in the system recorder for post-processing. Capturing the complete waveform of the backscatter signal enables distinguishing between neighborhood echoes of a range smaller than the pulse length. Full-waveform has shown potential to better describe land cover features through the additional physical information it can provide alongside the standard geometric information. To fully utilize full-waveform for enhanced object recognition and feature extraction, it is essential to develop an automatic and effective routine to manage and process full-waveform datasets in a manner which requires less human effort and reduces time needed to process large laser datasets efficiently. This research tackled this problem through introducing a novel processing strategy for full-waveform data based on a developed pulse detection methodto run through Matlab environment. The solution adopted a grid computing Condor-based approach, which showed significant potential to reduce the time and effort needed to process large datasets such as full-waveform aerial laser scanning to more than 300% in specific conditions.},
 year = {2013}
}

Copy | Download

TY  - JOUR
T1  - Processing Intensive Full-Waveform Aerial Laser Scanning Matlab Jobs through Condor
AU  - Fanar Mansour Abed
Y1  - 2013/08/10
PY  - 2013
N1  - https://doi.org/10.11648/j.iotcc.20130101.12
DO  - 10.11648/j.iotcc.20130101.12
T2  - Internet of Things and Cloud Computing
JF  - Internet of Things and Cloud Computing
JO  - Internet of Things and Cloud Computing
SP  - 5
EP  - 14
PB  - Science Publishing Group
SN  - 2376-7731
UR  - https://doi.org/10.11648/j.iotcc.20130101.12
AB  - Full-waveform aerial laser scanning is a laser system that records the entire backscattered signal of the laser pulse and stores it in the system recorder for post-processing. Capturing the complete waveform of the backscatter signal enables distinguishing between neighborhood echoes of a range smaller than the pulse length. Full-waveform has shown potential to better describe land cover features through the additional physical information it can provide alongside the standard geometric information. To fully utilize full-waveform for enhanced object recognition and feature extraction, it is essential to develop an automatic and effective routine to manage and process full-waveform datasets in a manner which requires less human effort and reduces time needed to process large laser datasets efficiently. This research tackled this problem through introducing a novel processing strategy for full-waveform data based on a developed pulse detection methodto run through Matlab environment. The solution adopted a grid computing Condor-based approach, which showed significant potential to reduce the time and effort needed to process large datasets such as full-waveform aerial laser scanning to more than 300% in specific conditions.
VL  - 1
IS  - 1
ER  -

Copy | Download