Internet of Things and Cloud Computing

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

Received: 23 June 2013    Accepted:     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.

DOI 10.11648/j.iotcc.20130101.12
Published in Internet of Things and Cloud Computing (Volume 1, Issue 1, June 2013)
Page(s) 5-14
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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), 2024. Published by Science Publishing Group

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Keywords

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

References
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Author Information
  • Surveying Engineering Department, College of Engineering, University of Baghdad, Baghdad, Iraq

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  • APA Style

    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

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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://download.sciencepg.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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    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.
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