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Assessment of unmanned aerial vehicle (UAV) photogrammetry towards shipping container counting / Muhammad Afiq Abdullah

Shipping container counting at depot in Malaysia is carried out manually. It is considered as labour intensive especially when large number of shipping container is involves. In this study, combinations of UAV images and geo-processing software are utilized for shipping container counting approach....

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Main Author: Abdullah, Muhammad Afiq
Format: Thesis
Language:English
Published: 2019
Online Access:https://ir.uitm.edu.my/id/eprint/89164/1/89164.pdf
https://ir.uitm.edu.my/id/eprint/89164/
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id my.uitm.ir.89164
record_format eprints
spelling my.uitm.ir.891642024-08-16T08:56:19Z https://ir.uitm.edu.my/id/eprint/89164/ Assessment of unmanned aerial vehicle (UAV) photogrammetry towards shipping container counting / Muhammad Afiq Abdullah Abdullah, Muhammad Afiq Shipping container counting at depot in Malaysia is carried out manually. It is considered as labour intensive especially when large number of shipping container is involves. In this study, combinations of UAV images and geo-processing software are utilized for shipping container counting approach. UAV images are post-processed using photogrammetric technique to create Digital Surface Model (DSM) which represents ground and above surface feature’s elevations. The constructed DSM is filtered to produce the Digital Terrain Model (DTM) that represents ground surface. The container’s candidates are then isolated by subtracting the DTM from DSM to generate a normalized DSM (nDSM). Knowing the standard dimensions of container, the number of container can be precisely extracted. The assessment is carried out based on five (5) accuracy levels of processing settings: Highest, High, Medium, Low and Lowest. The actual total number of containers is known based on verification by manual counting on-site. Highest to Low accuracy level of processing settings contributed to 100% of counting accuracy. Additionally, the Root-Mean-Square Error (RMSE) of container surface area modelling achieved within ±1.330m2 to ±2.703m2 for Highest processing settings. As for RMSE of container height modelling, within ±0.236m to ±0.520m is achieved for Highest processing settings. The optimum processing settings is proposed for certain requirements with specific constraints. The proposed technique is a high value in shipping container counting at depot for a diversity of uses. 2019 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/89164/1/89164.pdf Assessment of unmanned aerial vehicle (UAV) photogrammetry towards shipping container counting / Muhammad Afiq Abdullah. (2019) Masters thesis, thesis, Universiti Teknologi MARA (UiTM). <http://terminalib.uitm.edu.my/89164.pdf>
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
description Shipping container counting at depot in Malaysia is carried out manually. It is considered as labour intensive especially when large number of shipping container is involves. In this study, combinations of UAV images and geo-processing software are utilized for shipping container counting approach. UAV images are post-processed using photogrammetric technique to create Digital Surface Model (DSM) which represents ground and above surface feature’s elevations. The constructed DSM is filtered to produce the Digital Terrain Model (DTM) that represents ground surface. The container’s candidates are then isolated by subtracting the DTM from DSM to generate a normalized DSM (nDSM). Knowing the standard dimensions of container, the number of container can be precisely extracted. The assessment is carried out based on five (5) accuracy levels of processing settings: Highest, High, Medium, Low and Lowest. The actual total number of containers is known based on verification by manual counting on-site. Highest to Low accuracy level of processing settings contributed to 100% of counting accuracy. Additionally, the Root-Mean-Square Error (RMSE) of container surface area modelling achieved within ±1.330m2 to ±2.703m2 for Highest processing settings. As for RMSE of container height modelling, within ±0.236m to ±0.520m is achieved for Highest processing settings. The optimum processing settings is proposed for certain requirements with specific constraints. The proposed technique is a high value in shipping container counting at depot for a diversity of uses.
format Thesis
author Abdullah, Muhammad Afiq
spellingShingle Abdullah, Muhammad Afiq
Assessment of unmanned aerial vehicle (UAV) photogrammetry towards shipping container counting / Muhammad Afiq Abdullah
author_facet Abdullah, Muhammad Afiq
author_sort Abdullah, Muhammad Afiq
title Assessment of unmanned aerial vehicle (UAV) photogrammetry towards shipping container counting / Muhammad Afiq Abdullah
title_short Assessment of unmanned aerial vehicle (UAV) photogrammetry towards shipping container counting / Muhammad Afiq Abdullah
title_full Assessment of unmanned aerial vehicle (UAV) photogrammetry towards shipping container counting / Muhammad Afiq Abdullah
title_fullStr Assessment of unmanned aerial vehicle (UAV) photogrammetry towards shipping container counting / Muhammad Afiq Abdullah
title_full_unstemmed Assessment of unmanned aerial vehicle (UAV) photogrammetry towards shipping container counting / Muhammad Afiq Abdullah
title_sort assessment of unmanned aerial vehicle (uav) photogrammetry towards shipping container counting / muhammad afiq abdullah
publishDate 2019
url https://ir.uitm.edu.my/id/eprint/89164/1/89164.pdf
https://ir.uitm.edu.my/id/eprint/89164/
_version_ 1808975934781390848
score 13.211869

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