LIDAR for coastal monitoring study - A review

LIDAR is a well-known method for capturing points at extremely high resolution, but its resolution is insufficient for tasks like object recognition, façade categorization, and assessing the behavior of feature extraction in terms of edges, fractures, and changes. This review paper for coastal monit...

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Main Authors: Sekon, Jamaah, Majid, Zulkepli, Mohd. Ariff, Mohd. Farid
Format: Conference or Workshop Item
Published: 2023
Subjects:
Online Access:http://eprints.utm.my/107644/
http://dx.doi.org/10.1109/ICSGRC57744.2023.10215448
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spelling my.utm.1076442024-09-25T07:34:04Z http://eprints.utm.my/107644/ LIDAR for coastal monitoring study - A review Sekon, Jamaah Majid, Zulkepli Mohd. Ariff, Mohd. Farid H Social Sciences (General) LIDAR is a well-known method for capturing points at extremely high resolution, but its resolution is insufficient for tasks like object recognition, façade categorization, and assessing the behavior of feature extraction in terms of edges, fractures, and changes. This review paper for coastal monitoring study uses the Terrestrial Laser Scanning (TLS) 3D LIDAR data cloud to extract linear features, locate and categorize fractures, and apply the line effect technique. Maybe shorten the time it takes to analyze data, manage a massive data TLS point systematically, eliminate irrelevant data, and investigate different LIDAR applications. Thus, with the addition of TLS 3D LIDAR coastal monitoring and Geographic Information System (GIS) application, user friendly understanding changes in natural disaster issues, coastline management efficiently, erosion prevention risk and subsequent action plans for decision makers or the general public are countered. 2023 Conference or Workshop Item PeerReviewed Sekon, Jamaah and Majid, Zulkepli and Mohd. Ariff, Mohd. Farid (2023) LIDAR for coastal monitoring study - A review. In: 14th Control and System Graduate Research Colloquium (ICSGRC), 5 August 2023, Shah Alam, Malaysia. http://dx.doi.org/10.1109/ICSGRC57744.2023.10215448
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic H Social Sciences (General)
spellingShingle H Social Sciences (General)
Sekon, Jamaah
Majid, Zulkepli
Mohd. Ariff, Mohd. Farid
LIDAR for coastal monitoring study - A review
description LIDAR is a well-known method for capturing points at extremely high resolution, but its resolution is insufficient for tasks like object recognition, façade categorization, and assessing the behavior of feature extraction in terms of edges, fractures, and changes. This review paper for coastal monitoring study uses the Terrestrial Laser Scanning (TLS) 3D LIDAR data cloud to extract linear features, locate and categorize fractures, and apply the line effect technique. Maybe shorten the time it takes to analyze data, manage a massive data TLS point systematically, eliminate irrelevant data, and investigate different LIDAR applications. Thus, with the addition of TLS 3D LIDAR coastal monitoring and Geographic Information System (GIS) application, user friendly understanding changes in natural disaster issues, coastline management efficiently, erosion prevention risk and subsequent action plans for decision makers or the general public are countered.
format Conference or Workshop Item
author Sekon, Jamaah
Majid, Zulkepli
Mohd. Ariff, Mohd. Farid
author_facet Sekon, Jamaah
Majid, Zulkepli
Mohd. Ariff, Mohd. Farid
author_sort Sekon, Jamaah
title LIDAR for coastal monitoring study - A review
title_short LIDAR for coastal monitoring study - A review
title_full LIDAR for coastal monitoring study - A review
title_fullStr LIDAR for coastal monitoring study - A review
title_full_unstemmed LIDAR for coastal monitoring study - A review
title_sort lidar for coastal monitoring study - a review
publishDate 2023
url http://eprints.utm.my/107644/
http://dx.doi.org/10.1109/ICSGRC57744.2023.10215448
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