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Detection of tropical landslides using airborne lidar data and multi imagery: a case study in Genting Highland, Pahang

The landslide geomorphological system in a tropical region is complex, and its understanding often depends on the completeness and correctness of landslide inventorization. In mountainous regions, landslides pose a significant impact and are known as an important geomorphic process in shaping major...

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Main Authors: Khamsin, I., Abdul Rahman, Muhammad Zulkarnain, Razak, Khamarrul Azahari, Rizal, S.
Format: Article
Language:English
Published: Institute of Physics Publishing 2014
Subjects:
T Technology
Online Access:http://eprints.utm.my/id/eprint/52332/1/I.Khamsin2014_Detectionoftropicallandslides.pdf
http://eprints.utm.my/id/eprint/52332/
http://dx.doi.org/10.1088/1755-1315/18/1/012033
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spelling my.utm.523322018-09-17T04:01:40Z http://eprints.utm.my/id/eprint/52332/ Detection of tropical landslides using airborne lidar data and multi imagery: a case study in Genting Highland, Pahang Khamsin, I. Abdul Rahman, Muhammad Zulkarnain Razak, Khamarrul Azahari Rizal, S. T Technology The landslide geomorphological system in a tropical region is complex, and its understanding often depends on the completeness and correctness of landslide inventorization. In mountainous regions, landslides pose a significant impact and are known as an important geomorphic process in shaping major landscape in the tropics. A modern remote sensing based approach has revolutionized the landslide investigation in a forested terrain. Optical satellite imagery, aerial photographs and synthetic aperture radar images are less effective to create reliable tropical DTMs for landslide recognition, and even so in the forested equatorial regions. Airborne laser scanning (ALS) data have been used to construct the digital terrain model (DTM) under dense vegetation, but its reliability for landslide recognition in the tropics remains surprisingly unknown. The present study aims at providing better insight into the use of airborne laser scanning (ALS) data. For the bare-earth extraction, several prominent filtering algorithms and surface interpolation methods, i.e. progressive TIN densitification, morphological, and command prompt from Lastool are evaluated in a qualitative analysis, aiming at removing non-ground points while preserving important landslide features. As a result, a large landslide can be detected using OOA. Small landslides remain unrecognized. Three out of five landslides can be detected, with a 60 percent overall accuracy Institute of Physics Publishing 2014 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/52332/1/I.Khamsin2014_Detectionoftropicallandslides.pdf Khamsin, I. and Abdul Rahman, Muhammad Zulkarnain and Razak, Khamarrul Azahari and Rizal, S. (2014) Detection of tropical landslides using airborne lidar data and multi imagery: a case study in Genting Highland, Pahang. 8th International Symposium of the Digital Earth (ISDE8), 18 (1). ISSN 1755-1315 http://dx.doi.org/10.1088/1755-1315/18/1/012033 DOI: 10.1088/1755-1315/18/1/012033
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/
language English
topic T Technology
spellingShingle T Technology
Khamsin, I.
Abdul Rahman, Muhammad Zulkarnain
Razak, Khamarrul Azahari
Rizal, S.
Detection of tropical landslides using airborne lidar data and multi imagery: a case study in Genting Highland, Pahang
description The landslide geomorphological system in a tropical region is complex, and its understanding often depends on the completeness and correctness of landslide inventorization. In mountainous regions, landslides pose a significant impact and are known as an important geomorphic process in shaping major landscape in the tropics. A modern remote sensing based approach has revolutionized the landslide investigation in a forested terrain. Optical satellite imagery, aerial photographs and synthetic aperture radar images are less effective to create reliable tropical DTMs for landslide recognition, and even so in the forested equatorial regions. Airborne laser scanning (ALS) data have been used to construct the digital terrain model (DTM) under dense vegetation, but its reliability for landslide recognition in the tropics remains surprisingly unknown. The present study aims at providing better insight into the use of airborne laser scanning (ALS) data. For the bare-earth extraction, several prominent filtering algorithms and surface interpolation methods, i.e. progressive TIN densitification, morphological, and command prompt from Lastool are evaluated in a qualitative analysis, aiming at removing non-ground points while preserving important landslide features. As a result, a large landslide can be detected using OOA. Small landslides remain unrecognized. Three out of five landslides can be detected, with a 60 percent overall accuracy
format Article
author Khamsin, I.
Abdul Rahman, Muhammad Zulkarnain
Razak, Khamarrul Azahari
Rizal, S.
author_facet Khamsin, I.
Abdul Rahman, Muhammad Zulkarnain
Razak, Khamarrul Azahari
Rizal, S.
author_sort Khamsin, I.
title Detection of tropical landslides using airborne lidar data and multi imagery: a case study in Genting Highland, Pahang
title_short Detection of tropical landslides using airborne lidar data and multi imagery: a case study in Genting Highland, Pahang
title_full Detection of tropical landslides using airborne lidar data and multi imagery: a case study in Genting Highland, Pahang
title_fullStr Detection of tropical landslides using airborne lidar data and multi imagery: a case study in Genting Highland, Pahang
title_full_unstemmed Detection of tropical landslides using airborne lidar data and multi imagery: a case study in Genting Highland, Pahang
title_sort detection of tropical landslides using airborne lidar data and multi imagery: a case study in genting highland, pahang
publisher Institute of Physics Publishing
publishDate 2014
url http://eprints.utm.my/id/eprint/52332/1/I.Khamsin2014_Detectionoftropicallandslides.pdf
http://eprints.utm.my/id/eprint/52332/
http://dx.doi.org/10.1088/1755-1315/18/1/012033
_version_ 1643653182186848256
score 13.211869

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