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Landslide Susceptibility Assessment Using Bivariate Frequency Ratio from Pekan Nabalu to Kundasang Area of Sabah, Malaysia

A statistical bivariate model, Frequency Ratio was used to assess the landslide susceptibility of Pekan Nabalu to Kundasang area using Geographic Information System (GIS) as a tool. A total of 564 landslides (0.27km2) were detected from field observation, Google Earth satellite imagery and IFSAR ima...

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Main Authors: Rishanthiny Bala Krishnan, Rodeano Roslee
Format: Proceedings
Language:English
English
Published: Faculty of Science & Natural Resources, UMS 2022
Subjects:
Q1-390 Science (General)
QE1-350.62 General Including geographical divisions
Online Access:https://eprints.ums.edu.my/id/eprint/40650/1/ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/40650/2/FULL%20TEXT.pdf
https://eprints.ums.edu.my/id/eprint/40650/
https://www.ums.edu.my/fssa/index.php/research/conference-publication
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spelling my.ums.eprints.406502024-08-14T03:36:40Z https://eprints.ums.edu.my/id/eprint/40650/ Landslide Susceptibility Assessment Using Bivariate Frequency Ratio from Pekan Nabalu to Kundasang Area of Sabah, Malaysia Rishanthiny Bala Krishnan Rodeano Roslee Q1-390 Science (General) QE1-350.62 General Including geographical divisions A statistical bivariate model, Frequency Ratio was used to assess the landslide susceptibility of Pekan Nabalu to Kundasang area using Geographic Information System (GIS) as a tool. A total of 564 landslides (0.27km2) were detected from field observation, Google Earth satellite imagery and IFSAR imagery to produce a landslide inventory map (dependent factor). Eight (8) landslide causative factor maps (independent factor) namely slope angle, slope aspect, slope curvature, drainage proximity, lineament proximity, lithology, land use and soil series. The integration of the dependent factor and the independent factors resulted in a regional scale spatial Landslide Susceptibility Analysis map (LSA) with five susceptibility classes. About 11.39% (12.99km2), 25.56% (29.14km2), 29.67% (33.82km2), 23.6% (26.9km2) and 9.78% (11.15km2) are classified as Very Low, Low, Moderate, High, and Very High susceptibility classes respectively. Using AUC (Area Under Curve) validation method, the prediction rate is 82.63% and the success rate is 82.6%. The LSA map is considered reliable as 405 landslides (0.22km2) were detected in Moderate to Very High susceptibility classes. Therefore, this study would benefit various stakeholders, researchers, and other professionals to propose suitable mitigation measure and develop better landslide management plan. Faculty of Science & Natural Resources, UMS 2022 Proceedings PeerReviewed text en https://eprints.ums.edu.my/id/eprint/40650/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/40650/2/FULL%20TEXT.pdf Rishanthiny Bala Krishnan and Rodeano Roslee (2022) Landslide Susceptibility Assessment Using Bivariate Frequency Ratio from Pekan Nabalu to Kundasang Area of Sabah, Malaysia. https://www.ums.edu.my/fssa/index.php/research/conference-publication
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic Q1-390 Science (General)
QE1-350.62 General Including geographical divisions
spellingShingle Q1-390 Science (General)
QE1-350.62 General Including geographical divisions
Rishanthiny Bala Krishnan
Rodeano Roslee
Landslide Susceptibility Assessment Using Bivariate Frequency Ratio from Pekan Nabalu to Kundasang Area of Sabah, Malaysia
description A statistical bivariate model, Frequency Ratio was used to assess the landslide susceptibility of Pekan Nabalu to Kundasang area using Geographic Information System (GIS) as a tool. A total of 564 landslides (0.27km2) were detected from field observation, Google Earth satellite imagery and IFSAR imagery to produce a landslide inventory map (dependent factor). Eight (8) landslide causative factor maps (independent factor) namely slope angle, slope aspect, slope curvature, drainage proximity, lineament proximity, lithology, land use and soil series. The integration of the dependent factor and the independent factors resulted in a regional scale spatial Landslide Susceptibility Analysis map (LSA) with five susceptibility classes. About 11.39% (12.99km2), 25.56% (29.14km2), 29.67% (33.82km2), 23.6% (26.9km2) and 9.78% (11.15km2) are classified as Very Low, Low, Moderate, High, and Very High susceptibility classes respectively. Using AUC (Area Under Curve) validation method, the prediction rate is 82.63% and the success rate is 82.6%. The LSA map is considered reliable as 405 landslides (0.22km2) were detected in Moderate to Very High susceptibility classes. Therefore, this study would benefit various stakeholders, researchers, and other professionals to propose suitable mitigation measure and develop better landslide management plan.
format Proceedings
author Rishanthiny Bala Krishnan
Rodeano Roslee
author_facet Rishanthiny Bala Krishnan
Rodeano Roslee
author_sort Rishanthiny Bala Krishnan
title Landslide Susceptibility Assessment Using Bivariate Frequency Ratio from Pekan Nabalu to Kundasang Area of Sabah, Malaysia
title_short Landslide Susceptibility Assessment Using Bivariate Frequency Ratio from Pekan Nabalu to Kundasang Area of Sabah, Malaysia
title_full Landslide Susceptibility Assessment Using Bivariate Frequency Ratio from Pekan Nabalu to Kundasang Area of Sabah, Malaysia
title_fullStr Landslide Susceptibility Assessment Using Bivariate Frequency Ratio from Pekan Nabalu to Kundasang Area of Sabah, Malaysia
title_full_unstemmed Landslide Susceptibility Assessment Using Bivariate Frequency Ratio from Pekan Nabalu to Kundasang Area of Sabah, Malaysia
title_sort landslide susceptibility assessment using bivariate frequency ratio from pekan nabalu to kundasang area of sabah, malaysia
publisher Faculty of Science & Natural Resources, UMS
publishDate 2022
url https://eprints.ums.edu.my/id/eprint/40650/1/ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/40650/2/FULL%20TEXT.pdf
https://eprints.ums.edu.my/id/eprint/40650/
https://www.ums.edu.my/fssa/index.php/research/conference-publication
_version_ 1809140082423103488
score 13.211869

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