Landslide susceptibility mapping using the statistical index method and factor effect analysis along the E- W highway (Gerik - Jeli), Malaysia

Tareq H. Mezughi, Juhari Mat Akhir, Abdul Ghani Rafek, Ibrahim Abdullah

    Research output: Contribution to journalArticle

    2 Citations (Scopus)

    Abstract

    In this paper, a GIS-based methodology has been used to produce a landslide susceptibility map for a landslide-prone area located at the central northern part of Peninsular Malaysia along the E-W highway (Gerik - Jeli). The susceptibility assessment was based on a bivariate statistical method namely the statistical index by which the spatial relationship between landslides and causative factors have been evaluated. Landslide locations were identified from interpretation of aerial photographs, field surveys and previous studies conducted in the area. Spatial database for causative factors was constructed from topographical maps, geological maps, satellite data, hydrological data, soil data and field data. Ten thematic maps for factors considered in the analysis including: Slope gradient, slope aspect, elevation, distance from road, drainage density, lithology, strata dip map, foliation dip map, lineament density, and soil map were extracted from the constructed spatial database. The validation of assessment showed a satisfactory agreement between the susceptibility map and the landslide locations. The area under curve (AUC) of success rate for the model was (85.13%) and the AUC of prediction rate was (82.21%), indicating a high prediction accuracy. The influencing factors on the landslide susceptibility were evaluated qualitatively by excluding each factor from the analysis to select the positive factors that improve the prediction accuracy of the landslide susceptibility map. Factor effects revealed that all factors have relatively positive influences on the resulting landslide susceptibility map but the most effective factors on analysis are: distance from road (AUC = 0.725), lineament density (AUC = 0.756), slope gradient (AUC = 0.787), and lithology (AUC = 0.793). The statistical index (Wi) values of the considered variables pointed to the importance of three classes as the most contributing factors to landslides in the study area which are: less than 300 m distance from road (Wi >2.25), high and very high density lineament (Wi >1.44), slope gradient 35°- 45° (Wi =0.71), and lithological unit composes of phyllite and slate (Wi = 0.68).

    Original languageEnglish
    Pages (from-to)847-857
    Number of pages11
    JournalAustralian Journal of Basic and Applied Sciences
    Volume5
    Issue number6
    Publication statusPublished - Jun 2011

    Fingerprint

    index method
    landslide
    road
    lineament
    lithology
    prediction
    effect
    analysis
    phyllite
    slate
    foliation
    aerial photograph
    field survey
    satellite data
    dip
    GIS
    drainage
    methodology

    Keywords

    • East-West Highway (Malaysia)
    • Landslide causative factors
    • Landslide susceptibility
    • Statistical index

    ASJC Scopus subject areas

    • General

    Cite this

    Landslide susceptibility mapping using the statistical index method and factor effect analysis along the E- W highway (Gerik - Jeli), Malaysia. / Mezughi, Tareq H.; Akhir, Juhari Mat; Rafek, Abdul Ghani; Abdullah, Ibrahim.

    In: Australian Journal of Basic and Applied Sciences, Vol. 5, No. 6, 06.2011, p. 847-857.

    Research output: Contribution to journalArticle

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    AB - In this paper, a GIS-based methodology has been used to produce a landslide susceptibility map for a landslide-prone area located at the central northern part of Peninsular Malaysia along the E-W highway (Gerik - Jeli). The susceptibility assessment was based on a bivariate statistical method namely the statistical index by which the spatial relationship between landslides and causative factors have been evaluated. Landslide locations were identified from interpretation of aerial photographs, field surveys and previous studies conducted in the area. Spatial database for causative factors was constructed from topographical maps, geological maps, satellite data, hydrological data, soil data and field data. Ten thematic maps for factors considered in the analysis including: Slope gradient, slope aspect, elevation, distance from road, drainage density, lithology, strata dip map, foliation dip map, lineament density, and soil map were extracted from the constructed spatial database. The validation of assessment showed a satisfactory agreement between the susceptibility map and the landslide locations. The area under curve (AUC) of success rate for the model was (85.13%) and the AUC of prediction rate was (82.21%), indicating a high prediction accuracy. The influencing factors on the landslide susceptibility were evaluated qualitatively by excluding each factor from the analysis to select the positive factors that improve the prediction accuracy of the landslide susceptibility map. Factor effects revealed that all factors have relatively positive influences on the resulting landslide susceptibility map but the most effective factors on analysis are: distance from road (AUC = 0.725), lineament density (AUC = 0.756), slope gradient (AUC = 0.787), and lithology (AUC = 0.793). The statistical index (Wi) values of the considered variables pointed to the importance of three classes as the most contributing factors to landslides in the study area which are: less than 300 m distance from road (Wi >2.25), high and very high density lineament (Wi >1.44), slope gradient 35°- 45° (Wi =0.71), and lithological unit composes of phyllite and slate (Wi = 0.68).

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