INGENIEUR
Landslide Vulnerability Index
and Risk Analysis for Critical
Infrastructure (Part 1)
By Yusrin-Faiz W, Rohaizi M. J,
Zuhairi A. H., G. Mohd-Khairolden,
Zakaria M.
Construction Research Institute of
Malaysia
Che Hassandi A
Public Works Department
Khamarrul A. R
Universiti Teknologi Malaysia
INTRODUCTION: The objective of this project, funded by Construction Industry Development
Board (CIDB) Malaysia was to assist the construction industry in enhancing the resiliency of critical
infrastructures (CI) in facing disaster. An appropriate methodology and strategy for assessing
landslide vulnerability and determining a risk index for critical infrastructure was proposed. The
project promotes pre-disaster action rather than post-disaster reaction and aims at integrating
efforts for assessing landslide vulnerability and possible risk assessment in a quantitative manner
at specific sites; at the municipality and regional levels in Malaysia.
METHODOLOGY: The overall methodology of the project was divided into nine stages namely
i. Data collection; ii. Reviews regarding landslide vulnerability and risk assessment for critical
infrastructures; iii. Determination of critical infrastructures; iv. Review of methods of vulnerability
and risk assessment; v. Geospatial data processing and analysis; vi. Development of parameters
and indicators for vulnerability and risk assessment; vii. Preparation of recommendations for
suitable methods of vulnerability and risk assessment; viii. Evaluation of the proposed methodology
based on two specific study areas; ix. Project deliverables.
RESULTS: The proposed landslide vulnerability assessment requires determination of four clusters
i.e. susceptibility of critical infrastructures (C), the effect of the surrounding environment or
mitigation measures (E), susceptibility of people inside the residential buildings (P) and intensity
of landslide hazards (I) (Equation 1). Based on intensive literature reviews, initial information
on the landslide vulnerability clusters, indicators, sub-indicators, weights, vulnerability and risk
classes were determined for further improvement in Focus Group Discussions (FGDs). The initial
landslide vulnerability clusters were treated equally in which all the group of indicators have the
same influence on the vulnerability value. In this case each group was given a weight value of 25%
(or 0.25). The weight value was given equally among the indicators under each group or differently
based on their level of importance in vulnerability estimation. However, the outcomes of the FGDs
with sensititvity analysis and landslide vulnerability simulation found that this assumption should be
changed and each cluster should be treated differently. Therefore, the final weight for each cluster
has a different value.
CONCLUSION: The study successfully achieved the objective to assess and develop the
parameters/indicators of landslide vulnerability assessment of critical infrastructures (CI) and
assigning risk levels for each parameter. The landslide vulnerability indicators, sub-indicators and
their corresponding weights were tested in Ringlet and Lembah Bertam, Cameron Highlands with
support from various remotely sensed data, field data and other ancillary geospatial data.
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VOL
VOL 79
55 JULY-SEPTEMBER
JUNE 2013 2019